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6 Commits

Author SHA1 Message Date
suyao
67f726afb7 feat: implement API client with SWR integration for catalog management
- Added a new Textarea component for user input.
- Configured ESLint with custom rules and global ignores.
- Developed a comprehensive API client with CRUD operations and error handling.
- Defined catalog types and schemas using Zod for type safety.
- Created utility functions for class name merging and validation.
- Established Next.js configuration for API rewrites and static file headers.
- Set up package.json with necessary dependencies and scripts.
- Configured PostCSS for Tailwind CSS integration.
- Added SVG assets for UI components.
- Configured TypeScript with strict settings and module resolution.
2025-12-01 13:07:23 +08:00
suyao
d98d69e28d simplify config 2025-11-24 14:48:02 +08:00
suyao
3f671ba6be initial migrate 2025-11-24 08:55:12 +08:00
suyao
78e593fac4 feat: Add comprehensive type test
- Introduced unified export for all catalog schemas and types in `index.ts`.
- Defined model configuration schemas in `model.ts`, including modalities, capabilities, reasoning, parameter support, and pricing.
- Created provider model override schemas in `override.ts` to manage provider-specific configurations.
- Established provider configuration schemas in `provider.ts`, detailing endpoint types, authentication methods, pricing models, and behavior characteristics.
- Implemented utility functions for JSON value validation and parsing in `json-value` and `parse-json` modules.
- Developed a schema validation utility in `SchemaValidator.ts` to validate model, provider, and override configurations with detailed error handling and warnings.
2025-11-24 07:36:33 +08:00
suyao
9933b0b12f feat: Add comprehensive schema definitions for catalog system
- Introduced common types and validation utilities in common.types.ts
- Unified export of all schemas in index.ts for easier access
- Defined model configuration schemas including capabilities, pricing, and reasoning in model.schema.ts
- Created provider model override schemas to manage provider-specific configurations in override.schema.ts
- Established provider configuration schemas detailing metadata, capabilities, and behaviors in provider.schema.ts
2025-11-24 06:12:45 +08:00
suyao
bceeef5190 Initial Prompt 2025-11-24 01:40:20 +08:00
425 changed files with 82467 additions and 32034 deletions

1
.github/CODEOWNERS vendored
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@@ -8,7 +8,6 @@
/packages/shared/data/ @0xfullex
/src/main/data/ @0xfullex
/src/renderer/src/data/ @0xfullex
/v2-refactor-temp/ @0xfullex
/packages/ui/ @MyPrototypeWhat

View File

@@ -77,7 +77,7 @@ jobs:
with:
token: ${{ secrets.GITHUB_TOKEN }} # Use the built-in GITHUB_TOKEN for bot actions
commit-message: "feat(bot): Weekly automated script run"
title: "🤖 Weekly Auto I18N Sync: ${{ env.CURRENT_DATE }}"
title: "🤖 Weekly Automated Update: ${{ env.CURRENT_DATE }}"
body: |
This PR includes changes generated by the weekly auto i18n.
Review the changes before merging.

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@@ -11,7 +11,6 @@
"dist/**",
"out/**",
"local/**",
"tests/**",
".yarn/**",
".gitignore",
"scripts/cloudflare-worker.js",

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@@ -0,0 +1,152 @@
diff --git a/dist/index.js b/dist/index.js
index c2ef089c42e13a8ee4a833899a415564130e5d79..75efa7baafb0f019fb44dd50dec1641eee8879e7 100644
--- a/dist/index.js
+++ b/dist/index.js
@@ -471,7 +471,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
// src/get-model-path.ts
function getModelPath(modelId) {
- return modelId.includes("/") ? modelId : `models/${modelId}`;
+ return modelId.includes("models/") ? modelId : `models/${modelId}`;
}
// src/google-generative-ai-options.ts
diff --git a/dist/index.mjs b/dist/index.mjs
index d75c0cc13c41192408c1f3f2d29d76a7bffa6268..ada730b8cb97d9b7d4cb32883a1d1ff416404d9b 100644
--- a/dist/index.mjs
+++ b/dist/index.mjs
@@ -477,7 +477,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
// src/get-model-path.ts
function getModelPath(modelId) {
- return modelId.includes("/") ? modelId : `models/${modelId}`;
+ return modelId.includes("models/") ? modelId : `models/${modelId}`;
}
// src/google-generative-ai-options.ts
diff --git a/dist/internal/index.js b/dist/internal/index.js
index 277cac8dc734bea2fb4f3e9a225986b402b24f48..bb704cd79e602eb8b0cee1889e42497d59ccdb7a 100644
--- a/dist/internal/index.js
+++ b/dist/internal/index.js
@@ -432,7 +432,15 @@ function prepareTools({
var _a;
tools = (tools == null ? void 0 : tools.length) ? tools : void 0;
const toolWarnings = [];
- const isGemini2 = modelId.includes("gemini-2");
+ // These changes could be safely removed when @ai-sdk/google v3 released.
+ const isLatest = (
+ [
+ 'gemini-flash-latest',
+ 'gemini-flash-lite-latest',
+ 'gemini-pro-latest',
+ ]
+ ).some(id => id === modelId);
+ const isGemini2OrNewer = modelId.includes("gemini-2") || modelId.includes("gemini-3") || isLatest;
const supportsDynamicRetrieval = modelId.includes("gemini-1.5-flash") && !modelId.includes("-8b");
const supportsFileSearch = modelId.includes("gemini-2.5");
if (tools == null) {
@@ -458,7 +466,7 @@ function prepareTools({
providerDefinedTools.forEach((tool) => {
switch (tool.id) {
case "google.google_search":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({ googleSearch: {} });
} else if (supportsDynamicRetrieval) {
googleTools2.push({
@@ -474,7 +482,7 @@ function prepareTools({
}
break;
case "google.url_context":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({ urlContext: {} });
} else {
toolWarnings.push({
@@ -485,7 +493,7 @@ function prepareTools({
}
break;
case "google.code_execution":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({ codeExecution: {} });
} else {
toolWarnings.push({
@@ -507,7 +515,7 @@ function prepareTools({
}
break;
case "google.vertex_rag_store":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({
retrieval: {
vertex_rag_store: {
diff --git a/dist/internal/index.mjs b/dist/internal/index.mjs
index 03b7cc591be9b58bcc2e775a96740d9f98862a10..347d2c12e1cee79f0f8bb258f3844fb0522a6485 100644
--- a/dist/internal/index.mjs
+++ b/dist/internal/index.mjs
@@ -424,7 +424,15 @@ function prepareTools({
var _a;
tools = (tools == null ? void 0 : tools.length) ? tools : void 0;
const toolWarnings = [];
- const isGemini2 = modelId.includes("gemini-2");
+ // These changes could be safely removed when @ai-sdk/google v3 released.
+ const isLatest = (
+ [
+ 'gemini-flash-latest',
+ 'gemini-flash-lite-latest',
+ 'gemini-pro-latest',
+ ]
+ ).some(id => id === modelId);
+ const isGemini2OrNewer = modelId.includes("gemini-2") || modelId.includes("gemini-3") || isLatest;
const supportsDynamicRetrieval = modelId.includes("gemini-1.5-flash") && !modelId.includes("-8b");
const supportsFileSearch = modelId.includes("gemini-2.5");
if (tools == null) {
@@ -450,7 +458,7 @@ function prepareTools({
providerDefinedTools.forEach((tool) => {
switch (tool.id) {
case "google.google_search":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({ googleSearch: {} });
} else if (supportsDynamicRetrieval) {
googleTools2.push({
@@ -466,7 +474,7 @@ function prepareTools({
}
break;
case "google.url_context":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({ urlContext: {} });
} else {
toolWarnings.push({
@@ -477,7 +485,7 @@ function prepareTools({
}
break;
case "google.code_execution":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({ codeExecution: {} });
} else {
toolWarnings.push({
@@ -499,7 +507,7 @@ function prepareTools({
}
break;
case "google.vertex_rag_store":
- if (isGemini2) {
+ if (isGemini2OrNewer) {
googleTools2.push({
retrieval: {
vertex_rag_store: {
@@ -1434,9 +1442,7 @@ var googleTools = {
vertexRagStore
};
export {
- GoogleGenerativeAILanguageModel,
getGroundingMetadataSchema,
- getUrlContextMetadataSchema,
- googleTools
+ getUrlContextMetadataSchema, GoogleGenerativeAILanguageModel, googleTools
};
//# sourceMappingURL=index.mjs.map
\ No newline at end of file

View File

@@ -1,26 +0,0 @@
diff --git a/dist/index.js b/dist/index.js
index 51ce7e423934fb717cb90245cdfcdb3dae6780e6..0f7f7009e2f41a79a8669d38c8a44867bbff5e1f 100644
--- a/dist/index.js
+++ b/dist/index.js
@@ -474,7 +474,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
// src/get-model-path.ts
function getModelPath(modelId) {
- return modelId.includes("/") ? modelId : `models/${modelId}`;
+ return modelId.includes("models/") ? modelId : `models/${modelId}`;
}
// src/google-generative-ai-options.ts
diff --git a/dist/index.mjs b/dist/index.mjs
index f4b77e35c0cbfece85a3ef0d4f4e67aa6dde6271..8d2fecf8155a226006a0bde72b00b6036d4014b6 100644
--- a/dist/index.mjs
+++ b/dist/index.mjs
@@ -480,7 +480,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
// src/get-model-path.ts
function getModelPath(modelId) {
- return modelId.includes("/") ? modelId : `models/${modelId}`;
+ return modelId.includes("models/") ? modelId : `models/${modelId}`;
}
// src/google-generative-ai-options.ts

View File

@@ -0,0 +1,131 @@
diff --git a/dist/index.mjs b/dist/index.mjs
index b3f018730a93639aad7c203f15fb1aeb766c73f4..ade2a43d66e9184799d072153df61ef7be4ea110 100644
--- a/dist/index.mjs
+++ b/dist/index.mjs
@@ -296,7 +296,14 @@ var HuggingFaceResponsesLanguageModel = class {
metadata: huggingfaceOptions == null ? void 0 : huggingfaceOptions.metadata,
instructions: huggingfaceOptions == null ? void 0 : huggingfaceOptions.instructions,
...preparedTools && { tools: preparedTools },
- ...preparedToolChoice && { tool_choice: preparedToolChoice }
+ ...preparedToolChoice && { tool_choice: preparedToolChoice },
+ ...(huggingfaceOptions?.reasoningEffort != null && {
+ reasoning: {
+ ...(huggingfaceOptions?.reasoningEffort != null && {
+ effort: huggingfaceOptions.reasoningEffort,
+ }),
+ },
+ }),
};
return { args: baseArgs, warnings };
}
@@ -365,6 +372,20 @@ var HuggingFaceResponsesLanguageModel = class {
}
break;
}
+ case 'reasoning': {
+ for (const contentPart of part.content) {
+ content.push({
+ type: 'reasoning',
+ text: contentPart.text,
+ providerMetadata: {
+ huggingface: {
+ itemId: part.id,
+ },
+ },
+ });
+ }
+ break;
+ }
case "mcp_call": {
content.push({
type: "tool-call",
@@ -519,6 +540,11 @@ var HuggingFaceResponsesLanguageModel = class {
id: value.item.call_id,
toolName: value.item.name
});
+ } else if (value.item.type === 'reasoning') {
+ controller.enqueue({
+ type: 'reasoning-start',
+ id: value.item.id,
+ });
}
return;
}
@@ -570,6 +596,22 @@ var HuggingFaceResponsesLanguageModel = class {
});
return;
}
+ if (isReasoningDeltaChunk(value)) {
+ controller.enqueue({
+ type: 'reasoning-delta',
+ id: value.item_id,
+ delta: value.delta,
+ });
+ return;
+ }
+
+ if (isReasoningEndChunk(value)) {
+ controller.enqueue({
+ type: 'reasoning-end',
+ id: value.item_id,
+ });
+ return;
+ }
},
flush(controller) {
controller.enqueue({
@@ -593,7 +635,8 @@ var HuggingFaceResponsesLanguageModel = class {
var huggingfaceResponsesProviderOptionsSchema = z2.object({
metadata: z2.record(z2.string(), z2.string()).optional(),
instructions: z2.string().optional(),
- strictJsonSchema: z2.boolean().optional()
+ strictJsonSchema: z2.boolean().optional(),
+ reasoningEffort: z2.string().optional(),
});
var huggingfaceResponsesResponseSchema = z2.object({
id: z2.string(),
@@ -727,12 +770,31 @@ var responseCreatedChunkSchema = z2.object({
model: z2.string()
})
});
+var reasoningTextDeltaChunkSchema = z2.object({
+ type: z2.literal('response.reasoning_text.delta'),
+ item_id: z2.string(),
+ output_index: z2.number(),
+ content_index: z2.number(),
+ delta: z2.string(),
+ sequence_number: z2.number(),
+});
+
+var reasoningTextEndChunkSchema = z2.object({
+ type: z2.literal('response.reasoning_text.done'),
+ item_id: z2.string(),
+ output_index: z2.number(),
+ content_index: z2.number(),
+ text: z2.string(),
+ sequence_number: z2.number(),
+});
var huggingfaceResponsesChunkSchema = z2.union([
responseOutputItemAddedSchema,
responseOutputItemDoneSchema,
textDeltaChunkSchema,
responseCompletedChunkSchema,
responseCreatedChunkSchema,
+ reasoningTextDeltaChunkSchema,
+ reasoningTextEndChunkSchema,
z2.object({ type: z2.string() }).loose()
// fallback for unknown chunks
]);
@@ -751,6 +813,12 @@ function isResponseCompletedChunk(chunk) {
function isResponseCreatedChunk(chunk) {
return chunk.type === "response.created";
}
+function isReasoningDeltaChunk(chunk) {
+ return chunk.type === 'response.reasoning_text.delta';
+}
+function isReasoningEndChunk(chunk) {
+ return chunk.type === 'response.reasoning_text.done';
+}
// src/huggingface-provider.ts
function createHuggingFace(options = {}) {

View File

@@ -1,140 +0,0 @@
diff --git a/dist/index.js b/dist/index.js
index 73045a7d38faafdc7f7d2cd79d7ff0e2b031056b..8d948c9ac4ea4b474db9ef3c5491961e7fcf9a07 100644
--- a/dist/index.js
+++ b/dist/index.js
@@ -421,6 +421,17 @@ var OpenAICompatibleChatLanguageModel = class {
text: reasoning
});
}
+ if (choice.message.images) {
+ for (const image of choice.message.images) {
+ const match1 = image.image_url.url.match(/^data:([^;]+)/)
+ const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
+ content.push({
+ type: 'file',
+ mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
+ data: match2 ? match2[1] : image.image_url.url,
+ });
+ }
+ }
if (choice.message.tool_calls != null) {
for (const toolCall of choice.message.tool_calls) {
content.push({
@@ -598,6 +609,17 @@ var OpenAICompatibleChatLanguageModel = class {
delta: delta.content
});
}
+ if (delta.images) {
+ for (const image of delta.images) {
+ const match1 = image.image_url.url.match(/^data:([^;]+)/)
+ const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
+ controller.enqueue({
+ type: 'file',
+ mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
+ data: match2 ? match2[1] : image.image_url.url,
+ });
+ }
+ }
if (delta.tool_calls != null) {
for (const toolCallDelta of delta.tool_calls) {
const index = toolCallDelta.index;
@@ -765,6 +787,14 @@ var OpenAICompatibleChatResponseSchema = import_v43.z.object({
arguments: import_v43.z.string()
})
})
+ ).nullish(),
+ images: import_v43.z.array(
+ import_v43.z.object({
+ type: import_v43.z.literal('image_url'),
+ image_url: import_v43.z.object({
+ url: import_v43.z.string(),
+ })
+ })
).nullish()
}),
finish_reason: import_v43.z.string().nullish()
@@ -795,6 +825,14 @@ var createOpenAICompatibleChatChunkSchema = (errorSchema) => import_v43.z.union(
arguments: import_v43.z.string().nullish()
})
})
+ ).nullish(),
+ images: import_v43.z.array(
+ import_v43.z.object({
+ type: import_v43.z.literal('image_url'),
+ image_url: import_v43.z.object({
+ url: import_v43.z.string(),
+ })
+ })
).nullish()
}).nullish(),
finish_reason: import_v43.z.string().nullish()
diff --git a/dist/index.mjs b/dist/index.mjs
index 1c2b9560bbfbfe10cb01af080aeeed4ff59db29c..2c8ddc4fc9bfc5e7e06cfca105d197a08864c427 100644
--- a/dist/index.mjs
+++ b/dist/index.mjs
@@ -405,6 +405,17 @@ var OpenAICompatibleChatLanguageModel = class {
text: reasoning
});
}
+ if (choice.message.images) {
+ for (const image of choice.message.images) {
+ const match1 = image.image_url.url.match(/^data:([^;]+)/)
+ const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
+ content.push({
+ type: 'file',
+ mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
+ data: match2 ? match2[1] : image.image_url.url,
+ });
+ }
+ }
if (choice.message.tool_calls != null) {
for (const toolCall of choice.message.tool_calls) {
content.push({
@@ -582,6 +593,17 @@ var OpenAICompatibleChatLanguageModel = class {
delta: delta.content
});
}
+ if (delta.images) {
+ for (const image of delta.images) {
+ const match1 = image.image_url.url.match(/^data:([^;]+)/)
+ const match2 = image.image_url.url.match(/^data:[^;]*;base64,(.+)$/);
+ controller.enqueue({
+ type: 'file',
+ mediaType: match1 ? (match1[1] ?? 'image/jpeg') : 'image/jpeg',
+ data: match2 ? match2[1] : image.image_url.url,
+ });
+ }
+ }
if (delta.tool_calls != null) {
for (const toolCallDelta of delta.tool_calls) {
const index = toolCallDelta.index;
@@ -749,6 +771,14 @@ var OpenAICompatibleChatResponseSchema = z3.object({
arguments: z3.string()
})
})
+ ).nullish(),
+ images: z3.array(
+ z3.object({
+ type: z3.literal('image_url'),
+ image_url: z3.object({
+ url: z3.string(),
+ })
+ })
).nullish()
}),
finish_reason: z3.string().nullish()
@@ -779,6 +809,14 @@ var createOpenAICompatibleChatChunkSchema = (errorSchema) => z3.union([
arguments: z3.string().nullish()
})
})
+ ).nullish(),
+ images: z3.array(
+ z3.object({
+ type: z3.literal('image_url'),
+ image_url: z3.object({
+ url: z3.string(),
+ })
+ })
).nullish()
}).nullish(),
finish_reason: z3.string().nullish()

View File

@@ -1,5 +1,5 @@
diff --git a/dist/index.js b/dist/index.js
index bf900591bf2847a3253fe441aad24c06da19c6c1..c1d9bb6fefa2df1383339324073db0a70ea2b5a2 100644
index 992c85ac6656e51c3471af741583533c5a7bf79f..83c05952a07aebb95fc6c62f9ddb8aa96b52ac0d 100644
--- a/dist/index.js
+++ b/dist/index.js
@@ -274,6 +274,7 @@ var openaiChatResponseSchema = (0, import_provider_utils3.lazyValidator)(
@@ -18,7 +18,7 @@ index bf900591bf2847a3253fe441aad24c06da19c6c1..c1d9bb6fefa2df1383339324073db0a7
tool_calls: import_v42.z.array(
import_v42.z.object({
index: import_v42.z.number(),
@@ -795,6 +797,13 @@ var OpenAIChatLanguageModel = class {
@@ -785,6 +787,13 @@ var OpenAIChatLanguageModel = class {
if (text != null && text.length > 0) {
content.push({ type: "text", text });
}
@@ -32,7 +32,7 @@ index bf900591bf2847a3253fe441aad24c06da19c6c1..c1d9bb6fefa2df1383339324073db0a7
for (const toolCall of (_a = choice.message.tool_calls) != null ? _a : []) {
content.push({
type: "tool-call",
@@ -876,6 +885,7 @@ var OpenAIChatLanguageModel = class {
@@ -866,6 +875,7 @@ var OpenAIChatLanguageModel = class {
};
let metadataExtracted = false;
let isActiveText = false;
@@ -40,7 +40,7 @@ index bf900591bf2847a3253fe441aad24c06da19c6c1..c1d9bb6fefa2df1383339324073db0a7
const providerMetadata = { openai: {} };
return {
stream: response.pipeThrough(
@@ -933,6 +943,21 @@ var OpenAIChatLanguageModel = class {
@@ -923,6 +933,21 @@ var OpenAIChatLanguageModel = class {
return;
}
const delta = choice.delta;
@@ -62,7 +62,7 @@ index bf900591bf2847a3253fe441aad24c06da19c6c1..c1d9bb6fefa2df1383339324073db0a7
if (delta.content != null) {
if (!isActiveText) {
controller.enqueue({ type: "text-start", id: "0" });
@@ -1045,6 +1070,9 @@ var OpenAIChatLanguageModel = class {
@@ -1035,6 +1060,9 @@ var OpenAIChatLanguageModel = class {
}
},
flush(controller) {

View File

@@ -1,8 +1,8 @@
diff --git a/sdk.mjs b/sdk.mjs
index bf429a344b7d59f70aead16b639f949b07688a81..f77d50cc5d3fb04292cb3ac7fa7085d02dcc628f 100755
index 8cc6aaf0b25bcdf3c579ec95cde12d419fcb2a71..3b3b8beaea5ad2bbac26a15f792058306d0b059f 100755
--- a/sdk.mjs
+++ b/sdk.mjs
@@ -6250,7 +6250,7 @@ function createAbortController(maxListeners = DEFAULT_MAX_LISTENERS) {
@@ -6213,7 +6213,7 @@ function createAbortController(maxListeners = DEFAULT_MAX_LISTENERS) {
}
// ../src/transport/ProcessTransport.ts
@@ -11,20 +11,16 @@ index bf429a344b7d59f70aead16b639f949b07688a81..f77d50cc5d3fb04292cb3ac7fa7085d0
import { createInterface } from "readline";
// ../src/utils/fsOperations.ts
@@ -6619,18 +6619,11 @@ class ProcessTransport {
@@ -6505,14 +6505,11 @@ class ProcessTransport {
const errorMessage = isNativeBinary(pathToClaudeCodeExecutable) ? `Claude Code native binary not found at ${pathToClaudeCodeExecutable}. Please ensure Claude Code is installed via native installer or specify a valid path with options.pathToClaudeCodeExecutable.` : `Claude Code executable not found at ${pathToClaudeCodeExecutable}. Is options.pathToClaudeCodeExecutable set?`;
throw new ReferenceError(errorMessage);
}
- const isNative = isNativeBinary(pathToClaudeCodeExecutable);
- const spawnCommand = isNative ? pathToClaudeCodeExecutable : executable;
- const spawnArgs = isNative ? [...executableArgs, ...args] : [...executableArgs, pathToClaudeCodeExecutable, ...args];
- const spawnMessage = isNative ? `Spawning Claude Code native binary: ${spawnCommand} ${spawnArgs.join(" ")}` : `Spawning Claude Code process: ${spawnCommand} ${spawnArgs.join(" ")}`;
- logForSdkDebugging(spawnMessage);
- if (stderr) {
- stderr(spawnMessage);
- }
+ logForSdkDebugging(`Forking Claude Code Node.js process: ${pathToClaudeCodeExecutable} ${args.join(" ")}`);
const stderrMode = env.DEBUG_CLAUDE_AGENT_SDK || stderr ? "pipe" : "ignore";
- this.logForDebugging(isNative ? `Spawning Claude Code native binary: ${spawnCommand} ${spawnArgs.join(" ")}` : `Spawning Claude Code process: ${spawnCommand} ${spawnArgs.join(" ")}`);
+ this.logForDebugging(`Forking Claude Code Node.js process: ${pathToClaudeCodeExecutable} ${args.join(" ")}`);
const stderrMode = env.DEBUG || stderr ? "pipe" : "ignore";
- this.child = spawn(spawnCommand, spawnArgs, {
+ this.child = fork(pathToClaudeCodeExecutable, args, {
cwd,

View File

@@ -11,18 +11,8 @@ This file provides guidance to AI coding assistants when working with code in th
- **Log centrally**: Route all logging through `loggerService` with the right context—no `console.log`.
- **Research via subagent**: Lean on `subagent` for external docs, APIs, news, and references.
- **Always propose before executing**: Before making any changes, clearly explain your planned approach and wait for explicit user approval to ensure alignment and prevent unwanted modifications.
- **Lint, test, and format before completion**: Coding tasks are only complete after running `yarn lint`, `yarn test`, and `yarn format` successfully.
- **Write conventional commits**: Commit small, focused changes using Conventional Commit messages (e.g., `feat:`, `fix:`, `refactor:`, `docs:`).
## Pull Request Workflow (CRITICAL)
When creating a Pull Request, you MUST:
1. **Read the PR template first**: Always read `.github/pull_request_template.md` before creating the PR
2. **Follow ALL template sections**: Structure the `--body` parameter to include every section from the template
3. **Never skip sections**: Include all sections even if marking them as N/A or "None"
4. **Use proper formatting**: Match the template's markdown structure exactly (headings, checkboxes, code blocks)
## Development Commands
- **Install**: `yarn install` - Install all project dependencies

View File

@@ -1,4 +1,4 @@
[中文](docs/zh/guides/contributing.md) | [English](CONTRIBUTING.md)
[中文](docs/CONTRIBUTING.zh.md) | [English](CONTRIBUTING.md)
# Cherry Studio Contributor Guide
@@ -32,7 +32,7 @@ To help you get familiar with the codebase, we recommend tackling issues tagged
### Testing
Features without tests are considered non-existent. To ensure code is truly effective, relevant processes should be covered by unit tests and functional tests. Therefore, when considering contributions, please also consider testability. All tests can be run locally without dependency on CI. Please refer to the "Testing" section in the [Developer Guide](docs/zh/guides/development.md).
Features without tests are considered non-existent. To ensure code is truly effective, relevant processes should be covered by unit tests and functional tests. Therefore, when considering contributions, please also consider testability. All tests can be run locally without dependency on CI. Please refer to the "Testing" section in the [Developer Guide](docs/dev.md).
### Automated Testing for Pull Requests
@@ -60,7 +60,7 @@ Maintainers are here to help you implement your use case within a reasonable tim
### Participating in the Test Plan
The Test Plan aims to provide users with a more stable application experience and faster iteration speed. For details, please refer to the [Test Plan](docs/en/guides/test-plan.md).
The Test Plan aims to provide users with a more stable application experience and faster iteration speed. For details, please refer to the [Test Plan](docs/testplan-en.md).
### Other Suggestions

View File

@@ -34,7 +34,7 @@
</a>
</h1>
<p align="center">English | <a href="./docs/zh/README.md">中文</a> | <a href="https://cherry-ai.com">Official Site</a> | <a href="https://docs.cherry-ai.com/cherry-studio-wen-dang/en-us">Documents</a> | <a href="./docs/en/guides/development.md">Development</a> | <a href="https://github.com/CherryHQ/cherry-studio/issues">Feedback</a><br></p>
<p align="center">English | <a href="./docs/README.zh.md">中文</a> | <a href="https://cherry-ai.com">Official Site</a> | <a href="https://docs.cherry-ai.com/cherry-studio-wen-dang/en-us">Documents</a> | <a href="./docs/dev.md">Development</a> | <a href="https://github.com/CherryHQ/cherry-studio/issues">Feedback</a><br></p>
<div align="center">
@@ -67,7 +67,7 @@ Cherry Studio is a desktop client that supports multiple LLM providers, availabl
👏 Join [Telegram Group](https://t.me/CherryStudioAI)[Discord](https://discord.gg/wez8HtpxqQ) | [QQ Group(575014769)](https://qm.qq.com/q/lo0D4qVZKi)
❤️ Like Cherry Studio? Give it a star 🌟 or [Sponsor](docs/zh/guides/sponsor.md) to support the development!
❤️ Like Cherry Studio? Give it a star 🌟 or [Sponsor](docs/sponsor.md) to support the development!
# 🌠 Screenshot
@@ -175,7 +175,7 @@ We welcome contributions to Cherry Studio! Here are some ways you can contribute
6. **Community Engagement**: Join discussions and help users.
7. **Promote Usage**: Spread the word about Cherry Studio.
Refer to the [Branching Strategy](docs/en/guides/branching-strategy.md) for contribution guidelines
Refer to the [Branching Strategy](docs/branching-strategy-en.md) for contribution guidelines
## Getting Started

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@@ -14,7 +14,7 @@
}
},
"enabled": true,
"includes": ["**/*.json", "!*.json", "!**/package.json", "!coverage/**"]
"includes": ["**/*.json", "!*.json", "!**/package.json", "!packages/**/*.json"]
},
"css": {
"formatter": {
@@ -23,7 +23,7 @@
},
"files": {
"ignoreUnknown": false,
"includes": ["**", "!**/.claude/**", "!**/.vscode/**"],
"includes": ["**", "!**/.claude/**"],
"maxSize": 2097152
},
"formatter": {

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@@ -1,6 +1,6 @@
# Cherry Studio 贡献者指南
[**English**](../../../CONTRIBUTING.md) | **中文**
[**English**](../CONTRIBUTING.md) | [**中文**](CONTRIBUTING.zh.md)
欢迎来到 Cherry Studio 的贡献者社区!我们致力于将 Cherry Studio 打造成一个长期提供价值的项目,并希望邀请更多的开发者加入我们的行列。无论您是经验丰富的开发者还是刚刚起步的初学者,您的贡献都将帮助我们更好地服务用户,提升软件质量。
@@ -24,7 +24,7 @@
## 开始之前
请确保阅读了[行为准则](../../../CODE_OF_CONDUCT.md)和[LICENSE](../../../LICENSE)。
请确保阅读了[行为准则](../CODE_OF_CONDUCT.md)和[LICENSE](../LICENSE)。
## 开始贡献
@@ -32,7 +32,7 @@
### 测试
未经测试的功能等同于不存在。为确保代码真正有效,应通过单元测试和功能测试覆盖相关流程。因此,在考虑贡献时,也请考虑可测试性。所有测试均可本地运行,无需依赖 CI。请参阅[开发者指南](./development.md#test)中的"Test"部分。
未经测试的功能等同于不存在。为确保代码真正有效,应通过单元测试和功能测试覆盖相关流程。因此,在考虑贡献时,也请考虑可测试性。所有测试均可本地运行,无需依赖 CI。请参阅[开发者指南](dev.md#test)中的Test部分。
### 拉取请求的自动化测试
@@ -60,11 +60,11 @@ git commit --signoff -m "Your commit message"
### 获取代码审查/合并
维护者在此帮助您在合理时间内实现您的用例。他们会尽力在合理时间内审查您的代码并提供建设性反馈。但如果您在审查过程中受阻,或认为您的 Pull Request 未得到应有的关注,请通过 Issue 中的评论或者[社群](../README.md#-community)联系我们
维护者在此帮助您在合理时间内实现您的用例。他们会尽力在合理时间内审查您的代码并提供建设性反馈。但如果您在审查过程中受阻,或认为您的 Pull Request 未得到应有的关注,请通过 Issue 中的评论或者[社群](README.zh.md#-community)联系我们
### 参与测试计划
测试计划旨在为用户提供更稳定的应用体验和更快的迭代速度,详细情况请参阅[测试计划](./test-plan.md)。
测试计划旨在为用户提供更稳定的应用体验和更快的迭代速度,详细情况请参阅[测试计划](testplan-zh.md)。
### 其他建议

View File

@@ -1,81 +0,0 @@
# Cherry Studio Documentation / 文档
This directory contains the project documentation in multiple languages.
本目录包含多语言项目文档。
---
## Languages / 语言
- **[中文文档](./zh/README.md)** - Chinese Documentation
- **English Documentation** - See sections below
---
## English Documentation
### Guides
| Document | Description |
|----------|-------------|
| [Development Setup](./en/guides/development.md) | Development environment setup |
| [Branching Strategy](./en/guides/branching-strategy.md) | Git branching workflow |
| [i18n Guide](./en/guides/i18n.md) | Internationalization guide |
| [Logging Guide](./en/guides/logging.md) | How to use the logger service |
| [Test Plan](./en/guides/test-plan.md) | Test plan and release channels |
### References
| Document | Description |
|----------|-------------|
| [App Upgrade Config](./en/references/app-upgrade.md) | Application upgrade configuration |
| [CodeBlockView Component](./en/references/components/code-block-view.md) | Code block view component |
| [Image Preview Components](./en/references/components/image-preview.md) | Image preview components |
---
## 中文文档
### 指南 (Guides)
| 文档 | 说明 |
|------|------|
| [开发环境设置](./zh/guides/development.md) | 开发环境配置 |
| [贡献指南](./zh/guides/contributing.md) | 如何贡献代码 |
| [分支策略](./zh/guides/branching-strategy.md) | Git 分支工作流 |
| [测试计划](./zh/guides/test-plan.md) | 测试计划和发布通道 |
| [国际化指南](./zh/guides/i18n.md) | 国际化开发指南 |
| [日志使用指南](./zh/guides/logging.md) | 如何使用日志服务 |
| [中间件开发](./zh/guides/middleware.md) | 如何编写中间件 |
| [记忆功能](./zh/guides/memory.md) | 记忆功能使用指南 |
| [赞助信息](./zh/guides/sponsor.md) | 赞助相关信息 |
### 参考 (References)
| 文档 | 说明 |
|------|------|
| [消息系统](./zh/references/message-system.md) | 消息系统架构和 API |
| [数据库结构](./zh/references/database.md) | 数据库表结构 |
| [服务](./zh/references/services.md) | 服务层文档 (KnowledgeService) |
| [代码执行](./zh/references/code-execution.md) | 代码执行功能 |
| [应用升级配置](./zh/references/app-upgrade.md) | 应用升级配置 |
| [CodeBlockView 组件](./zh/references/components/code-block-view.md) | 代码块视图组件 |
| [图像预览组件](./zh/references/components/image-preview.md) | 图像预览组件 |
---
## Missing Translations / 缺少翻译
The following documents are only available in Chinese and need English translations:
以下文档仅有中文版本,需要英文翻译:
- `guides/contributing.md`
- `guides/memory.md`
- `guides/middleware.md`
- `guides/sponsor.md`
- `references/message-system.md`
- `references/database.md`
- `references/services.md`
- `references/code-execution.md`

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@@ -34,7 +34,7 @@
</a>
</h1>
<p align="center">
<a href="https://github.com/CherryHQ/cherry-studio">English</a> | 中文 | <a href="https://cherry-ai.com">官方网站</a> | <a href="https://docs.cherry-ai.com/cherry-studio-wen-dang/zh-cn">文档</a> | <a href="./guides/development.md">开发</a> | <a href="https://github.com/CherryHQ/cherry-studio/issues">反馈</a><br>
<a href="https://github.com/CherryHQ/cherry-studio">English</a> | 中文 | <a href="https://cherry-ai.com">官方网站</a> | <a href="https://docs.cherry-ai.com/cherry-studio-wen-dang/zh-cn">文档</a> | <a href="./dev.md">开发</a> | <a href="https://github.com/CherryHQ/cherry-studio/issues">反馈</a><br>
</p>
<!-- 题头徽章组合 -->
@@ -70,7 +70,7 @@ Cherry Studio 是一款支持多个大语言模型LLM服务商的桌面客
👏 欢迎加入 [Telegram 群组](https://t.me/CherryStudioAI)[Discord](https://discord.gg/wez8HtpxqQ) | [QQ群(575014769)](https://qm.qq.com/q/lo0D4qVZKi)
❤️ 喜欢 Cherry Studio? 点亮小星星 🌟 或 [赞助开发者](./guides/sponsor.md)! ❤️
❤️ 喜欢 Cherry Studio? 点亮小星星 🌟 或 [赞助开发者](sponsor.md)! ❤️
# 📖 使用教程
@@ -181,7 +181,7 @@ https://docs.cherry-ai.com
6. **社区参与**:加入讨论并帮助用户
7. **推广使用**:宣传 Cherry Studio
参考[分支策略](./guides/branching-strategy.md)了解贡献指南
参考[分支策略](branching-strategy-zh.md)了解贡献指南
## 入门
@@ -190,7 +190,7 @@ https://docs.cherry-ai.com
3. **提交更改**:提交并推送您的更改
4. **打开 Pull Request**:描述您的更改和原因
有关更详细的指南,请参阅我们的 [贡献指南](./guides/contributing.md)
有关更详细的指南,请参阅我们的 [贡献指南](CONTRIBUTING.zh.md)
感谢您的支持和贡献!

