Gitea
88 lines
3.0 KiB
JavaScript
88 lines
3.0 KiB
JavaScript
const axios = require('axios');
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const { GoogleGenerativeAI } = require('@google/generative-ai');
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const ai = new GoogleGenerativeAI({ apiKey: process.env.GEMINI_API_KEY });
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const fetchWrenData = async (prompt, tenantId) => {
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try {
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const url = process.env.WREN_AI_URL || 'http://localhost:5555/api/v1/text-to-sql';
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const response = await axios.post(url,
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{ prompt: prompt },
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{
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headers: {
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'X-Wren-Session-Properties': `@user_org_id=${tenantId}`,
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'Content-Type': 'application/json'
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}
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}
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);
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return response.data;
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} catch (error) {
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console.error('Wren AI Integration Error:', error.message);
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throw new Error('Failed to fetch data payload from Wren AI endpoint');
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}
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};
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const generateVegaSchema = async (question, dataArray) => {
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try {
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const model = ai.getGenerativeModel({
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model: 'gemini-2.5-flash',
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generationConfig: { responseMimeType: 'application/json' }
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});
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const systemPrompt = `You are a data visualization expert. I will provide a user's question and a JSON array of data.
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Your task is to generate a strictly valid Vega-Lite JSON specification to visualize this data.
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The data array will be provided to the Vega spec internally. Map the JSON keys to the correct x, y, and color axes.
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Choose the best chart type (bar, line, arc) based on the question.`;
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const userPrompt = `User Question: "${question}"\nData JSON: ${JSON.stringify(dataArray)}`;
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const result = await model.generateContent({
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contents: [{ role: 'user', parts: [{ text: `${systemPrompt}\n\n${userPrompt}` }] }]
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});
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return JSON.parse(result.response.text());
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} catch (error) {
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console.error('Gemini Engine Error:', error.message);
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throw new Error('Failed to transform data architecture into valid Vega-Lite spec');
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}
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};
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const handleOrchestration = async (req, res) => {
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try {
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const { prompt } = req.body;
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const tenant_id = req.user ? req.user.client_id : null;
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return res.status(200).json("ok");
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if (!prompt) {
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return res.status(400).json({ error: 'Prompt field is required in request body' });
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}
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if (!tenant_id) {
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return res.status(400).json({ error: 'Tenant context (client_id) missing from auth token' });
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}
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const wrenData = await fetchWrenData(prompt, tenant_id);
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const vegaSchema = await generateVegaSchema(prompt, wrenData);
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if (!vegaSchema || !vegaSchema.$schema) {
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return res.status(500).json({ error: 'Egress Pipeline Validation Failure: Output missing standard Vega $schema identifier' });
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}
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return res.status(200).json(vegaSchema);
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} catch (error) {
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console.error('API Gateway Orchestrator Crash:', error.message);
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return res.status(500).json({ error: error.message });
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}
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};
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module.exports = { handleOrchestration };
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