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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,138 @@ | ||
| /** | ||
| * Chat Completion Endpoint | ||
| * | ||
| * POST /api/v1/chat | ||
| * | ||
| * Generate chat completions using multi-provider LLM. | ||
| */ | ||
|
|
||
| import { NextRequest } from 'next/server'; | ||
| import { z } from 'zod'; | ||
| import { generateCompletion, generateStreamingCompletion, type LLMProviderType } from '@/lib/llm'; | ||
| import { | ||
| validateAPIKey, | ||
| hasPermission, | ||
| checkRateLimit, | ||
| authError, | ||
| rateLimitError, | ||
| } from '../utils/auth'; | ||
| import { ErrorResponses, handleError } from '../utils/errors'; | ||
|
|
||
| // Request validation schema | ||
| const ChatRequestSchema = z.object({ | ||
| messages: z.array( | ||
| z.object({ | ||
| role: z.enum(['system', 'user', 'assistant']), | ||
| content: z.string(), | ||
| }) | ||
| ), | ||
| provider: z.enum(['openai', 'anthropic', 'google', 'azure', 'ollama']).optional(), | ||
| model: z.string().optional(), | ||
| temperature: z.number().min(0).max(2).optional(), | ||
| maxTokens: z.number().positive().optional(), | ||
| stream: z.boolean().optional(), | ||
| }); | ||
|
|
||
| export async function POST(request: NextRequest) { | ||
| try { | ||
| // Authenticate | ||
| const keyInfo = await validateAPIKey(request); | ||
| if (!keyInfo) { | ||
| return authError('Invalid or missing API key'); | ||
| } | ||
|
|
||
| // Check permission | ||
| if (!hasPermission(keyInfo, 'chat')) { | ||
| return authError('API key does not have chat permission', 403); | ||
| } | ||
|
|
||
| // Check rate limit | ||
| const rateLimit = checkRateLimit(keyInfo); | ||
| if (!rateLimit.allowed) { | ||
| return rateLimitError(rateLimit.resetAt); | ||
| } | ||
|
|
||
| // Parse and validate request body | ||
| const body = await request.json(); | ||
| const validation = ChatRequestSchema.safeParse(body); | ||
|
|
||
| if (!validation.success) { | ||
| return ErrorResponses.validationError('Invalid request body', { | ||
| errors: validation.error.flatten().fieldErrors, | ||
| }); | ||
| } | ||
|
|
||
| const { messages, provider, model, temperature, maxTokens, stream } = validation.data; | ||
|
|
||
| // Determine provider and model | ||
| const llmProvider = (provider || 'openai') as LLMProviderType; | ||
| const llmModel = model || (llmProvider === 'openai' ? 'gpt-4o' : undefined); | ||
|
|
||
| if (!llmModel) { | ||
| return ErrorResponses.validationError('Model must be specified for this provider'); | ||
| } | ||
|
|
||
| // Build prompt from messages | ||
| const systemMessage = messages.find((m) => m.role === 'system')?.content; | ||
| const conversationMessages = messages.filter((m) => m.role !== 'system'); | ||
|
|
||
| // Format conversation for prompt | ||
| const prompt = conversationMessages | ||
| .map((m) => `${m.role === 'user' ? 'User' : 'Assistant'}: ${m.content}`) | ||
| .join('\n\n'); | ||
|
|
||
| const config = { | ||
| provider: llmProvider, | ||
| model: llmModel, | ||
| temperature, | ||
| maxTokens, | ||
| }; | ||
|
|
||
| if (stream) { | ||
| // Streaming response | ||
| const textStream = await generateStreamingCompletion({ | ||
| prompt, | ||
| config, | ||
| systemPrompt: systemMessage, | ||
| }); | ||
|
|
||
| // Return the stream with appropriate headers | ||
| return new Response(textStream, { | ||
| headers: { | ||
| 'Content-Type': 'text/event-stream', | ||
| 'Cache-Control': 'no-cache', | ||
| Connection: 'keep-alive', | ||
| 'X-RateLimit-Remaining': String(rateLimit.remaining), | ||
| 'X-RateLimit-Reset': String(rateLimit.resetAt), | ||
| }, | ||
| }); | ||
|
Comment on lines
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There was a problem hiding this comment. 🧩 Analysis chainClarify streaming format vs
🌐 Web query: 💡 Result: Use streamText and return its built-in SSE response helper — call result.toUIMessageStreamResponse() (or toDataStreamResponse for the simpler "data" protocol) and return that Response so the SDK sets the proper text/event-stream headers and protocol header for you. Example (Node / Vercel function): This yields a Response with Content-Type: text/event-stream; charset=utf-8 and x-vercel-ai-ui-message-stream: v1 (uses the SDK's UI message stream conversion). [1][2][3] Sources: Official SDK internals and examples. [1] [2] [3] Length of output: 2932 🏁 Script executed: #!/bin/bash