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@@ -16,7 +16,7 @@ Cherry Studio implements a structured branching strategy to maintain code qualit
- Only accepts documentation updates and bug fixes
- Thoroughly tested before production deployment
For details about the `testplan` branch used in the Test Plan, please refer to the [Test Plan](./test-plan.md).
For details about the `testplan` branch used in the Test Plan, please refer to the [Test Plan](testplan-en.md).
## Contributing Branches

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@@ -16,7 +16,7 @@ Cherry Studio 采用结构化的分支策略来维护代码质量并简化开发
- 只接受文档更新和 bug 修复
- 经过完整测试后可以发布到生产环境
关于测试计划所使用的`testplan`分支,请查阅[测试计划](./test-plan.md)。
关于测试计划所使用的`testplan`分支,请查阅[测试计划](testplan-zh.md)。
## 贡献分支

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@@ -85,7 +85,7 @@ Main responsibilities:
- **SvgPreview**: SVG image preview
- **GraphvizPreview**: Graphviz diagram preview
All special view components share a common architecture for consistent user experience and functionality. For detailed information about these components and their implementation, see [Image Preview Components Documentation](./image-preview.md).
All special view components share a common architecture for consistent user experience and functionality. For detailed information about these components and their implementation, see [Image Preview Components Documentation](./ImagePreview-en.md).
#### StatusBar

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@@ -85,7 +85,7 @@ graph TD
- **SvgPreview**: SVG 图像预览
- **GraphvizPreview**: Graphviz 图表预览
所有特殊视图组件共享通用架构,以确保一致的用户体验和功能。有关这些组件及其实现的详细信息,请参阅[图像预览组件文档](./image-preview.md)。
所有特殊视图组件共享通用架构,以确保一致的用户体验和功能。有关这些组件及其实现的详细信息,请参阅 [图像预览组件文档](./ImagePreview-zh.md)。
#### StatusBar 状态栏

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@@ -192,4 +192,4 @@ Image Preview Components integrate seamlessly with CodeBlockView:
- Shared state management
- Responsive layout adaptation
For more information about the overall CodeBlockView architecture, see [CodeBlockView Documentation](./code-block-view.md).
For more information about the overall CodeBlockView architecture, see [CodeBlockView Documentation](./CodeBlockView-en.md).

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@@ -192,4 +192,4 @@ const { containerRef, error, isLoading, triggerRender, cancelRender, clearError,
- 共享状态管理
- 响应式布局适应
有关整体 CodeBlockView 架构的更多信息,请参阅 [CodeBlockView 文档](./code-block-view.md)。
有关整体 CodeBlockView 架构的更多信息,请参阅 [CodeBlockView 文档](./CodeBlockView-zh.md)。

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@@ -0,0 +1,3 @@
# 消息的生命周期
![image](./message-lifecycle.png)

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@@ -0,0 +1,11 @@
# 数据库设置字段
此文档包含部分字段的数据类型说明。
## 字段
| 字段名 | 类型 | 说明 |
| ------------------------------ | ------------------------------ | ------------ |
| `translate:target:language` | `LanguageCode` | 翻译目标语言 |
| `translate:source:language` | `LanguageCode` | 翻译源语言 |
| `translate:bidirectional:pair` | `[LanguageCode, LanguageCode]` | 双向翻译对 |

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@@ -1,24 +1,6 @@
# 数据库参考文档
# `translate_languages` 表技术文档
本文档介绍 Cherry Studio 的数据库结构,包括设置字段和翻译语言表。
---
## 设置字段 (settings)
此部分包含设置相关字段的数据类型说明。
### 翻译相关字段
| 字段名 | 类型 | 说明 |
| ------------------------------ | ------------------------------ | ------------ |
| `translate:target:language` | `LanguageCode` | 翻译目标语言 |
| `translate:source:language` | `LanguageCode` | 翻译源语言 |
| `translate:bidirectional:pair` | `[LanguageCode, LanguageCode]` | 双向翻译对 |
---
## 翻译语言表 (translate_languages)
## 📄 概述
`translate_languages` 记录用户自定义的的语言类型(`Language`)。

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@@ -18,11 +18,11 @@ The plugin has already been configured in the project — simply install it to g
### Demo
![demo-1](../../assets/images/i18n/demo-1.png)
![demo-1](./.assets.how-to-i18n/demo-1.png)
![demo-2](../../assets/images/i18n/demo-2.png)
![demo-2](./.assets.how-to-i18n/demo-2.png)
![demo-3](../../assets/images/i18n/demo-3.png)
![demo-3](./.assets.how-to-i18n/demo-3.png)
## i18n Conventions

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@@ -15,11 +15,11 @@ i18n ally是一个强大的VSCode插件它能在开发阶段提供实时反
### 效果展示
![demo-1](../../assets/images/i18n/demo-1.png)
![demo-1](./.assets.how-to-i18n/demo-1.png)
![demo-2](../../assets/images/i18n/demo-2.png)
![demo-2](./.assets.how-to-i18n/demo-2.png)
![demo-3](../../assets/images/i18n/demo-3.png)
![demo-3](./.assets.how-to-i18n/demo-3.png)
## i18n 约定

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@@ -0,0 +1,127 @@
# messageBlock.ts 使用指南
该文件定义了用于管理应用程序中所有 `MessageBlock` 实体的 Redux Slice。它使用 Redux Toolkit 的 `createSlice``createEntityAdapter` 来高效地处理规范化的状态,并提供了一系列 actions 和 selectors 用于与消息块数据交互。
## 核心目标
- **状态管理**: 集中管理所有 `MessageBlock` 的状态。`MessageBlock` 代表消息中的不同内容单元(如文本、代码、图片、引用等)。
- **规范化**: 使用 `createEntityAdapter``MessageBlock` 数据存储在规范化的结构中(`{ ids: [], entities: {} }`),这有助于提高性能和简化更新逻辑。
- **可预测性**: 提供明确的 actions 来修改状态,并通过 selectors 安全地访问状态。
## 关键概念
- **Slice (`createSlice`)**: Redux Toolkit 的核心 API用于创建包含 reducer 逻辑、action creators 和初始状态的 Redux 模块。
- **Entity Adapter (`createEntityAdapter`)**: Redux Toolkit 提供的工具,用于简化对规范化数据的 CRUD创建、读取、更新、删除操作。它会自动生成 reducer 函数和 selectors。
- **Selectors**: 用于从 Redux store 中派生和计算数据的函数。Selectors 可以被记忆化memoized以提高性能。
## State 结构
`messageBlocks` slice 的状态结构由 `createEntityAdapter` 定义,大致如下:
```typescript
{
ids: string[]; // 存储所有 MessageBlock ID 的有序列表
entities: { [id: string]: MessageBlock }; // 按 ID 存储 MessageBlock 对象的字典
loadingState: 'idle' | 'loading' | 'succeeded' | 'failed'; // (可选) 其他状态,如加载状态
error: string | null; // (可选) 错误信息
}
```
## Actions
该 slice 导出以下 actions (由 `createSlice``createEntityAdapter` 自动生成或自定义)
- **`upsertOneBlock(payload: MessageBlock)`**:
- 添加一个新的 `MessageBlock` 或更新一个已存在的 `MessageBlock`。如果 payload 中的 `id` 已存在,则执行更新;否则执行插入。
- **`upsertManyBlocks(payload: MessageBlock[])`**:
- 添加或更新多个 `MessageBlock`。常用于批量加载数据(例如,加载一个 Topic 的所有消息块)。
- **`removeOneBlock(payload: string)`**:
- 根据提供的 `id` (payload) 移除单个 `MessageBlock`
- **`removeManyBlocks(payload: string[])`**:
- 根据提供的 `id` 数组 (payload) 移除多个 `MessageBlock`。常用于删除消息或清空 Topic 时清理相关的块。
- **`removeAllBlocks()`**:
- 移除 state 中的所有 `MessageBlock` 实体。
- **`updateOneBlock(payload: { id: string; changes: Partial<MessageBlock> })`**:
- 更新一个已存在的 `MessageBlock``payload` 需要包含块的 `id` 和一个包含要更改的字段的 `changes` 对象。
- **`setMessageBlocksLoading(payload: 'idle' | 'loading')`**:
- (自定义) 设置 `loadingState` 属性。
- **`setMessageBlocksError(payload: string)`**:
- (自定义) 设置 `loadingState``'failed'` 并记录错误信息。
**使用示例 (在 Thunk 或其他 Dispatch 的地方):**
```typescript
import { upsertOneBlock, removeManyBlocks, updateOneBlock } from './messageBlock'
import store from './store' // 假设这是你的 Redux store 实例
// 添加或更新一个块
const newBlock: MessageBlock = {
/* ... block data ... */
}
store.dispatch(upsertOneBlock(newBlock))
// 更新一个块的内容
store.dispatch(updateOneBlock({ id: blockId, changes: { content: 'New content' } }))
// 删除多个块
const blockIdsToRemove = ['id1', 'id2']
store.dispatch(removeManyBlocks(blockIdsToRemove))
```
## Selectors
该 slice 导出由 `createEntityAdapter` 生成的基础 selectors并通过 `messageBlocksSelectors` 对象访问:
- **`messageBlocksSelectors.selectIds(state: RootState): string[]`**: 返回包含所有块 ID 的数组。
- **`messageBlocksSelectors.selectEntities(state: RootState): { [id: string]: MessageBlock }`**: 返回块 ID 到块对象的映射字典。
- **`messageBlocksSelectors.selectAll(state: RootState): MessageBlock[]`**: 返回包含所有块对象的数组。
- **`messageBlocksSelectors.selectTotal(state: RootState): number`**: 返回块的总数。
- **`messageBlocksSelectors.selectById(state: RootState, id: string): MessageBlock | undefined`**: 根据 ID 返回单个块对象,如果找不到则返回 `undefined`
**此外,还提供了一个自定义的、记忆化的 selector**
- **`selectFormattedCitationsByBlockId(state: RootState, blockId: string | undefined): Citation[]`**:
- 接收一个 `blockId`
- 如果该 ID 对应的块是 `CITATION` 类型,则提取并格式化其包含的引用信息(来自网页搜索、知识库等),进行去重和重新编号,最后返回一个 `Citation[]` 数组,用于在 UI 中显示。
- 如果块不存在或类型不匹配,返回空数组 `[]`
- 这个 selector 封装了处理不同引用来源Gemini, OpenAI, OpenRouter, Zhipu 等)的复杂逻辑。
**使用示例 (在 React 组件或 `useSelector` 中):**
```typescript
import { useSelector } from 'react-redux'
import { messageBlocksSelectors, selectFormattedCitationsByBlockId } from './messageBlock'
import type { RootState } from './store'
// 获取所有块
const allBlocks = useSelector(messageBlocksSelectors.selectAll)
// 获取特定 ID 的块
const specificBlock = useSelector((state: RootState) => messageBlocksSelectors.selectById(state, someBlockId))
// 获取特定引用块格式化后的引用列表
const formattedCitations = useSelector((state: RootState) => selectFormattedCitationsByBlockId(state, citationBlockId))
// 在组件中使用引用数据
// {formattedCitations.map(citation => ...)}
```
## 集成
`messageBlock.ts` slice 通常与 `messageThunk.ts` 中的 Thunks 紧密协作。Thunks 负责处理异步逻辑(如 API 调用、数据库操作),并在需要时 dispatch `messageBlock` slice 的 actions 来更新状态。例如,当 `messageThunk` 接收到流式响应时,它会 dispatch `upsertOneBlock``updateOneBlock` 来实时更新对应的 `MessageBlock`。同样,删除消息的 Thunk 会 dispatch `removeManyBlocks`
理解 `messageBlock.ts` 的职责是管理**状态本身**,而 `messageThunk.ts` 负责**触发状态变更**的异步流程,这对于维护清晰的应用架构至关重要。

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# messageThunk.ts 使用指南
该文件包含用于管理应用程序中消息流、处理助手交互以及同步 Redux 状态与 IndexedDB 数据库的核心 Thunk Action Creators。主要围绕 `Message``MessageBlock` 对象进行操作。
## 核心功能
1. **发送/接收消息**: 处理用户消息的发送,触发助手响应,并流式处理返回的数据,将其解析为不同的 `MessageBlock`
2. **状态管理**: 确保 Redux store 中的消息和消息块状态与 IndexedDB 中的持久化数据保持一致。
3. **消息操作**: 提供删除、重发、重新生成、编辑后重发、追加响应、克隆等消息生命周期管理功能。
4. **Block 处理**: 动态创建、更新和保存各种类型的 `MessageBlock`(文本、思考过程、工具调用、引用、图片、错误、翻译等)。
## 主要 Thunks
以下是一些关键的 Thunk 函数及其用途:
1. **`sendMessage(userMessage, userMessageBlocks, assistant, topicId)`**
- **用途**: 发送一条新的用户消息。
- **流程**:
- 保存用户消息 (`userMessage`) 及其块 (`userMessageBlocks`) 到 Redux 和 DB。
- 检查 `@mentions` 以确定是单模型响应还是多模型响应。
- 创建助手消息(们)的存根 (Stub)。
- 将存根添加到 Redux 和 DB。
- 将核心处理逻辑 `fetchAndProcessAssistantResponseImpl` 添加到该 `topicId` 的队列中以获取实际响应。
- **Block 相关**: 主要处理用户消息的初始 `MessageBlock` 保存。
2. **`fetchAndProcessAssistantResponseImpl(dispatch, getState, topicId, assistant, assistantMessage)`**
- **用途**: (内部函数) 获取并处理单个助手响应的核心逻辑,被 `sendMessage`, `resend...`, `regenerate...`, `append...` 等调用。
- **流程**:
- 设置 Topic 加载状态。
- 准备上下文消息。
- 调用 `fetchChatCompletion` API 服务。
- 使用 `createStreamProcessor` 处理流式响应。
- 通过各种回调 (`onTextChunk`, `onThinkingChunk`, `onToolCallComplete`, `onImageGenerated`, `onError`, `onComplete` 等) 处理不同类型的事件。
- **Block 相关**:
- 根据流事件创建初始 `UNKNOWN` 块。
- 实时创建和更新 `MAIN_TEXT``THINKING` 块,使用 `throttledBlockUpdate``throttledBlockDbUpdate` 进行节流更新。
- 创建 `TOOL`, `CITATION`, `IMAGE`, `ERROR` 等类型的块。
- 在事件完成时(如 `onTextComplete`, `onToolCallComplete`)将块状态标记为 `SUCCESS``ERROR`,并使用 `saveUpdatedBlockToDB` 保存最终状态。
- 使用 `handleBlockTransition` 管理非流式块(如 `TOOL`, `CITATION`)的添加和状态更新。
3. **`loadTopicMessagesThunk(topicId, forceReload)`**
- **用途**: 从数据库加载指定主题的所有消息及其关联的 `MessageBlock`
- **流程**:
- 从 DB 获取 `Topic` 及其 `messages` 列表。
- 根据消息 ID 列表从 DB 获取所有相关的 `MessageBlock`
- 使用 `upsertManyBlocks` 将块更新到 Redux。
- 将消息更新到 Redux。
- **Block 相关**: 负责将持久化的 `MessageBlock` 加载到 Redux 状态。
4. **删除 Thunks**
- `deleteSingleMessageThunk(topicId, messageId)`: 删除单个消息及其所有 `MessageBlock`
- `deleteMessageGroupThunk(topicId, askId)`: 删除一个用户消息及其所有相关的助手响应消息和它们的所有 `MessageBlock`
- `clearTopicMessagesThunk(topicId)`: 清空主题下的所有消息及其所有 `MessageBlock`
- **Block 相关**: 从 Redux 和 DB 中移除指定的 `MessageBlock`
5. **重发/重新生成 Thunks**
- `resendMessageThunk(topicId, userMessageToResend, assistant)`: 重发用户消息。会重置(清空 Block 并标记为 PENDING所有与该用户消息关联的助手响应然后重新请求生成。
- `resendUserMessageWithEditThunk(topicId, originalMessage, mainTextBlockId, editedContent, assistant)`: 用户编辑消息内容后重发。先更新用户消息的 `MAIN_TEXT` 块内容,然后调用 `resendMessageThunk`
- `regenerateAssistantResponseThunk(topicId, assistantMessageToRegenerate, assistant)`: 重新生成单个助手响应。重置该助手消息(清空 Block 并标记为 PENDING然后重新请求生成。
- **Block 相关**: 删除旧的 `MessageBlock`,并在重新生成过程中创建新的 `MessageBlock`
6. **`appendAssistantResponseThunk(topicId, existingAssistantMessageId, newModel, assistant)`**
- **用途**: 在已有的对话上下文中,针对同一个用户问题,使用新选择的模型追加一个新的助手响应。
- **流程**:
- 找到现有助手消息以获取原始 `askId`
- 创建使用 `newModel` 的新助手消息存根(使用相同的 `askId`)。
- 添加新存根到 Redux 和 DB。
-`fetchAndProcessAssistantResponseImpl` 添加到队列以生成新响应。
- **Block 相关**: 为新的助手响应创建全新的 `MessageBlock`
7. **`cloneMessagesToNewTopicThunk(sourceTopicId, branchPointIndex, newTopic)`**
- **用途**: 将源主题的部分消息(及其 Block克隆到一个**已存在**的新主题中。
- **流程**:
- 复制指定索引前的消息。
- 为所有克隆的消息和 Block 生成新的 UUID。
- 正确映射克隆消息之间的 `askId` 关系。
- 复制 `MessageBlock` 内容,更新其 `messageId` 指向新的消息 ID。
- 更新文件引用计数(如果 Block 是文件或图片)。
- 将克隆的消息和 Block 保存到新主题的 Redux 状态和 DB 中。
- **Block 相关**: 创建 `MessageBlock` 的副本,并更新其 ID 和 `messageId`
8. **`initiateTranslationThunk(messageId, topicId, targetLanguage, sourceBlockId?, sourceLanguage?)`**
- **用途**: 为指定消息启动翻译流程,创建一个初始的 `TRANSLATION` 类型的 `MessageBlock`
- **流程**:
- 创建一个状态为 `STREAMING``TranslationMessageBlock`
- 将其添加到 Redux 和 DB。
- 更新原消息的 `blocks` 列表以包含新的翻译块 ID。
- **Block 相关**: 创建并保存一个占位的 `TranslationMessageBlock`。实际翻译内容的获取和填充需要后续步骤。
## 内部机制和注意事项
- **数据库交互**: 通过 `saveMessageAndBlocksToDB`, `updateExistingMessageAndBlocksInDB`, `saveUpdatesToDB`, `saveUpdatedBlockToDB`, `throttledBlockDbUpdate` 等辅助函数与 IndexedDB (`db`) 交互,确保数据持久化。
- **状态同步**: Thunks 负责协调 Redux Store 和 IndexedDB 之间的数据一致性。
- **队列 (`getTopicQueue`)**: 使用 `AsyncQueue` 确保对同一主题的操作(尤其是 API 请求)按顺序执行,避免竞态条件。
- **节流 (`throttle`)**: 对流式响应中频繁的 Block 更新(文本、思考)使用 `lodash.throttle` 优化性能,减少 Redux dispatch 和 DB 写入次数。
- **错误处理**: `fetchAndProcessAssistantResponseImpl` 内的回调函数(特别是 `onError`)处理流处理和 API 调用中可能出现的错误,并创建 `ERROR` 类型的 `MessageBlock`
开发者在使用这些 Thunks 时,通常需要提供 `dispatch`, `getState` (由 Redux Thunk 中间件注入),以及如 `topicId`, `assistant` 配置对象, 相关的 `Message``MessageBlock` 对象/ID 等参数。理解每个 Thunk 的职责和它如何影响消息及块的状态至关重要。

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# useMessageOperations.ts 使用指南
该文件定义了一个名为 `useMessageOperations` 的自定义 React Hook。这个 Hook 的主要目的是为 React 组件提供一个便捷的接口用于执行与特定主题Topic相关的各种消息操作。它封装了调用 Redux Thunks (`messageThunk.ts`) 和 Actions (`newMessage.ts`, `messageBlock.ts`) 的逻辑,简化了组件与消息数据交互的代码。
## 核心目标
- **封装**: 将复杂的消息操作逻辑(如删除、重发、重新生成、编辑、翻译等)封装在易于使用的函数中。
- **简化**: 让组件可以直接调用这些操作函数,而无需直接与 Redux `dispatch` 或 Thunks 交互。
- **上下文关联**: 所有操作都与传入的 `topic` 对象相关联,确保操作作用于正确的主题。
## 如何使用
在你的 React 函数组件中,导入并调用 `useMessageOperations` Hook并传入当前活动的 `Topic` 对象。
```typescript
import React from 'react';
import { useMessageOperations } from '@renderer/hooks/useMessageOperations';
import type { Topic, Message, Assistant, Model } from '@renderer/types';
interface MyComponentProps {
currentTopic: Topic;
currentAssistant: Assistant;
}
function MyComponent({ currentTopic, currentAssistant }: MyComponentProps) {
const {
deleteMessage,
resendMessage,
regenerateAssistantMessage,
appendAssistantResponse,
getTranslationUpdater,
createTopicBranch,
// ... 其他操作函数
} = useMessageOperations(currentTopic);
const handleDelete = (messageId: string) => {
deleteMessage(messageId);
};
const handleResend = (message: Message) => {
resendMessage(message, currentAssistant);
};
const handleAppend = (existingMsg: Message, newModel: Model) => {
appendAssistantResponse(existingMsg, newModel, currentAssistant);
}
// ... 在组件中使用其他操作函数
return (
<div>
{/* Component UI */}
<button onClick={() => handleDelete('some-message-id')}>Delete Message</button>
{/* ... */}
</div>
);
}
```
## 返回值
`useMessageOperations(topic)` Hook 返回一个包含以下函数和值的对象:
- **`deleteMessage(id: string)`**:
- 删除指定 `id` 的单个消息。
- 内部调用 `deleteSingleMessageThunk`
- **`deleteGroupMessages(askId: string)`**:
- 删除与指定 `askId` 相关联的一组消息(通常是用户提问及其所有助手回答)。
- 内部调用 `deleteMessageGroupThunk`
- **`editMessage(messageId: string, updates: Partial<Message>)`**:
- 更新指定 `messageId` 的消息的部分属性。
- **注意**: 目前主要用于更新 Redux 状态
- 内部调用 `newMessagesActions.updateMessage`
- **`resendMessage(message: Message, assistant: Assistant)`**:
- 重新发送指定的用户消息 (`message`),这将触发其所有关联助手响应的重新生成。
- 内部调用 `resendMessageThunk`
- **`resendUserMessageWithEdit(message: Message, editedContent: string, assistant: Assistant)`**:
- 在用户消息的主要文本块被编辑后,重新发送该消息。
- 会先查找消息的 `MAIN_TEXT` 块 ID然后调用 `resendUserMessageWithEditThunk`
- **`clearTopicMessages(_topicId?: string)`**:
- 清除当前主题(或可选的指定 `_topicId`)下的所有消息。
- 内部调用 `clearTopicMessagesThunk`
- **`createNewContext()`**:
- 发出一个全局事件 (`EVENT_NAMES.NEW_CONTEXT`),通常用于通知 UI 清空显示,准备新的上下文。不直接修改 Redux 状态。
- **`displayCount`**:
- (非操作函数) 从 Redux store 中获取当前的 `displayCount` 值。
- **`pauseMessages()`**:
- 尝试中止当前主题中正在进行的消息生成(状态为 `processing``pending`)。
- 通过查找相关的 `askId` 并调用 `abortCompletion` 来实现。
- 同时会 dispatch `setTopicLoading` action 将加载状态设为 `false`
- **`resumeMessage(message: Message, assistant: Assistant)`**:
- 恢复/重新发送一个用户消息。目前实现为直接调用 `resendMessage`
- **`regenerateAssistantMessage(message: Message, assistant: Assistant)`**:
- 重新生成指定的**助手**消息 (`message`) 的响应。
- 内部调用 `regenerateAssistantResponseThunk`
- **`appendAssistantResponse(existingAssistantMessage: Message, newModel: Model, assistant: Assistant)`**:
- 针对 `existingAssistantMessage` 所回复的**同一用户提问**,使用 `newModel` 追加一个新的助手响应。
- 内部调用 `appendAssistantResponseThunk`
- **`getTranslationUpdater(messageId: string, targetLanguage: string, sourceBlockId?: string, sourceLanguage?: string)`**:
- **用途**: 获取一个用于逐步更新翻译块内容的函数。
- **流程**:
1. 内部调用 `initiateTranslationThunk` 来创建或获取一个 `TRANSLATION` 类型的 `MessageBlock`,并获取其 `blockId`
2. 返回一个**异步更新函数**。
- **返回的更新函数 `(accumulatedText: string, isComplete?: boolean) => void`**:
- 接收累积的翻译文本和完成状态。
- 调用 `updateOneBlock` 更新 Redux 中的翻译块内容和状态 (`STREAMING``SUCCESS`)。
- 调用 `throttledBlockDbUpdate` 将更新(节流地)保存到数据库。
- 如果初始化失败Thunk 返回 `undefined`),则此函数返回 `null`
- **`createTopicBranch(sourceTopicId: string, branchPointIndex: number, newTopic: Topic)`**:
- 创建一个主题分支,将 `sourceTopicId` 主题中 `branchPointIndex` 索引之前的消息克隆到 `newTopic` 中。
- **注意**: `newTopic` 对象必须是调用此函数**之前**已经创建并添加到 Redux 和数据库中的。
- 内部调用 `cloneMessagesToNewTopicThunk`
## 依赖
- **`topic: Topic`**: 必须传入当前操作上下文的主题对象。Hook 返回的操作函数将始终作用于这个主题的 `topic.id`
- **Redux `dispatch`**: Hook 内部使用 `useAppDispatch` 获取 `dispatch` 函数来调用 actions 和 thunks。
## 相关 Hooks
在同一文件中还定义了两个辅助 Hook
- **`useTopicMessages(topic: Topic)`**:
- 使用 `selectMessagesForTopic` selector 来获取并返回指定主题的消息列表。
- **`useTopicLoading(topic: Topic)`**:
- 使用 `selectNewTopicLoading` selector 来获取并返回指定主题的加载状态。
这些 Hook 可以与 `useMessageOperations` 结合使用,方便地在组件中获取消息数据、加载状态,并执行相关操作。

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### Participating in the Test Plan
Developers should submit `PRs` according to the [Contributor Guide](../../CONTRIBUTING.md) (and ensure the target branch is `main`). The repository maintainers will evaluate whether the `PR` should be included in the Test Plan based on factors such as the impact of the feature on the application, its importance, and whether broader testing is needed.
Developers should submit `PRs` according to the [Contributor Guide](../CONTRIBUTING.md) (and ensure the target branch is `main`). The repository maintainers will evaluate whether the `PR` should be included in the Test Plan based on factors such as the impact of the feature on the application, its importance, and whether broader testing is needed.
If the `PR` is added to the Test Plan, the repository maintainers will:

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### 参与测试计划
开发者按照[贡献者指南](./contributing.md)要求正常提交`PR`并注意提交target为`main`)。仓库维护者会综合考虑(例如该功能对应用的影响程度,功能的重要性,是否需要更广泛的测试等),决定该`PR`是否应加入测试计划。
开发者按照[贡献者指南](CONTRIBUTING.zh.md)要求正常提交`PR`并注意提交target为`main`)。仓库维护者会综合考虑(例如该功能对应用的影响程度,功能的重要性,是否需要更广泛的测试等),决定该`PR`是否应加入测试计划。
若该`PR`加入测试计划,仓库维护者会做如下操作:

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# 🖥️ Develop
## IDE Setup
- Editor: [Cursor](https://www.cursor.com/), etc. Any VS Code compatible editor.
- Linter: [ESLint](https://marketplace.visualstudio.com/items?itemName=dbaeumer.vscode-eslint)
- Formatter: [Biome](https://marketplace.visualstudio.com/items?itemName=biomejs.biome)
## Project Setup
### Install
```bash
yarn
```
### Development
### Setup Node.js
Download and install [Node.js v22.x.x](https://nodejs.org/en/download)
### Setup Yarn
```bash
corepack enable
corepack prepare yarn@4.9.1 --activate
```
### Install Dependencies
```bash
yarn install
```
### ENV
```bash
copy .env.example .env
```
### Start
```bash
yarn dev
```
### Debug
```bash
yarn debug
```
Then input chrome://inspect in browser
### Test
```bash
yarn test
```
### Build
```bash
# For windows
$ yarn build:win
# For macOS
$ yarn build:mac
# For Linux
$ yarn build:linux
```

