feat(05-03): Integrate AI fallback system into research search (Exa → Ollama/Gemini/OpenRouter/OpenCode)
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@@ -1,3 +1,5 @@
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const { generateWithFallback } = require('../utils/gemini-fallback');
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const DEFAULT_EXA_API_URL = 'https://api.exa.ai/search';
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const buildSummary = (results) => {
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@@ -20,56 +22,106 @@ const buildSummary = (results) => {
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return snippets.slice(0, 3).join(' ');
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};
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const generateFallbackSummary = async (query, numResults) => {
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try {
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console.log('🔄 Fallback: Generating AI summary for query:', query);
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const prompt = `Provide a concise summary of exercise form and technique for: "${query}". Include key points about proper form, common mistakes, and benefits. Keep it to 2-3 sentences.`;
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const response = await generateWithFallback(prompt, {
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temperature: 0.7,
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maxTokens: 256
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});
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if (response.success && response.data) {
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console.log(`✅ AI fallback summary generated (provider: ${response.provider})`);
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// Extract text from the appropriate response format
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let summaryText = '';
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if (response.data.response) {
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summaryText = response.data.response;
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} else if (response.data.choices?.[0]?.message?.content) {
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summaryText = response.data.choices[0].message.content;
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}
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return {
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summary: summaryText,
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results: [], // No source links from AI fallback
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provider: response.provider
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};
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}
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} catch (err) {
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console.error('AI fallback summary generation failed:', err.message);
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}
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// Last resort: simple template
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return {
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summary: `Exercise information for ${query}. Consult a fitness professional for proper form and safety guidelines.`,
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results: [],
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provider: 'template'
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};
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};
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const searchExerciseResearch = async ({ query, numResults = 5 }) => {
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if (!query || typeof query !== 'string') {
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throw new Error('Query must be a non-empty string');
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}
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const apiKey = process.env.EXA_API_KEY;
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if (!apiKey) {
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throw new Error('EXA_API_KEY is not configured');
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// Tier 1: Try Exa API if configured
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if (apiKey) {
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try {
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console.log('📍 Tier 1: Attempting Exa search API...');
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const apiUrl = process.env.EXA_API_URL || DEFAULT_EXA_API_URL;
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const response = await fetch(apiUrl, {
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method: 'POST',
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headers: {
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'content-type': 'application/json',
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'x-api-key': apiKey
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},
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body: JSON.stringify({
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query,
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numResults,
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type: 'neural',
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useAutoprompt: true
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})
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});
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if (!response.ok) {
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throw new Error(`Exa search failed: ${response.status}`);
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}
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const data = await response.json();
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const results = (data.results || []).map((result) => ({
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id: result.id,
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title: result.title,
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url: result.url,
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snippet: Array.isArray(result.highlights) && result.highlights.length > 0
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? result.highlights[0]
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: result.snippet,
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highlight: result.highlight,
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publishedDate: result.publishedDate,
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score: result.score
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}));
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console.log('✅ Exa API success');
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return {
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summary: buildSummary(results),
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results,
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provider: 'exa'
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};
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} catch (err) {
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console.warn(`⚠️ Exa API failed: ${err.message}, falling back to AI...`);
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}
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} else {
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console.warn('⚠️ EXA_API_KEY not configured, using AI fallback...');
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}
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const apiUrl = process.env.EXA_API_URL || DEFAULT_EXA_API_URL;
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const response = await fetch(apiUrl, {
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method: 'POST',
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headers: {
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'content-type': 'application/json',
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'x-api-key': apiKey
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},
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body: JSON.stringify({
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query,
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numResults,
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type: 'neural',
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useAutoprompt: true
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})
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});
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if (!response.ok) {
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const text = await response.text();
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throw new Error(`Exa search failed: ${response.status} ${text}`);
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}
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const data = await response.json();
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const results = (data.results || []).map((result) => ({
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id: result.id,
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title: result.title,
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url: result.url,
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snippet: Array.isArray(result.highlights) && result.highlights.length > 0
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? result.highlights[0]
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: result.snippet,
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highlight: result.highlight,
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publishedDate: result.publishedDate,
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score: result.score
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}));
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return {
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summary: buildSummary(results),
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results
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};
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// Tier 2: Fallback to AI-generated summary
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return generateFallbackSummary(query, numResults);
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};
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module.exports = {
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searchExerciseResearch
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searchExerciseResearch,
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generateFallbackSummary
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};
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