immersive2/server/api/ollama.js
Michael Mainguy 4ca98cf980 Add LangChain model wrappers and enhance diagram AI tools
- Migrate to LangChain for model abstraction (@langchain/anthropic, @langchain/ollama)
- Add custom ChatCloudflare class for Cloudflare Workers AI
- Simplify API routes using unified LangChain interface
- Add session preferences API for storing user settings
- Add connection label preference (ask user once, remember for session)
- Add shape modification support (change entity shapes via AI)
- Add template setter to DiagramObject for shape changes
- Improve entity inference with fuzzy matching
- Map colors to 16 toolbox palette colors
- Limit conversation history to last 6 messages
- Fix model switching to accept display names

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-14 10:17:15 -06:00

98 lines
3.6 KiB
JavaScript

import { Router } from "express";
import { getSession, addMessage } from "../services/sessionStore.js";
import {
getOllamaModel,
buildLangChainMessages,
aiMessageToClaudeResponse
} from "../services/langchainModels.js";
const router = Router();
router.post("/*path", async (req, res) => {
const requestStart = Date.now();
console.log(`[Ollama API] ========== REQUEST START ==========`);
const { sessionId, model: modelId, max_tokens, system: systemPrompt, messages } = req.body;
console.log(`[Ollama API] Session ID: ${sessionId || 'none'}`);
console.log(`[Ollama API] Model: ${modelId}`);
console.log(`[Ollama API] Messages count: ${messages?.length || 0}`);
try {
// Get LangChain model with tools bound
const model = getOllamaModel(modelId);
// Build messages with entity context and history
const langChainMessages = buildLangChainMessages(
sessionId,
messages,
systemPrompt
);
console.log(`[Ollama API] Sending request via LangChain...`);
const fetchStart = Date.now();
// Invoke model
const response = await model.invoke(langChainMessages);
const fetchDuration = Date.now() - fetchStart;
console.log(`[Ollama API] Response received in ${fetchDuration}ms`);
// Convert to Claude API format for client compatibility
const claudeResponse = aiMessageToClaudeResponse(response, modelId);
console.log(`[Ollama API] Response converted. Stop reason: ${claudeResponse.stop_reason}, content blocks: ${claudeResponse.content.length}`);
// Store messages to session if applicable
if (sessionId && claudeResponse.content) {
const session = getSession(sessionId);
if (session) {
const userMessage = messages?.[messages.length - 1];
if (userMessage && userMessage.role === 'user' && typeof userMessage.content === 'string') {
addMessage(sessionId, {
role: 'user',
content: userMessage.content
});
console.log(`[Ollama API] Stored user message to session`);
}
const assistantContent = claudeResponse.content
.filter(c => c.type === 'text')
.map(c => c.text)
.join('\n');
if (assistantContent) {
addMessage(sessionId, {
role: 'assistant',
content: assistantContent
});
console.log(`[Ollama API] Stored assistant response to session (${assistantContent.length} chars)`);
}
}
}
const totalDuration = Date.now() - requestStart;
console.log(`[Ollama API] ========== REQUEST COMPLETE (${totalDuration}ms) ==========`);
res.json(claudeResponse);
} catch (error) {
const totalDuration = Date.now() - requestStart;
console.error(`[Ollama API] ========== REQUEST FAILED (${totalDuration}ms) ==========`);
console.error(`[Ollama API] Error:`, error);
// Check if it's a connection error
if (error.cause?.code === 'ECONNREFUSED' || error.message?.includes('ECONNREFUSED')) {
return res.status(503).json({
error: "Ollama is not running",
details: `Could not connect to Ollama. Make sure Ollama is installed and running.`
});
}
res.status(500).json({
error: "Failed to call Ollama",
details: error.message
});
}
});
export default router;