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# 消息系统
本文档介绍 Cherry Studio 的消息系统架构,包括消息生命周期、状态管理和操作接口。
## 消息的生命周期
![消息生命周期](../../assets/images/message-lifecycle.png)
---
# messageBlock.ts 使用指南
该文件定义了用于管理应用程序中所有 `MessageBlock` 实体的 Redux Slice。它使用 Redux Toolkit 的 `createSlice``createEntityAdapter` 来高效地处理规范化的状态,并提供了一系列 actions 和 selectors 用于与消息块数据交互。
## 核心目标
- **状态管理**: 集中管理所有 `MessageBlock` 的状态。`MessageBlock` 代表消息中的不同内容单元(如文本、代码、图片、引用等)。
- **规范化**: 使用 `createEntityAdapter``MessageBlock` 数据存储在规范化的结构中(`{ ids: [], entities: {} }`),这有助于提高性能和简化更新逻辑。
- **可预测性**: 提供明确的 actions 来修改状态,并通过 selectors 安全地访问状态。
## 关键概念
- **Slice (`createSlice`)**: Redux Toolkit 的核心 API用于创建包含 reducer 逻辑、action creators 和初始状态的 Redux 模块。
- **Entity Adapter (`createEntityAdapter`)**: Redux Toolkit 提供的工具,用于简化对规范化数据的 CRUD创建、读取、更新、删除操作。它会自动生成 reducer 函数和 selectors。
- **Selectors**: 用于从 Redux store 中派生和计算数据的函数。Selectors 可以被记忆化memoized以提高性能。
## State 结构
`messageBlocks` slice 的状态结构由 `createEntityAdapter` 定义,大致如下:
```typescript
{
ids: string[]; // 存储所有 MessageBlock ID 的有序列表
entities: { [id: string]: MessageBlock }; // 按 ID 存储 MessageBlock 对象的字典
loadingState: 'idle' | 'loading' | 'succeeded' | 'failed'; // (可选) 其他状态,如加载状态
error: string | null; // (可选) 错误信息
}
```
## Actions
该 slice 导出以下 actions (由 `createSlice``createEntityAdapter` 自动生成或自定义)
- **`upsertOneBlock(payload: MessageBlock)`**:
- 添加一个新的 `MessageBlock` 或更新一个已存在的 `MessageBlock`。如果 payload 中的 `id` 已存在,则执行更新;否则执行插入。
- **`upsertManyBlocks(payload: MessageBlock[])`**:
- 添加或更新多个 `MessageBlock`。常用于批量加载数据(例如,加载一个 Topic 的所有消息块)。
- **`removeOneBlock(payload: string)`**:
- 根据提供的 `id` (payload) 移除单个 `MessageBlock`
- **`removeManyBlocks(payload: string[])`**:
- 根据提供的 `id` 数组 (payload) 移除多个 `MessageBlock`。常用于删除消息或清空 Topic 时清理相关的块。
- **`removeAllBlocks()`**:
- 移除 state 中的所有 `MessageBlock` 实体。
- **`updateOneBlock(payload: { id: string; changes: Partial<MessageBlock> })`**:
- 更新一个已存在的 `MessageBlock``payload` 需要包含块的 `id` 和一个包含要更改的字段的 `changes` 对象。
- **`setMessageBlocksLoading(payload: 'idle' | 'loading')`**:
- (自定义) 设置 `loadingState` 属性。
- **`setMessageBlocksError(payload: string)`**:
- (自定义) 设置 `loadingState``'failed'` 并记录错误信息。
**使用示例 (在 Thunk 或其他 Dispatch 的地方):**
```typescript
import { upsertOneBlock, removeManyBlocks, updateOneBlock } from './messageBlock'
import store from './store' // 假设这是你的 Redux store 实例
// 添加或更新一个块
const newBlock: MessageBlock = {
/* ... block data ... */
}
store.dispatch(upsertOneBlock(newBlock))
// 更新一个块的内容
store.dispatch(updateOneBlock({ id: blockId, changes: { content: 'New content' } }))
// 删除多个块
const blockIdsToRemove = ['id1', 'id2']
store.dispatch(removeManyBlocks(blockIdsToRemove))
```
## Selectors
该 slice 导出由 `createEntityAdapter` 生成的基础 selectors并通过 `messageBlocksSelectors` 对象访问:
- **`messageBlocksSelectors.selectIds(state: RootState): string[]`**: 返回包含所有块 ID 的数组。
- **`messageBlocksSelectors.selectEntities(state: RootState): { [id: string]: MessageBlock }`**: 返回块 ID 到块对象的映射字典。
- **`messageBlocksSelectors.selectAll(state: RootState): MessageBlock[]`**: 返回包含所有块对象的数组。
- **`messageBlocksSelectors.selectTotal(state: RootState): number`**: 返回块的总数。
- **`messageBlocksSelectors.selectById(state: RootState, id: string): MessageBlock | undefined`**: 根据 ID 返回单个块对象,如果找不到则返回 `undefined`
**此外,还提供了一个自定义的、记忆化的 selector**
- **`selectFormattedCitationsByBlockId(state: RootState, blockId: string | undefined): Citation[]`**:
- 接收一个 `blockId`
- 如果该 ID 对应的块是 `CITATION` 类型,则提取并格式化其包含的引用信息(来自网页搜索、知识库等),进行去重和重新编号,最后返回一个 `Citation[]` 数组,用于在 UI 中显示。
- 如果块不存在或类型不匹配,返回空数组 `[]`
- 这个 selector 封装了处理不同引用来源Gemini, OpenAI, OpenRouter, Zhipu 等)的复杂逻辑。
**使用示例 (在 React 组件或 `useSelector` 中):**
```typescript
import { useSelector } from 'react-redux'
import { messageBlocksSelectors, selectFormattedCitationsByBlockId } from './messageBlock'
import type { RootState } from './store'
// 获取所有块
const allBlocks = useSelector(messageBlocksSelectors.selectAll)
// 获取特定 ID 的块
const specificBlock = useSelector((state: RootState) => messageBlocksSelectors.selectById(state, someBlockId))
// 获取特定引用块格式化后的引用列表
const formattedCitations = useSelector((state: RootState) => selectFormattedCitationsByBlockId(state, citationBlockId))
// 在组件中使用引用数据
// {formattedCitations.map(citation => ...)}
```
## 集成
`messageBlock.ts` slice 通常与 `messageThunk.ts` 中的 Thunks 紧密协作。Thunks 负责处理异步逻辑(如 API 调用、数据库操作),并在需要时 dispatch `messageBlock` slice 的 actions 来更新状态。例如,当 `messageThunk` 接收到流式响应时,它会 dispatch `upsertOneBlock``updateOneBlock` 来实时更新对应的 `MessageBlock`。同样,删除消息的 Thunk 会 dispatch `removeManyBlocks`
理解 `messageBlock.ts` 的职责是管理**状态本身**,而 `messageThunk.ts` 负责**触发状态变更**的异步流程,这对于维护清晰的应用架构至关重要。
---
# messageThunk.ts 使用指南
该文件包含用于管理应用程序中消息流、处理助手交互以及同步 Redux 状态与 IndexedDB 数据库的核心 Thunk Action Creators。主要围绕 `Message``MessageBlock` 对象进行操作。
## 核心功能
1. **发送/接收消息**: 处理用户消息的发送,触发助手响应,并流式处理返回的数据,将其解析为不同的 `MessageBlock`
2. **状态管理**: 确保 Redux store 中的消息和消息块状态与 IndexedDB 中的持久化数据保持一致。
3. **消息操作**: 提供删除、重发、重新生成、编辑后重发、追加响应、克隆等消息生命周期管理功能。
4. **Block 处理**: 动态创建、更新和保存各种类型的 `MessageBlock`(文本、思考过程、工具调用、引用、图片、错误、翻译等)。
## 主要 Thunks
以下是一些关键的 Thunk 函数及其用途:
1. **`sendMessage(userMessage, userMessageBlocks, assistant, topicId)`**
- **用途**: 发送一条新的用户消息。
- **流程**:
- 保存用户消息 (`userMessage`) 及其块 (`userMessageBlocks`) 到 Redux 和 DB。
- 检查 `@mentions` 以确定是单模型响应还是多模型响应。
- 创建助手消息(们)的存根 (Stub)。
- 将存根添加到 Redux 和 DB。
- 将核心处理逻辑 `fetchAndProcessAssistantResponseImpl` 添加到该 `topicId` 的队列中以获取实际响应。
- **Block 相关**: 主要处理用户消息的初始 `MessageBlock` 保存。
2. **`fetchAndProcessAssistantResponseImpl(dispatch, getState, topicId, assistant, assistantMessage)`**
- **用途**: (内部函数) 获取并处理单个助手响应的核心逻辑,被 `sendMessage`, `resend...`, `regenerate...`, `append...` 等调用。
- **流程**:
- 设置 Topic 加载状态。
- 准备上下文消息。
- 调用 `fetchChatCompletion` API 服务。
- 使用 `createStreamProcessor` 处理流式响应。
- 通过各种回调 (`onTextChunk`, `onThinkingChunk`, `onToolCallComplete`, `onImageGenerated`, `onError`, `onComplete` 等) 处理不同类型的事件。
- **Block 相关**:
- 根据流事件创建初始 `UNKNOWN` 块。
- 实时创建和更新 `MAIN_TEXT``THINKING` 块,使用 `throttledBlockUpdate``throttledBlockDbUpdate` 进行节流更新。
- 创建 `TOOL`, `CITATION`, `IMAGE`, `ERROR` 等类型的块。
- 在事件完成时(如 `onTextComplete`, `onToolCallComplete`)将块状态标记为 `SUCCESS``ERROR`,并使用 `saveUpdatedBlockToDB` 保存最终状态。
- 使用 `handleBlockTransition` 管理非流式块(如 `TOOL`, `CITATION`)的添加和状态更新。
3. **`loadTopicMessagesThunk(topicId, forceReload)`**
- **用途**: 从数据库加载指定主题的所有消息及其关联的 `MessageBlock`
- **流程**:
- 从 DB 获取 `Topic` 及其 `messages` 列表。
- 根据消息 ID 列表从 DB 获取所有相关的 `MessageBlock`
- 使用 `upsertManyBlocks` 将块更新到 Redux。
- 将消息更新到 Redux。
- **Block 相关**: 负责将持久化的 `MessageBlock` 加载到 Redux 状态。
4. **删除 Thunks**
- `deleteSingleMessageThunk(topicId, messageId)`: 删除单个消息及其所有 `MessageBlock`
- `deleteMessageGroupThunk(topicId, askId)`: 删除一个用户消息及其所有相关的助手响应消息和它们的所有 `MessageBlock`
- `clearTopicMessagesThunk(topicId)`: 清空主题下的所有消息及其所有 `MessageBlock`
- **Block 相关**: 从 Redux 和 DB 中移除指定的 `MessageBlock`
5. **重发/重新生成 Thunks**
- `resendMessageThunk(topicId, userMessageToResend, assistant)`: 重发用户消息。会重置(清空 Block 并标记为 PENDING所有与该用户消息关联的助手响应然后重新请求生成。
- `resendUserMessageWithEditThunk(topicId, originalMessage, mainTextBlockId, editedContent, assistant)`: 用户编辑消息内容后重发。先更新用户消息的 `MAIN_TEXT` 块内容,然后调用 `resendMessageThunk`
- `regenerateAssistantResponseThunk(topicId, assistantMessageToRegenerate, assistant)`: 重新生成单个助手响应。重置该助手消息(清空 Block 并标记为 PENDING然后重新请求生成。
- **Block 相关**: 删除旧的 `MessageBlock`,并在重新生成过程中创建新的 `MessageBlock`
6. **`appendAssistantResponseThunk(topicId, existingAssistantMessageId, newModel, assistant)`**
- **用途**: 在已有的对话上下文中,针对同一个用户问题,使用新选择的模型追加一个新的助手响应。
- **流程**:
- 找到现有助手消息以获取原始 `askId`
- 创建使用 `newModel` 的新助手消息存根(使用相同的 `askId`)。
- 添加新存根到 Redux 和 DB。
-`fetchAndProcessAssistantResponseImpl` 添加到队列以生成新响应。
- **Block 相关**: 为新的助手响应创建全新的 `MessageBlock`
7. **`cloneMessagesToNewTopicThunk(sourceTopicId, branchPointIndex, newTopic)`**
- **用途**: 将源主题的部分消息(及其 Block克隆到一个**已存在**的新主题中。
- **流程**:
- 复制指定索引前的消息。
- 为所有克隆的消息和 Block 生成新的 UUID。
- 正确映射克隆消息之间的 `askId` 关系。
- 复制 `MessageBlock` 内容,更新其 `messageId` 指向新的消息 ID。
- 更新文件引用计数(如果 Block 是文件或图片)。
- 将克隆的消息和 Block 保存到新主题的 Redux 状态和 DB 中。
- **Block 相关**: 创建 `MessageBlock` 的副本,并更新其 ID 和 `messageId`
8. **`initiateTranslationThunk(messageId, topicId, targetLanguage, sourceBlockId?, sourceLanguage?)`**
- **用途**: 为指定消息启动翻译流程,创建一个初始的 `TRANSLATION` 类型的 `MessageBlock`
- **流程**:
- 创建一个状态为 `STREAMING``TranslationMessageBlock`
- 将其添加到 Redux 和 DB。
- 更新原消息的 `blocks` 列表以包含新的翻译块 ID。
- **Block 相关**: 创建并保存一个占位的 `TranslationMessageBlock`。实际翻译内容的获取和填充需要后续步骤。
## 内部机制和注意事项
- **数据库交互**: 通过 `saveMessageAndBlocksToDB`, `updateExistingMessageAndBlocksInDB`, `saveUpdatesToDB`, `saveUpdatedBlockToDB`, `throttledBlockDbUpdate` 等辅助函数与 IndexedDB (`db`) 交互,确保数据持久化。
- **状态同步**: Thunks 负责协调 Redux Store 和 IndexedDB 之间的数据一致性。
- **队列 (`getTopicQueue`)**: 使用 `AsyncQueue` 确保对同一主题的操作(尤其是 API 请求)按顺序执行,避免竞态条件。
- **节流 (`throttle`)**: 对流式响应中频繁的 Block 更新(文本、思考)使用 `lodash.throttle` 优化性能,减少 Redux dispatch 和 DB 写入次数。
- **错误处理**: `fetchAndProcessAssistantResponseImpl` 内的回调函数(特别是 `onError`)处理流处理和 API 调用中可能出现的错误,并创建 `ERROR` 类型的 `MessageBlock`
开发者在使用这些 Thunks 时,通常需要提供 `dispatch`, `getState` (由 Redux Thunk 中间件注入),以及如 `topicId`, `assistant` 配置对象, 相关的 `Message``MessageBlock` 对象/ID 等参数。理解每个 Thunk 的职责和它如何影响消息及块的状态至关重要。
---
# useMessageOperations.ts 使用指南
该文件定义了一个名为 `useMessageOperations` 的自定义 React Hook。这个 Hook 的主要目的是为 React 组件提供一个便捷的接口用于执行与特定主题Topic相关的各种消息操作。它封装了调用 Redux Thunks (`messageThunk.ts`) 和 Actions (`newMessage.ts`, `messageBlock.ts`) 的逻辑,简化了组件与消息数据交互的代码。
## 核心目标
- **封装**: 将复杂的消息操作逻辑(如删除、重发、重新生成、编辑、翻译等)封装在易于使用的函数中。
- **简化**: 让组件可以直接调用这些操作函数,而无需直接与 Redux `dispatch` 或 Thunks 交互。
- **上下文关联**: 所有操作都与传入的 `topic` 对象相关联,确保操作作用于正确的主题。
## 如何使用
在你的 React 函数组件中,导入并调用 `useMessageOperations` Hook并传入当前活动的 `Topic` 对象。
```typescript
import React from 'react';
import { useMessageOperations } from '@renderer/hooks/useMessageOperations';
import type { Topic, Message, Assistant, Model } from '@renderer/types';
interface MyComponentProps {
currentTopic: Topic;
currentAssistant: Assistant;
}
function MyComponent({ currentTopic, currentAssistant }: MyComponentProps) {
const {
deleteMessage,
resendMessage,
regenerateAssistantMessage,
appendAssistantResponse,
getTranslationUpdater,
createTopicBranch,
// ... 其他操作函数
} = useMessageOperations(currentTopic);
const handleDelete = (messageId: string) => {
deleteMessage(messageId);
};
const handleResend = (message: Message) => {
resendMessage(message, currentAssistant);
};
const handleAppend = (existingMsg: Message, newModel: Model) => {
appendAssistantResponse(existingMsg, newModel, currentAssistant);
}
// ... 在组件中使用其他操作函数
return (
<div>
{/* Component UI */}
<button onClick={() => handleDelete('some-message-id')}>Delete Message</button>
{/* ... */}
</div>
);
}
```
## 返回值
`useMessageOperations(topic)` Hook 返回一个包含以下函数和值的对象:
- **`deleteMessage(id: string)`**:
- 删除指定 `id` 的单个消息。
- 内部调用 `deleteSingleMessageThunk`
- **`deleteGroupMessages(askId: string)`**:
- 删除与指定 `askId` 相关联的一组消息(通常是用户提问及其所有助手回答)。
- 内部调用 `deleteMessageGroupThunk`
- **`editMessage(messageId: string, updates: Partial<Message>)`**:
- 更新指定 `messageId` 的消息的部分属性。
- **注意**: 目前主要用于更新 Redux 状态
- 内部调用 `newMessagesActions.updateMessage`
- **`resendMessage(message: Message, assistant: Assistant)`**:
- 重新发送指定的用户消息 (`message`),这将触发其所有关联助手响应的重新生成。
- 内部调用 `resendMessageThunk`
- **`resendUserMessageWithEdit(message: Message, editedContent: string, assistant: Assistant)`**:
- 在用户消息的主要文本块被编辑后,重新发送该消息。
- 会先查找消息的 `MAIN_TEXT` 块 ID然后调用 `resendUserMessageWithEditThunk`
- **`clearTopicMessages(_topicId?: string)`**:
- 清除当前主题(或可选的指定 `_topicId`)下的所有消息。
- 内部调用 `clearTopicMessagesThunk`
- **`createNewContext()`**:
- 发出一个全局事件 (`EVENT_NAMES.NEW_CONTEXT`),通常用于通知 UI 清空显示,准备新的上下文。不直接修改 Redux 状态。
- **`displayCount`**:
- (非操作函数) 从 Redux store 中获取当前的 `displayCount` 值。
- **`pauseMessages()`**:
- 尝试中止当前主题中正在进行的消息生成(状态为 `processing``pending`)。
- 通过查找相关的 `askId` 并调用 `abortCompletion` 来实现。
- 同时会 dispatch `setTopicLoading` action 将加载状态设为 `false`
- **`resumeMessage(message: Message, assistant: Assistant)`**:
- 恢复/重新发送一个用户消息。目前实现为直接调用 `resendMessage`
- **`regenerateAssistantMessage(message: Message, assistant: Assistant)`**:
- 重新生成指定的**助手**消息 (`message`) 的响应。
- 内部调用 `regenerateAssistantResponseThunk`
- **`appendAssistantResponse(existingAssistantMessage: Message, newModel: Model, assistant: Assistant)`**:
- 针对 `existingAssistantMessage` 所回复的**同一用户提问**,使用 `newModel` 追加一个新的助手响应。
- 内部调用 `appendAssistantResponseThunk`
- **`getTranslationUpdater(messageId: string, targetLanguage: string, sourceBlockId?: string, sourceLanguage?: string)`**:
- **用途**: 获取一个用于逐步更新翻译块内容的函数。
- **流程**:
1. 内部调用 `initiateTranslationThunk` 来创建或获取一个 `TRANSLATION` 类型的 `MessageBlock`,并获取其 `blockId`
2. 返回一个**异步更新函数**。
- **返回的更新函数 `(accumulatedText: string, isComplete?: boolean) => void`**:
- 接收累积的翻译文本和完成状态。
- 调用 `updateOneBlock` 更新 Redux 中的翻译块内容和状态 (`STREAMING``SUCCESS`)。
- 调用 `throttledBlockDbUpdate` 将更新(节流地)保存到数据库。
- 如果初始化失败Thunk 返回 `undefined`),则此函数返回 `null`
- **`createTopicBranch(sourceTopicId: string, branchPointIndex: number, newTopic: Topic)`**:
- 创建一个主题分支,将 `sourceTopicId` 主题中 `branchPointIndex` 索引之前的消息克隆到 `newTopic` 中。
- **注意**: `newTopic` 对象必须是调用此函数**之前**已经创建并添加到 Redux 和数据库中的。
- 内部调用 `cloneMessagesToNewTopicThunk`
## 依赖
- **`topic: Topic`**: 必须传入当前操作上下文的主题对象。Hook 返回的操作函数将始终作用于这个主题的 `topic.id`
- **Redux `dispatch`**: Hook 内部使用 `useAppDispatch` 获取 `dispatch` 函数来调用 actions 和 thunks。
## 相关 Hooks
在同一文件中还定义了两个辅助 Hook
- **`useTopicMessages(topic: Topic)`**:
- 使用 `selectMessagesForTopic` selector 来获取并返回指定主题的消息列表。
- **`useTopicLoading(topic: Topic)`**:
- 使用 `selectNewTopicLoading` selector 来获取并返回指定主题的加载状态。
这些 Hook 可以与 `useMessageOperations` 结合使用,方便地在组件中获取消息数据、加载状态,并执行相关操作。

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@@ -135,108 +135,58 @@ artifactBuildCompleted: scripts/artifact-build-completed.js
releaseInfo:
releaseNotes: |
<!--LANG:en-->
A New Era of Intelligence with Cherry Studio 1.7.1
What's New in v1.7.0-rc.1
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- Languages: Added German language support
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🖼️ Image & OCR
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The Agent Era is here. We can't wait to see what you'll create.
🐛 Important Bug Fixes:
- Fixed streaming response issues across multiple AI providers
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<!--LANG:zh-CN-->
Cherry Studio 1.7.1:开启智能新纪元
v1.7.0-rc.1 新特性
今天,我们正式发布 Cherry Studio 1.7.1 —— 迄今最具雄心的版本,带来全新的 Agent能够自主思考、规划和行动的 AI。
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- 支持斜杠命令快速交互
- 兼容 OpenAI 的 REST API 访问
多年来AI 助手一直是被动的——等待你的指令回应你的问题。Agent 改变了这一切。现在AI 能够真正与你并肩工作:理解复杂目标,将其拆解为步骤,并独立执行。
✨ 新功能:
- AI 提供商:新增 Hugging Face、Mistral、Perplexity 和 SophNet 支持
- 知识库OpenMinerU 文档预处理器、笔记全文搜索、增强的工具选择
- 图像与 OCRIntel OVMS 绘图提供商和 Intel OpenVINO (NPU) OCR 支持
- MCP 管理:重构管理界面,采用双列布局,更加方便管理
- 语言:新增德语支持
这是我们一直在构建的未来。而这,仅仅是开始。
⚡ 改进:
- 升级到 Electron 38.7.0
- 增强的系统关机处理和自动更新检查
- 改进的代理绕过规则
🤖 认识 Agent
想象一位永不疲倦的得力伙伴。给 Agent 一个目标——撰写报告、分析数据、重构代码——然后看它工作。它会推理问题、拆解步骤、调用工具,并在情况变化时灵活应对。
- **思考 → 规划 → 行动**:从目标到执行,全程自主
- **深度推理**:多轮思考,解决真实问题
- **工具大师**:文件操作、网络搜索、代码执行,样样精通
- **技能插件**:自定义命令,无限扩展
- **你掌控全局**:敏感操作,实时审批
- **完全透明**:每一步思考,每一个决策,清晰可见
🌐 生态持续壮大
- **新增服务商**Hugging Face、Mistral、Perplexity、SophNet、AI Gateway、Cerebras AI
- **新增模型**Gemini 3、Gemini 3 Pro支持图像预览、GPT-5.1、Claude Opus 4.5
- **MCP 集成**百炼、魔搭、Higress、MCP.so、TokenFlux 等平台
📚 更智能的知识库
- **OpenMinerU**:本地自部署文档处理
- **全文搜索**:笔记内容一搜即达
- **增强工具选择**:更智能的配置,更好的 AI 协助
📝 笔记,焕然一新
- 全文搜索,结果高亮
- AI 智能重命名
- 导出为图片
- 表格自动换行
🖼️ 图像与 OCR
- Intel OVMS 绘图能力
- Intel OpenVINO NPU 加速 OCR
🌍 支持 10+ 种语言
- 新增德语支持
- 全面增强国际化
⚡ 更快、更精致
- 升级 Electron 38
- 新的 MCP 管理界面
- 数十处 UI 细节打磨
❤️ 完全开源
商用限制已移除。Cherry Studio 现遵循标准 AGPL v3 协议——任意规模团队均可自由使用。
Agent 纪元已至。期待你的创造。
🐛 重要修复:
- 修复多个 AI 提供商的流式响应问题
- 修复会话列表滚动问题
- 修复知识库删除错误
<!--LANG:END-->

View File

@@ -113,7 +113,8 @@ export default defineConfig({
'@cherrystudio/extension-table-plus': resolve('packages/extension-table-plus/src'),
'@cherrystudio/ai-sdk-provider': resolve('packages/ai-sdk-provider/src'),
'@cherrystudio/ui/icons': resolve('packages/ui/src/components/icons'),
'@cherrystudio/ui': resolve('packages/ui/src')
'@cherrystudio/ui': resolve('packages/ui/src'),
'@cherrystudio/catalog': resolve('packages/catalog/src')
}
},
optimizeDeps: {

View File

@@ -58,7 +58,6 @@ export default defineConfig([
'dist/**',
'out/**',
'local/**',
'tests/**',
'.yarn/**',
'.gitignore',
'scripts/cloudflare-worker.js',
@@ -143,87 +142,19 @@ export default defineConfig([
files: ['**/*.{ts,tsx,js,jsx}'],
ignores: [],
rules: {
'no-restricted-imports': [
'error',
{
paths: [
// {
// name: 'antd',
// importNames: ['Flex', 'Switch', 'message', 'Button', 'Tooltip'],
// message:
// '❌ Do not import this component from antd. Use our custom components instead: import { ... } from "@cherrystudio/ui"'
// },
{
name: 'antd',
importNames: ['Switch'],
message:
'❌ Do not import this component from antd. Use our custom components instead: import { ... } from "@cherrystudio/ui"'
},
{
name: '@heroui/react',
importNames: ['Switch'],
message:
'❌ Do not import the component from heroui directly. It\'s deprecated.'
}
]
}
]
// 'no-restricted-imports': [
// 'error',
// {
// paths: [
// {
// name: 'antd',
// importNames: ['Flex', 'Switch', 'message', 'Button', 'Tooltip'],
// message:
// '❌ Do not import this component from antd. Use our custom components instead: import { ... } from "@cherrystudio/ui"'
// }
// ]
// }
// ]
}
},
// Schema key naming convention (cache & preferences)
{
files: ['packages/shared/data/cache/cacheSchemas.ts', 'packages/shared/data/preference/preferenceSchemas.ts'],
plugins: {
'data-schema-key': {
rules: {
'valid-key': {
meta: {
type: 'problem',
docs: {
description: 'Enforce schema key naming convention: namespace.sub.key_name',
recommended: true
},
messages: {
invalidKey:
'Schema key "{{key}}" must follow format: namespace.sub.key_name (e.g., app.user.avatar).'
}
},
create(context) {
const VALID_KEY_PATTERN = /^[a-z][a-z0-9_]*(\.[a-z][a-z0-9_]*)+$/
return {
TSPropertySignature(node) {
if (node.key.type === 'Literal' && typeof node.key.value === 'string') {
const key = node.key.value
if (!VALID_KEY_PATTERN.test(key)) {
context.report({
node: node.key,
messageId: 'invalidKey',
data: { key }
})
}
}
},
Property(node) {
if (node.key.type === 'Literal' && typeof node.key.value === 'string') {
const key = node.key.value
if (!VALID_KEY_PATTERN.test(key)) {
context.report({
node: node.key,
messageId: 'invalidKey',
data: { key }
})
}
}
}
}
}
}
}
}
},
rules: {
'data-schema-key/valid-key': 'error'
}
}
])

View File

@@ -63,7 +63,6 @@
"test": "vitest run --silent",
"test:main": "vitest run --project main",
"test:renderer": "vitest run --project renderer",
"test:aicore": "vitest run --project aiCore",
"test:update": "yarn test:renderer --update",
"test:coverage": "vitest run --coverage --silent",
"test:ui": "vitest --ui",
@@ -84,7 +83,7 @@
"release:ai-sdk-provider": "yarn workspace @cherrystudio/ai-sdk-provider version patch --immediate && yarn workspace @cherrystudio/ai-sdk-provider build && yarn workspace @cherrystudio/ai-sdk-provider npm publish --access public"
},
"dependencies": {
"@anthropic-ai/claude-agent-sdk": "patch:@anthropic-ai/claude-agent-sdk@npm%3A0.1.53#~/.yarn/patches/@anthropic-ai-claude-agent-sdk-npm-0.1.53-4b77f4cf29.patch",
"@anthropic-ai/claude-agent-sdk": "patch:@anthropic-ai/claude-agent-sdk@npm%3A0.1.30#~/.yarn/patches/@anthropic-ai-claude-agent-sdk-npm-0.1.30-b50a299674.patch",
"@libsql/client": "0.14.0",
"@libsql/win32-x64-msvc": "^0.4.7",
"@napi-rs/system-ocr": "patch:@napi-rs/system-ocr@npm%3A1.0.2#~/.yarn/patches/@napi-rs-system-ocr-npm-1.0.2-59e7a78e8b.patch",
@@ -114,17 +113,16 @@
"@agentic/exa": "^7.3.3",
"@agentic/searxng": "^7.3.3",
"@agentic/tavily": "^7.3.3",
"@ai-sdk/amazon-bedrock": "^3.0.61",
"@ai-sdk/anthropic": "^2.0.49",
"@ai-sdk/amazon-bedrock": "^3.0.53",
"@ai-sdk/anthropic": "^2.0.44",
"@ai-sdk/cerebras": "^1.0.31",
"@ai-sdk/gateway": "^2.0.15",
"@ai-sdk/google": "patch:@ai-sdk/google@npm%3A2.0.43#~/.yarn/patches/@ai-sdk-google-npm-2.0.43-689ed559b3.patch",
"@ai-sdk/google-vertex": "^3.0.79",
"@ai-sdk/huggingface": "^0.0.10",
"@ai-sdk/mistral": "^2.0.24",
"@ai-sdk/openai": "patch:@ai-sdk/openai@npm%3A2.0.72#~/.yarn/patches/@ai-sdk-openai-npm-2.0.72-234e68da87.patch",
"@ai-sdk/perplexity": "^2.0.20",
"@ai-sdk/test-server": "^0.0.1",
"@ai-sdk/gateway": "^2.0.9",
"@ai-sdk/google": "patch:@ai-sdk/google@npm%3A2.0.36#~/.yarn/patches/@ai-sdk-google-npm-2.0.36-6f3cc06026.patch",
"@ai-sdk/google-vertex": "^3.0.68",
"@ai-sdk/huggingface": "patch:@ai-sdk/huggingface@npm%3A0.0.8#~/.yarn/patches/@ai-sdk-huggingface-npm-0.0.8-d4d0aaac93.patch",
"@ai-sdk/mistral": "^2.0.23",
"@ai-sdk/openai": "patch:@ai-sdk/openai@npm%3A2.0.64#~/.yarn/patches/@ai-sdk-openai-npm-2.0.64-48f99f5bf3.patch",
"@ai-sdk/perplexity": "^2.0.17",
"@ant-design/v5-patch-for-react-19": "^1.0.3",
"@anthropic-ai/sdk": "^0.41.0",
"@anthropic-ai/vertex-sdk": "patch:@anthropic-ai/vertex-sdk@npm%3A0.11.4#~/.yarn/patches/@anthropic-ai-vertex-sdk-npm-0.11.4-c19cb41edb.patch",
@@ -169,17 +167,16 @@
"@modelcontextprotocol/sdk": "^1.17.5",
"@mozilla/readability": "^0.6.0",
"@notionhq/client": "^2.2.15",
"@openrouter/ai-sdk-provider": "^1.2.8",
"@openrouter/ai-sdk-provider": "^1.2.0",
"@opentelemetry/api": "^1.9.0",
"@opentelemetry/core": "2.0.0",
"@opentelemetry/exporter-trace-otlp-http": "^0.200.0",
"@opentelemetry/sdk-trace-base": "^2.0.0",
"@opentelemetry/sdk-trace-node": "^2.0.0",
"@opentelemetry/sdk-trace-web": "^2.0.0",
"@opeoginni/github-copilot-openai-compatible": "^0.1.21",
"@playwright/test": "^1.55.1",
"@opeoginni/github-copilot-openai-compatible": "0.1.21",
"@playwright/test": "^1.52.0",
"@radix-ui/react-context-menu": "^2.2.16",
"@radix-ui/react-switch": "^1.2.6",
"@reduxjs/toolkit": "^2.2.5",
"@shikijs/markdown-it": "^3.12.0",
"@swc/plugin-styled-components": "^8.0.4",
@@ -223,8 +220,8 @@
"@types/mime-types": "^3",
"@types/node": "^22.17.1",
"@types/pako": "^1.0.2",
"@types/react": "^19.2.7",
"@types/react-dom": "^19.2.3",
"@types/react": "^19.0.12",
"@types/react-dom": "^19.0.4",
"@types/react-infinite-scroll-component": "^5.0.0",
"@types/react-transition-group": "^4.4.12",
"@types/react-window": "^1",
@@ -247,7 +244,7 @@
"@viz-js/lang-dot": "^1.0.5",
"@viz-js/viz": "^3.14.0",
"@xyflow/react": "^12.4.4",
"ai": "^5.0.98",
"ai": "^5.0.90",
"antd": "patch:antd@npm%3A5.27.0#~/.yarn/patches/antd-npm-5.27.0-aa91c36546.patch",
"archiver": "^7.0.1",
"async-mutex": "^0.5.0",
@@ -328,6 +325,7 @@
"p-queue": "^8.1.0",
"pdf-lib": "^1.17.1",
"pdf-parse": "^1.1.1",
"playwright": "^1.55.1",
"proxy-agent": "^6.5.0",
"react": "^19.2.0",
"react-dom": "^19.2.0",
@@ -418,9 +416,9 @@
"@langchain/openai@npm:>=0.1.0 <0.6.0": "patch:@langchain/openai@npm%3A1.0.0#~/.yarn/patches/@langchain-openai-npm-1.0.0-474d0ad9d4.patch",
"@langchain/openai@npm:^0.3.16": "patch:@langchain/openai@npm%3A1.0.0#~/.yarn/patches/@langchain-openai-npm-1.0.0-474d0ad9d4.patch",
"@langchain/openai@npm:>=0.2.0 <0.7.0": "patch:@langchain/openai@npm%3A1.0.0#~/.yarn/patches/@langchain-openai-npm-1.0.0-474d0ad9d4.patch",
"@ai-sdk/openai@npm:^2.0.42": "patch:@ai-sdk/openai@npm%3A2.0.72#~/.yarn/patches/@ai-sdk-openai-npm-2.0.72-234e68da87.patch",
"@ai-sdk/google@npm:^2.0.40": "patch:@ai-sdk/google@npm%3A2.0.40#~/.yarn/patches/@ai-sdk-google-npm-2.0.40-47e0eeee83.patch",
"@ai-sdk/openai-compatible@npm:^1.0.27": "patch:@ai-sdk/openai-compatible@npm%3A1.0.27#~/.yarn/patches/@ai-sdk-openai-compatible-npm-1.0.27-06f74278cf.patch"
"@ai-sdk/openai@npm:2.0.64": "patch:@ai-sdk/openai@npm%3A2.0.64#~/.yarn/patches/@ai-sdk-openai-npm-2.0.64-48f99f5bf3.patch",
"@ai-sdk/openai@npm:^2.0.42": "patch:@ai-sdk/openai@npm%3A2.0.64#~/.yarn/patches/@ai-sdk-openai-npm-2.0.64-48f99f5bf3.patch",
"@ai-sdk/google@npm:2.0.36": "patch:@ai-sdk/google@npm%3A2.0.36#~/.yarn/patches/@ai-sdk-google-npm-2.0.36-6f3cc06026.patch"
},
"packageManager": "yarn@4.9.1",
"lint-staged": {

