app.py

import os
import requests
from flask import Flask, request, jsonify
from llama_cpp import Llama
import subprocess
import time
import json

app = Flask(__name__)

# Use /tmp directory for storing the model
MODEL_DIR = "/tmp/model"
MODEL_PATH = os.path.join(MODEL_DIR, "calme-3.3-llamaloi-3b.Q4_K_M.gguf")
GH_PAT = os.getenv("GH_PAT")  # GitHub Personal Access Token
REPO_URL = "https://github.com/NitinBot001/Audio-url-new-js.git"

def download_model():
    os.makedirs(MODEL_DIR, exist_ok=True)  # Create the /tmp/model directory
    if not os.path.exists(MODEL_PATH):
        print("Downloading model...")
        r = requests.get(
            "https://huggingface.co/MaziyarPanahi/calme-3.3-llamaloi-3b-GGUF/resolve/main/calme-3.3-llamaloi-3b.Q4_K_M.gguf",
            stream=True,
        )
        with open(MODEL_PATH, "wb") as f:
            for chunk in r.iter_content(chunk_size=8192):
                f.write(chunk)

def start_tunnel():
    # Start nport tunnel
    tunnel_process = subprocess.Popen(
        ["npx", "nport", "-s", "ai-service", "-p", "7860"],  # Use port 7860
        stdout=subprocess.PIPE,
        stderr=subprocess.PIPE,
    )
    time.sleep(10)  # Wait for tunnel to establish

    # Extract tunnel URL from logs
    tunnel_url = None
    for line in iter(tunnel_process.stdout.readline, b""):
        line = line.decode("utf-8").strip()
        if "your domain is:" in line:
            tunnel_url = line.split("your domain is: ")[1]
            break

    if not tunnel_url:
        raise Exception("Failed to extract tunnel URL")

    return tunnel_url

def push_tunnel_url_to_repo(tunnel_url):
    # Create instance.json
    instance_data = {"tunnel_url": tunnel_url}
    with open("/tmp/instance.json", "w") as f:
        json.dump(instance_data, f)

    # Clone the repository
    repo_dir = "/tmp/repo"
    repo_url = f"https://x-access-token:{GH_PAT}@github.com/NitinBot001/Audio-url-new-js.git"
    subprocess.run(
        ["git", "clone", repo_url, repo_dir],
        check=True,
    )
    os.chdir(repo_dir)

    # Move instance.json to the repository
    subprocess.run(["mv", "/tmp/instance.json", "."], check=True)

    # Configure Git locally (without --global)
    subprocess.run(["git", "config", "user.email", "[email protected]"], check=True)
    subprocess.run(["git", "config", "user.name", "github-actions"], check=True)

    # Commit and push changes
    subprocess.run(["git", "add", "instance.json"], check=True)
    subprocess.run(["git", "commit", "-m", f"Update tunnel URL to {tunnel_url}"], check=True)
    subprocess.run(["git", "push", "origin", "main"], check=True)

@app.route("/chat", methods=["POST"])
def chat():
    data = request.json
    # Construct the prompt without duplicate special tokens
    prompt = (
        f"<|begin_of_text|>"
        f"<|start_header_id|>user<|end_header_id|>\n"
        f"{data.get('message', '')}"
        f"<|eot_id|>\n"
        f"<|start_header_id|>assistant<|end_header_id|>\n"
    )
    output = llm(
        prompt,
        max_tokens=2048,
        stop=["<|eot_id|>"],
        temperature=0.8,
        top_p=0.9,
    )
    return jsonify({"response": output["choices"][0]["text"].strip()})

if __name__ == "__main__":
    # Download the model
    download_model()

    # Initialize the LLM
    llm = Llama(
        model_path=MODEL_PATH,
        n_ctx=131072,  # Set to match the training context length
        n_threads=2,
        n_gpu_layers=0,
        verbose=False,
    )

    # Start the tunnel and push the URL
    tunnel_url = start_tunnel()
    push_tunnel_url_to_repo(tunnel_url)

    # Run the Flask app (for development only)
    app.run(host="0.0.0.0", port=7860)