Create app.py

app.py

@@ -0,0 +1,80 @@
+from flask import Flask, request, jsonify
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import os
+import json
+
+app = Flask(__name__)
+
+HISTORY_FILE = "history.json"
+MAX_HISTORY = 10  # Keep only the last 10 lines per user
+
+# Load history from file (or create empty)
+if os.path.exists(HISTORY_FILE):
+    with open(HISTORY_FILE, "r", encoding="utf-8") as f:
+        user_histories = json.load(f)
+else:
+    user_histories = {}
+
+# Choose a Transformers-compatible DeepSeek Distill model
+MODEL_NAME = "deepseek-ai/DeepSeek-R1-Distill-Qwen-7B"  # change to bigger model if GPU allows
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def save_history():
+    """Save all histories to a JSON file."""
+    with open(HISTORY_FILE, "w", encoding="utf-8") as f:
+        json.dump(user_histories, f, ensure_ascii=False, indent=2)
+
+@app.route("/message", methods=["GET"])
+def handle_message():
+    user_message = request.args.get("message")
+    user_id = request.args.get("userid")
+
+    if not user_message or not user_id:
+        return jsonify({"error": "Both 'message' and 'userid' are required"}), 400
+
+    # Retrieve or initialize history
+    history = user_histories.get(user_id, [])
+
+
+    history.append(f"User: {user_message}")
+
+
+    history = history[-MAX_HISTORY:]
+
+
+    conversation_text = "\n".join(history) + "\nAI:"
+
+
+    inputs = tokenizer(conversation_text, return_tensors="pt").to(model.device)
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=256,
+        temperature=0.6,
+        do_sample=True
+    )
+
+    reply = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+ 
+    if "AI:" in reply:
+        reply_text = reply.split("AI:")[-1].strip()
+    else:
+        reply_text = reply.strip()
+
+
+    history.append(f"AI: {reply_text}")
+    user_histories[user_id] = history
+
+    
+    save_history()
+
+    return jsonify({"response": reply_text})
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5000, debug=True)