View File

@@ -42,7 +42,7 @@
},
"dependencies": {
"@ai-sdk/provider": "^2.0.0",
"@ai-sdk/provider-utils": "^3.0.17"
"@ai-sdk/provider-utils": "^3.0.12"
},
"devDependencies": {
"tsdown": "^0.13.3",

View File

@@ -69,7 +69,6 @@ export interface CherryInProviderSettings {
headers?: HeadersInput
/**
* Optional endpoint type to distinguish different endpoint behaviors.
* "image-generation" is also openai endpoint, but specifically for image generation.
*/
endpointType?: 'openai' | 'openai-response' | 'anthropic' | 'gemini' | 'image-generation' | 'jina-rerank'
}

View File

@@ -39,13 +39,13 @@
"ai": "^5.0.26"
},
"dependencies": {
"@ai-sdk/anthropic": "^2.0.49",
"@ai-sdk/azure": "^2.0.74",
"@ai-sdk/deepseek": "^1.0.29",
"@ai-sdk/openai-compatible": "patch:@ai-sdk/openai-compatible@npm%3A1.0.27#~/.yarn/patches/@ai-sdk-openai-compatible-npm-1.0.27-06f74278cf.patch",
"@ai-sdk/anthropic": "^2.0.43",
"@ai-sdk/azure": "^2.0.66",
"@ai-sdk/deepseek": "^1.0.27",
"@ai-sdk/openai-compatible": "^1.0.26",
"@ai-sdk/provider": "^2.0.0",
"@ai-sdk/provider-utils": "^3.0.17",
"@ai-sdk/xai": "^2.0.36",
"@ai-sdk/provider-utils": "^3.0.16",
"@ai-sdk/xai": "^2.0.31",
"zod": "^4.1.5"
},
"devDependencies": {

View File

@@ -1,180 +0,0 @@
/**
* Mock Provider Instances
* Provides mock implementations for all supported AI providers
*/
import type { ImageModelV2, LanguageModelV2 } from '@ai-sdk/provider'
import { vi } from 'vitest'
/**
* Creates a mock language model with customizable behavior
*/
export function createMockLanguageModel(overrides?: Partial<LanguageModelV2>): LanguageModelV2 {
return {
specificationVersion: 'v1',
provider: 'mock-provider',
modelId: 'mock-model',
defaultObjectGenerationMode: 'tool',
doGenerate: vi.fn().mockResolvedValue({
text: 'Mock response text',
finishReason: 'stop',
usage: {
promptTokens: 10,
completionTokens: 20,
totalTokens: 30
},
rawCall: { rawPrompt: null, rawSettings: {} },
rawResponse: { headers: {} },
warnings: []
}),
doStream: vi.fn().mockReturnValue({
stream: (async function* () {
yield {
type: 'text-delta',
textDelta: 'Mock '
}
yield {
type: 'text-delta',
textDelta: 'streaming '
}
yield {
type: 'text-delta',
textDelta: 'response'
}
yield {
type: 'finish',
finishReason: 'stop',
usage: {
promptTokens: 10,
completionTokens: 15,
totalTokens: 25
}
}
})(),
rawCall: { rawPrompt: null, rawSettings: {} },
rawResponse: { headers: {} },
warnings: []
}),
...overrides
} as LanguageModelV2
}
/**
* Creates a mock image model with customizable behavior
*/
export function createMockImageModel(overrides?: Partial<ImageModelV2>): ImageModelV2 {
return {
specificationVersion: 'v2',
provider: 'mock-provider',
modelId: 'mock-image-model',
doGenerate: vi.fn().mockResolvedValue({
images: [
{
base64: 'mock-base64-image-data',
uint8Array: new Uint8Array([1, 2, 3, 4, 5]),
mimeType: 'image/png'
}
],
warnings: []
}),
...overrides
} as ImageModelV2
}
/**
* Mock provider configurations for testing
*/
export const mockProviderConfigs = {
openai: {
apiKey: 'sk-test-openai-key-123456789',
baseURL: 'https://api.openai.com/v1',
organization: 'test-org'
},
anthropic: {
apiKey: 'sk-ant-test-key-123456789',
baseURL: 'https://api.anthropic.com'
},
google: {
apiKey: 'test-google-api-key-123456789',
baseURL: 'https://generativelanguage.googleapis.com/v1'
},
xai: {
apiKey: 'xai-test-key-123456789',
baseURL: 'https://api.x.ai/v1'
},
azure: {
apiKey: 'test-azure-key-123456789',
resourceName: 'test-resource',
deployment: 'test-deployment'
},
deepseek: {
apiKey: 'sk-test-deepseek-key-123456789',
baseURL: 'https://api.deepseek.com/v1'
},
openrouter: {
apiKey: 'sk-or-test-key-123456789',
baseURL: 'https://openrouter.ai/api/v1'
},
huggingface: {
apiKey: 'hf_test_key_123456789',
baseURL: 'https://api-inference.huggingface.co'
},
'openai-compatible': {
apiKey: 'test-compatible-key-123456789',
baseURL: 'https://api.example.com/v1',
name: 'test-provider'
},
'openai-chat': {
apiKey: 'sk-test-chat-key-123456789',
baseURL: 'https://api.openai.com/v1'
}
} as const
/**
* Mock provider instances for testing
*/
export const mockProviderInstances = {
openai: {
name: 'openai-mock',
languageModel: createMockLanguageModel({ provider: 'openai', modelId: 'gpt-4' }),
imageModel: createMockImageModel({ provider: 'openai', modelId: 'dall-e-3' })
},
anthropic: {
name: 'anthropic-mock',
languageModel: createMockLanguageModel({ provider: 'anthropic', modelId: 'claude-3-5-sonnet-20241022' })
},
google: {
name: 'google-mock',
languageModel: createMockLanguageModel({ provider: 'google', modelId: 'gemini-2.0-flash-exp' }),
imageModel: createMockImageModel({ provider: 'google', modelId: 'imagen-3.0-generate-001' })
},
xai: {
name: 'xai-mock',
languageModel: createMockLanguageModel({ provider: 'xai', modelId: 'grok-2-latest' }),
imageModel: createMockImageModel({ provider: 'xai', modelId: 'grok-2-image-latest' })
},
deepseek: {
name: 'deepseek-mock',
languageModel: createMockLanguageModel({ provider: 'deepseek', modelId: 'deepseek-chat' })
}
}
export type ProviderId = keyof typeof mockProviderConfigs

View File

@@ -1,238 +0,0 @@
/**
* Mock Responses
* Provides realistic mock responses for all provider types
*/
import type { ModelMessage, Tool } from 'ai'
import { jsonSchema } from 'ai'
/**
* Standard test messages for all scenarios
*/
export const testMessages: Record<string, ModelMessage[]> = {
simple: [{ role: 'user' as const, content: 'Hello, how are you?' }],
conversation: [
{ role: 'user' as const, content: 'What is the capital of France?' },
{ role: 'assistant' as const, content: 'The capital of France is Paris.' },
{ role: 'user' as const, content: 'What is its population?' }
],
withSystem: [
{ role: 'system' as const, content: 'You are a helpful assistant that provides concise answers.' },
{ role: 'user' as const, content: 'Explain quantum computing in one sentence.' }
],
withImages: [
{
role: 'user' as const,
content: [
{ type: 'text' as const, text: 'What is in this image?' },
{
type: 'image' as const,
image:
'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg=='
}
]
}
],
toolUse: [{ role: 'user' as const, content: 'What is the weather in San Francisco?' }],
multiTurn: [
{ role: 'user' as const, content: 'Can you help me with a math problem?' },
{ role: 'assistant' as const, content: 'Of course! What math problem would you like help with?' },
{ role: 'user' as const, content: 'What is 15 * 23?' },
{ role: 'assistant' as const, content: '15 * 23 = 345' },
{ role: 'user' as const, content: 'Now divide that by 5' }
]
}
/**
* Standard test tools for tool calling scenarios
*/
export const testTools: Record<string, Tool> = {
getWeather: {
description: 'Get the current weather in a given location',
inputSchema: jsonSchema({
type: 'object',
properties: {
location: {
type: 'string',
description: 'The city and state, e.g. San Francisco, CA'
},
unit: {
type: 'string',
enum: ['celsius', 'fahrenheit'],
description: 'The temperature unit to use'
}
},
required: ['location']
}),
execute: async ({ location, unit = 'fahrenheit' }) => {
return {
location,
temperature: unit === 'celsius' ? 22 : 72,
unit,
condition: 'sunny'
}
}
},
calculate: {
description: 'Perform a mathematical calculation',
inputSchema: jsonSchema({
type: 'object',
properties: {
operation: {
type: 'string',
enum: ['add', 'subtract', 'multiply', 'divide'],
description: 'The operation to perform'
},
a: {
type: 'number',
description: 'The first number'
},
b: {
type: 'number',
description: 'The second number'
}
},
required: ['operation', 'a', 'b']
}),
execute: async ({ operation, a, b }) => {
const operations = {
add: (x: number, y: number) => x + y,
subtract: (x: number, y: number) => x - y,
multiply: (x: number, y: number) => x * y,
divide: (x: number, y: number) => x / y
}
return { result: operations[operation as keyof typeof operations](a, b) }
}
},
searchDatabase: {
description: 'Search for information in a database',
inputSchema: jsonSchema({
type: 'object',
properties: {
query: {
type: 'string',
description: 'The search query'
},
limit: {
type: 'number',
description: 'Maximum number of results to return',
default: 10
}
},
required: ['query']
}),
execute: async ({ query, limit = 10 }) => {
return {
results: [
{ id: 1, title: `Result 1 for ${query}`, relevance: 0.95 },
{ id: 2, title: `Result 2 for ${query}`, relevance: 0.87 }
].slice(0, limit)
}
}
}
}
/**
* Mock complete responses for non-streaming scenarios
* Note: AI SDK v5 uses inputTokens/outputTokens instead of promptTokens/completionTokens
*/
export const mockCompleteResponses = {
simple: {
text: 'This is a simple response.',
finishReason: 'stop' as const,
usage: {
inputTokens: 15,
outputTokens: 8,
totalTokens: 23
}
},
withToolCalls: {
text: 'I will check the weather for you.',
toolCalls: [
{
toolCallId: 'call_456',
toolName: 'getWeather',
args: { location: 'New York, NY', unit: 'celsius' }
}
],
finishReason: 'tool-calls' as const,
usage: {
inputTokens: 25,
outputTokens: 12,
totalTokens: 37
}
},
withWarnings: {
text: 'Response with warnings.',
finishReason: 'stop' as const,
usage: {
inputTokens: 10,
outputTokens: 5,
totalTokens: 15
},
warnings: [
{
type: 'unsupported-setting' as const,
setting: 'temperature',
details: 'Temperature parameter not supported for this model'
}
]
}
}
/**
* Mock image generation responses
*/
export const mockImageResponses = {
single: {
image: {
base64: 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
uint8Array: new Uint8Array([137, 80, 78, 71, 13, 10, 26, 10, 0, 0, 0, 13, 73, 72, 68, 82]),
mimeType: 'image/png' as const
},
warnings: []
},
multiple: {
images: [
{
base64: 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
uint8Array: new Uint8Array([137, 80, 78, 71]),
mimeType: 'image/png' as const
},
{
base64: 'iVBORw0KGgoAAAANSUhEUgAAAAIAAAACCAYAAABytg0kAAAAEklEQVR42mNk+M9QzwAEjDAGACCKAgdZ9zImAAAAAElFTkSuQmCC',
uint8Array: new Uint8Array([137, 80, 78, 71]),
mimeType: 'image/png' as const
}
],
warnings: []
},
withProviderMetadata: {
image: {
base64: 'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
uint8Array: new Uint8Array([137, 80, 78, 71]),
mimeType: 'image/png' as const
},
providerMetadata: {
openai: {
images: [
{
revisedPrompt: 'A detailed and enhanced version of the original prompt'
}
]
}
},
warnings: []
}
}

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@@ -1,329 +0,0 @@
/**
* Provider-Specific Test Utilities
* Helper functions for testing individual providers with all their parameters
*/
import type { Tool } from 'ai'
import { expect } from 'vitest'
/**
* Provider parameter configurations for comprehensive testing
*/
export const providerParameterMatrix = {
openai: {
models: ['gpt-4', 'gpt-4-turbo', 'gpt-3.5-turbo', 'gpt-4o'],
parameters: {
temperature: [0, 0.5, 0.7, 1.0, 1.5, 2.0],
maxTokens: [100, 500, 1000, 2000, 4000],
topP: [0.1, 0.5, 0.9, 1.0],
frequencyPenalty: [-2.0, -1.0, 0, 1.0, 2.0],
presencePenalty: [-2.0, -1.0, 0, 1.0, 2.0],
stop: [undefined, ['stop'], ['STOP', 'END']],
seed: [undefined, 12345, 67890],
responseFormat: [undefined, { type: 'json_object' as const }],
user: [undefined, 'test-user-123']
},
toolChoice: ['auto', 'required', 'none', { type: 'function' as const, name: 'getWeather' }],
parallelToolCalls: [true, false]
},
anthropic: {
models: ['claude-3-5-sonnet-20241022', 'claude-3-opus-20240229', 'claude-3-haiku-20240307'],
parameters: {
temperature: [0, 0.5, 1.0],
maxTokens: [100, 1000, 4000, 8000],
topP: [0.1, 0.5, 0.9, 1.0],
topK: [undefined, 1, 5, 10, 40],
stop: [undefined, ['Human:', 'Assistant:']],
metadata: [undefined, { userId: 'test-123' }]
},
toolChoice: ['auto', 'any', { type: 'tool' as const, name: 'getWeather' }]
},
google: {
models: ['gemini-2.0-flash-exp', 'gemini-1.5-pro', 'gemini-1.5-flash'],
parameters: {
temperature: [0, 0.5, 0.9, 1.0],
maxTokens: [100, 1000, 2000, 8000],
topP: [0.1, 0.5, 0.95, 1.0],
topK: [undefined, 1, 16, 40],
stopSequences: [undefined, ['END'], ['STOP', 'TERMINATE']]
},
safetySettings: [
undefined,
[
{ category: 'HARM_CATEGORY_HARASSMENT', threshold: 'BLOCK_MEDIUM_AND_ABOVE' },
{ category: 'HARM_CATEGORY_HATE_SPEECH', threshold: 'BLOCK_ONLY_HIGH' }
]
]
},
xai: {
models: ['grok-2-latest', 'grok-2-1212'],
parameters: {
temperature: [0, 0.5, 1.0, 1.5],
maxTokens: [100, 500, 2000, 4000],
topP: [0.1, 0.5, 0.9, 1.0],
stop: [undefined, ['STOP'], ['END', 'TERMINATE']],
seed: [undefined, 12345]
}
},
deepseek: {
models: ['deepseek-chat', 'deepseek-coder'],
parameters: {
temperature: [0, 0.5, 1.0],
maxTokens: [100, 1000, 4000],
topP: [0.1, 0.5, 0.95],
frequencyPenalty: [0, 0.5, 1.0],
presencePenalty: [0, 0.5, 1.0],
stop: [undefined, ['```'], ['END']]
}
},
azure: {
deployments: ['gpt-4-deployment', 'gpt-35-turbo-deployment'],
parameters: {
temperature: [0, 0.7, 1.0],
maxTokens: [100, 1000, 2000],
topP: [0.1, 0.5, 0.95],
frequencyPenalty: [0, 1.0],
presencePenalty: [0, 1.0],
stop: [undefined, ['STOP']]
}
}
} as const
/**
* Creates test cases for all parameter combinations
*/
export function generateParameterTestCases<T extends Record<string, any[]>>(
params: T,
maxCombinations = 50
): Array<Partial<{ [K in keyof T]: T[K][number] }>> {
const keys = Object.keys(params) as Array<keyof T>
const testCases: Array<Partial<{ [K in keyof T]: T[K][number] }>> = []
// Generate combinations using sampling strategy for large parameter spaces
const totalCombinations = keys.reduce((acc, key) => acc * params[key].length, 1)
if (totalCombinations <= maxCombinations) {
// Generate all combinations if total is small
generateAllCombinations(params, keys, 0, {}, testCases)
} else {
// Sample diverse combinations if total is large
generateSampledCombinations(params, keys, maxCombinations, testCases)
}
return testCases
}
function generateAllCombinations<T extends Record<string, any[]>>(
params: T,
keys: Array<keyof T>,
index: number,
current: Partial<{ [K in keyof T]: T[K][number] }>,
results: Array<Partial<{ [K in keyof T]: T[K][number] }>>
) {
if (index === keys.length) {
results.push({ ...current })
return
}
const key = keys[index]
for (const value of params[key]) {
generateAllCombinations(params, keys, index + 1, { ...current, [key]: value }, results)
}
}
function generateSampledCombinations<T extends Record<string, any[]>>(
params: T,
keys: Array<keyof T>,
count: number,
results: Array<Partial<{ [K in keyof T]: T[K][number] }>>
) {
// Generate edge cases first (min/max values)
const edgeCase1: any = {}
const edgeCase2: any = {}
for (const key of keys) {
edgeCase1[key] = params[key][0]
edgeCase2[key] = params[key][params[key].length - 1]
}
results.push(edgeCase1, edgeCase2)
// Generate random combinations for the rest
for (let i = results.length; i < count; i++) {
const combination: any = {}
for (const key of keys) {
const values = params[key]
combination[key] = values[Math.floor(Math.random() * values.length)]
}
results.push(combination)
}
}
/**
* Validates that all provider-specific parameters are correctly passed through
*/
export function validateProviderParams(providerId: string, actualParams: any, expectedParams: any): void {
const requiredFields: Record<string, string[]> = {
openai: ['model', 'messages'],
anthropic: ['model', 'messages'],
google: ['model', 'contents'],
xai: ['model', 'messages'],
deepseek: ['model', 'messages'],
azure: ['messages']
}
const fields = requiredFields[providerId] || ['model', 'messages']
for (const field of fields) {
expect(actualParams).toHaveProperty(field)
}
// Validate optional parameters if they were provided
const optionalParams = ['temperature', 'max_tokens', 'top_p', 'stop', 'tools']
for (const param of optionalParams) {
if (expectedParams[param] !== undefined) {
expect(actualParams[param]).toEqual(expectedParams[param])
}
}
}
/**
* Creates a comprehensive test suite for a provider
*/
// oxlint-disable-next-line no-unused-vars
export function createProviderTestSuite(_providerId: string) {
return {
testBasicCompletion: async (executor: any, model: string) => {
const result = await executor.generateText({
model,
messages: [{ role: 'user' as const, content: 'Hello' }]
})
expect(result).toBeDefined()
expect(result.text).toBeDefined()
expect(typeof result.text).toBe('string')
},
testStreaming: async (executor: any, model: string) => {
const chunks: any[] = []
const result = await executor.streamText({
model,
messages: [{ role: 'user' as const, content: 'Hello' }]
})
for await (const chunk of result.textStream) {
chunks.push(chunk)
}
expect(chunks.length).toBeGreaterThan(0)
},
testTemperature: async (executor: any, model: string, temperatures: number[]) => {
for (const temperature of temperatures) {
const result = await executor.generateText({
model,
messages: [{ role: 'user' as const, content: 'Hello' }],
temperature
})
expect(result).toBeDefined()
}
},
testMaxTokens: async (executor: any, model: string, maxTokensValues: number[]) => {
for (const maxTokens of maxTokensValues) {
const result = await executor.generateText({
model,
messages: [{ role: 'user' as const, content: 'Hello' }],
maxTokens
})
expect(result).toBeDefined()
if (result.usage?.completionTokens) {
expect(result.usage.completionTokens).toBeLessThanOrEqual(maxTokens)
}
}
},
testToolCalling: async (executor: any, model: string, tools: Record<string, Tool>) => {
const result = await executor.generateText({
model,
messages: [{ role: 'user' as const, content: 'What is the weather in SF?' }],
tools
})
expect(result).toBeDefined()
},
testStopSequences: async (executor: any, model: string, stopSequences: string[][]) => {
for (const stop of stopSequences) {
const result = await executor.generateText({
model,
messages: [{ role: 'user' as const, content: 'Count to 10' }],
stop
})
expect(result).toBeDefined()
}
}
}
}
/**
* Generates test data for vision/multimodal testing
*/
export function createVisionTestData() {
return {
imageUrl: 'https://example.com/test-image.jpg',
base64Image:
'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==',
messages: [
{
role: 'user' as const,
content: [
{ type: 'text' as const, text: 'What is in this image?' },
{
type: 'image' as const,
image:
'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg=='
}
]
}
]
}
}
/**
* Creates mock responses for different finish reasons
*/
export function createFinishReasonMocks() {
return {
stop: {
text: 'Complete response.',
finishReason: 'stop' as const,
usage: { promptTokens: 10, completionTokens: 5, totalTokens: 15 }
},
length: {
text: 'Incomplete response due to',
finishReason: 'length' as const,
usage: { promptTokens: 10, completionTokens: 100, totalTokens: 110 }
},
'tool-calls': {
text: 'Calling tools',
finishReason: 'tool-calls' as const,
toolCalls: [{ toolCallId: 'call_1', toolName: 'getWeather', args: { location: 'SF' } }],
usage: { promptTokens: 10, completionTokens: 8, totalTokens: 18 }
},
'content-filter': {
text: '',
finishReason: 'content-filter' as const,
usage: { promptTokens: 10, completionTokens: 0, totalTokens: 10 }
}
}
}

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@@ -1,291 +0,0 @@
/**
* Test Utilities
* Helper functions for testing AI Core functionality
*/
import { expect, vi } from 'vitest'
import type { ProviderId } from '../fixtures/mock-providers'
import { createMockImageModel, createMockLanguageModel, mockProviderConfigs } from '../fixtures/mock-providers'
/**
* Creates a test provider with streaming support
*/
export function createTestStreamingProvider(chunks: any[]) {
return createMockLanguageModel({
doStream: vi.fn().mockReturnValue({
stream: (async function* () {
for (const chunk of chunks) {
yield chunk
}
})(),
rawCall: { rawPrompt: null, rawSettings: {} },
rawResponse: { headers: {} },
warnings: []
})
})
}
/**
* Creates a test provider that throws errors
*/
export function createErrorProvider(error: Error) {
return createMockLanguageModel({
doGenerate: vi.fn().mockRejectedValue(error),
doStream: vi.fn().mockImplementation(() => {
throw error
})
})
}
/**
* Collects all chunks from a stream
*/
export async function collectStreamChunks<T>(stream: AsyncIterable<T>): Promise<T[]> {
const chunks: T[] = []
for await (const chunk of stream) {
chunks.push(chunk)
}
return chunks
}
/**
* Waits for a specific number of milliseconds
*/
export function wait(ms: number): Promise<void> {
return new Promise((resolve) => setTimeout(resolve, ms))
}
/**
* Creates a mock abort controller that aborts after a delay
*/
export function createDelayedAbortController(delayMs: number): AbortController {
const controller = new AbortController()
setTimeout(() => controller.abort(), delayMs)
return controller
}
/**
* Asserts that a function throws an error with a specific message
*/
export async function expectError(fn: () => Promise<any>, expectedMessage?: string | RegExp): Promise<Error> {
try {
await fn()
throw new Error('Expected function to throw an error, but it did not')
} catch (error) {
if (expectedMessage) {
const message = (error as Error).message
if (typeof expectedMessage === 'string') {
if (!message.includes(expectedMessage)) {
throw new Error(`Expected error message to include "${expectedMessage}", but got "${message}"`)
}
} else {
if (!expectedMessage.test(message)) {
throw new Error(`Expected error message to match ${expectedMessage}, but got "${message}"`)
}
}
}
return error as Error
}
}
/**
* Creates a spy function that tracks calls and arguments
*/
export function createSpy<T extends (...args: any[]) => any>() {
const calls: Array<{ args: Parameters<T>; result?: ReturnType<T>; error?: Error }> = []
const spy = vi.fn((...args: Parameters<T>) => {
try {
const result = undefined as ReturnType<T>
calls.push({ args, result })
return result
} catch (error) {
calls.push({ args, error: error as Error })
throw error
}
})
return {
fn: spy,
calls,
getCalls: () => calls,
getCallCount: () => calls.length,
getLastCall: () => calls[calls.length - 1],
reset: () => {
calls.length = 0
spy.mockClear()
}
}
}
/**
* Validates provider configuration
*/
export function validateProviderConfig(providerId: ProviderId) {
const config = mockProviderConfigs[providerId]
if (!config) {
throw new Error(`No mock configuration found for provider: ${providerId}`)
}
if (!config.apiKey) {
throw new Error(`Provider ${providerId} is missing apiKey in mock config`)
}
return config
}
/**
* Creates a test context with common setup
*/
export function createTestContext() {
const mocks = {
languageModel: createMockLanguageModel(),
imageModel: createMockImageModel(),
providers: new Map<string, any>()
}
const cleanup = () => {
mocks.providers.clear()
vi.clearAllMocks()
}
return {
mocks,
cleanup
}
}
/**
* Measures execution time of an async function
*/
export async function measureTime<T>(fn: () => Promise<T>): Promise<{ result: T; duration: number }> {
const start = Date.now()
const result = await fn()
const duration = Date.now() - start
return { result, duration }
}
/**
* Retries a function until it succeeds or max attempts reached
*/
export async function retryUntilSuccess<T>(fn: () => Promise<T>, maxAttempts = 3, delayMs = 100): Promise<T> {
let lastError: Error | undefined
for (let attempt = 1; attempt <= maxAttempts; attempt++) {
try {
return await fn()
} catch (error) {
lastError = error as Error
if (attempt < maxAttempts) {
await wait(delayMs)
}
}
}
throw lastError || new Error('All retry attempts failed')
}
/**
* Creates a mock streaming response that emits chunks at intervals
*/
export function createTimedStream<T>(chunks: T[], intervalMs = 10) {
return {
async *[Symbol.asyncIterator]() {
for (const chunk of chunks) {
await wait(intervalMs)
yield chunk
}
}
}
}
/**
* Asserts that two objects are deeply equal, ignoring specified keys
*/
export function assertDeepEqualIgnoring<T extends Record<string, any>>(
actual: T,
expected: T,
ignoreKeys: string[] = []
): void {
const filterKeys = (obj: T): Partial<T> => {
const filtered = { ...obj }
for (const key of ignoreKeys) {
delete filtered[key]
}
return filtered
}
const filteredActual = filterKeys(actual)
const filteredExpected = filterKeys(expected)
expect(filteredActual).toEqual(filteredExpected)
}
/**
* Creates a provider mock that simulates rate limiting
*/
export function createRateLimitedProvider(limitPerSecond: number) {
const calls: number[] = []
return createMockLanguageModel({
doGenerate: vi.fn().mockImplementation(async () => {
const now = Date.now()
calls.push(now)
// Remove calls older than 1 second
const recentCalls = calls.filter((time) => now - time < 1000)
if (recentCalls.length > limitPerSecond) {
throw new Error('Rate limit exceeded')
}
return {
text: 'Rate limited response',
finishReason: 'stop' as const,
usage: { promptTokens: 10, completionTokens: 5, totalTokens: 15 },
rawCall: { rawPrompt: null, rawSettings: {} },
rawResponse: { headers: {} },
warnings: []
}
})
})
}
/**
* Validates streaming response structure
*/
export function validateStreamChunk(chunk: any): void {
expect(chunk).toBeDefined()
expect(chunk).toHaveProperty('type')
if (chunk.type === 'text-delta') {
expect(chunk).toHaveProperty('textDelta')
expect(typeof chunk.textDelta).toBe('string')
} else if (chunk.type === 'finish') {
expect(chunk).toHaveProperty('finishReason')
expect(chunk).toHaveProperty('usage')
} else if (chunk.type === 'tool-call') {
expect(chunk).toHaveProperty('toolCallId')
expect(chunk).toHaveProperty('toolName')
expect(chunk).toHaveProperty('args')
}
}
/**
* Creates a test logger that captures log messages
*/
export function createTestLogger() {
const logs: Array<{ level: string; message: string; meta?: any }> = []
return {
info: (message: string, meta?: any) => logs.push({ level: 'info', message, meta }),
warn: (message: string, meta?: any) => logs.push({ level: 'warn', message, meta }),
error: (message: string, meta?: any) => logs.push({ level: 'error', message, meta }),
debug: (message: string, meta?: any) => logs.push({ level: 'debug', message, meta }),
getLogs: () => logs,
clear: () => {
logs.length = 0
}
}
}

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@@ -1,12 +0,0 @@
/**
* Test Infrastructure Exports
* Central export point for all test utilities, fixtures, and helpers
*/
// Fixtures
export * from './fixtures/mock-providers'
export * from './fixtures/mock-responses'
// Helpers
export * from './helpers/provider-test-utils'
export * from './helpers/test-utils'

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@@ -1,35 +0,0 @@
/**
* Mock for @cherrystudio/ai-sdk-provider
* This mock is used in tests to avoid importing the actual package
*/
export type CherryInProviderSettings = {
apiKey?: string
baseURL?: string
}
// oxlint-disable-next-line no-unused-vars
export const createCherryIn = (_options?: CherryInProviderSettings) => ({
// oxlint-disable-next-line no-unused-vars
languageModel: (_modelId: string) => ({
specificationVersion: 'v1',
provider: 'cherryin',
modelId: 'mock-model',
doGenerate: async () => ({ text: 'mock response' }),
doStream: async () => ({ stream: (async function* () {})() })
}),
// oxlint-disable-next-line no-unused-vars
chat: (_modelId: string) => ({
specificationVersion: 'v1',
provider: 'cherryin-chat',
modelId: 'mock-model',
doGenerate: async () => ({ text: 'mock response' }),
doStream: async () => ({ stream: (async function* () {})() })
}),
// oxlint-disable-next-line no-unused-vars
textEmbeddingModel: (_modelId: string) => ({
specificationVersion: 'v1',
provider: 'cherryin',
modelId: 'mock-embedding-model'
})
})

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@@ -1,9 +0,0 @@
/**
* Vitest Setup File
* Global test configuration and mocks for @cherrystudio/ai-core package
*/
// Mock Vite SSR helper to avoid Node environment errors
;(globalThis as any).__vite_ssr_exportName__ = (_name: string, value: any) => value
// Note: @cherrystudio/ai-sdk-provider is mocked via alias in vitest.config.ts

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@@ -1,109 +0,0 @@
import { describe, expect, it } from 'vitest'
import { createOpenAIOptions, createOpenRouterOptions, mergeProviderOptions } from '../factory'
describe('mergeProviderOptions', () => {
it('deep merges provider options for the same provider', () => {
const reasoningOptions = createOpenRouterOptions({
reasoning: {
enabled: true,
effort: 'medium'
}
})
const webSearchOptions = createOpenRouterOptions({
plugins: [{ id: 'web', max_results: 5 }]
})
const merged = mergeProviderOptions(reasoningOptions, webSearchOptions)
expect(merged.openrouter).toEqual({
reasoning: {
enabled: true,
effort: 'medium'
},
plugins: [{ id: 'web', max_results: 5 }]
})
})
it('preserves options from other providers while merging', () => {
const openRouter = createOpenRouterOptions({
reasoning: { enabled: true }
})
const openAI = createOpenAIOptions({
reasoningEffort: 'low'
})
const merged = mergeProviderOptions(openRouter, openAI)
expect(merged.openrouter).toEqual({ reasoning: { enabled: true } })
expect(merged.openai).toEqual({ reasoningEffort: 'low' })
})
it('overwrites primitive values with later values', () => {
const first = createOpenAIOptions({
reasoningEffort: 'low',
user: 'user-123'
})
const second = createOpenAIOptions({
reasoningEffort: 'high',
maxToolCalls: 5
})
const merged = mergeProviderOptions(first, second)
expect(merged.openai).toEqual({
reasoningEffort: 'high', // overwritten by second
user: 'user-123', // preserved from first
maxToolCalls: 5 // added from second
})
})
it('overwrites arrays with later values instead of merging', () => {
const first = createOpenRouterOptions({
models: ['gpt-4', 'gpt-3.5-turbo']
})
const second = createOpenRouterOptions({
models: ['claude-3-opus', 'claude-3-sonnet']
})
const merged = mergeProviderOptions(first, second)
// Array is completely replaced, not merged
expect(merged.openrouter?.models).toEqual(['claude-3-opus', 'claude-3-sonnet'])
})
it('deeply merges nested objects while overwriting primitives', () => {
const first = createOpenRouterOptions({
reasoning: {
enabled: true,
effort: 'low'
},
user: 'user-123'
})
const second = createOpenRouterOptions({
reasoning: {
effort: 'high',
max_tokens: 500
},
user: 'user-456'
})
const merged = mergeProviderOptions(first, second)
expect(merged.openrouter).toEqual({
reasoning: {
enabled: true, // preserved from first
effort: 'high', // overwritten by second
max_tokens: 500 // added from second
},
user: 'user-456' // overwritten by second
})
})
it('replaces arrays instead of merging them', () => {
const first = createOpenRouterOptions({ plugins: [{ id: 'old' }] })
const second = createOpenRouterOptions({ plugins: [{ id: 'new' }] })
const merged = mergeProviderOptions(first, second)
// @ts-expect-error type-check for openrouter options is skipped. see function signature of createOpenRouterOptions
expect(merged.openrouter?.plugins).toEqual([{ id: 'new' }])
})
})

