Upload main.py

main.py

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+from flask import Flask, request, jsonify
+from sentence_transformers import SentenceTransformer
+from pinecone import Pinecone
+import google.generativeai as genai
+from langdetect import detect
+
+# تهيئة الموديلات
+embedding_model = SentenceTransformer("intfloat/multilingual-e5-large")
+
+pc = Pinecone(api_key="pcsk_3ax4D8_PH7vWF1KWAMRpyjmEnXhwxswmHSjvqgwovna3xGGbfsgZsMRtRyFi9uCpPyi4B9")
+index = pc.Index("newindex")
+
+genai.configure(api_key="AIzaSyBXtRzMkpm9RNDO09A9N3XoG_vfjgUe5Vw")
+model = genai.GenerativeModel("gemini-2.0-flash")
+
+app = Flask(__name__)
+chat_history = []
+
+def detect_language(text):
+    try:
+        return detect(text)
+    except:
+        return "unknown"
+
+def get_answer_from_pinecone(user_question, embedding_model, index, top_k=5, similarity_threshold=0.7):
+    try:
+        question_vector = embedding_model.encode(user_question).tolist()
+    except Exception as e:
+        return [f"❌ Error embedding question: {e}"]
+
+    try:
+        search_result = index.query(
+            vector=question_vector,
+            top_k=top_k,
+            include_metadata=True
+        )
+    except Exception as e:
+        return [f"❌ Error querying Pinecone: {e}"]
+
+    matches = [m for m in search_result.matches if m.score >= similarity_threshold]
+    sorted_matches = sorted(matches, key=lambda x: x.score, reverse=True)
+
+    answers = []
+    for m in sorted_matches:
+        answer = m.metadata.get('answer', '').strip()
+        source = m.metadata.get('source', 'unknown')
+        score = round(m.score, 3)
+        if answer:
+            answers.append(f"• ({score}) from [{source}]:\n{answer}")
+    return answers if answers else ["⚠️ No similar answers found."]
+
+def ask_gemini_with_combined_answer(user_question, pinecone_answers=[], history=[]):
+    context = "\n".join([f"👤 {q}\n🤖 {a}" for q, a in history])
+    extracted_info = "\n".join([f"• {ans}" for ans in pinecone_answers]) if pinecone_answers else "None"
+    lang = detect_language(user_question)
+
+    if lang == "ar":
+        greeting = "مرحبًا! 😊"
+        instructions = """
+❗ هام: استخدم فقط المعلومات من قاعدة البيانات.
+
+📜 المحادثة السابقة:
+{context}
+
+👤 المستخدم يسأل: {user_question}
+📚 معلومات من قاعدة البيانات:
+{extracted_info}
+
+📌 الرد:
+"""
+    else:
+        greeting = "Hello! 😊"
+        instructions = """
+❗ Important: Use only database information.
+
+📜 Previous conversation:
+{context}
+
+👤 User asks: {user_question}
+📚 Retrieved info:
+{extracted_info}
+
+📌 Response:
+"""
+
+    prompt = instructions.format(
+        context=context or ("لا يوجد" if lang == "ar" else "None"),
+        user_question=user_question,
+        extracted_info=extracted_info
+    )
+    response = model.generate_content(prompt)
+    return f"{greeting}\n{response.text.strip()}"
+
+@app.route("/ask", methods=["POST"])
+def ask():
+    data = request.json
+    question = data.get("question")
+    if not question:
+        return jsonify({"error": "Missing question"}), 400
+
+    pinecone_answer = get_answer_from_pinecone(question, embedding_model, index)
+    final_answer = ask_gemini_with_combined_answer(question, pinecone_answer, chat_history)
+    chat_history.append((question, final_answer))
+
+    return jsonify({
+        "question": question,
+        "pinecone_matches": pinecone_answer,
+        "answer": final_answer
+    })
+
+@app.route("/")
+def home():
+    return "🤖 API is running. Use POST /ask with {'question': '...'}"
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)