feat: support ai-sdk, add stream-switch #62
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,12 @@ | ||
| import type { LlmConfig } from '../types/index.js'; | ||
| import type { BaseAi } from './base-ai.js'; | ||
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| export async function getAiInstance(llmConfig: LlmConfig): Promise<BaseAi> { | ||
| if (llmConfig.useSDK) { | ||
| const { AiSDK } = await import('./ai-sdk/ai-sdk.js'); | ||
| return new AiSDK(llmConfig); | ||
| } | ||
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| const { AiRestApi } = await import('./ai-rest-api/ai-rest-api.js'); | ||
| return new AiRestApi(llmConfig); | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,114 @@ | ||
| import type { ChatBody, ChatCompleteResponse, LlmConfig } from '../../types/index.js'; | ||
| import { Role } from '../../types/index.js'; | ||
| import { BaseAi } from '../base-ai.js'; | ||
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| type AiRestApiConfig = Extract<LlmConfig, { useSDK?: false | undefined; url: string; apiKey: string; model: string }>; | ||
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| export class AiRestApi extends BaseAi { | ||
| llmConfig: AiRestApiConfig; | ||
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| constructor(llmConfig: AiRestApiConfig) { | ||
| super(); | ||
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| this.llmConfig = llmConfig; | ||
| } | ||
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| async chat(chatBody: ChatBody): Promise<ChatCompleteResponse | Error> { | ||
| const { url, apiKey } = this.llmConfig; | ||
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| try { | ||
| const modelId = | ||
| typeof chatBody.model === 'string' | ||
| ? chatBody.model | ||
| : ((chatBody.model as any)?.modelId ?? String(chatBody.model)); | ||
| const normalizedBody = { ...chatBody, model: modelId }; | ||
| const response = await fetch(url, { | ||
| method: 'POST', | ||
| headers: { | ||
| ...(this.llmConfig.headers ?? {}), | ||
| Authorization: `Bearer ${apiKey}`, | ||
| 'Content-Type': 'application/json', | ||
| }, | ||
| body: JSON.stringify(normalizedBody), | ||
| signal: this.llmConfig.abortSignal, | ||
| }); | ||
| if (!response.ok) { | ||
| return new Error(`HTTP error ${response.status}: ${await response.text()}`); | ||
| } | ||
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| return (await response.json()) as ChatCompleteResponse; | ||
| } catch (error) { | ||
| console.error('Error calling chat/complete:', error); | ||
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| return error as Error; | ||
| } | ||
| } | ||
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| async chatStream(chatBody: ChatBody): Promise<globalThis.ReadableStream<Uint8Array>> { | ||
| const { url, apiKey } = this.llmConfig; | ||
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| try { | ||
| const modelId = | ||
| typeof chatBody.model === 'string' | ||
| ? chatBody.model | ||
| : ((chatBody.model as any)?.modelId ?? String(chatBody.model)); | ||
| const normalizedBody = { ...chatBody, model: modelId }; | ||
| const response = await fetch(url, { | ||
| method: 'POST', | ||
| headers: { | ||
| ...(this.llmConfig.headers ?? {}), | ||
| Authorization: `Bearer ${apiKey}`, | ||
| 'Content-Type': 'application/json', | ||
| }, | ||
| body: JSON.stringify({ ...normalizedBody, stream: true }), | ||
| signal: this.llmConfig.abortSignal, | ||
| }); | ||
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| if (!response.ok) { | ||
| const errorText = await response.text(); | ||
| const errorMessage = `Failed to call chat API! ${errorText}`; | ||
| console.error('Failed to call chat API:', errorMessage); | ||
| return this.generateErrorStream(errorMessage); | ||
| } | ||
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| if (!response.body) { | ||
| return this.generateErrorStream('Response body is empty!'); | ||
| } | ||
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| return response.body; | ||
| } catch (error) { | ||
| console.error('Failed to call streaming chat/complete:', error); | ||
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| return this.generateErrorStream(`Failed to call chat API! ${error}`); | ||
| } | ||
| } | ||
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| protected generateErrorStream(errorMessage: string): ReadableStream<Uint8Array> { | ||
| const errorResponse: ChatCompleteResponse = { | ||
| id: `chat-error-${Date.now()}`, | ||
| object: 'chat.completion.chunk', | ||
| created: Math.floor(Date.now() / 1000), | ||
| model: this.llmConfig.model, | ||
| choices: [ | ||
| { | ||
| finish_reason: 'error', | ||
| native_finish_reason: 'error', | ||
| delta: { | ||
| role: Role.ASSISTANT, | ||
| content: errorMessage, | ||
| }, | ||
| }, | ||
| ], | ||
| }; | ||
| const data = `data: ${JSON.stringify(errorResponse)}\n\n`; | ||
| const encoder = new TextEncoder(); | ||
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| return new ReadableStream<Uint8Array>({ | ||
| start(controller) { | ||
| controller.enqueue(encoder.encode(data)); | ||
| controller.enqueue(encoder.encode('data: [DONE]\n\n')); | ||
| controller.close(); | ||
| }, | ||
| }); | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1 @@ | ||
| export * from './ai-rest-api.js'; |
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🛠️ Refactor suggestion
REST example: bridge Web ReadableStream to Node and set SSE headers.
streamResponseis a Web stream;resis a Node writable. Also set SSE headers.Also applies to: 100-107
🤖 Prompt for AI Agents