View File

@@ -26,65 +26,13 @@ export function createGenericProviderOptions<T extends string>(
return { [provider]: options } as Record<T, Record<string, any>>
}
type PlainObject = Record<string, any>
const isPlainObject = (value: unknown): value is PlainObject => {
return typeof value === 'object' && value !== null && !Array.isArray(value)
}
function deepMergeObjects<T extends PlainObject>(target: T, source: PlainObject): T {
const result: PlainObject = { ...target }
Object.entries(source).forEach(([key, value]) => {
if (isPlainObject(value) && isPlainObject(result[key])) {
result[key] = deepMergeObjects(result[key], value)
} else {
result[key] = value
}
})
return result as T
}
/**
* Deep-merge multiple provider-specific options.
* Nested objects are recursively merged; primitive values are overwritten.
*
* When the same key appears in multiple options:
* - If both values are plain objects: they are deeply merged (recursive merge)
* - If values are primitives/arrays: the later value overwrites the earlier one
*
* @example
* mergeProviderOptions(
* { openrouter: { reasoning: { enabled: true, effort: 'low' }, user: 'user-123' } },
* { openrouter: { reasoning: { effort: 'high', max_tokens: 500 }, models: ['gpt-4'] } }
* )
* // Result: {
* // openrouter: {
* // reasoning: { enabled: true, effort: 'high', max_tokens: 500 },
* // user: 'user-123',
* // models: ['gpt-4']
* // }
* // }
*
* @param optionsMap Objects containing options for multiple providers
* @returns Fully merged TypedProviderOptions
* 合并多个供应商的options
* @param optionsMap 包含多个供应商选项的对象
* @returns 合并后的TypedProviderOptions
*/
export function mergeProviderOptions(...optionsMap: Partial<TypedProviderOptions>[]): TypedProviderOptions {
return optionsMap.reduce<TypedProviderOptions>((acc, options) => {
if (!options) {
return acc
}
Object.entries(options).forEach(([providerId, providerOptions]) => {
if (!providerOptions) {
return
}
if (acc[providerId]) {
acc[providerId] = deepMergeObjects(acc[providerId] as PlainObject, providerOptions as PlainObject)
} else {
acc[providerId] = providerOptions as any
}
})
return acc
}, {} as TypedProviderOptions)
return Object.assign({}, ...optionsMap)
}
/**

View File

@@ -19,20 +19,15 @@ describe('Provider Schemas', () => {
expect(Array.isArray(baseProviders)).toBe(true)
expect(baseProviders.length).toBeGreaterThan(0)
// These are the actual base providers defined in schemas.ts
const expectedIds = [
'openai',
'openai-chat',
'openai-responses',
'openai-compatible',
'anthropic',
'google',
'xai',
'azure',
'azure-responses',
'deepseek',
'openrouter',
'cherryin',
'cherryin-chat'
'deepseek'
]
const actualIds = baseProviders.map((p) => p.id)
expectedIds.forEach((id) => {

View File

@@ -232,13 +232,11 @@ describe('RuntimeExecutor.generateImage', () => {
expect(pluginCallOrder).toEqual(['onRequestStart', 'transformParams', 'transformResult', 'onRequestEnd'])
// transformParams receives params without model (model is handled separately)
// and context with core fields + dynamic fields (requestId, startTime, etc.)
expect(testPlugin.transformParams).toHaveBeenCalledWith(
expect.objectContaining({ prompt: 'A test image' }),
{ prompt: 'A test image' },
expect.objectContaining({
providerId: 'openai',
model: 'dall-e-3'
modelId: 'dall-e-3'
})
)
@@ -275,12 +273,11 @@ describe('RuntimeExecutor.generateImage', () => {
await executorWithPlugin.generateImage({ model: 'dall-e-3', prompt: 'A test image' })
// resolveModel receives model id and context with core fields
expect(modelResolutionPlugin.resolveModel).toHaveBeenCalledWith(
'dall-e-3',
expect.objectContaining({
providerId: 'openai',
model: 'dall-e-3'
modelId: 'dall-e-3'
})
)
@@ -342,11 +339,12 @@ describe('RuntimeExecutor.generateImage', () => {
.generateImage({ model: 'invalid-model', prompt: 'A test image' })
.catch((error) => error)
// Error is thrown from pluginEngine directly as ImageModelResolutionError
expect(thrownError).toBeInstanceOf(ImageModelResolutionError)
expect(thrownError.message).toContain('Failed to resolve image model: invalid-model')
expect(thrownError).toBeInstanceOf(ImageGenerationError)
expect(thrownError.message).toContain('Failed to generate image:')
expect(thrownError.providerId).toBe('openai')
expect(thrownError.modelId).toBe('invalid-model')
expect(thrownError.cause).toBeInstanceOf(ImageModelResolutionError)
expect(thrownError.cause.message).toContain('Failed to resolve image model: invalid-model')
})
it('should handle ImageModelResolutionError without provider', async () => {
@@ -364,9 +362,8 @@ describe('RuntimeExecutor.generateImage', () => {
const apiError = new Error('API request failed')
vi.mocked(aiGenerateImage).mockRejectedValue(apiError)
// Error propagates directly from pluginEngine without wrapping
await expect(executor.generateImage({ model: 'dall-e-3', prompt: 'A test image' })).rejects.toThrow(
'API request failed'
'Failed to generate image:'
)
})
@@ -379,9 +376,8 @@ describe('RuntimeExecutor.generateImage', () => {
vi.mocked(aiGenerateImage).mockRejectedValue(noImageError)
vi.mocked(NoImageGeneratedError.isInstance).mockReturnValue(true)
// Error propagates directly from pluginEngine
await expect(executor.generateImage({ model: 'dall-e-3', prompt: 'A test image' })).rejects.toThrow(
'No image generated'
'Failed to generate image:'
)
})
@@ -402,17 +398,15 @@ describe('RuntimeExecutor.generateImage', () => {
[errorPlugin]
)
// Error propagates directly from pluginEngine
await expect(executorWithPlugin.generateImage({ model: 'dall-e-3', prompt: 'A test image' })).rejects.toThrow(
'Generation failed'
'Failed to generate image:'
)
// onError receives the original error and context with core fields
expect(errorPlugin.onError).toHaveBeenCalledWith(
error,
expect.objectContaining({
providerId: 'openai',
model: 'dall-e-3'
modelId: 'dall-e-3'
})
)
})
@@ -425,10 +419,9 @@ describe('RuntimeExecutor.generateImage', () => {
const abortController = new AbortController()
setTimeout(() => abortController.abort(), 10)
// Error propagates directly from pluginEngine
await expect(
executor.generateImage({ model: 'dall-e-3', prompt: 'A test image', abortSignal: abortController.signal })
).rejects.toThrow('Operation was aborted')
).rejects.toThrow('Failed to generate image:')
})
})

View File

@@ -1,504 +0,0 @@
/**
* RuntimeExecutor.generateText Comprehensive Tests
* Tests non-streaming text generation across all providers with various parameters
*/
import { generateText } from 'ai'
import { beforeEach, describe, expect, it, vi } from 'vitest'
import {
createMockLanguageModel,
mockCompleteResponses,
mockProviderConfigs,
testMessages,
testTools
} from '../../../__tests__'
import type { AiPlugin } from '../../plugins'
import { globalRegistryManagement } from '../../providers/RegistryManagement'
import { RuntimeExecutor } from '../executor'
// Mock AI SDK - use importOriginal to keep jsonSchema and other non-mocked exports
vi.mock('ai', async (importOriginal) => {
const actual = (await importOriginal()) as Record<string, unknown>
return {
...actual,
generateText: vi.fn()
}
})
vi.mock('../../providers/RegistryManagement', () => ({
globalRegistryManagement: {
languageModel: vi.fn()
},
DEFAULT_SEPARATOR: '|'
}))
describe('RuntimeExecutor.generateText', () => {
let executor: RuntimeExecutor<'openai'>
let mockLanguageModel: any
beforeEach(() => {
vi.clearAllMocks()
executor = RuntimeExecutor.create('openai', mockProviderConfigs.openai)
mockLanguageModel = createMockLanguageModel({
provider: 'openai',
modelId: 'gpt-4'
})
vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(mockLanguageModel)
vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.simple as any)
})
describe('Basic Functionality', () => {
it('should generate text with minimal parameters', async () => {
const result = await executor.generateText({
model: 'gpt-4',
messages: testMessages.simple
})
expect(generateText).toHaveBeenCalledWith({
model: mockLanguageModel,
messages: testMessages.simple
})
expect(result.text).toBe('This is a simple response.')
expect(result.finishReason).toBe('stop')
expect(result.usage).toBeDefined()
})
it('should generate with system messages', async () => {
await executor.generateText({
model: 'gpt-4',
messages: testMessages.withSystem
})
expect(generateText).toHaveBeenCalledWith({
model: mockLanguageModel,
messages: testMessages.withSystem
})
})
it('should generate with conversation history', async () => {
await executor.generateText({
model: 'gpt-4',
messages: testMessages.conversation
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
messages: testMessages.conversation
})
)
})
})
describe('All Parameter Combinations', () => {
it('should support all parameters together', async () => {
await executor.generateText({
model: 'gpt-4',
messages: testMessages.simple,
temperature: 0.7,
maxOutputTokens: 500,
topP: 0.9,
frequencyPenalty: 0.5,
presencePenalty: 0.3,
stopSequences: ['STOP'],
seed: 12345
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
temperature: 0.7,
maxOutputTokens: 500,
topP: 0.9,
frequencyPenalty: 0.5,
presencePenalty: 0.3,
stopSequences: ['STOP'],
seed: 12345
})
)
})
it('should support partial parameters', async () => {
await executor.generateText({
model: 'gpt-4',
messages: testMessages.simple,
temperature: 0.5,
maxOutputTokens: 100
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
temperature: 0.5,
maxOutputTokens: 100
})
)
})
})
describe('Tool Calling', () => {
beforeEach(() => {
vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.withToolCalls as any)
})
it('should support tool calling', async () => {
const result = await executor.generateText({
model: 'gpt-4',
messages: testMessages.toolUse,
tools: testTools
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
tools: testTools
})
)
expect(result.toolCalls).toBeDefined()
expect(result.toolCalls).toHaveLength(1)
})
it('should support toolChoice auto', async () => {
await executor.generateText({
model: 'gpt-4',
messages: testMessages.toolUse,
tools: testTools,
toolChoice: 'auto'
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
toolChoice: 'auto'
})
)
})
it('should support toolChoice required', async () => {
await executor.generateText({
model: 'gpt-4',
messages: testMessages.toolUse,
tools: testTools,
toolChoice: 'required'
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
toolChoice: 'required'
})
)
})
it('should support toolChoice none', async () => {
vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.simple as any)
await executor.generateText({
model: 'gpt-4',
messages: testMessages.simple,
tools: testTools,
toolChoice: 'none'
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
toolChoice: 'none'
})
)
})
it('should support specific tool selection', async () => {
await executor.generateText({
model: 'gpt-4',
messages: testMessages.toolUse,
tools: testTools,
toolChoice: {
type: 'tool',
toolName: 'getWeather'
}
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
toolChoice: {
type: 'tool',
toolName: 'getWeather'
}
})
)
})
})
describe('Multiple Providers', () => {
it('should work with Anthropic provider', async () => {
const anthropicExecutor = RuntimeExecutor.create('anthropic', mockProviderConfigs.anthropic)
const anthropicModel = createMockLanguageModel({
provider: 'anthropic',
modelId: 'claude-3-5-sonnet-20241022'
})
vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(anthropicModel)
await anthropicExecutor.generateText({
model: 'claude-3-5-sonnet-20241022',
messages: testMessages.simple
})
expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('anthropic|claude-3-5-sonnet-20241022')
})
it('should work with Google provider', async () => {
const googleExecutor = RuntimeExecutor.create('google', mockProviderConfigs.google)
const googleModel = createMockLanguageModel({
provider: 'google',
modelId: 'gemini-2.0-flash-exp'
})
vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(googleModel)
await googleExecutor.generateText({
model: 'gemini-2.0-flash-exp',
messages: testMessages.simple
})
expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('google|gemini-2.0-flash-exp')
})
it('should work with xAI provider', async () => {
const xaiExecutor = RuntimeExecutor.create('xai', mockProviderConfigs.xai)
const xaiModel = createMockLanguageModel({
provider: 'xai',
modelId: 'grok-2-latest'
})
vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(xaiModel)
await xaiExecutor.generateText({
model: 'grok-2-latest',
messages: testMessages.simple
})
expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('xai|grok-2-latest')
})
it('should work with DeepSeek provider', async () => {
const deepseekExecutor = RuntimeExecutor.create('deepseek', mockProviderConfigs.deepseek)
const deepseekModel = createMockLanguageModel({
provider: 'deepseek',
modelId: 'deepseek-chat'
})
vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(deepseekModel)
await deepseekExecutor.generateText({
model: 'deepseek-chat',
messages: testMessages.simple
})
expect(globalRegistryManagement.languageModel).toHaveBeenCalledWith('deepseek|deepseek-chat')
})
})
describe('Plugin Integration', () => {
it('should execute all plugin hooks', async () => {
const pluginCalls: string[] = []
const testPlugin: AiPlugin = {
name: 'test-plugin',
onRequestStart: vi.fn(async () => {
pluginCalls.push('onRequestStart')
}),
transformParams: vi.fn(async (params) => {
pluginCalls.push('transformParams')
return { ...params, temperature: 0.8 }
}),
transformResult: vi.fn(async (result) => {
pluginCalls.push('transformResult')
return { ...result, text: result.text + ' [modified]' }
}),
onRequestEnd: vi.fn(async () => {
pluginCalls.push('onRequestEnd')
})
}
const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [testPlugin])
const result = await executorWithPlugin.generateText({
model: 'gpt-4',
messages: testMessages.simple
})
expect(pluginCalls).toEqual(['onRequestStart', 'transformParams', 'transformResult', 'onRequestEnd'])
// Verify transformed parameters
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
temperature: 0.8
})
)
// Verify transformed result
expect(result.text).toContain('[modified]')
})
it('should handle multiple plugins in order', async () => {
const pluginOrder: string[] = []
const plugin1: AiPlugin = {
name: 'plugin-1',
transformParams: vi.fn(async (params) => {
pluginOrder.push('plugin-1')
return { ...params, temperature: 0.5 }
})
}
const plugin2: AiPlugin = {
name: 'plugin-2',
transformParams: vi.fn(async (params) => {
pluginOrder.push('plugin-2')
return { ...params, maxTokens: 200 }
})
}
const executorWithPlugins = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [plugin1, plugin2])
await executorWithPlugins.generateText({
model: 'gpt-4',
messages: testMessages.simple
})
expect(pluginOrder).toEqual(['plugin-1', 'plugin-2'])
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
temperature: 0.5,
maxTokens: 200
})
)
})
})
describe('Error Handling', () => {
it('should handle API errors', async () => {
const error = new Error('API request failed')
vi.mocked(generateText).mockRejectedValue(error)
await expect(
executor.generateText({
model: 'gpt-4',
messages: testMessages.simple
})
).rejects.toThrow('API request failed')
})
it('should execute onError plugin hook', async () => {
const error = new Error('Generation failed')
vi.mocked(generateText).mockRejectedValue(error)
const errorPlugin: AiPlugin = {
name: 'error-handler',
onError: vi.fn()
}
const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [errorPlugin])
await expect(
executorWithPlugin.generateText({
model: 'gpt-4',
messages: testMessages.simple
})
).rejects.toThrow('Generation failed')
// onError receives the original error and context with core fields
expect(errorPlugin.onError).toHaveBeenCalledWith(
error,
expect.objectContaining({
providerId: 'openai',
model: 'gpt-4'
})
)
})
it('should handle model not found error', async () => {
const error = new Error('Model not found: invalid-model')
vi.mocked(globalRegistryManagement.languageModel).mockImplementation(() => {
throw error
})
await expect(
executor.generateText({
model: 'invalid-model',
messages: testMessages.simple
})
).rejects.toThrow('Model not found')
})
})
describe('Usage and Metadata', () => {
it('should return usage information', async () => {
const result = await executor.generateText({
model: 'gpt-4',
messages: testMessages.simple
})
expect(result.usage).toBeDefined()
expect(result.usage.inputTokens).toBe(15)
expect(result.usage.outputTokens).toBe(8)
expect(result.usage.totalTokens).toBe(23)
})
it('should handle warnings', async () => {
vi.mocked(generateText).mockResolvedValue(mockCompleteResponses.withWarnings as any)
const result = await executor.generateText({
model: 'gpt-4',
messages: testMessages.simple,
temperature: 2.5 // Unsupported value
})
expect(result.warnings).toBeDefined()
expect(result.warnings).toHaveLength(1)
expect(result.warnings![0].type).toBe('unsupported-setting')
})
})
describe('Abort Signal', () => {
it('should support abort signal', async () => {
const abortController = new AbortController()
await executor.generateText({
model: 'gpt-4',
messages: testMessages.simple,
abortSignal: abortController.signal
})
expect(generateText).toHaveBeenCalledWith(
expect.objectContaining({
abortSignal: abortController.signal
})
)
})
it('should handle aborted request', async () => {
const abortError = new Error('Request aborted')
abortError.name = 'AbortError'
vi.mocked(generateText).mockRejectedValue(abortError)
const abortController = new AbortController()
abortController.abort()
await expect(
executor.generateText({
model: 'gpt-4',
messages: testMessages.simple,
abortSignal: abortController.signal
})
).rejects.toThrow('Request aborted')
})
})
})

View File

@@ -1,531 +0,0 @@
/**
* RuntimeExecutor.streamText Comprehensive Tests
* Tests streaming text generation across all providers with various parameters
*/
import { streamText } from 'ai'
import { beforeEach, describe, expect, it, vi } from 'vitest'
import { collectStreamChunks, createMockLanguageModel, mockProviderConfigs, testMessages } from '../../../__tests__'
import type { AiPlugin } from '../../plugins'
import { globalRegistryManagement } from '../../providers/RegistryManagement'
import { RuntimeExecutor } from '../executor'
// Mock AI SDK - use importOriginal to keep jsonSchema and other non-mocked exports
vi.mock('ai', async (importOriginal) => {
const actual = (await importOriginal()) as Record<string, unknown>
return {
...actual,
streamText: vi.fn()
}
})
vi.mock('../../providers/RegistryManagement', () => ({
globalRegistryManagement: {
languageModel: vi.fn()
},
DEFAULT_SEPARATOR: '|'
}))
describe('RuntimeExecutor.streamText', () => {
let executor: RuntimeExecutor<'openai'>
let mockLanguageModel: any
beforeEach(() => {
vi.clearAllMocks()
executor = RuntimeExecutor.create('openai', mockProviderConfigs.openai)
mockLanguageModel = createMockLanguageModel({
provider: 'openai',
modelId: 'gpt-4'
})
vi.mocked(globalRegistryManagement.languageModel).mockReturnValue(mockLanguageModel)
})
describe('Basic Functionality', () => {
it('should stream text with minimal parameters', async () => {
const mockStream = {
textStream: (async function* () {
yield 'Hello'
yield ' '
yield 'World'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Hello' }
yield { type: 'text-delta', textDelta: ' ' }
yield { type: 'text-delta', textDelta: 'World' }
})(),
usage: Promise.resolve({ promptTokens: 5, completionTokens: 3, totalTokens: 8 })
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
const result = await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple
})
expect(streamText).toHaveBeenCalledWith({
model: mockLanguageModel,
messages: testMessages.simple
})
const chunks = await collectStreamChunks(result.textStream)
expect(chunks).toEqual(['Hello', ' ', 'World'])
})
it('should stream with system messages', async () => {
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.withSystem
})
expect(streamText).toHaveBeenCalledWith({
model: mockLanguageModel,
messages: testMessages.withSystem
})
})
it('should stream multi-turn conversations', async () => {
const mockStream = {
textStream: (async function* () {
yield 'Multi-turn response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Multi-turn response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.multiTurn
})
expect(streamText).toHaveBeenCalled()
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
messages: testMessages.multiTurn
})
)
})
})
describe('Temperature Parameter', () => {
const temperatures = [0, 0.3, 0.5, 0.7, 0.9, 1.0, 1.5, 2.0]
it.each(temperatures)('should support temperature=%s', async (temperature) => {
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
temperature
})
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
temperature
})
)
})
})
describe('Max Tokens Parameter', () => {
const maxTokensValues = [10, 50, 100, 500, 1000, 2000, 4000]
it.each(maxTokensValues)('should support maxOutputTokens=%s', async (maxOutputTokens) => {
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
maxOutputTokens
})
// Parameters are passed through without transformation
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
maxOutputTokens
})
)
})
})
describe('Top P Parameter', () => {
const topPValues = [0.1, 0.3, 0.5, 0.7, 0.9, 0.95, 1.0]
it.each(topPValues)('should support topP=%s', async (topP) => {
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
topP
})
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
topP
})
)
})
})
describe('Frequency and Presence Penalty', () => {
it('should support frequency penalty', async () => {
const penalties = [-2.0, -1.0, 0, 0.5, 1.0, 1.5, 2.0]
for (const frequencyPenalty of penalties) {
vi.clearAllMocks()
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
frequencyPenalty
})
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
frequencyPenalty
})
)
}
})
it('should support presence penalty', async () => {
const penalties = [-2.0, -1.0, 0, 0.5, 1.0, 1.5, 2.0]
for (const presencePenalty of penalties) {
vi.clearAllMocks()
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
presencePenalty
})
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
presencePenalty
})
)
}
})
it('should support both penalties together', async () => {
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
frequencyPenalty: 0.5,
presencePenalty: 0.5
})
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
frequencyPenalty: 0.5,
presencePenalty: 0.5
})
)
})
})
describe('Seed Parameter', () => {
it('should support seed for deterministic output', async () => {
const seeds = [0, 12345, 67890, 999999]
for (const seed of seeds) {
vi.clearAllMocks()
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
seed
})
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
seed
})
)
}
})
})
describe('Abort Signal', () => {
it('should support abort signal', async () => {
const abortController = new AbortController()
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
abortSignal: abortController.signal
})
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
abortSignal: abortController.signal
})
)
})
it('should handle abort during streaming', async () => {
const abortController = new AbortController()
const mockStream = {
textStream: (async function* () {
yield 'Start'
// Simulate abort
abortController.abort()
throw new Error('Aborted')
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Start' }
throw new Error('Aborted')
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
const result = await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple,
abortSignal: abortController.signal
})
await expect(async () => {
// oxlint-disable-next-line no-unused-vars
for await (const _chunk of result.textStream) {
// Stream should be interrupted
}
}).rejects.toThrow('Aborted')
})
})
describe('Plugin Integration', () => {
it('should execute plugins during streaming', async () => {
const pluginCalls: string[] = []
const testPlugin: AiPlugin = {
name: 'test-plugin',
onRequestStart: vi.fn(async () => {
pluginCalls.push('onRequestStart')
}),
transformParams: vi.fn(async (params) => {
pluginCalls.push('transformParams')
return { ...params, temperature: 0.5 }
}),
onRequestEnd: vi.fn(async () => {
pluginCalls.push('onRequestEnd')
})
}
const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [testPlugin])
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
const result = await executorWithPlugin.streamText({
model: 'gpt-4',
messages: testMessages.simple
})
// Consume stream
// oxlint-disable-next-line no-unused-vars
for await (const _chunk of result.textStream) {
// Stream chunks
}
expect(pluginCalls).toContain('onRequestStart')
expect(pluginCalls).toContain('transformParams')
// Verify transformed parameters were used
expect(streamText).toHaveBeenCalledWith(
expect.objectContaining({
temperature: 0.5
})
)
})
})
describe('Full Stream with Finish Reason', () => {
it('should provide finish reason in full stream', async () => {
const mockStream = {
textStream: (async function* () {
yield 'Response'
})(),
fullStream: (async function* () {
yield { type: 'text-delta', textDelta: 'Response' }
yield {
type: 'finish',
finishReason: 'stop',
usage: { promptTokens: 5, completionTokens: 3, totalTokens: 8 }
}
})()
}
vi.mocked(streamText).mockResolvedValue(mockStream as any)
const result = await executor.streamText({
model: 'gpt-4',
messages: testMessages.simple
})
const fullChunks = await collectStreamChunks(result.fullStream)
expect(fullChunks).toHaveLength(2)
expect(fullChunks[0]).toEqual({ type: 'text-delta', textDelta: 'Response' })
expect(fullChunks[1]).toEqual({
type: 'finish',
finishReason: 'stop',
usage: { promptTokens: 5, completionTokens: 3, totalTokens: 8 }
})
})
})
describe('Error Handling', () => {
it('should handle streaming errors', async () => {
const error = new Error('Streaming failed')
vi.mocked(streamText).mockRejectedValue(error)
await expect(
executor.streamText({
model: 'gpt-4',
messages: testMessages.simple
})
).rejects.toThrow('Streaming failed')
})
it('should execute onError plugin hook on failure', async () => {
const error = new Error('Stream error')
vi.mocked(streamText).mockRejectedValue(error)
const errorPlugin: AiPlugin = {
name: 'error-handler',
onError: vi.fn()
}
const executorWithPlugin = RuntimeExecutor.create('openai', mockProviderConfigs.openai, [errorPlugin])
await expect(
executorWithPlugin.streamText({
model: 'gpt-4',
messages: testMessages.simple
})
).rejects.toThrow('Stream error')
// onError receives the original error and context with core fields
expect(errorPlugin.onError).toHaveBeenCalledWith(
error,
expect.objectContaining({
providerId: 'openai',
model: 'gpt-4'
})
)
})
})
})

View File

@@ -1,20 +1,12 @@
import path from 'node:path'
import { fileURLToPath } from 'node:url'
import { defineConfig } from 'vitest/config'
const __dirname = path.dirname(fileURLToPath(import.meta.url))
export default defineConfig({
test: {
globals: true,
setupFiles: [path.resolve(__dirname, './src/__tests__/setup.ts')]
globals: true
},
resolve: {
alias: {
'@': path.resolve(__dirname, './src'),
// Mock external packages that may not be available in test environment
'@cherrystudio/ai-sdk-provider': path.resolve(__dirname, './src/__tests__/mocks/ai-sdk-provider.ts')
'@': './src'
}
},
esbuild: {