# Search for imports of Vercel AI SDK to understand what's being used
rg -n "streamText\|toUIMessageStreamResponse\|toDataStreamResponse" --type=ts -B2 -A2Length of output: 0 🏁 Script executed: #!/bin/bash
# Find where Response is constructed with text/event-stream
rg -n "text/event-stream" --type=ts -B5 -A5Length of output: 736 Length of output: 729 Fix streaming response to use Vercel AI SDK's proper SSE helper The review comment is correct. Per Vercel AI SDK recommendations, use Required changes:
🤖 Prompt for AI Agents |
||
| } else { | ||
| // Non-streaming response | ||
| const result = await generateCompletion({ | ||
| prompt, | ||
| config, | ||
| systemPrompt: systemMessage, | ||
| }); | ||
|
|
||
| return Response.json( | ||
| { | ||
| success: true, | ||
| data: { | ||
| content: result.text, | ||
| usage: result.usage, | ||
| model: llmModel, | ||
| provider: llmProvider, | ||
| }, | ||
| }, | ||
| { | ||
| headers: { | ||
| 'X-RateLimit-Remaining': String(rateLimit.remaining), | ||
| 'X-RateLimit-Reset': String(rateLimit.resetAt), | ||
| }, | ||
| } | ||
| ); | ||
| } | ||
| } catch (error) { | ||
| return handleError(error); | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,124 @@ | ||
| /** | ||
| * Document Extraction Endpoint | ||
| * | ||
| * POST /api/v1/extract | ||
| * | ||
| * Extract text from PDF documents using OCR. | ||
| */ | ||
|
|
||
| import { NextRequest } from 'next/server'; | ||
| import { z } from 'zod'; | ||
| import { extractText, type OCRMethod } from '@/lib/ocr'; | ||
| import { | ||
| validateAPIKey, | ||
| hasPermission, | ||
| checkRateLimit, | ||
| authError, | ||
| rateLimitError, | ||
| } from '../utils/auth'; | ||
| import { ErrorResponses, handleError } from '../utils/errors'; | ||
|
|
||
| // Request validation schema | ||
| const ExtractRequestSchema = z.object({ | ||
| // Either file (base64) or url must be provided | ||
| file: z.string().optional(), | ||
| url: z.string().url().optional(), | ||
| // OCR options | ||
| method: z.enum(['llmwhisperer', 'deepseek', 'textract', 'tesseract', 'pdfjs']).optional(), | ||
| preserveLayout: z.boolean().optional(), | ||
| detectForms: z.boolean().optional(), | ||
| extractTables: z.boolean().optional(), | ||
| pages: z.array(z.number().positive()).optional(), | ||
| language: z.string().optional(), | ||
| password: z.string().optional(), | ||
| }); | ||
|
|
||
| export async function POST(request: NextRequest) { | ||
| try { | ||
| // Authenticate | ||
| const keyInfo = await validateAPIKey(request); | ||
| if (!keyInfo) { | ||
| return authError('Invalid or missing API key'); | ||
| } | ||
|
|
||
| // Check permission | ||
| if (!hasPermission(keyInfo, 'extract')) { | ||
| return authError('API key does not have extraction permission', 403); | ||
| } | ||
|
|
||
| // Check rate limit | ||
| const rateLimit = checkRateLimit(keyInfo); | ||
| if (!rateLimit.allowed) { | ||
| return rateLimitError(rateLimit.resetAt); | ||
| } | ||
|
|
||
| // Parse and validate request body | ||
| const body = await request.json(); | ||
| const validation = ExtractRequestSchema.safeParse(body); | ||
|
|
||
| if (!validation.success) { | ||
| return ErrorResponses.validationError('Invalid request body', { | ||
| errors: validation.error.flatten().fieldErrors, | ||
| }); | ||
| } | ||
|
|
||
| const { file, url, method, preserveLayout, detectForms, extractTables, pages, language, password } = | ||
| validation.data; | ||
|
|
||
| // Ensure either file or url is provided | ||
| if (!file && !url) { | ||
| return ErrorResponses.validationError('Either file (base64) or url must be provided'); | ||
| } | ||
|
|
||
| // Convert base64 to buffer if file provided | ||
| let input: Buffer | string; | ||
| if (file) { | ||
| try { | ||
| input = Buffer.from(file, 'base64'); | ||
| } catch { | ||
| return ErrorResponses.validationError('Invalid base64 file data'); | ||
| } | ||
| } else { | ||
| input = url!; | ||
| } | ||
|
Comment on lines
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There was a problem hiding this comment. Tighten input-source and base64 handling; avoid unnecessary cast A few small issues in the input handling block:
