vk98's picture
Initial backend deployment - Hono proxy + ColPali embedding API
5dfbe50
import { Hono } from 'hono';
import { streamSSE } from 'hono/streaming';
import { v4 as uuidv4 } from 'uuid';
import { z } from 'zod';
import { config } from '../config';
import { cache } from '../services/cache';
import { vespaRequest } from '../services/vespa-https';
const backendApi = new Hono();
// Search request schema
const searchQuerySchema = z.object({
query: z.string().min(1).max(500),
ranking: z.enum(['hybrid', 'colpali', 'bm25']).optional().default('hybrid'),
});
// Main search endpoint - /fetch_results
backendApi.get('/fetch_results', async (c) => {
try {
const query = c.req.query('query');
const ranking = c.req.query('ranking') || 'hybrid';
const validation = searchQuerySchema.safeParse({ query, ranking });
if (!validation.success) {
return c.json({ error: 'Invalid request', details: validation.error.issues }, 400);
}
const validatedData = validation.data;
// Check cache
const cacheKey = `search:${validatedData.query}:${validatedData.ranking}`;
const cachedResult = cache.get(cacheKey);
if (cachedResult) {
c.header('X-Cache', 'HIT');
return c.json(cachedResult);
}
// Build YQL query based on ranking
let yql = '';
let searchParams: any = {
query: validatedData.query,
hits: '20'
};
switch (validatedData.ranking) {
case 'colpali':
// Use retrieval-and-rerank profile for ColPali
yql = `select * from linqto where userQuery() limit 20`;
searchParams.ranking = 'retrieval-and-rerank';
break;
case 'bm25':
yql = `select * from linqto where userQuery() limit 20`;
searchParams.ranking = 'default';
break;
case 'hybrid':
default:
yql = `select * from linqto where userQuery() limit 20`;
searchParams.ranking = 'default';
break;
}
// For ColPali ranking, we need embeddings
let body: any = {};
let useNearestNeighbor = false;
if (validatedData.ranking === 'colpali') {
try {
// Call embedding API to get query embeddings
const embeddingResponse = await fetch(
`http://localhost:7861/embed_query?query=${encodeURIComponent(validatedData.query)}`
);
if (embeddingResponse.ok) {
const embeddingData = await embeddingResponse.json();
// Create nearestNeighbor query string
const numTokens = Object.keys(embeddingData.embeddings.binary).length;
const maxTokens = Math.min(numTokens, 20); // Limit to 20 tokens to avoid timeouts
const nnClauses = [];
// Add individual rq tensors for nearestNeighbor
for (let i = 0; i < maxTokens; i++) {
body[`input.query(rq${i})`] = embeddingData.embeddings.binary[i.toString()];
nnClauses.push(`({targetHits:10}nearestNeighbor(embedding,rq${i}))`);
}
// Update YQL for nearestNeighbor search
if (nnClauses.length > 0) {
yql = `select * from linqto where ${nnClauses.join(' OR ')} limit 20`;
useNearestNeighbor = true;
}
// Add qt and qtb for ranking
body["input.query(qt)"] = embeddingData.embeddings.float;
body["input.query(qtb)"] = embeddingData.embeddings.binary;
body["presentation.timing"] = true;
} else {
// Fall back to text-only search
searchParams.ranking = 'default';
}
} catch (error) {
console.log('Embedding API not available, falling back to text search');
searchParams.ranking = 'default';
}
}
// Query Vespa directly
const searchUrl = `${config.vespaAppUrl}/search/`;
const urlSearchParams = new URLSearchParams({
yql,
...searchParams
});
// Use ranking.profile for Vespa instead of ranking
if (searchParams.ranking) {
urlSearchParams.delete('ranking');
urlSearchParams.set('ranking.profile', searchParams.ranking);
}
const startTime = Date.now();
let requestOptions: any = {};
// Only use POST with body if we have embeddings
if (Object.keys(body).length > 0) {
requestOptions = {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(body)
};
} else {
requestOptions = {
method: 'GET'
};
}
console.log('Vespa query URL:', `${searchUrl}?${urlSearchParams}`);
console.log('Request options:', requestOptions);
const response = await vespaRequest(`${searchUrl}?${urlSearchParams}`, requestOptions);
if (!response.ok && response.status !== 504) {
const errorText = await response.text();
console.error('Vespa error:', errorText);
throw new Error(`Vespa returned ${response.status}: ${errorText}`);
}
const data = await response.json();
const searchTime = (Date.now() - startTime) / 1000; // Convert to seconds
// Generate query_id for sim_map compatibility
const queryId = uuidv4();
// Transform to match expected format
if (data.root && data.root.children) {
data.root.children.forEach((hit: any, idx: number) => {
if (!hit.fields) hit.fields = {};
// Add sim_map identifier for compatibility
hit.fields.sim_map = `${queryId}_${idx}`;
});
}
// Add timing information
data.timing = {
searchtime: searchTime
};
// Cache the result
cache.set(cacheKey, data);
c.header('X-Cache', 'MISS');
return c.json(data);
} catch (error) {
console.error('Search error:', error);
return c.json({
error: 'Search failed',
message: error instanceof Error ? error.message : 'Unknown error'
}, 500);
}
});
// Full image endpoint - /full_image
backendApi.get('/full_image', async (c) => {
try {
const docId = c.req.query('doc_id'); // Note: backend expects doc_id, not docId