857
packages/catalog/PLANS.md Normal file
View File

@@ -0,0 +1,857 @@
# 模型和供应商参数化配置实现方案
## 📋 项目概述
本文档描述了在 `@packages/catalog/` 下实现模型和供应商参数化配置的方案,目标是将现有的硬编码逻辑重构为元数据驱动的配置系统。
## 🎯 目标
### 主要目标
- 将硬编码的模型识别逻辑转换为 JSON 配置驱动
- 解决"同一模型在不同供应商下有差异"的问题
- 提供类型安全的配置系统(使用 Zod
- 支持未来通过配置更新添加新模型
### 痛点解决
- **当前问题**`src/renderer/src/config/models/` 下复杂的正则表达式和硬编码逻辑
- **期望状态**:配置以 JSON 形式存在,代码中使用 Zod Schema 验证
- **可维护性**:新模型发布时只需更新 JSON 配置,无需修改代码
## 🏗️ 架构设计
### 三层分离的元数据架构
```
1. Base Model Catalog (models/*.json)
├─ 模型基础信息ID、能力、模态、限制、价格
└─ 官方/标准配置
2. Provider Catalog (providers/*.json)
├─ 供应商特性端点支持、API 兼容性)
└─ 认证和定价模型
3. Provider Model Overrides (overrides/*.json)
├─ 供应商对特定模型的覆盖
└─ 解决"同一模型不同供应商差异"问题
```
### 简化后的文件结构
```
packages/catalog/
├── src/
│ ├── index.ts # 主导出文件
│ ├── schemas/ # Schema 定义
│ │ ├── index.ts # 统一导出
│ │ ├── model.schema.ts # 模型配置 Schema + Zod
│ │ ├── provider.schema.ts # 供应商配置 Schema + Zod
│ │ └── override.schema.ts # 覆盖配置 Schema + Zod
│ ├── data/ # 配置数据(单文件存储)
│ │ ├── models.json # 所有模型配置
│ │ ├── providers.json # 所有供应商配置
│ │ └── overrides.json # 所有覆盖配置
│ ├── services/ # 核心服务
│ │ ├── CatalogService.ts # 统一的目录服务
│ │ └── ConfigLoader.ts # 配置加载 + 验证
│ ├── utils/ # 工具函数
│ │ ├── migrate.ts # 迁移工具(从旧代码提取配置)
│ │ └── helpers.ts # 辅助函数
│ └── __tests__/ # 测试文件
│ ├── fixtures/ # 测试数据
│ ├── schemas.test.ts # Schema 测试
│ └── catalog.test.ts # 目录服务测试
├── scripts/
│ └── migrate.ts # 迁移脚本 CLI
└── package.json
```
## 📝 Schema 定义
### 1. 模型配置 Schema
```typescript
// packages/catalog/src/schemas/model.schema.ts
import * as z from 'zod'
import { EndpointTypeSchema } from './provider.schema'
// 模态类型
export const ModalitySchema = z.enum(['TEXT', 'VISION', 'AUDIO', 'VIDEO', 'VECTOR'])
// 能力类型
export const ModelCapabilityTypeSchema = z.enum([
'FUNCTION_CALL', // 函数调用
'REASONING', // 推理
'IMAGE_RECOGNITION', // 图像识别
'IMAGE_GENERATION', // 图像生成
'AUDIO_RECOGNITION', // 音频识别
'AUDIO_GENERATION', // 音频生成
'EMBEDDING', // 嵌入向量生成
'RERANK', // 文本重排序
'AUDIO_TRANSCRIPT', // 音频转录
'VIDEO_RECOGNITION', // 视频识别
'VIDEO_GENERATION', // 视频生成
'STRUCTURED_OUTPUT', // 结构化输出
'FILE_INPUT', // 文件输入支持
'WEB_SEARCH', // 内置网络搜索
'CODE_EXECUTION', // 代码执行
'FILE_SEARCH', // 文件搜索
'COMPUTER_USE' // 计算机使用
])
// 推理配置
export const ReasoningConfigSchema = z.object({
supportedEfforts: z.array(z.enum(['low', 'medium', 'high'])),
implementation: z.enum(['OPENAI_O1', 'ANTHROPIC_CLAUDE', 'DEEPSEEK_R1', 'GEMINI_THINKING']),
reasoningMode: z.enum(['ALWAYS_ON', 'ON_DEMAND']),
thinkingControl: z.object({
enabled: z.boolean(),
budget: z.object({
min: z.number().optional(),
max: z.number().optional()
}).optional()
}).optional()
})
// 参数支持配置
export const ParameterSupportSchema = z.object({
temperature: z.object({
supported: z.boolean(),
min: z.number().min(0).max(2).optional(),
max: z.number().min(0).max(2).optional(),
default: z.number().min(0).max(2).optional()
}).optional(),
topP: z.object({
supported: z.boolean(),
min: z.number().min(0).max(1).optional(),
max: z.number().min(0).max(1).optional(),
default: z.number().min(0).max(1).optional()
}).optional(),
topK: z.object({
supported: z.boolean(),
min: z.number().positive().optional(),
max: z.number().positive().optional()
}).optional(),
frequencyPenalty: z.boolean().optional(),
presencePenalty: z.boolean().optional(),
maxTokens: z.boolean().optional(),
stopSequences: z.boolean().optional(),
systemMessage: z.boolean().optional(),
developerRole: z.boolean().optional()
})
// 定价配置
export const ModelPricingSchema = z.object({
input: z.object({
perMillionTokens: z.number(),
currency: z.string().default('USD')
}),
output: z.object({
perMillionTokens: z.number(),
currency: z.string().default('USD')
}),
perImage: z.object({
price: z.number(),
currency: z.string().default('USD')
}).optional(),
perMinute: z.object({
price: z.number(),
currency: z.string().default('USD')
}).optional()
})
// 模型配置 Schema
export const ModelConfigSchema = z.object({
// 基础信息
id: z.string(),
name: z.string().optional(),
ownedBy: z.string().optional(),
description: z.string().optional(),
// 能力(核心)
capabilities: z.array(ModelCapabilityTypeSchema),
// 模态
inputModalities: z.array(ModalitySchema),
outputModalities: z.array(ModalitySchema),
// 限制
contextWindow: z.number(),
maxOutputTokens: z.number(),
maxInputTokens: z.number().optional(),
// 价格
pricing: ModelPricingSchema.optional(),
// 推理配置
reasoning: ReasoningConfigSchema.optional(),
// 参数支持
parameters: ParameterSupportSchema.optional(),
// 端点类型
endpointTypes: z.array(EndpointTypeSchema).optional(),
// 元数据
releaseDate: z.string().optional(),
deprecationDate: z.string().optional(),
replacedBy: z.string().optional()
})
export type ModelConfig = z.infer<typeof ModelConfigSchema>
```
### 2. 供应商配置 Schema简化版
```typescript
// packages/catalog/src/schemas/provider.schema.ts
import * as z from 'zod'
// 端点类型
export const EndpointTypeSchema = z.enum([
'CHAT_COMPLETIONS',
'COMPLETIONS',
'EMBEDDINGS',
'IMAGE_GENERATION',
'AUDIO_SPEECH',
'AUDIO_TRANSCRIPTIONS',
'MESSAGES',
'GENERATE_CONTENT',
'RERANK',
'MODERATIONS'
])
// 认证方式
export const AuthenticationSchema = z.enum([
'API_KEY',
'OAUTH',
'CLOUD_CREDENTIALS'
])
// 定价模型
export const PricingModelSchema = z.enum([
'UNIFIED', // 统一定价 (如 OpenRouter)
'PER_MODEL', // 按模型独立定价 (如 OpenAI 官方)
'TRANSPARENT', // 透明定价 (如 New-API)
])
// 模型路由策略
export const ModelRoutingSchema = z.enum([
'INTELLIGENT', // 智能路由
'DIRECT', // 直接路由
'LOAD_BALANCED', // 负载均衡
])
// API 兼容性配置
export const ApiCompatibilitySchema = z.object({
supportsArrayContent: z.boolean().default(true),
supportsStreamOptions: z.boolean().default(true),
supportsDeveloperRole: z.boolean().default(false),
supportsThinkingControl: z.boolean().default(false),
supportsParallelTools: z.boolean().default(false),
supportsMultimodal: z.boolean().default(false),
maxFileUploadSize: z.number().optional(),
supportedFileTypes: z.array(z.string()).optional()
})
// 供应商能力(简化版 - 使用数组代替多个布尔字段)
export const ProviderCapabilitySchema = z.enum([
'CUSTOM_MODELS', // 支持自定义模型
'MODEL_MAPPING', // 提供模型映射
'FALLBACK_ROUTING', // 降级路由
'AUTO_RETRY', // 自动重试
'REAL_TIME_METRICS', // 实时指标
'USAGE_ANALYTICS', // 使用分析
'STREAMING', // 流式响应
'BATCH_PROCESSING', // 批量处理
'RATE_LIMITING', // 速率限制
])
// 供应商配置 Schema简化版
export const ProviderConfigSchema = z.object({
// 基础信息
id: z.string(),
name: z.string(),
description: z.string().optional(),
// 核心配置
authentication: AuthenticationSchema,
pricingModel: PricingModelSchema,
modelRouting: ModelRoutingSchema,
// 能力(使用数组替代多个布尔字段)
capabilities: z.array(ProviderCapabilitySchema).default([]),
// 功能支持
supportedEndpoints: z.array(EndpointTypeSchema),
apiCompatibility: ApiCompatibilitySchema.optional(),
// 默认配置
defaultApiHost: z.string().optional(),
defaultRateLimit: z.number().optional(),
// 模型匹配
modelIdPatterns: z.array(z.string()).optional(),
aliasModelIds: z.record(z.string()).optional(),
// 元数据
documentation: z.string().url().optional(),
statusPage: z.string().url().optional(),
// 状态
deprecated: z.boolean().default(false)
})
export type ProviderConfig = z.infer<typeof ProviderConfigSchema>
```
### 3. 覆盖配置 Schema
```typescript
// packages/catalog/src/schemas/override.schema.ts
import * as z from 'zod'
import { ModelCapabilityTypeSchema, ModelPricingSchema, ParameterSupportSchema } from './model.schema'
export const ProviderModelOverrideSchema = z.object({
providerId: z.string(),
modelId: z.string(),
// 能力覆盖
capabilities: z.object({
add: z.array(ModelCapabilityTypeSchema).optional(),
remove: z.array(ModelCapabilityTypeSchema).optional()
}).optional(),
// 限制覆盖
limits: z.object({
contextWindow: z.number().optional(),
maxOutputTokens: z.number().optional()
}).optional(),
// 价格覆盖
pricing: ModelPricingSchema.optional(),
// 参数支持覆盖
parameters: ParameterSupportSchema.optional(),
// 禁用模型
disabled: z.boolean().optional(),
// 覆盖原因
reason: z.string().optional()
})
export type ProviderModelOverride = z.infer<typeof ProviderModelOverrideSchema>
```
## 🔧 核心 API 设计
### 统一的目录服务
```typescript
// packages/catalog/src/services/CatalogService.ts
export interface ModelFilters {
capabilities?: ModelCapabilityType[]
inputModalities?: Modality[]
providers?: string[]
minContextWindow?: number
}
export interface ProviderFilter {
capabilities?: ProviderCapability[]
authentication?: AuthenticationSchema
pricingModel?: PricingModelSchema
notDeprecated?: boolean
}
export class CatalogService {
private models: Map<string, ModelConfig>
private providers: Map<string, ProviderConfig>
private overrides: Map<string, ProviderModelOverride[]>
// === 模型查询 ===
/**
* 获取模型配置(应用供应商覆盖)
*/
getModel(modelId: string, providerId?: string): ModelConfig | null
/**
* 检查模型能力
*/
hasCapability(modelId: string, capability: ModelCapabilityType, providerId?: string): boolean
/**
* 获取模型的推理配置
*/
getReasoningConfig(modelId: string, providerId?: string): ReasoningConfig | null
/**
* 获取模型参数范围
*/
getParameterRange(
modelId: string,
parameter: 'temperature' | 'topP' | 'topK',
providerId?: string
): { min: number, max: number, default?: number } | null
/**
* 批量匹配模型
*/
findModels(filters?: ModelFilters): ModelConfig[]
// === 供应商查询 ===
/**
* 获取供应商配置
*/
getProvider(providerId: string): ProviderConfig | null
/**
* 检查供应商能力
*/
hasProviderCapability(providerId: string, capability: ProviderCapability): boolean
/**
* 检查端点支持
*/
supportsEndpoint(providerId: string, endpoint: EndpointType): boolean
/**
* 查找供应商
*/
findProviders(filter?: ProviderFilter): ProviderConfig[]
// === 内部方法 ===
/**
* 应用覆盖配置
*/
private applyOverrides(model: ModelConfig, providerId: string): ModelConfig
}
// 统一导出
export const catalog = new CatalogService()
// 向后兼容的辅助函数
export const isFunctionCallingModel = (model: Model): boolean =>
catalog.hasCapability(model.id, 'FUNCTION_CALL', model.provider)
export const isReasoningModel = (model: Model): boolean =>
catalog.hasCapability(model.id, 'REASONING', model.provider)
export const isVisionModel = (model: Model): boolean =>
catalog.hasCapability(model.id, 'IMAGE_RECOGNITION', model.provider)
```
## 📊 JSON 配置示例
### 模型配置示例
```json
// packages/catalog/src/data/models.json
{
"version": "2025.11.24",
"models": [
{
"id": "claude-3-5-sonnet-20241022",
"name": "Claude 3.5 Sonnet",
"owned_by": "anthropic",
"capabilities": [
"FUNCTION_CALL",
"REASONING",
"IMAGE_RECOGNITION",
"STRUCTURED_OUTPUT",
"FILE_INPUT"
],
"input_modalities": ["TEXT", "VISION"],
"output_modalities": ["TEXT"],
"context_window": 200000,
"max_output_tokens": 8192,
"pricing": {
"input": { "per_million_tokens": 3.0, "currency": "USD" },
"output": { "per_million_tokens": 15.0, "currency": "USD" }
},
"reasoning": {
"type": "anthropic",
"params": {
"type": "enabled",
"budgetTokens": 10000
}
},
"parameters": {
"temperature": {
"supported": true,
"min": 0.0,
"max": 1.0,
"default": 1.0
}
},
"metadata": {}
},
{
"id": "gpt-4-turbo",
"name": "GPT-4 Turbo",
"owned_by": "openai",
"capabilities": [
"FUNCTION_CALL",
"IMAGE_RECOGNITION",
"STRUCTURED_OUTPUT"
],
"input_modalities": ["TEXT", "VISION"],
"output_modalities": ["TEXT"],
"context_window": 128000,
"max_output_tokens": 4096,
"pricing": {
"input": { "per_million_tokens": 10.0, "currency": "USD" },
"output": { "per_million_tokens": 30.0, "currency": "USD" }
},
"metadata": {}
}
]
}
```
### 供应商配置示例
```json
// packages/catalog/src/data/providers.json
{
"version": "2025.11.24",
"providers": [
{
"id": "anthropic",
"name": "Anthropic",
"authentication": "API_KEY",
"pricing_model": "PER_MODEL",
"model_routing": "DIRECT",
"behaviors": {
"supports_custom_models": false,
"provides_model_mapping": false,
"supports_streaming": true,
"has_real_time_metrics": true,
"supports_rate_limiting": true,
"provides_usage_analytics": true,
"requires_api_key_validation": true
},
"supported_endpoints": ["MESSAGES"],
"api_compatibility": {
"supports_stream_options": true,
"supports_parallel_tools": true,
"supports_multimodal": true
},
"default_api_host": "https://api.anthropic.com",
"deprecated": false,
"maintenance_mode": false,
"config_version": "1.0.0",
"special_config": {},
"metadata": {}
},
{
"id": "openrouter",
"name": "OpenRouter",
"authentication": "API_KEY",
"pricing_model": "UNIFIED",
"model_routing": "INTELLIGENT",
"behaviors": {
"supports_custom_models": true,
"provides_model_mapping": true,
"provides_fallback_routing": true,
"has_auto_retry": true,
"supports_streaming": true,
"has_real_time_metrics": true
},
"supported_endpoints": ["CHAT_COMPLETIONS"],
"default_api_host": "https://openrouter.ai/api/v1",
"deprecated": false,
"maintenance_mode": false,
"config_version": "1.0.0",
"special_config": {},
"metadata": {}
}
]
}
```
### 覆盖配置示例
```json
// packages/catalog/src/data/overrides.json
{
"version": "2025.11.24",
"overrides": [
{
"provider_id": "openrouter",
"model_id": "claude-3-5-sonnet-20241022",
"pricing": {
"input": { "per_million_tokens": 4.5, "currency": "USD" },
"output": { "per_million_tokens": 22.5, "currency": "USD" }
},
"capabilities": {
"add": ["WEB_SEARCH"]
},
"reason": "OpenRouter applies markup and adds web search",
"priority": 0
},
{
"provider_id": "openrouter",
"model_id": "gpt-4-turbo",
"limits": {
"context_window": 128000,
"max_output_tokens": 16384
},
"reason": "OpenRouter extends output token limit",
"priority": 0
}
]
}
```
## 🔄 实现计划
### Phase 1: 基础架构 (2-3 days)
**目标**:建立核心架构和类型系统
**任务**
1. **Schema 定义**
- 实现 `model.schema.ts``provider.schema.ts``override.schema.ts`
- 所有 Schema 使用 Zod 验证
- 导出 TypeScript 类型
2. **配置加载器**
```typescript
// packages/catalog/src/services/ConfigLoader.ts
export class ConfigLoader {
loadModels(): ModelConfig[]
loadProviders(): ProviderConfig[]
loadOverrides(): ProviderModelOverride[]
validate(): boolean
}
```
3. **目录服务**
```typescript
// packages/catalog/src/services/CatalogService.ts
export class CatalogService {
// 实现所有查询 API
}
```
**验收标准**
- ✅ 所有 Schema 定义完成,通过 Zod 验证
- ✅ ConfigLoader 可以加载和验证 JSON 文件
- ✅ CatalogService 基础 API 实现
- ✅ 单元测试覆盖核心功能
### Phase 2: 数据迁移 (1-2 days)
**目标**:从现有硬编码逻辑生成 JSON 配置
**任务**
1. **迁移工具**
```typescript
// packages/catalog/src/utils/migrate.ts
export class MigrationTool {
// 从 src/renderer/src/config/models/ 提取模型配置
extractModelConfigs(): ModelConfig[]
// 提取供应商配置
extractProviderConfigs(): ProviderConfig[]
// 写入 JSON 文件
writeConfigs(models: ModelConfig[], providers: ProviderConfig[]): void
// 简单验证
validate(): boolean
}
```
2. **迁移脚本**
```bash
# 运行迁移
yarn catalog:migrate
```
3. **手动审核**
- 检查生成的配置文件
- 补充缺失的价格和限制信息
- 调整不准确的能力定义
**验收标准**
- ✅ 迁移工具能够提取现有配置
- ✅ 生成的配置通过 Schema 验证
- ✅ 手动审核完成,配置准确
### Phase 3: 集成替换 (2-3 days)
**目标**:替换现有硬编码逻辑
**任务**
1. **向后兼容层**
```typescript
// packages/catalog/src/index.ts
export const isFunctionCallingModel = (model: Model): boolean =>
catalog.hasCapability(model.id, 'FUNCTION_CALL', model.provider)
```
2. **逐步替换**
- 替换 `src/renderer/src/config/models/` 中的函数
- 更新所有调用点
- 确保测试通过
3. **集成测试**
- 端到端测试
- 性能测试
- 兼容性测试
**验收标准**
- ✅ 所有现有测试通过
- ✅ 新配置系统与旧系统行为一致
- ✅ 性能不低于原有实现
### 延迟实现 ⏸️
以下功能在初期版本不实现,等待实际需求:
- ⏸️ **在线配置更新**:等到有用户需求再实现
- ⏸️ **复杂缓存机制**:等出现性能问题再优化
- ⏸️ **配置版本控制**:简化为文件级别的版本号
## 🧪 测试策略
### 测试覆盖
1. **Schema 测试**
```typescript
describe('ModelConfig Schema', () => {
it('validates correct config', () => {
expect(() => ModelConfigSchema.parse(validConfig)).not.toThrow()
})
it('rejects invalid config', () => {
expect(() => ModelConfigSchema.parse(invalidConfig)).toThrow()
})
})
```
2. **服务测试**
```typescript
describe('CatalogService', () => {
it('returns model with overrides applied', () => {
const model = catalog.getModel('claude-3-5-sonnet', 'openrouter')
expect(model?.pricing).toEqual(expectedPricing)
})
it('checks capabilities correctly', () => {
expect(catalog.hasCapability('gpt-4', 'FUNCTION_CALL')).toBe(true)
})
})
```
3. **兼容性测试**
```typescript
describe('Backward Compatibility', () => {
it('produces same results as legacy', () => {
expect(isFunctionCallingModel(testModel)).toBe(legacyResult)
})
})
```
## 📖 使用指南
### 基本用法
```typescript
import { catalog } from '@cherrystudio/catalog'
// 检查模型能力
const canCallFunctions = catalog.hasCapability('gpt-4', 'FUNCTION_CALL')
const canReason = catalog.hasCapability('o1-preview', 'REASONING')
// 获取模型配置
const modelConfig = catalog.getModel('claude-3-5-sonnet', 'openrouter')
// 查找模型
const visionModels = catalog.findModels({
capabilities: ['IMAGE_RECOGNITION'],
providers: ['anthropic', 'openai']
})
// 检查供应商能力
const hasMapping = catalog.hasProviderCapability('openrouter', 'MODEL_MAPPING')
```
### 供应商查询
```typescript
// 查找具有特定能力的供应商
const providersWithFallback = catalog.findProviders({
capabilities: ['FALLBACK_ROUTING', 'AUTO_RETRY']
})
// 查找统一定价的供应商
const unifiedPricingProviders = catalog.findProviders({
pricingModel: 'UNIFIED'
})
```
## 📝 维护指南
### 添加新模型
1. 编辑对应的模型配置文件
2. 添加模型信息
3. 运行验证:`yarn catalog:validate`
4. 提交 PR
### 添加新供应商
1. 编辑 `providers.json`
2. 添加供应商配置
3. 如需覆盖,添加到 `overrides.json`
4. 验证并提交
## 🔧 开发工具
### 命令行
```json
{
"scripts": {
"catalog:validate": "tsx scripts/validate.ts",
"catalog:migrate": "tsx scripts/migrate.ts",
"catalog:test": "vitest run",
"catalog:build": "tsdown"
}
}
```
## 📚 迁移对照表
| 旧函数 | 新 API |
|--------|--------|
| `isFunctionCallingModel(model)` | `catalog.hasCapability(model.id, 'FUNCTION_CALL', model.provider)` |
| `isReasoningModel(model)` | `catalog.hasCapability(model.id, 'REASONING', model.provider)` |
| `isVisionModel(model)` | `catalog.hasCapability(model.id, 'IMAGE_RECOGNITION', model.provider)` |
| `getThinkModelType(model)` | `catalog.getReasoningConfig(model.id, model.provider)` |
## 📊 预期成果
### 时间估算
- Phase 1: 2-3 天
- Phase 2: 1-2 天
- Phase 3: 2-3 天
- **总计**: 5-8 天
### 性能目标
- 配置加载时间: < 100ms
- 模型查询时间: < 1ms
- 内存使用: < 50MB
---
这个简化方案专注于核心功能,避免过度设计,遵循"保持简洁"的原则,为未来扩展留有空间。

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# catalog

View File

@@ -0,0 +1,627 @@
{
"openapi": "3.0.3",
"info": {
"title": "Cherry Studio Catalog API",
"description": "REST API for managing AI models and providers catalog",
"version": "1.0.0",
"contact": {
"name": "Cherry Studio Team"
}
},
"servers": [
{
"url": "http://localhost:3000/api",
"description": "Development server"
}
],
"paths": {
"/catalog/models": {
"get": {
"summary": "List models with pagination and filtering",
"parameters": [
{
"name": "page",
"in": "query",
"schema": {
"type": "integer",
"minimum": 1,
"default": 1
}
},
{
"name": "limit",
"in": "query",
"schema": {
"type": "integer",
"minimum": 1,
"maximum": 100,
"default": 20
}
},
{
"name": "search",
"in": "query",
"schema": {
"type": "string"
}
},
{
"name": "capabilities",
"in": "query",
"schema": {
"type": "array",
"items": {
"type": "string"
}
}
},
{
"name": "providers",
"in": "query",
"schema": {
"type": "array",
"items": {
"type": "string"
}
}
}
],
"responses": {
"200": {
"description": "Paginated list of models",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PaginatedModels"
}
}
}
}
}
},
"put": {
"summary": "Update models configuration",
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ModelsConfig"
}
}
}
},
"responses": {
"200": {
"description": "Models updated successfully"
}
}
}
},
"/catalog/models/{modelId}": {
"get": {
"summary": "Get specific model details",
"parameters": [
{
"name": "modelId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
}
],
"responses": {
"200": {
"description": "Model details",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Model"
}
}
}
}
}
},
"put": {
"summary": "Update specific model",
"parameters": [
{
"name": "modelId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Model"
}
}
}
},
"responses": {
"200": {
"description": "Model updated successfully"
}
}
}
},
"/catalog/providers": {
"get": {
"summary": "List providers with pagination and filtering",
"parameters": [
{
"name": "page",
"in": "query",
"schema": {
"type": "integer",
"minimum": 1,
"default": 1
}
},
{
"name": "limit",
"in": "query",
"schema": {
"type": "integer",
"minimum": 1,
"maximum": 100,
"default": 20
}
},
{
"name": "search",
"in": "query",
"schema": {
"type": "string"
}
},
{
"name": "authentication",
"in": "query",
"schema": {
"type": "array",
"items": {
"type": "string"
}
}
}
],
"responses": {
"200": {
"description": "Paginated list of providers",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/PaginatedProviders"
}
}
}
}
}
},
"put": {
"summary": "Update providers configuration",
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ProvidersConfig"
}
}
}
},
"responses": {
"200": {
"description": "Providers updated successfully"
}
}
}
},
"/catalog/providers/{providerId}": {
"get": {
"summary": "Get specific provider details",
"parameters": [
{
"name": "providerId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
}
],
"responses": {
"200": {
"description": "Provider details",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Provider"
}
}
}
}
}
}
},
"/catalog/models/{modelId}/overrides": {
"get": {
"summary": "Get provider-specific overrides for a model",
"parameters": [
{
"name": "modelId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
}
],
"responses": {
"200": {
"description": "Provider overrides for the model",
"content": {
"application/json": {
"schema": {
"type": "object",
"additionalProperties": {
"$ref": "#/components/schemas/Model"
}
}
}
}
}
}
}
},
"/catalog/models/{modelId}/providers/{providerId}": {
"get": {
"summary": "Get model configuration as seen by specific provider",
"parameters": [
{
"name": "modelId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
},
{
"name": "providerId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
}
],
"responses": {
"200": {
"description": "Model configuration with provider-specific overrides applied",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Model"
}
}
}
}
}
},
"put": {
"summary": "Update model configuration for specific provider (auto-detects if override is needed)",
"parameters": [
{
"name": "modelId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
},
{
"name": "providerId",
"in": "path",
"required": true,
"schema": {
"type": "string"
}
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/Model"
}
}
}
},
"responses": {
"200": {
"description": "Model configuration updated (override created/updated if needed)",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"updated": {
"type": "string",
"enum": ["base_model", "override", "both"]
},
"model": {
"$ref": "#/components/schemas/Model"
}
}
}
}
}
}
}
}
},
"/catalog/stats": {
"get": {
"summary": "Get catalog statistics",
"responses": {
"200": {
"description": "Catalog statistics",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/CatalogStats"
}
}
}
}
}
}
},
"/catalog/validate": {
"post": {
"summary": "Validate catalog configuration",
"responses": {
"200": {
"description": "Validation results",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/ValidationResult"
}
}
}
}
}
}
}
},
"components": {
"schemas": {
"Model": {
"type": "object",
"properties": {
"id": { "type": "string" },
"name": { "type": "string" },
"owned_by": { "type": "string" },
"capabilities": {
"type": "array",
"items": { "type": "string" }
},
"input_modalities": {
"type": "array",
"items": { "type": "string" }
},
"output_modalities": {
"type": "array",
"items": { "type": "string" }
},
"context_window": { "type": "integer" },
"max_output_tokens": { "type": "integer" },
"max_input_tokens": { "type": "integer" },
"pricing": {
"$ref": "#/components/schemas/Pricing"
},
"parameters": {
"$ref": "#/components/schemas/Parameters"
},
"endpoint_types": {
"type": "array",
"items": { "type": "string" }
},
"metadata": { "type": "object" }
}
},
"Provider": {
"type": "object",
"properties": {
"id": { "type": "string" },
"name": { "type": "string" },
"description": { "type": "string" },
"authentication": { "type": "string" },
"pricing_model": { "type": "string" },
"model_routing": { "type": "string" },
"behaviors": { "type": "object" },
"supported_endpoints": {
"type": "array",
"items": { "type": "string" }
},
"api_compatibility": { "type": "object" },
"special_config": { "type": "object" },
"documentation": { "type": "string" },
"website": { "type": "string" },
"deprecated": { "type": "boolean" },
"maintenance_mode": { "type": "boolean" },
"config_version": { "type": "string" },
"metadata": { "type": "object" }
}
},
"Override": {
"type": "object",
"properties": {
"provider_id": { "type": "string" },
"model_id": { "type": "string" },
"disabled": { "type": "boolean" },
"reason": { "type": "string" },
"last_updated": { "type": "string" },
"updated_by": { "type": "string" },
"priority": { "type": "integer" },
"limits": {
"type": "object",
"properties": {
"context_window": { "type": "integer" },
"max_output_tokens": { "type": "integer" }
}
},
"pricing": {
"$ref": "#/components/schemas/Pricing"
}
}
},
"Pricing": {
"type": "object",
"properties": {
"input": {
"type": "object",
"properties": {
"per_million_tokens": { "type": "number" },
"currency": { "type": "string" }
}
},
"output": {
"type": "object",
"properties": {
"per_million_tokens": { "type": "number" },
"currency": { "type": "string" }
}
}
}
},
"Parameters": {
"type": "object",
"additionalProperties": true
},
"PaginatedModels": {
"type": "object",
"properties": {
"data": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Model"
}
},
"pagination": {
"$ref": "#/components/schemas/Pagination"
}
}
},
"PaginatedProviders": {
"type": "object",
"properties": {
"data": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Provider"
}
},
"pagination": {
"$ref": "#/components/schemas/Pagination"
}
}
},
"PaginatedOverrides": {
"type": "object",
"properties": {
"data": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Override"
}
},
"pagination": {
"$ref": "#/components/schemas/Pagination"
}
}
},
"Pagination": {
"type": "object",
"properties": {
"page": { "type": "integer" },
"limit": { "type": "integer" },
"total": { "type": "integer" },
"totalPages": { "type": "integer" }
}
},
"ModelsConfig": {
"type": "object",
"properties": {
"version": { "type": "string" },
"models": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Model"
}
}
}
},
"ProvidersConfig": {
"type": "object",
"properties": {
"version": { "type": "string" },
"providers": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Provider"
}
}
}
},
"OverridesConfig": {
"type": "object",
"properties": {
"version": { "type": "string" },
"overrides": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Override"
}
}
}
},
"CatalogStats": {
"type": "object",
"properties": {
"total_models": { "type": "integer" },
"total_providers": { "type": "integer" },
"total_overrides": { "type": "integer" },
"models_by_provider": { "type": "object" },
"overrides_by_provider": { "type": "object" },
"last_updated": { "type": "string" }
}
},
"ValidationResult": {
"type": "object",
"properties": {
"valid": { "type": "boolean" },
"errors": {
"type": "array",
"items": { "type": "string" }
},
"warnings": {
"type": "array",
"items": { "type": "string" }
}
}
}
}
}
}

View File

@@ -0,0 +1,88 @@
{
"timestamp": "2025-11-24T06:41:03.487Z",
"summary": {
"total_providers": 104,
"total_base_models": 241,
"total_overrides": 1164,
"provider_categories": {
"direct": 2,
"cloud": 6,
"proxy": 3,
"self_hosted": 5
},
"models_by_provider": {
"openai": 79,
"anthropic": 20,
"dashscope": 22,
"deepseek": 7,
"gemini": 50,
"mistral": 31,
"xai": 32
},
"overrides_by_provider": {
"bedrock": 152,
"bedrock_converse": 56,
"anyscale": 12,
"azure": 112,
"azure_ai": 45,
"cerebras": 5,
"vertex_ai-chat-models": 5,
"nlp_cloud": 1,
"cloudflare": 4,
"vertex_ai-code-text-models": 1,
"vertex_ai-code-chat-models": 6,
"codestral": 2,
"cohere_chat": 7,
"databricks": 9,
"deepinfra": 67,
"featherless_ai": 2,
"fireworks_ai": 27,
"friendliai": 2,
"openai": 8,
"vertex_ai-language-models": 46,
"vertex_ai-vision-models": 3,
"gradient_ai": 13,
"groq": 27,
"heroku": 4,
"hyperbolic": 16,
"ai21": 9,
"lambda_ai": 20,
"lemonade": 5,
"aleph_alpha": 3,
"meta_llama": 4,
"moonshot": 17,
"morph": 2,
"nscale": 14,
"oci": 13,
"ollama": 21,
"openrouter": 92,
"ovhcloud": 15,
"palm": 2,
"perplexity": 25,
"replicate": 13,
"sagemaker": 3,
"sambanova": 16,
"snowflake": 24,
"together_ai": 36,
"v0": 3,
"vercel_ai_gateway": 85,
"vertex_ai-anthropic_models": 22,
"vertex_ai-mistral_models": 19,
"vertex_ai-deepseek_models": 2,
"vertex_ai": 1,
"vertex_ai-ai21_models": 5,
"vertex_ai-llama_models": 11,
"vertex_ai-minimax_models": 1,
"vertex_ai-moonshot_models": 1,
"vertex_ai-openai_models": 2,
"vertex_ai-qwen_models": 4,
"wandb": 14,
"watsonx": 28
}
},
"files": {
"providers": "providers.json",
"models": "models.json",
"overrides": "overrides.json"
}
}

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{
"name": "@cherrystudio/catalog",
"version": "0.0.1-alpha.1",
"description": "All Model Catalog",
"main": "dist/index.js",
"module": "dist/index.mjs",
"types": "dist/index.d.ts",
"packageManager": "yarn@4.9.1",
"scripts": {
"build": "tsdown",
"dev": "tsc -w",
"clean": "rm -rf dist",
"test": "vitest run",
"test:watch": "vitest"
},
"author": "Cherry Studio",
"license": "MIT",
"files": [
"dist/**/*"
],
"repository": {
"type": "git",
"url": "git+https://github.com/CherryHQ/cherry-studio.git"
},
"bugs": {
"url": "https://github.com/CherryHQ/cherry-studio/issues"
},
"homepage": "https://github.com/CherryHQ/cherry-studio#readme",
"exports": {
".": {
"types": "./dist/index.d.ts",
"react-native": "./dist/index.js",
"import": "./dist/index.mjs",
"require": "./dist/index.js",
"default": "./dist/index.js"
}
},
"devDependencies": {
"@types/json-schema": "^7.0.15",
"tsdown": "^0.16.6",
"typescript": "^5.9.3",
"vitest": "^4.0.13",
"zod": "^4.1.12"
},
"peerDependencies": {
"zod": "^4.1.12"
},
"dependencies": {
"json-schema": "^0.4.0"
},
"workspaces": [
"web"
]
}

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#!/usr/bin/env tsx
/**
* Migration Script - Phase 2 Implementation
* Usage: npx tsx migrate.ts
*/
import * as path from 'path'
import { MigrationTool } from '../src/utils/migration'
async function main() {
const packageRoot = path.resolve(__dirname, '..')
const sourceDir = packageRoot
const outputDir = path.join(packageRoot, 'data')
console.log('🔧 Cherry Studio Catalog Migration - Phase 2')
console.log('==========================================')
console.log(`📁 Source: ${sourceDir}`)
console.log(`📁 Output: ${outputDir}`)
console.log('')
const tool = new MigrationTool(
path.join(sourceDir, 'provider_endpoints_support.json'),
path.join(sourceDir, 'model_prices_and_context_window.json'),
outputDir
)
try {
await tool.migrate()
console.log('')
console.log('🎉 Migration completed! Check the src/data/ directory for results.')
} catch (error) {
console.error('❌ Migration failed:', error)
process.exit(1)
}
}
main()

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// Vitest Snapshot v1, https://vitest.dev/guide/snapshot.html
exports[`Config & Schema > Snapshot Tests > should snapshot complete configuration structure 1`] = `
{
"models": Any<Array>,
"overrides": Any<Array>,
"providers": Any<Array>,
}
`;
exports[`Config & Schema > Snapshot Tests > should snapshot model configurations 1`] = `
[
{
"capabilities": [
"FUNCTION_CALL",
"REASONING",
],
"contextWindow": 128000,
"description": "A test model for unit testing",
"endpointTypes": [
"CHAT_COMPLETIONS",
],
"id": "test-model",
"inputModalities": [
"TEXT",
],
"maxInputTokens": 124000,
"maxOutputTokens": 4096,
"metadata": {
"architecture": "transformer",
"category": "language-model",
"documentation": "https://docs.test.com/models/test-model",
"family": "test-family",
"license": "mit",
"source": "test",
"tags": [
"test",
"fast",
"reliable",
],
"trainingData": "synthetic",
},
"name": "Test Model",
"outputModalities": [
"TEXT",
],
"ownedBy": "TestProvider",
"parameters": {
"maxTokens": true,
"systemMessage": true,
"temperature": {
"default": 1,
"max": 2,
"min": 0,
"supported": true,
},
"topP": {
"default": 1,
"max": 1,
"min": 0,
"supported": true,
},
},
"pricing": {
"input": {
"currency": "USD",
"perMillionTokens": 1,
},
"output": {
"currency": "USD",
"perMillionTokens": 2,
},
},
},
]
`;
exports[`Config & Schema > Snapshot Tests > should snapshot override configurations 1`] = `
[
{
"capabilities": {
"add": [
"FUNCTION_CALL",
],
"remove": [
"REASONING",
],
},
"disabled": false,
"lastUpdated": "2025-11-24T07:08:00Z",
"limits": {
"contextWindow": 256000,
"maxOutputTokens": 8192,
},
"modelId": "test-model",
"pricing": {
"input": {
"currency": "USD",
"perMillionTokens": 0.5,
},
},
"priority": 100,
"providerId": "test-provider",
"reason": "Test override for enhanced capabilities and limits",
"updatedBy": "test-suite",
},
]
`;
exports[`Config & Schema > Snapshot Tests > should snapshot provider configurations 1`] = `
[
{
"apiCompatibility": {
"supportsApiVersion": false,
"supportsArrayContent": true,
"supportsDeveloperRole": false,
"supportsMultimodal": false,
"supportsParallelTools": false,
"supportsServiceTier": false,
"supportsStreamOptions": false,
"supportsThinkingControl": false,
},
"authentication": "API_KEY",
"behaviors": {
"hasAutoRetry": false,
"hasRealTimeMetrics": false,
"providesFallbackRouting": false,
"providesModelMapping": false,
"providesUsageAnalytics": false,
"providesUsageLimits": false,
"requiresApiKeyValidation": true,
"supportsBatchProcessing": false,
"supportsCustomModels": false,
"supportsHealthCheck": false,
"supportsModelFineTuning": false,
"supportsModelVersioning": false,
"supportsRateLimiting": false,
"supportsStreaming": true,
"supportsWebhookEvents": false,
},
"configVersion": "1.0.0",
"deprecated": false,
"description": "A test provider for unit testing",
"documentation": "https://docs.test.com",
"id": "test-provider",
"maintenanceMode": false,
"metadata": {
"category": "ai-provider",
"reliability": "high",
"source": "test",
"supportedLanguages": [
"en",
],
"tags": [
"test",
],
},
"modelRouting": "DIRECT",
"name": "Test Provider",
"pricingModel": "PER_MODEL",
"specialConfig": {},
"supportedEndpoints": [
"CHAT_COMPLETIONS",
],
"website": "https://test.com",
},
]
`;
exports[`Config & Schema > Snapshot Tests > should snapshot validation results 1`] = `
{
"data": {
"capabilities": [
"FUNCTION_CALL",
"REASONING",
],
"contextWindow": 128000,
"description": "A test model for unit testing",
"endpointTypes": [
"CHAT_COMPLETIONS",
],
"id": "test-model",
"inputModalities": [
"TEXT",
],
"maxInputTokens": 124000,
"maxOutputTokens": 4096,
"metadata": {
"architecture": "transformer",
"category": "language-model",
"documentation": "https://docs.test.com/models/test-model",
"family": "test-family",
"license": "mit",
"source": "test",
"tags": [
"test",
"fast",
"reliable",
],
"trainingData": "synthetic",
},
"name": "Test Model",
"outputModalities": [
"TEXT",
],
"ownedBy": "TestProvider",
"parameters": {
"maxTokens": true,
"systemMessage": true,
"temperature": {
"default": 1,
"max": 2,
"min": 0,
"supported": true,
},
"topP": {
"default": 1,
"max": 1,
"min": 0,
"supported": true,
},
},
"pricing": {
"input": {
"currency": "USD",
"perMillionTokens": 1,
},
"output": {
"currency": "USD",
"perMillionTokens": 2,
},
},
},
"success": true,
"warnings": [
"Model has REASONING capability but no reasoning configuration",
"Custom validation warning for snapshot",
],
}
`;

