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Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

chat.py

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+import requests
+import os
+
+OPENROUTER_API_KEY = "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"
+
+
+SYSTEM_PROMPT = """
+You are MentorAI, an educational assistant.
+Always answer in numbered lists.
+One idea per line.
+Use simple language for high school students.
+Do not repeat points.
+"""
+
+# =========================
+# AI RESPONSE GENERATOR
+# =========================
+def generate_response(messages):
+    try:
+        payload = {
+            "model": "xiaomi/mimo-v2-flash:free",
+            "messages": [
+                {"role": "system", "content": SYSTEM_PROMPT},
+                *messages
+            ]
+        }
+
+        response = requests.post(
+            "https://openrouter.ai/api/v1/chat/completions",
+            headers={
+                "Authorization": f"Bearer {OPENROUTER_API_KEY}",
+                "Content-Type": "application/json"
+            },
+            json=payload,
+            timeout=30
+        )
+
+        data = response.json()
+
+        if "choices" not in data:
+            return "⚠️ AI error. Try again."
+
+        return data["choices"][0]["message"]["content"]
+
+    except Exception as e:
+<<<<<<< HEAD
+        return f"⚠️ AI service error: {str(e)}"
+=======
+        return f"⚠️ AI service error: {str(e)}"
+>>>>>>> 338342138b282483579892c59b03a2491140a888

classifier.py

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+from transformers import pipeline
+
+classifier = pipeline("zero-shot-classification", model = "facebook/bart-large-mnli")
+
+LABELS = [
+    "learning question",
+    "casual conversation",
+    "homework cheating",
+    "off topic"
+]
+
+def is_supported_question(text: str) -> bool:
+    result = classifier(text, LABELS)
+    top_label = result["labels"][0]
+    return top_label == "learning question"

main.py

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+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from chat import generate_response
+from classifier import is_supported_question
+
+app = FastAPI(title="MentorAI Backend")
+
+# =========================
+# CORS (VERY IMPORTANT)
+# =========================
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Hugging Face requires this
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# =========================
+# SESSION MEMORY (LIGHT)
+# =========================
+sessions = {}
+MAX_MESSAGES = 6
+
+class ChatRequest(BaseModel):
+    session_id: str
+    message: str
+
+# =========================
+# HEALTH CHECK
+# =========================
+@app.get("/")
+def home():
+    return {"status": "MentorAI backend running"}
+
+# =========================
+# CHAT ENDPOINT
+# =========================
+@app.post("/chat")
+def chat(req: ChatRequest):
+    if not is_supported_question(req.message):
+        return {
+            "response": "⚠️ MentorAI only answers learning-related questions."
+        }
+
+    if req.session_id not in sessions:
+        sessions[req.session_id] = []
+
+    sessions[req.session_id].append({
+        "role": "user",
+        "content": req.message.strip()
+    })
+
+    sessions[req.session_id] = sessions[req.session_id][-MAX_MESSAGES:]
+
+    ai_reply = generate_response(sessions[req.session_id])
+
+    # Deduplicate lines
+    seen = set()
+    clean_lines = []
+    for line in ai_reply.split("\n"):
+        line = line.strip()
+        if line and line not in seen:
+            seen.add(line)
+            clean_lines.append(line)
+
+    final_reply = "\n".join(clean_lines)
+
+    sessions[req.session_id].append({
+        "role": "assistant",
+        "content": final_reply
+    })
+
+    return {"response": final_reply}

requirements.txt

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+<<<<<<< HEAD
+fastapi
+uvicorn
+requests
+
+=======
+fastapi
+uvicorn
+requests
+
+>>>>>>> 338342138b282483579892c59b03a2491140a888