These refinements would make the endpoint behavior more predictable and validation errors clearer without changing the overall design. Also applies to: 85-97 |
||
|
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| // Extract text | ||
| const result = await extractText({ | ||
| input, | ||
| options: { | ||
| method: method as OCRMethod, | ||
| preserveLayout, | ||
| detectForms, | ||
| extractTables, | ||
| pages, | ||
| language, | ||
| password, | ||
| }, | ||
| }); | ||
|
|
||
| // Return result with rate limit headers | ||
| return Response.json( | ||
| { | ||
| success: true, | ||
| data: { | ||
| text: result.text, | ||
| markdown: result.markdown, | ||
| confidence: result.confidence, | ||
| method: result.method, | ||
| pageCount: result.pageCount, | ||
| processingTimeMs: result.processingTimeMs, | ||
| tables: result.tables, | ||
| formFields: result.formFields, | ||
| }, | ||
| }, | ||
| { | ||
| headers: { | ||
| 'X-RateLimit-Remaining': String(rateLimit.remaining), | ||
| 'X-RateLimit-Reset': String(rateLimit.resetAt), | ||
| }, | ||
| } | ||
| ); | ||
| } catch (error) { | ||
| return handleError(error); | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,55 @@ | ||
| /** | ||
| * Health Check Endpoint | ||
| * | ||
| * GET /api/v1/health | ||
| * | ||
| * Returns service health status and available features. | ||
| */ | ||
|
|
||
| import { NextRequest } from 'next/server'; | ||
| import { isProviderAvailable, getAvailableProviders } from '@/lib/llm'; | ||
| import { getLLMWhispererQuota } from '@/lib/ocr'; | ||
|
|
||
| export async function GET(request: NextRequest) { | ||
| const startTime = Date.now(); | ||
|
|
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| // Check service health | ||
| const [llmProviders, ocrQuota] = await Promise.all([ | ||
| getAvailableProviders(), | ||
| getLLMWhispererQuota(), | ||
| ]); | ||
|
|
||
| const health = { | ||
| status: 'healthy', | ||
| timestamp: new Date().toISOString(), | ||
| version: '1.0.0', | ||
| responseTimeMs: Date.now() - startTime, | ||
| services: { | ||
| llm: { | ||
| status: llmProviders.length > 0 ? 'available' : 'degraded', | ||
| providers: llmProviders, | ||
| }, | ||
| ocr: { | ||
| status: ocrQuota ? 'available' : 'limited', | ||
| llmwhisperer: ocrQuota | ||
| ? { | ||
| remaining: ocrQuota.remaining, | ||
| limit: ocrQuota.limit, | ||
| } | ||
| : null, | ||
| textract: !!process.env.AWS_ACCESS_KEY_ID, | ||
| deepseek: !!process.env.DEEPSEEK_OCR_ENDPOINT, | ||
| }, | ||
| database: { | ||
| status: process.env.NEXT_PUBLIC_SUPABASE_URL ? 'configured' : 'not_configured', | ||
| }, | ||
| }, | ||
| }; | ||
|
|
||
| // Determine overall status | ||
| if (llmProviders.length === 0 && !ocrQuota) { | ||
| health.status = 'degraded'; | ||
| } | ||
|
|
||
| return Response.json(health); | ||
| } |
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🧩 Analysis chain
New AI/SDK dependencies align with the LLM/OCR features; verify version compatibility
The added
@ai-sdk/*,ai, and@aws-sdk/client-textractdependencies match the new multi‑provider LLM and Textract usage. From a structure standpoint this looks fine; just ensure the chosen versions are compatible with your Next 14 / React 18 / Node.js runtime and each other (peer deps, bundling, ESM/CJS).Also applies to: 40-40
🌐 Web query:
💡 Result:
Short answer: Yes — these package versions are compatible with a Next.js 14.2.8 + React 18 app, provided your runtime Node.js meets the Next.js v14 minimum (Node 18.17+) and you satisfy the AI SDK peer deps (notably zod >= 3.25.0). Evidence:
What to check in your project
Sources
If you want, I can fetch the exact peerDependencies sections from each package.json for these exact versions and paste them here.
Length of output: 25
Upgrade zod to satisfy ai@5.x peer dependency requirement
The added dependencies are compatible with Next.js 14.2.8 + React 18 (Node 18.17+), but zod needs to be upgraded. The AI SDK v5 package (ai@5.0.95) requires zod >= 3.25.0 as a peer dependency. Currently, package.json specifies zod@^3.23.8, which falls below the minimum. Update to zod@^3.25.0 or higher to prevent runtime failures when using the AI SDK providers.
🤖 Prompt for AI Agents