Delete app.py

app.py

@@ -1,61 +0,0 @@
-from flask import Flask, render_template, request, jsonify
-from huggingface_hub import InferenceClient
-
-# Initialize the Flask app
-app = Flask(__name__)
-
-# Initialize the Hugging Face Inference Client (Replace with your actual model identifier)
-client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
-
-# Parameters from the image
-MAX_TOKENS = 1520
-TEMPERATURE = 0.7
-TOP_P = 0.95
-
-# In-memory storage for active chats (to maintain chat history)
-chat_history = {}
-
-@app.route("/")
-def home():
-    return render_template("editor.html")
-
-@app.route("/generate_code", methods=["POST"])
-def generate_code():
-    # Get the user ID (or session) and the prompt
-    user_id = request.json.get("user_id")
-    prompt = request.json.get("prompt")
-
-    # Get chat history for the user or initialize it
-    if user_id not in chat_history:
-        chat_history[user_id] = []
-
-    # Append the user's prompt to the chat history
-    chat_history[user_id].append({"role": "user", "content": prompt})
-
-    # System message
-    system_message = "You are a friendly chatbot."
-
-    # Build the messages for the model
-    messages = [{"role": "system", "content": system_message}]
-    messages.extend(chat_history[user_id])  # Add previous conversation history
-
-    # Generate the response
-    generated_code = ""
-    for msg in client.chat_completion(
-        messages=messages,
-        max_tokens=MAX_TOKENS,
-        temperature=TEMPERATURE,
-        top_p=TOP_P,
-        stream=True,
-    ):
-        token = msg.choices[0].delta.content
-        generated_code += token
-
-    # Save the assistant's response to the chat history
-    chat_history[user_id].append({"role": "assistant", "content": generated_code})
-
-    return jsonify({"code": generated_code})
-
-if __name__ == "__main__":
-    app.run(debug=True, port=7860)
-