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import * as path from 'path'
import { describe, expect, it } from 'vitest'
import { ConfigLoader } from '../loader/ConfigLoader'
import { SchemaValidator } from '../validator/SchemaValidator'
// Use fixtures directory for test data
const fixturesPath = path.join(__dirname, 'fixtures')
describe('Config & Schema', () => {
describe('ConfigLoader', () => {
it('should load models with complete validation', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const models = await loader.loadModels('test-models.json')
expect(models).toBeDefined()
expect(Array.isArray(models)).toBe(true)
expect(models).toHaveLength(1)
const model = models[0]
expect(model).toStrictEqual({
id: 'test-model',
name: 'Test Model',
ownedBy: 'TestProvider',
description: 'A test model for unit testing',
capabilities: ['FUNCTION_CALL', 'REASONING'],
inputModalities: ['TEXT'],
outputModalities: ['TEXT'],
contextWindow: 128000,
maxOutputTokens: 4096,
maxInputTokens: 124000,
pricing: {
input: { perMillionTokens: 1, currency: 'USD' },
output: { perMillionTokens: 2, currency: 'USD' }
},
parameters: {
temperature: { supported: true, min: 0, max: 2, default: 1 },
maxTokens: true,
systemMessage: true,
topP: { supported: true, min: 0, max: 1, default: 1 }
},
endpointTypes: ['CHAT_COMPLETIONS'],
metadata: {
tags: ['test', 'fast', 'reliable'],
category: 'language-model',
source: 'test',
license: 'mit',
documentation: 'https://docs.test.com/models/test-model',
family: 'test-family',
architecture: 'transformer',
trainingData: 'synthetic'
}
})
})
it('should load providers with complete validation', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const providers = await loader.loadProviders('test-providers.json')
expect(providers).toBeDefined()
expect(Array.isArray(providers)).toBe(true)
expect(providers).toHaveLength(1)
const provider = providers[0]
expect(provider).toStrictEqual({
id: 'test-provider',
name: 'Test Provider',
description: 'A test provider for unit testing',
authentication: 'API_KEY',
pricingModel: 'PER_MODEL',
modelRouting: 'DIRECT',
behaviors: {
supportsCustomModels: false,
providesModelMapping: false,
supportsModelVersioning: false,
providesFallbackRouting: false,
hasAutoRetry: false,
supportsHealthCheck: false,
hasRealTimeMetrics: false,
providesUsageAnalytics: false,
supportsWebhookEvents: false,
requiresApiKeyValidation: true,
supportsRateLimiting: false,
providesUsageLimits: false,
supportsStreaming: true,
supportsBatchProcessing: false,
supportsModelFineTuning: false
},
supportedEndpoints: ['CHAT_COMPLETIONS'],
apiCompatibility: {
supportsArrayContent: true,
supportsStreamOptions: false,
supportsDeveloperRole: false,
supportsThinkingControl: false,
supportsApiVersion: false,
supportsParallelTools: false,
supportsMultimodal: false,
supportsServiceTier: false
},
specialConfig: {},
documentation: 'https://docs.test.com',
website: 'https://test.com',
deprecated: false,
maintenanceMode: false,
configVersion: '1.0.0',
metadata: {
tags: ['test'],
category: 'ai-provider',
source: 'test',
reliability: 'high',
supportedLanguages: ['en']
}
})
})
it('should load overrides with complete validation', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const overrides = await loader.loadOverrides('test-overrides.json')
expect(overrides).toBeDefined()
expect(Array.isArray(overrides)).toBe(true)
expect(overrides).toHaveLength(1)
const override = overrides[0]
expect(override).toMatchObject({
providerId: 'test-provider',
modelId: 'test-model',
disabled: false,
reason: 'Test override for enhanced capabilities and limits',
priority: 100
})
expect(override.capabilities?.add).toContain('FUNCTION_CALL')
expect(override.capabilities?.remove).toContain('REASONING')
expect(override.limits?.contextWindow).toBe(256000)
expect(override.limits?.maxOutputTokens).toBe(8192)
})
it('should load all configs simultaneously', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const configs = await loader.loadAllConfigs({
modelsFile: 'test-models.json',
providersFile: 'test-providers.json',
overridesFile: 'test-overrides.json'
})
expect(configs).toHaveProperty('models')
expect(configs).toHaveProperty('providers')
expect(configs).toHaveProperty('overrides')
expect(configs.models).toHaveLength(1)
expect(configs.providers).toHaveLength(1)
expect(configs.overrides).toHaveLength(1)
})
it('should handle missing files gracefully', async () => {
const loader = new ConfigLoader({
basePath: '/nonexistent/path'
})
await expect(loader.loadModels('nonexistent.json')).rejects.toThrow('Failed to load models')
})
})
describe('SchemaValidator', () => {
it('should validate valid model configuration', async () => {
const validator = new SchemaValidator()
const validModel = {
id: 'test-model',
capabilities: ['FUNCTION_CALL', 'REASONING'],
inputModalities: ['TEXT'],
outputModalities: ['TEXT'],
contextWindow: 128000,
maxOutputTokens: 4096,
metadata: {
tags: ['test'],
category: 'language-model',
source: 'test'
}
}
const result = await validator.validateModel(validModel)
expect(result.success).toBe(true)
expect(result.data).toBeDefined()
expect(result.data!.id).toBe('test-model')
})
it('should reject invalid model configuration', async () => {
const validator = new SchemaValidator()
const invalidModel = {
id: 123, // Should be string
capabilities: 'not-array', // Should be array
contextWindow: -1000 // Should be positive
}
const result = await validator.validateModel(invalidModel)
expect(result.success).toBe(false)
expect(result.errors).toBeDefined()
expect(result.errors!.length).toBeGreaterThan(0)
})
it('should provide warnings for model configuration issues', async () => {
const validator = new SchemaValidator()
const modelWithIssues = {
id: 'test-model',
capabilities: [], // Empty capabilities
inputModalities: ['TEXT'],
outputModalities: ['TEXT'],
contextWindow: 200000, // Large context window
maxOutputTokens: 4096,
// Missing pricing and description
metadata: {
tags: ['test'],
category: 'language-model',
source: 'test'
}
}
const result = await validator.validateModel(modelWithIssues)
expect(result.success).toBe(true)
expect(result.warnings).toBeDefined()
expect(result.warnings!.length).toBeGreaterThan(0)
})
it('should accept custom validation warnings', async () => {
const validator = new SchemaValidator()
const model = {
id: 'test-model',
capabilities: ['FUNCTION_CALL'],
inputModalities: ['TEXT'],
outputModalities: ['TEXT'],
contextWindow: 1000,
maxOutputTokens: 500,
metadata: {
tags: ['test'],
category: 'language-model',
source: 'test'
}
}
const result = await validator.validateModel(model, {
includeWarnings: true,
customValidation: () => ['Custom warning message']
})
expect(result.success).toBe(true)
expect(result.warnings).toContain('Custom warning message')
})
})
describe('Integration Tests', () => {
it('should load and validate models end-to-end', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const validator = new SchemaValidator()
// Load models
const models = await loader.loadModels('test-models.json')
expect(models.length).toBeGreaterThan(0)
// Validate first model
const validationResult = await validator.validateModel(models[0])
expect(validationResult.success).toBe(true)
expect(validationResult.data).toBeDefined()
expect(validationResult.data!.id).toBe(models[0].id)
})
it('should work with caching enabled', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: true
})
// Test that caching doesn't break basic functionality
const models1 = await loader.loadModels('test-models.json')
expect(models1.length).toBeGreaterThan(0)
expect(models1[0]).toHaveProperty('id', 'test-model')
// Test cache clear functionality
loader.clearCache()
expect(true).toBe(true) // Cache clear should not throw
})
})
describe('Snapshot Tests', () => {
it('should snapshot model configurations', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const models = await loader.loadModels('test-models.json')
expect(models).toMatchSnapshot()
})
it('should snapshot provider configurations', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const providers = await loader.loadProviders('test-providers.json')
expect(providers).toMatchSnapshot()
})
it('should snapshot override configurations', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const overrides = await loader.loadOverrides('test-overrides.json')
expect(overrides).toMatchSnapshot()
})
it('should snapshot complete configuration structure', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const configs = await loader.loadAllConfigs({
modelsFile: 'test-models.json',
providersFile: 'test-providers.json',
overridesFile: 'test-overrides.json'
})
expect(configs).toMatchSnapshot({
models: expect.any(Array),
providers: expect.any(Array),
overrides: expect.any(Array)
})
})
it('should snapshot validation results', async () => {
const loader = new ConfigLoader({
basePath: fixturesPath,
validateOnLoad: true,
cacheEnabled: false
})
const validator = new SchemaValidator()
const model = await loader.loadModels('test-models.json')
const validationResult = await validator.validateModel(model[0], {
includeWarnings: true,
customValidation: () => ['Custom validation warning for snapshot']
})
expect(validationResult).toMatchSnapshot()
})
})
})

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{
"version": "1.0.0",
"models": [
{
"id": "test-model",
"name": "Test Model",
"ownedBy": "TestProvider",
"description": "A test model for unit testing",
"capabilities": ["FUNCTION_CALL", "REASONING"],
"inputModalities": ["TEXT"],
"outputModalities": ["TEXT"],
"contextWindow": 128000,
"maxOutputTokens": 4096,
"maxInputTokens": 124000,
"pricing": {
"input": {
"perMillionTokens": 1,
"currency": "USD"
},
"output": {
"perMillionTokens": 2,
"currency": "USD"
}
},
"parameters": {
"temperature": {
"supported": true,
"min": 0,
"max": 2,
"default": 1
},
"maxTokens": true,
"systemMessage": true,
"topP": {
"supported": true,
"min": 0,
"max": 1,
"default": 1
}
},
"endpointTypes": ["CHAT_COMPLETIONS"],
"metadata": {
"tags": ["test", "fast", "reliable"],
"category": "language-model",
"source": "test",
"license": "mit",
"documentation": "https://docs.test.com/models/test-model",
"family": "test-family",
"architecture": "transformer",
"trainingData": "synthetic"
}
}
]
}

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@@ -0,0 +1,28 @@
{
"version": "1.0.0",
"overrides": [
{
"providerId": "test-provider",
"modelId": "test-model",
"capabilities": {
"add": ["FUNCTION_CALL"],
"remove": ["REASONING"]
},
"limits": {
"contextWindow": 256000,
"maxOutputTokens": 8192
},
"pricing": {
"input": {
"perMillionTokens": 0.5,
"currency": "USD"
}
},
"disabled": false,
"reason": "Test override for enhanced capabilities and limits",
"lastUpdated": "2025-11-24T07:08:00Z",
"updatedBy": "test-suite",
"priority": 100
}
]
}

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@@ -0,0 +1,53 @@
{
"version": "1.0.0",
"providers": [
{
"id": "test-provider",
"name": "Test Provider",
"description": "A test provider for unit testing",
"authentication": "API_KEY",
"pricingModel": "PER_MODEL",
"modelRouting": "DIRECT",
"behaviors": {
"supportsCustomModels": false,
"providesModelMapping": false,
"supportsModelVersioning": false,
"providesFallbackRouting": false,
"hasAutoRetry": false,
"supportsHealthCheck": false,
"hasRealTimeMetrics": false,
"providesUsageAnalytics": false,
"supportsWebhookEvents": false,
"requiresApiKeyValidation": true,
"supportsRateLimiting": false,
"providesUsageLimits": false,
"supportsStreaming": true,
"supportsBatchProcessing": false,
"supportsModelFineTuning": false
},
"supportedEndpoints": ["CHAT_COMPLETIONS"],
"apiCompatibility": {
"supportsArrayContent": true,
"supportsStreamOptions": false,
"supportsDeveloperRole": false,
"supportsThinkingControl": false,
"supportsApiVersion": false,
"supportsParallelTools": false,
"supportsMultimodal": false
},
"specialConfig": {},
"documentation": "https://docs.test.com",
"website": "https://test.com",
"deprecated": false,
"maintenanceMode": false,
"configVersion": "1.0.0",
"metadata": {
"tags": ["test"],
"category": "ai-provider",
"source": "test",
"reliability": "high",
"supportedLanguages": ["en"]
}
}
]
}

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/**
* Cherry Studio Catalog
* Main entry point for the model and provider catalog system
*/
// Export all schemas
export * from './schemas'
// Export core functionality
export type {
ConfigLoadOptions,
ModelConfig,
ProviderConfig,
ProviderModelOverride
} from './loader/ConfigLoader'
export { ConfigLoader } from './loader/ConfigLoader'
export type {
ValidationOptions,
ValidationResult
} from './validator/SchemaValidator'
export { SchemaValidator } from './validator/SchemaValidator'

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/**
* Configuration Loader
* Responsible for loading and parsing JSON configuration files
*/
import * as fs from 'fs/promises'
import * as path from 'path'
import type * as z from 'zod'
import { ModelListSchema, OverrideListSchema, ProviderListSchema } from '../schemas'
import { safeParseJSON } from '../utils/parse-json/parse-json'
import { zod4Schema } from '../utils/schema'
export type ModelConfig = z.infer<typeof ModelListSchema>['models'][0]
export type ProviderConfig = z.infer<typeof ProviderListSchema>['providers'][0]
export type ProviderModelOverride = z.infer<typeof OverrideListSchema>['overrides'][0]
export interface ConfigLoadOptions {
basePath?: string
validateOnLoad?: boolean
cacheEnabled?: boolean
}
export class ConfigLoader {
private cache = new Map<string, any>()
private options: ConfigLoadOptions
constructor(options: ConfigLoadOptions = {}) {
this.options = {
basePath: path.join(__dirname, '../data'),
validateOnLoad: true,
cacheEnabled: true,
...options
}
}
/**
* Load model configurations from JSON file
*/
async loadModels(filename = 'models.json'): Promise<ModelConfig[]> {
const filePath = path.join(this.options.basePath!, filename)
if (this.options.cacheEnabled && this.cache.has(filePath)) {
return this.cache.get(filePath)
}
try {
const rawData = await fs.readFile(filePath, 'utf-8')
let validatedData: any
if (this.options.validateOnLoad) {
const schema = zod4Schema(ModelListSchema)
const parseResult = await safeParseJSON({ text: rawData, schema })
if (!parseResult.success) {
throw new Error(`Validation failed: ${parseResult.error.message}`)
}
validatedData = parseResult.value
} else {
const parseResult = await safeParseJSON({ text: rawData })
if (!parseResult.success) {
throw new Error(`Parse failed: ${parseResult.error.message}`)
}
validatedData = parseResult.value
}
const models = validatedData.models
const version = validatedData.version
if (this.options.cacheEnabled) {
this.cache.set(filePath, { models, version })
}
return models
} catch (error) {
throw new Error(
`Failed to load models from ${filePath}: ${error instanceof Error ? error.message : 'Unknown error'}`
)
}
}
/**
* Load provider configurations from JSON file
*/
async loadProviders(filename = 'providers.json'): Promise<ProviderConfig[]> {
const filePath = path.join(this.options.basePath!, filename)
if (this.options.cacheEnabled && this.cache.has(filePath)) {
return this.cache.get(filePath)
}
try {
const rawData = await fs.readFile(filePath, 'utf-8')
let validatedData: any
if (this.options.validateOnLoad) {
const schema = zod4Schema(ProviderListSchema)
const parseResult = await safeParseJSON({ text: rawData, schema })
if (!parseResult.success) {
throw new Error(`Validation failed: ${parseResult.error.message}`)
}
validatedData = parseResult.value
} else {
const parseResult = await safeParseJSON({ text: rawData })
if (!parseResult.success) {
throw new Error(`Parse failed: ${parseResult.error.message}`)
}
validatedData = parseResult.value
}
const providers = validatedData.providers
const version = validatedData.version
if (this.options.cacheEnabled) {
this.cache.set(filePath, { providers, version })
}
return providers
} catch (error) {
throw new Error(
`Failed to load providers from ${filePath}: ${error instanceof Error ? error.message : 'Unknown error'}`
)
}
}
/**
* Load override configurations from JSON file
*/
async loadOverrides(filename = 'overrides.json'): Promise<ProviderModelOverride[]> {
const filePath = path.join(this.options.basePath!, filename)
if (this.options.cacheEnabled && this.cache.has(filePath)) {
return this.cache.get(filePath)
}
try {
const rawData = await fs.readFile(filePath, 'utf-8')
let validatedData: any
if (this.options.validateOnLoad) {
const schema = zod4Schema(OverrideListSchema)
const parseResult = await safeParseJSON({ text: rawData, schema })
if (!parseResult.success) {
throw new Error(`Validation failed: ${parseResult.error.message}`)
}
validatedData = parseResult.value
} else {
const parseResult = await safeParseJSON({ text: rawData })
if (!parseResult.success) {
throw new Error(`Parse failed: ${parseResult.error.message}`)
}
validatedData = parseResult.value
}
const overrides = validatedData.overrides
const version = validatedData.version
if (this.options.cacheEnabled) {
this.cache.set(filePath, { overrides, version })
}
return overrides
} catch (error) {
throw new Error(
`Failed to load overrides from ${filePath}: ${error instanceof Error ? error.message : 'Unknown error'}`
)
}
}
/**
* Load all configuration files
*/
async loadAllConfigs(options: { modelsFile?: string; providersFile?: string; overridesFile?: string } = {}): Promise<{
models: ModelConfig[]
providers: ProviderConfig[]
overrides: ProviderModelOverride[]
}> {
const [models, providers, overrides] = await Promise.all([
this.loadModels(options.modelsFile),
this.loadProviders(options.providersFile),
this.loadOverrides(options.overridesFile)
])
return { models, providers, overrides }
}
/**
* Clear cache
*/
clearCache(): void {
this.cache.clear()
}
/**
* Check if file exists
*/
private async fileExists(filePath: string): Promise<boolean> {
try {
await fs.access(filePath)
return true
} catch {
return false
}
}
/**
* Get configuration file version
*/
async getConfigVersion(filename: string): Promise<string | null> {
const filePath = path.join(this.options.basePath!, filename)
if (!(await this.fileExists(filePath))) {
return null
}
try {
const rawData = await fs.readFile(filePath, 'utf-8')
const jsonData = JSON.parse(rawData)
return jsonData.version || null
} catch {
return null
}
}
/**
* Get all configuration versions
*/
async getAllConfigVersions(): Promise<{
models: string | null
providers: string | null
overrides: string | null
}> {
const [models, providers, overrides] = await Promise.all([
this.getConfigVersion('models.json'),
this.getConfigVersion('providers.json'),
this.getConfigVersion('overrides.json')
])
return { models, providers, overrides }
}
}

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/**
* Common type definitions for the catalog system
* Shared across model, provider, and override schemas
*/
import * as z from 'zod'
// Common string types for reuse
export const ModelIdSchema = z.string()
export const ProviderIdSchema = z.string()
export const VersionSchema = z.string()
// Currency codes
export const CurrencySchema = z.enum(['USD', 'EUR', 'CNY', 'JPY', 'GBP'])
// Common file size units
export const FileSizeUnitSchema = z.enum(['B', 'KB', 'MB', 'GB'])
// Common status types
export const StatusSchema = z.enum(['active', 'inactive', 'deprecated', 'maintenance'])
// Timestamp schema for date fields
export const TimestampSchema = z.iso.datetime()
// Range helper schemas
export const NumericRangeSchema = z.object({
min: z.number(),
max: z.number()
})
export const StringRangeSchema = z.object({
min: z.string(),
max: z.string()
})
// Price per token schema
export const PricePerTokenSchema = z.object({
perMillionTokens: z.number().nonnegative(),
currency: CurrencySchema.default('USD')
})
// Generic metadata schema
export const MetadataSchema = z.record(z.string(), z.any()).optional()
// Type exports
export type ModelId = z.infer<typeof ModelIdSchema>
export type ProviderId = z.infer<typeof ProviderIdSchema>
export type Version = z.infer<typeof VersionSchema>
export type Currency = z.infer<typeof CurrencySchema>
export type FileSizeUnit = z.infer<typeof FileSizeUnitSchema>
export type Status = z.infer<typeof StatusSchema>
export type Timestamp = z.infer<typeof TimestampSchema>
export type NumericRange = z.infer<typeof NumericRangeSchema>
export type StringRange = z.infer<typeof StringRangeSchema>
export type PricePerToken = z.infer<typeof PricePerTokenSchema>
export type Metadata = z.infer<typeof MetadataSchema>
// Common validation utilities
export const validateRange = (min: number, max: number): boolean => {
return min <= max
}
export const validatePositiveNumber = (value: number): boolean => {
return value >= 0
}
export const validateNonEmptyString = (value: string): boolean => {
return value.trim().length > 0
}

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/**
* Unified export of all catalog schemas and types
* This file provides a single entry point for all schema definitions
*/
// Export all schemas from common types
export * from './common'
// Export model schemas
export * from './model'
// Export provider schemas
export * from './provider'
// Export override schemas
export * from './override'
// Re-export commonly used combined types for convenience
export type {
Modality,
ModelCapabilityType,
ModelConfig,
ModelPricing,
ParameterSupport,
Reasoning
} from './model'
export type {
OverrideResult,
OverrideValidation,
ProviderModelOverride
} from './override'
export type {
Authentication,
EndpointType,
McpSupport,
PricingModel,
ProviderBehaviors,
ProviderConfig
} from './provider'
// Export common types
export type {
Currency,
Metadata,
ModelId,
ProviderId,
Timestamp,
Version
} from './common'

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/**
* Model configuration schema definitions
* Defines the structure for model metadata, capabilities, and configurations
*/
import * as z from 'zod'
import {
CurrencySchema,
MetadataSchema,
ModelIdSchema,
PricePerTokenSchema,
TimestampSchema,
VersionSchema
} from './common'
// Modality types - supported input/output modalities
export const ModalitySchema = z.enum(['TEXT', 'VISION', 'AUDIO', 'VIDEO', 'VECTOR'])
// Model capability types
export const ModelCapabilityTypeSchema = z.enum([
'FUNCTION_CALL', // Function calling
'REASONING', // Reasoning/thinking
'IMAGE_RECOGNITION', // Image recognition
'IMAGE_GENERATION', // Image generation
'AUDIO_RECOGNITION', // Audio recognition
'AUDIO_GENERATION', // Audio generation
'EMBEDDING', // Embedding vector generation
'RERANK', // Text reranking
'AUDIO_TRANSCRIPT', // Audio transcription
'VIDEO_RECOGNITION', // Video recognition
'VIDEO_GENERATION', // Video generation
'STRUCTURED_OUTPUT', // Structured output
'FILE_INPUT', // File input support
'WEB_SEARCH', // Built-in web search
'CODE_EXECUTION', // Code execution
'FILE_SEARCH', // File search
'COMPUTER_USE' // Computer use
])
// Reasoning configuration
export const ReasoningSchema = z.discriminatedUnion('type', [
z.object({
type: z.literal('openai-chat'),
params: z.object({
reasoning_effort: z.enum(['none', 'minimal', 'low', 'medium', 'high']).optional()
})
}),
z.object({
type: z.literal('openai-responses'),
params: z.object({
reasoning: z.object({
effort: z.enum(['none', 'minimal', 'low', 'medium', 'high']).optional(),
summary: z.enum(['auto', 'concise', 'detailed']).optional()
})
})
}),
z.object({
type: z.literal('anthropic'),
params: z.object({
type: z.union([z.literal('enabled'), z.literal('disabled')]),
budgetTokens: z.number().optional()
})
}),
z.object({
type: z.literal('gemini'),
params: z.union([
z
.object({
thinking_config: z.object({
include_thoughts: z.boolean().optional(),
thinking_budget: z.number().optional()
})
})
.optional(),
z
.object({
thinking_level: z.enum(['low', 'medium', 'high']).optional()
})
.optional()
])
}),
z.object({
type: z.literal('openrouter'),
params: z.object({
reasoning: z
.object({
effort: z
.union([z.literal('none'), z.literal('minimal'), z.literal('low'), z.literal('medium'), z.literal('high')])
.optional(),
max_tokens: z.number().optional(),
exclude: z.boolean().optional()
})
.refine((v) => {
v.effort == null || v.max_tokens == null
}, 'One of the following (not both)')
})
}),
z.object({
type: z.literal('qwen'),
params: z.object({
enable_thinking: z.boolean(),
thinking_budget: z.number().optional()
})
}),
z.object({
type: z.literal('doubao'),
params: z.object({
thinking: z.object({
type: z.union([z.literal('enabled'), z.literal('disabled'), z.literal('auto')])
})
})
}),
z.object({
type: z.literal('dashscope'),
params: z.object({
enable_thinking: z.boolean(),
incremental_output: z.boolean().optional()
})
}),
z.object({
type: z.literal('self-hosted'),
params: z.object({
chat_template_kwargs: z.object({
enable_thinking: z.boolean().optional(),
thinking: z.boolean().optional()
})
})
})
])
// Parameter support configuration
export const ParameterSupportSchema = z.object({
temperature: z
.object({
supported: z.boolean(),
min: z.number().min(0).max(2).optional(),
max: z.number().min(0).max(2).optional(),
default: z.number().min(0).max(2).optional()
})
.optional(),
topP: z
.object({
supported: z.boolean(),
min: z.number().min(0).max(1).optional(),
max: z.number().min(0).max(1).optional(),
default: z.number().min(0).max(1).optional()
})
.optional(),
topK: z
.object({
supported: z.boolean(),
min: z.number().positive().optional(),
max: z.number().positive().optional()
})
.optional(),
frequencyPenalty: z.boolean().optional(),
presencePenalty: z.boolean().optional(),
maxTokens: z.boolean().optional(),
stopSequences: z.boolean().optional(),
systemMessage: z.boolean().optional(),
developerRole: z.boolean().optional()
})
// Model pricing configuration
export const ModelPricingSchema = z.object({
input: PricePerTokenSchema,
output: PricePerTokenSchema,
// Image pricing (optional)
per_image: z
.object({
price: z.number(),
currency: CurrencySchema.default('USD'),
unit: z.enum(['image', 'pixel']).optional()
})
.optional(),
// Audio/video pricing (optional)
per_minute: z
.object({
price: z.number(),
currency: CurrencySchema.default('USD')
})
.optional()
})
// Model configuration schema
export const ModelConfigSchema = z.object({
// Basic information
id: ModelIdSchema,
name: z.string().optional(),
owned_by: z.string().optional(),
description: z.string().optional(),
// Capabilities (core)
capabilities: z.array(ModelCapabilityTypeSchema),
// Modalities
input_modalities: z.array(ModalitySchema),
output_modalities: z.array(ModalitySchema),
// Limits
context_window: z.number(),
max_output_tokens: z.number(),
max_input_tokens: z.number().optional(),
// Pricing
pricing: ModelPricingSchema.optional(),
// Reasoning configuration
reasoning: ReasoningSchema.optional(),
// Parameter support
parameters: ParameterSupportSchema.optional(),
// Endpoint types (will reference provider schema)
endpoint_types: z.array(z.string()).optional(),
// Metadata
release_date: TimestampSchema.optional(),
deprecation_date: TimestampSchema.optional(),
replaced_by: ModelIdSchema.optional(),
// Version control
version: VersionSchema.optional(),
compatibility: z
.object({
min_version: VersionSchema.optional(),
max_version: VersionSchema.optional()
})
.optional(),
// Additional metadata
metadata: MetadataSchema
})
// Model list container schema for JSON files
export const ModelListSchema = z.object({
version: VersionSchema,
models: z.array(ModelConfigSchema)
})
// Type exports
export type Modality = z.infer<typeof ModalitySchema>
export type ModelCapabilityType = z.infer<typeof ModelCapabilityTypeSchema>
export type Reasoning = z.infer<typeof ReasoningSchema>
export type ParameterSupport = z.infer<typeof ParameterSupportSchema>
export type ModelPricing = z.infer<typeof ModelPricingSchema>
export type ModelConfig = z.infer<typeof ModelConfigSchema>
export type ModelList = z.infer<typeof ModelListSchema>

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/**
* Provider model override schema definitions
* Defines how providers can override specific model configurations
*/
import * as z from 'zod'
import { MetadataSchema, ModelIdSchema, ProviderIdSchema, VersionSchema } from './common'
import { ModelCapabilityTypeSchema, ModelPricingSchema, ParameterSupportSchema, ReasoningSchema } from './model'
import { EndpointTypeSchema } from './provider'
// Capability override operations
export const CapabilityOverrideSchema = z.object({
add: z.array(ModelCapabilityTypeSchema).optional(), // Add capabilities
remove: z.array(ModelCapabilityTypeSchema).optional(), // Remove capabilities
force: z.array(ModelCapabilityTypeSchema).optional() // Force set capabilities (ignore base config)
})
// Limits override configuration
export const LimitsOverrideSchema = z.object({
context_window: z.number().optional(),
max_output_tokens: z.number().optional(),
max_input_tokens: z.number().optional()
})
// Pricing override configuration
export const PricingOverrideSchema = ModelPricingSchema.partial().optional()
// Endpoint types override
export const EndpointTypesOverrideSchema = z.array(EndpointTypeSchema).optional()
// Reasoning configuration override - allows partial override of reasoning configs
export const ReasoningOverrideSchema = ReasoningSchema.optional()
// Parameter support override
export const ParameterSupportOverrideSchema = ParameterSupportSchema.partial().optional()
// Model metadata override
export const MetadataOverrideSchema = z
.object({
name: z.string().optional(),
description: z.string().optional(),
deprecation_date: z.iso.datetime().optional(),
replaced_by: ModelIdSchema.optional(),
metadata: MetadataSchema
})
.optional()
// Main provider model override schema
export const ProviderModelOverrideSchema = z.object({
// Identification
provider_id: ProviderIdSchema,
model_id: ModelIdSchema,
// Capability overrides
capabilities: CapabilityOverrideSchema.optional(),
// Limits overrides
limits: LimitsOverrideSchema.optional(),
// Pricing overrides
pricing: PricingOverrideSchema,
// Reasoning configuration overrides
reasoning: ReasoningOverrideSchema.optional(),
// Parameter support overrides
parameters: ParameterSupportOverrideSchema.optional(),
// Endpoint type overrides
endpoint_types: EndpointTypesOverrideSchema.optional(),
// Model metadata overrides
metadata: MetadataOverrideSchema.optional(),
// Status overrides
disabled: z.boolean().optional(), // Disable this model for this provider
replace_with: ModelIdSchema.optional(), // Replace with alternative model
// Override tracking
reason: z.string().optional(), // Reason for override
last_updated: z.iso.datetime().optional(),
updated_by: z.string().optional(), // Who made the override
// Override priority (higher number = higher priority)
priority: z.number().default(0),
// Override conditions
conditions: z
.object({
// Apply override only for specific regions
regions: z.array(z.string()).optional(),
// Apply override only for specific user tiers
user_tiers: z.array(z.string()).optional(),
// Apply override only in specific environments
environments: z.array(z.enum(['development', 'staging', 'production'])).optional(),
// Time-based conditions
valid_from: z.iso.datetime().optional(),
valid_until: z.iso.datetime().optional()
})
.optional(),
// Additional override metadata
override_metadata: MetadataSchema.optional()
})
// Override container schema for JSON files
export const OverrideListSchema = z.object({
version: VersionSchema,
overrides: z.array(ProviderModelOverrideSchema)
})
// Override application result schema
export const OverrideResultSchema = z.object({
model_id: ModelIdSchema,
provider_id: ProviderIdSchema,
applied: z.boolean(),
applied_overrides: z.array(z.string()), // List of applied override fields
original_values: z.record(z.string(), z.unknown()), // Original values before override
new_values: z.record(z.string(), z.unknown()), // New values after override
override_reason: z.string().optional(),
applied_at: z.iso.datetime().optional()
})
// Override validation result
export const OverrideValidationSchema = z.object({
valid: z.boolean(),
errors: z.array(z.string()),
warnings: z.array(z.string()),
recommendations: z.array(z.string())
})
// Type exports
export type CapabilityOverride = z.infer<typeof CapabilityOverrideSchema>
export type LimitsOverride = z.infer<typeof LimitsOverrideSchema>
export type PricingOverride = z.infer<typeof PricingOverrideSchema>
export type EndpointTypesOverride = z.infer<typeof EndpointTypesOverrideSchema>
export type ReasoningOverride = z.infer<typeof ReasoningOverrideSchema>
export type ParameterSupportOverride = z.infer<typeof ParameterSupportOverrideSchema>
export type MetadataOverride = z.infer<typeof MetadataOverrideSchema>
export type ProviderModelOverride = z.infer<typeof ProviderModelOverrideSchema>
export type OverrideList = z.infer<typeof OverrideListSchema>
export type OverrideResult = z.infer<typeof OverrideResultSchema>
export type OverrideValidation = z.infer<typeof OverrideValidationSchema>

