app.py

import os, re, json, base64, requests
from flask import Flask, request, jsonify, send_file
from flask_cors import CORS
from groq import Groq
from supabase import create_client, Client

app = Flask(__name__)
CORS(app)

client   = Groq(api_key=os.environ["GROQ_API_KEY"])
supabase = create_client(os.environ["SUPABASE_URL"], os.environ["SUPABASE_KEY"])

def fetch_wikipedia(search_term):
    search_term = search_term.replace(" ", "_")
    url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{search_term}"
    return requests.get(url, headers={"User-Agent": "EucalyptusLens/1.0"}).json()

def clean_wikipedia(data):
    summary = data.get("extract", "")
    summary = re.sub(r'\[.*?\]', '', summary)
    summary = re.sub(r'\s{2,}', ' ', summary)
    summary = re.sub(r'[^\x00-\x7F]+', '', summary).strip()
    return {"title": data.get("title",""), "summary": summary, "url": data.get("content_urls",{}).get("desktop",{}).get("page","")}

def build_rag_context(c):
    return f"Plant: {c['title']}\nSummary: {c['summary']}\nSource: {c['url']}\n"

def identify_plant(image_path):
    with open(image_path,"rb") as f:
        b64 = base64.b64encode(f.read()).decode("utf-8")
    response = client.chat.completions.create(
        model="meta-llama/llama-4-scout-17b-16e-instruct",
        messages=[{"role":"user","content":[
            {"type":"image_url","image_url":{"url":f"data:image/jpeg;base64,{b64}"}},
            {"type":"text","text":'''You are an expert botanist. Respond in JSON only:
{"common_name":"...","scientific_name":"...","family":"...","confidence":"high/medium/low","key_features":["..."],"wikipedia_search_term":"..."}'''}
        ]}],
        temperature=0.2, max_tokens=500
    )
    return json.loads(re.sub(r'```json|```','',response.choices[0].message.content).strip())

def analyze_plant(image_path):
    plant = identify_plant(image_path)
    cleaned = clean_wikipedia(fetch_wikipedia(plant.get("wikipedia_search_term", plant.get("common_name",""))))
    return {"identification": plant, "wikipedia": build_rag_context(cleaned)}

def save_to_supabase(result):
    id = result["identification"]
    supabase.table("plant_history").insert({
        "common_name": id.get("common_name"), "scientific_name": id.get("scientific_name"),
        "family": id.get("family"), "confidence": id.get("confidence"),
        "key_features": id.get("key_features"), "wikipedia_summary": result["wikipedia"],
        "wikipedia_url": id.get("wikipedia_search_term")
    }).execute()

@app.route("/")
def index():
    return send_file("index.html")

@app.route("/analyze", methods=["POST"])
def analyze():
    if "file" not in request.files:
        return jsonify({"error": "No file"}), 400
    file = request.files["file"]
    file.save("temp.jpg")
    result = analyze_plant("temp.jpg")
    os.remove("temp.jpg")
    save_to_supabase(result)
    return jsonify(result)

@app.route("/history", methods=["GET"])
def history():
    return jsonify(supabase.table("plant_history").select("*").order("created_at", desc=True).execute().data)

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=int(os.environ.get("PORT", 5000)))