foodsnap/supabase/functions/coach-generator/index.ts

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import { serve } from "https://deno.land/std@0.168.0/http/server.ts";
import { COACH_SYSTEM_PROMPT } from "./prompt.ts";
const corsHeaders = {
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Headers': 'authorization, x-client-info, apikey, content-type',
};
serve(async (req) => {
// Handle CORS preflight requests
if (req.method === 'OPTIONS') {
return new Response('ok', { headers: corsHeaders });
}
try {
const { photos, goal } = await req.json();
if (!photos || (!photos.front && !photos.side && !photos.back)) {
throw new Error("Pelo menos uma foto é necessária.");
}
const GEMINI_API_KEY = Deno.env.get("GEMINI_API_KEY");
if (!GEMINI_API_KEY) {
throw new Error("Servidor não configurado (API Key ausente).");
}
// Prepare Image Parts
const parts = [];
// System Prompt
parts.push({ text: COACH_SYSTEM_PROMPT });
// User Goal
parts.push({ text: `Objetivo do Usuário: ${goal}\nAnalise as fotos e gere o protocolo.` });
// Images
for (const [key, value] of Object.entries(photos)) {
if (typeof value === 'string' && value.includes('base64,')) {
// value example: "data:image/jpeg;base64,/9j/4AAQSkZJRg..."
const base64Data = value.split(',')[1];
// Detect mime type
const mimeMatch = value.match(/^data:(.*);base64/);
const mimeType = mimeMatch ? mimeMatch[1] : 'image/jpeg';
parts.push({
inline_data: {
mime_type: mimeType,
data: base64Data
}
});
}
}
// Call Gemini API via Fetch (More stable than SDK in Deno Edge)
// Using user-specified model: gemini-2.5-flash
const response = await fetch(
`https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key=${GEMINI_API_KEY}`,
{
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
contents: [{ parts: parts }],
generationConfig: {
temperature: 0.2,
response_mime_type: "application/json"
}
})
}
);
if (!response.ok) {
const errorText = await response.text();
console.error("Gemini API Error:", errorText);
throw new Error(`Erro na IA (${response.status}): ${errorText}`);
}
const data = await response.json();
const generatedText = data.candidates?.[0]?.content?.parts?.[0]?.text;
if (!generatedText) {
console.error("Gemini Empty Response:", JSON.stringify(data));
throw new Error("A IA não conseguiu analisar as imagens. Tente fotos com melhor iluminação.");
}
let jsonResponse;
try {
// Clean markdown blocks if present (common in Gemini responses)
const cleaned = generatedText.replace(/```json/g, '').replace(/```/g, '').trim();
jsonResponse = JSON.parse(cleaned);
} catch (e) {
console.error("JSON Parse Error:", generatedText);
throw new Error("Erro ao processar a resposta da IA. Tente novamente.");
}
// Basic validation of the response structure
if (!jsonResponse.analysis || !jsonResponse.diet || !jsonResponse.workout) {
throw new Error("A resposta da IA veio incompleta. Por favor, tente novamente.");
}
return new Response(JSON.stringify(jsonResponse), {
headers: { ...corsHeaders, 'Content-Type': 'application/json' },
status: 200
});
} catch (error) {
console.error("Function Error:", error);
return new Response(JSON.stringify({ error: error.message }), {
headers: { ...corsHeaders, 'Content-Type': 'application/json' },
status: 400 // Return 400 so client sees it as error, but with body
});
}
});