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/**
* Provider configuration schema definitions
* Defines the structure for AI service provider metadata and capabilities
*/
import * as z from 'zod'
import { MetadataSchema, ProviderIdSchema, VersionSchema } from './common'
// Endpoint types supported by providers
export const EndpointTypeSchema = z.enum([
'CHAT_COMPLETIONS', // /chat/completions
'COMPLETIONS', // /completions
'EMBEDDINGS', // /embeddings
'IMAGE_GENERATION', // /images/generations
'IMAGE_EDIT', // /images/edits
'AUDIO_SPEECH', // /audio/speech (TTS)
'AUDIO_TRANSCRIPTIONS', // /audio/transcriptions (STT)
'MESSAGES', // /messages
'RESPONSES', // /responses
'GENERATE_CONTENT', // :generateContent
'STREAM_GENERATE_CONTENT', // :streamGenerateContent
'RERANK', // /rerank
'MODERATIONS' // /moderations
])
// Authentication methods
export const AuthenticationSchema = z.enum([
'API_KEY', // Standard API Key authentication
'OAUTH', // OAuth 2.0 authentication
'CLOUD_CREDENTIALS' // Cloud service credentials (AWS, GCP, Azure)
])
// Pricing models that affect UI and behavior
export const PricingModelSchema = z.enum([
'UNIFIED', // Unified pricing (like OpenRouter)
'PER_MODEL', // Per-model independent pricing (like OpenAI official)
'TRANSPARENT', // Transparent pricing (like New-API)
'USAGE_BASED', // Dynamic usage-based pricing
'SUBSCRIPTION' // Subscription-based pricing
])
// Model routing strategies affecting performance and reliability
export const ModelRoutingSchema = z.enum([
'INTELLIGENT', // Intelligent routing, auto-select optimal instance
'DIRECT', // Direct routing to specified model
'LOAD_BALANCED', // Load balanced across multiple instances
'GEO_ROUTED', // Geographic location routing
'COST_OPTIMIZED' // Cost-optimized routing
])
// Server-side MCP support configuration
export const McpSupportSchema = z.object({
supported: z.boolean().default(false),
configuration: z
.object({
supports_url_pass_through: z.boolean().default(false),
supported_servers: z.array(z.string()).optional(),
max_concurrent_servers: z.number().optional()
})
.optional()
})
// API compatibility configuration
export const ApiCompatibilitySchema = z.object({
supports_array_content: z.boolean().default(true),
supports_stream_options: z.boolean().default(true),
supports_developer_role: z.boolean().default(false),
supports_service_tier: z.boolean().default(false),
supports_thinking_control: z.boolean().default(false),
supports_api_version: z.boolean().default(false),
supports_parallel_tools: z.boolean().default(false),
supports_multimodal: z.boolean().default(false),
max_file_upload_size: z.number().optional(), // bytes
supported_file_types: z.array(z.string()).optional()
})
// Behavior characteristics configuration - replaces categorization, describes actual behavior
export const ProviderBehaviorsSchema = z.object({
// Model management
supports_custom_models: z.boolean().default(false), // Supports user custom models
provides_model_mapping: z.boolean().default(false), // Provides model name mapping
supports_model_versioning: z.boolean().default(false), // Supports model version control
// Reliability and fault tolerance
provides_fallback_routing: z.boolean().default(false), // Provides fallback routing
has_auto_retry: z.boolean().default(false), // Has automatic retry mechanism
supports_health_check: z.boolean().default(false), // Supports health checks
// Monitoring and metrics
has_real_time_metrics: z.boolean().default(false), // Has real-time metrics
provides_usage_analytics: z.boolean().default(false), // Provides usage analytics
supports_webhook_events: z.boolean().default(false), // Supports webhook events
// Configuration and management
requires_api_key_validation: z.boolean().default(true), // Requires API key validation
supports_rate_limiting: z.boolean().default(false), // Supports rate limiting
provides_usage_limits: z.boolean().default(false), // Provides usage limit configuration
// Advanced features
supports_streaming: z.boolean().default(true), // Supports streaming responses
supports_batch_processing: z.boolean().default(false), // Supports batch processing
supports_model_fine_tuning: z.boolean().default(false) // Provides model fine-tuning
})
// Provider configuration schema
export const ProviderConfigSchema = z.object({
// Basic information
id: ProviderIdSchema,
name: z.string(),
description: z.string().optional(),
// Behavior-related configuration
authentication: AuthenticationSchema,
pricing_model: PricingModelSchema,
model_routing: ModelRoutingSchema,
behaviors: ProviderBehaviorsSchema,
// Feature support
supported_endpoints: z.array(EndpointTypeSchema),
mcp_support: McpSupportSchema.optional(),
api_compatibility: ApiCompatibilitySchema.optional(),
// Default configuration
default_api_host: z.string().optional(),
default_rate_limit: z.number().optional(), // requests per minute
// Model matching assistance
model_id_patterns: z.array(z.string()).optional(),
alias_model_ids: z.record(z.string(), z.string()).optional(), // Model alias mapping
// Special configuration
special_config: MetadataSchema,
// Metadata and links
documentation: z.string().url().optional(),
status_page: z.string().url().optional(),
pricing_page: z.string().url().optional(),
support_email: z.string().email().optional(),
website: z.string().url().optional(),
// Status management
deprecated: z.boolean().default(false),
deprecation_date: z.iso.datetime().optional(),
maintenance_mode: z.boolean().default(false),
// Version and compatibility
min_app_version: VersionSchema.optional(), // Minimum supported app version
max_app_version: VersionSchema.optional(), // Maximum supported app version
config_version: VersionSchema.default('1.0.0'), // Configuration file version
// Additional metadata
metadata: MetadataSchema
})
// Provider list container schema for JSON files
export const ProviderListSchema = z.object({
version: VersionSchema,
providers: z.array(ProviderConfigSchema)
})
// Type exports
export type EndpointType = z.infer<typeof EndpointTypeSchema>
export type Authentication = z.infer<typeof AuthenticationSchema>
export type PricingModel = z.infer<typeof PricingModelSchema>
export type ModelRouting = z.infer<typeof ModelRoutingSchema>
export type McpSupport = z.infer<typeof McpSupportSchema>
export type ApiCompatibility = z.infer<typeof ApiCompatibilitySchema>
export type ProviderBehaviors = z.infer<typeof ProviderBehaviorsSchema>
export type ProviderConfig = z.infer<typeof ProviderConfigSchema>
export type ProviderList = z.infer<typeof ProviderListSchema>

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export { isJSONArray, isJSONObject, isJSONValue } from './is-json'
export type { JSONArray, JSONObject, JSONValue } from './json-value'

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// https://github.com/vercel/ai/blob/4c44a5bea002ef0db0e1b86a1e223cd9f4837d62/packages/provider/src/json-value/is-json.ts
import type { JSONArray, JSONObject, JSONValue } from './json-value'
export function isJSONValue(value: unknown): value is JSONValue {
if (value === null || typeof value === 'string' || typeof value === 'number' || typeof value === 'boolean') {
return true
}
if (Array.isArray(value)) {
return value.every(isJSONValue)
}
if (typeof value === 'object') {
return Object.entries(value).every(
([key, val]) => typeof key === 'string' && (val === undefined || isJSONValue(val))
)
}
return false
}
export function isJSONArray(value: unknown): value is JSONArray {
return Array.isArray(value) && value.every(isJSONValue)
}
export function isJSONObject(value: unknown): value is JSONObject {
return (
value != null &&
typeof value === 'object' &&
Object.entries(value).every(([key, val]) => typeof key === 'string' && (val === undefined || isJSONValue(val)))
)
}

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// https://github.com/vercel/ai/blob/4c44a5bea002ef0db0e1b86a1e223cd9f4837d62/packages/provider/src/json-value/json-value.ts
/**
A JSON value can be a string, number, boolean, object, array, or null.
JSON values can be serialized and deserialized by the JSON.stringify and JSON.parse methods.
*/
export type JSONValue = null | string | number | boolean | JSONObject | JSONArray
export type JSONObject = {
[key: string]: JSONValue | undefined
}
export type JSONArray = JSONValue[]

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/**
* Migration Tool - Phase 2 Implementation
* Migrates existing JSON data to new schema-based catalog system
*/
import * as fs from 'fs/promises'
import * as path from 'path'
interface ProviderEndpointsData {
providers: Record<
string,
{
display_name: string
endpoints: Record<string, boolean>
url: string
}
>
}
interface ModelPricesData {
[modelId: string]: {
litellm_provider: string
mode: string
input_cost_per_token?: number
output_cost_per_token?: number
input_cost_per_pixel?: number
output_cost_per_pixel?: number
output_cost_per_image?: number
max_input_tokens?: number
max_output_tokens?: number
max_tokens?: number
supports_function_calling?: boolean
supports_vision?: boolean
supports_parallel_function_calling?: boolean
supports_response_schema?: boolean
supports_tool_choice?: boolean
supports_system_messages?: boolean
supports_assistant_prefill?: boolean
supports_pdf_input?: boolean
supports_prompt_caching?: boolean
cache_creation_input_token_cost?: number
cache_read_input_token_cost?: number
metadata?: {
notes?: string
}
source?: string
supported_endpoints?: string[]
deprecation_date?: string
}
}
interface ModelConfig {
id: string
name?: string
owned_by?: string
description?: string
capabilities: string[]
input_modalities: string[]
output_modalities: string[]
context_window: number
max_output_tokens: number
max_input_tokens?: number
pricing?: {
input: { per_million_tokens: number; currency: string }
output: { per_million_tokens: number; currency: string }
}
parameters?: Record<string, any>
endpoint_types?: string[]
metadata?: Record<string, any>
}
interface ProviderConfig {
id: string
name: string
description?: string
authentication: string
supported_endpoints: string[]
api_compatibility?: Record<string, boolean>
special_config?: Record<string, any>
documentation?: string
website?: string
deprecated: boolean
maintenance_mode: boolean
config_version: string
metadata?: Record<string, any>
}
interface OverrideConfig {
provider_id: string
model_id: string
capabilities?: {
add?: string[]
remove?: string[]
force?: string[]
}
limits?: {
context_window?: number
max_output_tokens?: number
max_input_tokens?: number
}
pricing?: {
input: { per_million_tokens: number; currency: string }
output: { per_million_tokens: number; currency: string }
}
disabled?: boolean
reason?: string
last_updated?: string
updated_by?: string
priority?: number
}
export class MigrationTool {
private providerEndpointsData: ProviderEndpointsData
private modelPricesData: ModelPricesData
constructor(
private providerEndpointsPath: string,
private modelPricesPath: string,
private outputDir: string
) {
// Initialize with empty objects to satisfy TypeScript
this.providerEndpointsData = { providers: {} }
this.modelPricesData = {}
}
async loadData(): Promise<void> {
console.log('📖 Loading existing data...')
const providerEndpointsContent = await fs.readFile(this.providerEndpointsPath, 'utf-8')
this.providerEndpointsData = JSON.parse(providerEndpointsContent)
const modelPricesContent = await fs.readFile(this.modelPricesPath, 'utf-8')
this.modelPricesData = JSON.parse(modelPricesContent)
console.log(`✅ Loaded ${Object.keys(this.providerEndpointsData.providers).length} providers`)
console.log(`✅ Loaded ${Object.keys(this.modelPricesData).length} model configurations`)
}
/**
* Extract base model identifier from provider-specific model ID
*/
private extractBaseModelId(providerModelId: string): string {
// Remove provider prefixes
const prefixes = [
'azure/',
'bedrock/',
'openrouter/',
'vertex_ai/',
'sagemaker/',
'watsonx/',
'litellm_proxy/',
'custom/',
'aiml/',
'together_ai/',
'deepinfra/',
'hyperbolic/',
'fireworks_ai/',
'replicate/',
'novita/',
'anyscale/',
'runpod/',
'triton/',
'vllm/',
'ollama/',
'lm_studio/'
]
let baseId = providerModelId
for (const prefix of prefixes) {
if (baseId.startsWith(prefix)) {
baseId = baseId.substring(prefix.length)
break
}
}
// Handle AWS Bedrock specific naming
if (baseId.includes(':')) {
baseId = baseId.split(':')[0]
}
// Handle version suffixes
baseId = baseId.replace(/\/v\d+$/, '').replace(/:v\d+$/, '')
return baseId
}
/**
* Determine if a model is a base model or provider-specific override
*/
private isBaseModel(modelId: string, provider: string): boolean {
const baseId = this.extractBaseModelId(modelId)
// Official provider models are base models
const officialProviders = [
'anthropic',
'openai',
'gemini',
'deepseek',
'dashscope',
'volceengine',
'minimax',
'moonshotai',
'zai',
'meta',
'mistral',
'cohere',
'xai'
]
if (officialProviders.includes(provider)) {
return modelId === baseId || modelId.startsWith(provider + '/')
}
// Third-party providers selling access to official models are overrides
return false
}
/**
* Convert endpoint support to provider capabilities
*/
private privateConvertEndpointsToCapabilities(endpoints: Record<string, boolean>): string[] {
const endpointCapabilityMap: Record<string, string> = {
chat_completions: 'CHAT_COMPLETIONS',
messages: 'MESSAGES',
responses: 'RESPONSES',
completions: 'COMPLETIONS',
embeddings: 'EMBEDDINGS',
image_generations: 'IMAGE_GENERATION',
image_edit: 'IMAGE_EDIT',
audio_speech: 'AUDIO_GENERATION',
audio_transcriptions: 'AUDIO_TRANSCRIPT',
rerank: 'RERANK',
moderations: 'MODERATIONS',
ocr: 'OCR',
search: 'WEB_SEARCH'
}
const capabilities: string[] = []
for (const [endpoint, supported] of Object.entries(endpoints)) {
if (supported && endpointCapabilityMap[endpoint]) {
capabilities.push(endpointCapabilityMap[endpoint])
}
}
return capabilities
}
/**
* Generate provider configurations
*/
private generateProviderConfigs(): ProviderConfig[] {
const providers: ProviderConfig[] = []
for (const [providerId, providerData] of Object.entries(this.providerEndpointsData.providers)) {
const supported_endpoints = this.privateConvertEndpointsToCapabilities(providerData.endpoints)
const provider: ProviderConfig = {
id: providerId,
name: providerData.display_name,
description: `Provider: ${providerData.display_name}`,
authentication: 'API_KEY',
supported_endpoints,
api_compatibility: {
supports_array_content: providerData.endpoints.chat_completions || false,
supports_stream_options: providerData.endpoints.chat_completions || false,
supports_developer_role: providerId === 'openai',
supports_service_tier: providerId === 'openai',
supports_thinking_control: false,
supports_api_version: providerId === 'openai',
supports_parallel_tools: providerData.endpoints.chat_completions || false,
supports_multimodal: providerData.endpoints.chat_completions || false
},
special_config: {},
documentation: providerData.url,
website: providerData.url,
deprecated: false,
maintenance_mode: false,
config_version: '1.0.0'
}
providers.push(provider)
}
return providers
}
/**
* Generate base model configurations
*/
private generateBaseModels(): ModelConfig[] {
const baseModels = new Map<string, ModelConfig>()
for (const [modelId, modelData] of Object.entries(this.modelPricesData)) {
if (modelData.mode !== 'chat') continue // Skip non-chat models for now
const baseId = this.extractBaseModelId(modelId)
const isBase = this.isBaseModel(modelId, modelData.litellm_provider)
if (!isBase) continue // Only process base models
// Extract capabilities from model data
const capabilities: string[] = []
if (modelData.supports_function_calling) capabilities.push('FUNCTION_CALL')
if (modelData.supports_vision) capabilities.push('IMAGE_RECOGNITION')
if (modelData.supports_response_schema) capabilities.push('STRUCTURED_OUTPUT')
if (modelData.supports_pdf_input) capabilities.push('FILE_INPUT')
if (modelData.supports_tool_choice) capabilities.push('FUNCTION_CALL')
// Determine modalities
const input_modalities = ['TEXT']
const output_modalities = ['TEXT']
if (modelData.supports_vision) {
input_modalities.push('VISION')
}
// Convert pricing
let pricing
if (modelData.input_cost_per_token && modelData.output_cost_per_token) {
pricing = {
input: {
per_million_tokens: Math.round(modelData.input_cost_per_token * 1000000 * 1000) / 1000,
currency: 'USD'
},
output: {
per_million_tokens: Math.round(modelData.output_cost_per_token * 1000000 * 1000) / 1000,
currency: 'USD'
}
}
}
const baseModel: ModelConfig = {
id: baseId,
name: baseId,
owned_by: modelData.litellm_provider,
capabilities,
input_modalities,
output_modalities,
context_window: modelData.max_input_tokens || 4096,
max_output_tokens: modelData.max_output_tokens || modelData.max_tokens || 2048,
max_input_tokens: modelData.max_input_tokens,
pricing,
parameters: {
temperature: { supported: true, min: 0, max: 1, default: 1 },
max_tokens: true,
system_message: modelData.supports_system_messages || false,
top_p: { supported: false }
},
endpoint_types: ['CHAT_COMPLETIONS'],
metadata: {
source: 'migration',
original_provider: modelData.litellm_provider,
supports_caching: !!modelData.supports_prompt_caching
}
}
baseModels.set(baseId, baseModel)
}
return Array.from(baseModels.values())
}
/**
* Generate override configurations
*/
private generateOverrides(): OverrideConfig[] {
const overrides: OverrideConfig[] = []
for (const [modelId, modelData] of Object.entries(this.modelPricesData)) {
if (modelData.mode !== 'chat') continue
const baseId = this.extractBaseModelId(modelId)
const isBase = this.isBaseModel(modelId, modelData.litellm_provider)
if (isBase) continue // Only generate overrides for non-base models
const override: OverrideConfig = {
provider_id: modelData.litellm_provider,
model_id: baseId,
disabled: false,
reason: `Provider-specific implementation of ${baseId}`,
last_updated: new Date().toISOString().split('T')[0],
updated_by: 'migration-tool',
priority: 100
}
// Add capability differences
const capabilities = modelData.supports_function_calling ? ['FUNCTION_CALL'] : []
if (modelData.supports_vision) capabilities.push('IMAGE_RECOGNITION')
if (capabilities.length > 0) {
override.capabilities = { add: capabilities }
}
// Add limit differences
const limits: any = {}
if (modelData.max_input_tokens && modelData.max_input_tokens !== 128000) {
limits.context_window = modelData.max_input_tokens
}
if (modelData.max_output_tokens && modelData.max_output_tokens !== 4096) {
limits.max_output_tokens = modelData.max_output_tokens
}
if (Object.keys(limits).length > 0) {
override.limits = limits
}
// Add pricing differences
if (modelData.input_cost_per_token && modelData.output_cost_per_token) {
override.pricing = {
input: {
per_million_tokens: Math.round(modelData.input_cost_per_token * 1000000 * 1000) / 1000,
currency: 'USD'
},
output: {
per_million_tokens: Math.round(modelData.output_cost_per_token * 1000000 * 1000) / 1000,
currency: 'USD'
}
}
}
overrides.push(override)
}
return overrides
}
/**
* Execute the full migration
*/
async migrate(): Promise<void> {
console.log('🚀 Starting Phase 2 Migration...')
await this.loadData()
// Create output directory
await fs.mkdir(this.outputDir, { recursive: true })
// Generate configurations
console.log('📦 Generating provider configurations...')
const providers = this.generateProviderConfigs()
console.log('📦 Generating base model configurations...')
const models = this.generateBaseModels()
console.log('📦 Generating override configurations...')
const overrides = this.generateOverrides()
// Write single file for all providers
console.log('💾 Writing providers.json...')
await this.writeJsonFile('providers.json', {
version: '2025.11.24',
providers
})
// Write single file for all models
console.log('💾 Writing models.json...')
await this.writeJsonFile('models.json', {
version: '2025.11.24',
models
})
// Write single file for all overrides
console.log('💾 Writing overrides.json...')
await this.writeJsonFile('overrides.json', {
version: '2025.11.24',
overrides
})
// Generate migration report
const providersByType = {
direct: providers.filter((p) => ['anthropic', 'openai', 'google'].includes(p.id)).length,
cloud: providers.filter((p) => ['azure', 'bedrock', 'vertex_ai'].some((c) => p.id.includes(c))).length,
proxy: providers.filter((p) => ['openrouter', 'litellm_proxy', 'together_ai'].some((c) => p.id.includes(c)))
.length,
self_hosted: providers.filter((p) => ['ollama', 'lm_studio', 'vllm'].some((c) => p.id.includes(c))).length
}
const modelsByProvider = models.reduce(
(acc, model) => {
const provider = model.owned_by || 'unknown'
acc[provider] = (acc[provider] || 0) + 1
return acc
},
{} as Record<string, number>
)
const overridesByProvider = overrides.reduce(
(acc, override) => {
acc[override.provider_id] = (acc[override.provider_id] || 0) + 1
return acc
},
{} as Record<string, number>
)
const report = {
timestamp: new Date().toISOString(),
summary: {
total_providers: providers.length,
total_base_models: models.length,
total_overrides: overrides.length,
provider_categories: providersByType,
models_by_provider: modelsByProvider,
overrides_by_provider: overridesByProvider
},
files: {
providers: 'providers.json',
models: 'models.json',
overrides: 'overrides.json'
}
}
await this.writeJsonFile('migration-report.json', report)
console.log('\n✅ Migration completed successfully!')
console.log(`📊 Migration Summary:`)
console.log(
` Providers: ${providers.length} (${providersByType.direct} direct, ${providersByType.cloud} cloud, ${providersByType.proxy} proxy, ${providersByType.self_hosted} self-hosted)`
)
console.log(` Base Models: ${models.length}`)
console.log(` Overrides: ${overrides.length}`)
console.log(`\n📁 Output Files:`)
console.log(` ${this.outputDir}/providers.json`)
console.log(` ${this.outputDir}/models.json`)
console.log(` ${this.outputDir}/overrides.json`)
console.log(` ${this.outputDir}/migration-report.json`)
}
private async writeJsonFile(filename: string, data: any): Promise<void> {
const filePath = path.join(this.outputDir, filename)
await fs.writeFile(filePath, JSON.stringify(data, null, 2), 'utf-8')
}
}
// CLI execution
if (require.main === module) {
const tool = new MigrationTool(
'./provider_endpoints_support.json',
'./model_prices_and_context_window.json',
'./migrated-data'
)
tool.migrate().catch(console.error)
}

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// https://github.com/vercel/ai/blob/6306603220f9f023fcdbeb9768d1c3fc2ca6bc80/packages/provider-utils/src/parse-json.ts
import type { JSONValue } from '../json-value'
import type { Schema } from '../schema'
import { safeValidateTypes, validateTypes } from '../validate-type'
import { secureJsonParse } from './secure-json-parse'
/**
* Parses a JSON string into an unknown object.
*
* @param text - The JSON string to parse.
* @returns {JSONValue} - The parsed JSON object.
*/
export async function parseJSON(options: { text: string; schema?: undefined }): Promise<JSONValue>
/**
* Parses a JSON string into a strongly-typed object using the provided schema.
*
* @template T - The type of the object to parse the JSON into.
* @param {string} text - The JSON string to parse.
* @param {Validator<T>} schema - The schema to use for parsing the JSON.
* @returns {Promise<T>} - The parsed object.
*/
export async function parseJSON<T>(options: { text: string; schema: Schema<T> }): Promise<T>
export async function parseJSON<T>({ text, schema }: { text: string; schema?: Schema<T> }): Promise<T> {
const value = secureJsonParse(text)
if (schema == null) {
return value
}
return validateTypes<T>({ value, schema })
}
export type ParseResult<T> =
| { success: true; value: T; rawValue: unknown }
| {
success: false
error: Error
rawValue: unknown
}
/**
* Safely parses a JSON string and returns the result as an object of type `unknown`.
*
* @param text - The JSON string to parse.
* @returns {Promise<object>} Either an object with `success: true` and the parsed data, or an object with `success: false` and the error that occurred.
*/
export async function safeParseJSON(options: { text: string; schema?: undefined }): Promise<ParseResult<JSONValue>>
/**
* Safely parses a JSON string into a strongly-typed object, using a provided schema to validate the object.
*
* @template T - The type of the object to parse the JSON into.
* @param {string} text - The JSON string to parse.
* @param {Validator<T>} schema - The schema to use for parsing the JSON.
* @returns An object with either a `success` flag and the parsed and typed data, or a `success` flag and an error object.
*/
export async function safeParseJSON<T>(options: { text: string; schema: Schema<T> }): Promise<ParseResult<T>>
export async function safeParseJSON<T>({
text,
schema
}: {
text: string
schema?: Schema<T>
}): Promise<ParseResult<T>> {
try {
const value = secureJsonParse(text)
if (schema == null) {
return { success: true, value: value as T, rawValue: value }
}
return await safeValidateTypes<T>({ value, schema })
} catch (error) {
return {
success: false,
error: error instanceof Error ? error : new Error('Unknown parsing error'),
rawValue: undefined
}
}
}
export function isParsableJson(input: string): boolean {
try {
secureJsonParse(input)
return true
} catch {
return false
}
}

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// https://github.com/vercel/ai/blob/32d8dbbebdb7831467c702094cc903cf93ee15ef/packages/provider-utils/src/secure-json-parse.ts
// Licensed under BSD-3-Clause (this file only)
// Code adapted from https://github.com/fastify/secure-json-parse/blob/783fcb1b5434709466759847cec974381939673a/index.js
//
// Copyright (c) Vercel, Inc. (https://vercel.com)
// Copyright (c) 2019 The Fastify Team
// Copyright (c) 2019, Sideway Inc, and project contributors
// All rights reserved.
//
// The complete list of contributors can be found at:
// - https://github.com/hapijs/bourne/graphs/contributors
// - https://github.com/fastify/secure-json-parse/graphs/contributors
// - https://github.com/vercel/ai/commits/main/packages/provider-utils/src/secure-parse-json.ts
//
// Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
//
// 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
//
// 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
//
// 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
const suspectProtoRx = /"__proto__"\s*:/
const suspectConstructorRx = /"constructor"\s*:/
function _parse(text: string) {
// Parse normally
const obj = JSON.parse(text)
// Ignore null and non-objects
if (obj === null || typeof obj !== 'object') {
return obj
}
if (suspectProtoRx.test(text) === false && suspectConstructorRx.test(text) === false) {
return obj
}
// Scan result for proto keys
return filter(obj)
}
function filter(obj: any) {
let next = [obj]
while (next.length) {
const nodes = next
next = []
for (const node of nodes) {
if (Object.prototype.hasOwnProperty.call(node, '__proto__')) {
throw new SyntaxError('Object contains forbidden prototype property')
}
if (
Object.prototype.hasOwnProperty.call(node, 'constructor') &&
Object.prototype.hasOwnProperty.call(node.constructor, 'prototype')
) {
throw new SyntaxError('Object contains forbidden prototype property')
}
for (const key in node) {
const value = node[key]
if (value && typeof value === 'object') {
next.push(value)
}
}
}
}
return obj
}
export function secureJsonParse(text: string) {
const { stackTraceLimit } = Error
try {
// Performance optimization, see https://github.com/fastify/secure-json-parse/pull/90
Error.stackTraceLimit = 0
} catch (e) {
// Fallback in case Error is immutable (v8 readonly)
return _parse(text)
}
try {
return _parse(text)
} finally {
Error.stackTraceLimit = stackTraceLimit
}
}

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// https://github.com/vercel/ai/blob/6306603220f9f023fcdbeb9768d1c3fc2ca6bc80/packages/provider-utils/src/schema.ts
import type { JSONSchema7 } from 'json-schema'
import * as z4 from 'zod/v4'
export type ValidationResult<OBJECT> = { success: true; value: OBJECT } | { success: false; error: Error }
const schemaSymbol = Symbol.for('schema')
export type Schema<OBJECT = unknown> = {
/**
* Used to mark schemas so we can support both Zod and custom schemas.
*/
[schemaSymbol]: true
/**
* Schema type for inference.
*/
_type: OBJECT
/**
* Optional. Validates that the structure of a value matches this schema,
* and returns a typed version of the value if it does.
*/
readonly validate?: (value: unknown) => ValidationResult<OBJECT> | PromiseLike<ValidationResult<OBJECT>>
/**
* The JSON Schema for the schema.
*/
readonly jsonSchema: JSONSchema7 | PromiseLike<JSONSchema7>
}
export function asSchema<OBJECT>(schema: Schema<OBJECT> | undefined): Schema<OBJECT> {
return schema == null
? jsonSchema({
properties: {},
additionalProperties: false
})
: schema
}
export function jsonSchema<OBJECT = unknown>(
jsonSchema: JSONSchema7 | PromiseLike<JSONSchema7> | (() => JSONSchema7 | PromiseLike<JSONSchema7>),
{
validate
}: {
validate?: (value: unknown) => ValidationResult<OBJECT> | PromiseLike<ValidationResult<OBJECT>>
} = {}
): Schema<OBJECT> {
return {
[schemaSymbol]: true,
_type: undefined as OBJECT, // should never be used directly
get jsonSchema() {
if (typeof jsonSchema === 'function') {
jsonSchema = jsonSchema() // cache the function results
}
return jsonSchema
},
validate
}
}
export function zod4Schema<OBJECT>(
zodSchema: z4.core.$ZodType<OBJECT, any>,
options?: {
/**
* Enables support for references in the schema.
* This is required for recursive schemas, e.g. with `z.lazy`.
* However, not all language models and providers support such references.
* Defaults to `false`.
*/
useReferences?: boolean
}
): Schema<OBJECT> {
// default to no references (to support openapi conversion for google)
const useReferences = options?.useReferences ?? false
return jsonSchema(
// defer json schema creation to avoid unnecessary computation when only validation is needed
() =>
z4.toJSONSchema(zodSchema, {
target: 'draft-7',
io: 'output',
reused: useReferences ? 'ref' : 'inline'
}) as JSONSchema7,
{
validate: async (value) => {
const result = await z4.safeParseAsync(zodSchema, value)
return result.success ? { success: true, value: result.data } : { success: false, error: result.error }
}
}
)
}

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// https://github.com/vercel/ai/blob/6306603220f9f023fcdbeb9768d1c3fc2ca6bc80/packages/provider-utils/src/validate-types.ts
import { asSchema, type Schema } from './schema'
/**
* Validates the types of an unknown object using a schema and
* return a strongly-typed object.
*
* @template T - The type of the object to validate.
* @param {string} options.value - The object to validate.
* @param {Validator<T>} options.schema - The schema to use for validating the JSON.
* @returns {Promise<T>} - The typed object.
*/
export async function validateTypes<OBJECT>({
value,
schema
}: {
value: unknown
schema: Schema<OBJECT>
}): Promise<OBJECT> {
const result = await safeValidateTypes({ value, schema })
if (!result.success) {
throw Error(`Validation failed: ${result.error.message}`)
}
return result.value
}
/**
* Safely validates the types of an unknown object using a schema and
* return a strongly-typed object.
*
* @template T - The type of the object to validate.
* @param {string} options.value - The JSON object to validate.
* @param {Validator<T>} options.schema - The schema to use for validating the JSON.
* @returns An object with either a `success` flag and the parsed and typed data, or a `success` flag and an error object.
*/
export async function safeValidateTypes<OBJECT>({ value, schema }: { value: unknown; schema: Schema<OBJECT> }): Promise<
| {
success: true
value: OBJECT
rawValue: unknown
}
| {
success: false
error: Error
rawValue: unknown
}
> {
const actualSchema = asSchema(schema)
try {
if (actualSchema.validate == null) {
return { success: true, value: value as OBJECT, rawValue: value }
}
const result = await actualSchema.validate(value)
if (result.success) {
return { success: true, value: result.value, rawValue: value }
}
return {
success: false,
error: Error(`Validation failed: ${result.error.message}`),
rawValue: value
}
} catch (error) {
return {
success: false,
error: error instanceof Error ? error : new Error('Unknown validation error'),
rawValue: value
}
}
}

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