if (!docId) {
return c.json({ error: 'doc_id is required' }, 400);
}
// Check cache
const cacheKey = `fullimage:${docId}`;
const cachedImage = cache.get<{ base64_image: string }>(cacheKey);
if (cachedImage) {
c.header('X-Cache', 'HIT');
return c.json(cachedImage);
}
// Query Vespa for the document
const searchUrl = `${config.vespaAppUrl}/search/`;
const searchParams = new URLSearchParams({
yql: `select * from linqto where id contains "${docId}"`,
hits: '1'
});
const response = await vespaRequest(`${searchUrl}?${searchParams}`);
if (!response.ok) {
throw new Error(`Vespa returned ${response.status}`);
}
const data = await response.json();
if (data.root?.children?.[0]?.fields) {
const fields = data.root.children[0].fields;
const base64Image = fields.full_image || fields.image;
if (base64Image) {
const result = { base64_image: base64Image };
cache.set(cacheKey, result, 86400); // 24 hours
c.header('X-Cache', 'MISS');
return c.json(result);
}
}
return c.json({ error: 'Image not found' }, 404);
} catch (error) {
console.error('Full image error:', error);
return c.json({
error: 'Failed to fetch image',
message: error instanceof Error ? error.message : 'Unknown error'
}, 500);
}
});
// Query suggestions endpoint - /suggestions
backendApi.get('/suggestions', async (c) => {
try {
const query = c.req.query('query') || '';
// Static suggestions for now
const staticSuggestions = [
'linqto bankruptcy',
'linqto filing date',
'linqto creditors',
'linqto assets',
'linqto liabilities',
'linqto chapter 11',
'linqto docket',
'linqto plan',
'linqto disclosure statement',
'linqto claims',
];
if (!query) {
return c.json({ suggestions: staticSuggestions.slice(0, 5) });
}
const lowerQuery = query.toLowerCase();
const filtered = staticSuggestions
.filter(s => s.startsWith(lowerQuery))
.slice(0, 5);
return c.json({ suggestions: filtered });
} catch (error) {
console.error('Suggestions error:', error);
return c.json({
error: 'Failed to fetch suggestions',
suggestions: []
}, 500);
}
});
// Similarity maps endpoint - /get_sim_map
backendApi.get('/get_sim_map', async (c) => {
try {
const queryId = c.req.query('query_id'); // Note: backend expects query_id
const idx = c.req.query('idx');
const token = c.req.query('token');
const tokenIdx = c.req.query('token_idx'); // Note: backend expects token_idx
if (!queryId || !idx || !token || !tokenIdx) {
return c.json({ error: 'Missing required parameters' }, 400);
}
// Return placeholder HTML
const html = `
<div style="padding: 20px; text-align: center;">
<h3>Similarity Map</h3>
<p>Query: ${token}</p>
<p>Document: ${idx}</p>
<p style="color: #666;">
Similarity map generation requires the ColPali model.
This is a placeholder for the demo.
</p>
</div>
`;
return c.html(html);
} catch (error) {
console.error('Similarity map error:', error);
return c.json({
error: 'Failed to generate similarity map',
message: error instanceof Error ? error.message : 'Unknown error'
}, 500);
}
});
// Visual RAG Chat SSE endpoint - /get-message
backendApi.get('/get-message', async (c) => {
const queryId = c.req.query('query_id'); // Note: backend expects query_id
const query = c.req.query('query');
const docIds = c.req.query('doc_ids'); // Note: backend expects doc_ids
if (!queryId || !query || !docIds) {
return c.json({ error: 'Missing required parameters: query_id, query, doc_ids' }, 400);
}
return streamSSE(c, async (stream) => {
try {
// Mock response for now - in production this would use an LLM
// Extract key information from the query
const messages = [];
if (query.toLowerCase().includes('when') && query.toLowerCase().includes('file')) {
messages.push(
`I'll analyze the search results for your query: "${query}"`,
"",
"Based on the documents provided:",
"",
"**LINQTO filed for Chapter 11 bankruptcy on July 7, 2025**",
"",
"The filing was made in the United States Bankruptcy Court for the Southern District of Texas under case number 25-90186.",
"",
"Key details:",
"• Filing Date: July 7, 2025 (Petition Date)",
"• Court: Southern District of Texas",
"• Case Number: 25-90186",
"• Chapter: 11 (Reorganization)",
"",
"This is a demo response. In production, an LLM would analyze the actual document contents for more details."
);
} else {
messages.push(
`I'll analyze the search results for your query: "${query}"`,
"Based on the documents provided, here are the key findings:",
"1. LINQTO filed for Chapter 11 bankruptcy protection on July 7, 2025",
"2. The filing includes detailed financial statements and creditor information",
"3. Various claims and assets are documented in the court filings",
"",
"This is a demo response. In production, this would analyze the actual document contents using an LLM."
);
}
for (const msg of messages) {
await stream.writeSSE({ data: msg });
await new Promise(resolve => setTimeout(resolve, 500)); // Simulate typing delay
}
} catch (error) {
console.error('Chat streaming error:', error);
await stream.writeSSE({
event: 'error',
data: JSON.stringify({
error: 'Streaming failed',
message: error instanceof Error ? error.message : 'Unknown error'
}),
});
}
});
});
export { backendApi };