Jon
adb33154cc
- Add LLM analysis integration to optimized agentic RAG processor - Fix strategy routing in job queue service to use configured processing strategy - Update ProcessingResult interface to include LLM analysis results - Integrate vector database operations with semantic chunking - Add comprehensive CIM review generation with proper error handling - Fix TypeScript errors and improve type safety - Ensure complete pipeline from upload to final analysis output The optimized agentic RAG processor now: - Creates intelligent semantic chunks with metadata enrichment - Generates vector embeddings for all chunks - Stores chunks in pgvector database with optimized batching - Runs LLM analysis to generate comprehensive CIM reviews - Provides complete integration from upload to final output Tested successfully with STAX CIM document processing.
49 lines
1.5 KiB
JavaScript
49 lines
1.5 KiB
JavaScript
const axios = require('axios');
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async function testLLMProcessing() {
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try {
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console.log('🚀 Testing LLM Processing for STAX CIM...');
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// First, authenticate to get a valid token
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const loginResponse = await axios.post('http://localhost:5000/api/auth/login', {
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email: 'test@stax-processing.com',
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password: 'TestPass123!'
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});
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console.log('✅ Authentication successful');
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console.log('Login response structure:', Object.keys(loginResponse.data));
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const token = loginResponse.data.data?.tokens?.accessToken;
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console.log('Token:', token ? 'Received' : 'Not received');
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if (!token) {
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console.error('No token received from login');
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return;
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}
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// Document ID that's already in the system
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const documentId = '0876b7f4-0899-4eb0-b2c6-434ec4e7a46d';
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// Trigger LLM processing
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const response = await axios.post(`http://localhost:5000/api/documents/${documentId}/process`, {
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processingType: 'llm',
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template: 'BPCP CIM Review Template'
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}, {
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${token}`
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}
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});
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console.log('✅ LLM Processing triggered successfully');
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console.log('Response:', response.data);
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} catch (error) {
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console.error('❌ Error:', error.response?.data || error.message);
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if (error.response?.data) {
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console.error('Full error response:', JSON.stringify(error.response.data, null, 2));
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}
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}
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}
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testLLMProcessing();
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