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Update app.py
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app.py
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import os
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import threading
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from flask import Flask, jsonify, request
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from llama_cpp import Llama
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import requests
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import subprocess
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import json
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app = Flask(__name__)
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#
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REPO_URL = "https://github.com/NitinBot001/Audio-url-new-js.git"
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def
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url = "https://huggingface.co/MaziyarPanahi/calme-3.3-llamaloi-3b-GGUF/resolve/main/calme-3.3-llamaloi-3b.Q4_K_M.gguf"
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with requests.get(url, stream=True) as r:
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r.raise_for_status()
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with open(MODEL_PATH, "wb") as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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# 2. Initialize LLM
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global llm
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llm = Llama(
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model_path=MODEL_PATH,
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n_ctx=8192, # Reduced from 131072 for faster startup
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n_threads=2,
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n_gpu_layers=0,
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verbose=False
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)
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push_tunnel_url_to_repo(tunnel_url)
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except Exception as e:
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print(f"Background init failed: {str(e)}")
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def start_tunnel():
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["npx", "nport", "-s", "
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE
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)
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# Wait for tunnel
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repo_dir = "/tmp/repo"
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subprocess.run(
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"git", "clone",
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with open(f"{repo_dir}/instance.json", "w") as f:
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json.dump({"tunnel_url": url}, f)
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subprocess.run(["git", "-C", repo_dir, "add", "."], check=True)
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subprocess.run([
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"git", "-C", repo_dir,
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"commit", "-m", f"Update tunnel URL: {url}"
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], check=True)
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subprocess.run(["git", "-C", repo_dir, "push"], check=True)
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@app.route("/chat", methods=["GET"])
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def chat():
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if 'llm' not in globals():
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return jsonify({"error": "Initializing, try again later"}), 503
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message = request.args.get("message", "")
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prompt = f"<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n{message}<|eot_id|>\n<|start_header_id|>assistant<|end_header_id|>\n"
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output = llm(prompt, max_tokens=512, stop=["<|eot_id|>"])
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return jsonify({"response": output['choices'][0]['text'].strip()})
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if __name__ == "__main__":
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#
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app.run(host="0.0.0.0", port=7860)
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import os
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import requests
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from flask import Flask, request, jsonify
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from llama_cpp import Llama
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import subprocess
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import time
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import json
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app = Flask(__name__)
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# Use /tmp directory for storing the model
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MODEL_DIR = "/tmp/model"
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MODEL_PATH = os.path.join(MODEL_DIR, "calme-3.3-llamaloi-3b.Q4_K_M.gguf")
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GH_PAT = os.getenv("GH_PAT") # GitHub Personal Access Token
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REPO_URL = "https://github.com/NitinBot001/Audio-url-new-js.git"
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def download_model():
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os.makedirs(MODEL_DIR, exist_ok=True) # Create the /tmp/model directory
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if not os.path.exists(MODEL_PATH):
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print("Downloading model...")
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r = requests.get(
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"https://huggingface.co/MaziyarPanahi/calme-3.3-llamaloi-3b-GGUF/resolve/main/calme-3.3-llamaloi-3b.Q4_K_M.gguf",
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stream=True,
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)
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with open(MODEL_PATH, "wb") as f:
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for chunk in r.iter_content(chunk_size=8192):
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f.write(chunk)
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def start_tunnel():
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# Start nport tunnel
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tunnel_process = subprocess.Popen(
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["npx", "nport", "-s", "ai-service", "-p", "7860"], # Use port 7860
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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)
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time.sleep(10) # Wait for tunnel to establish
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# Extract tunnel URL from logs
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tunnel_url = None
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for line in iter(tunnel_process.stdout.readline, b""):
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line = line.decode("utf-8").strip()
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if "your domain is:" in line:
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tunnel_url = line.split("your domain is: ")[1]
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break
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if not tunnel_url:
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raise Exception("Failed to extract tunnel URL")
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return tunnel_url
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def push_tunnel_url_to_repo(tunnel_url):
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# Create instance.json
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instance_data = {"tunnel_url": tunnel_url}
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with open("/tmp/instance.json", "w") as f:
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json.dump(instance_data, f)
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# Clone the repository
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repo_dir = "/tmp/repo"
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repo_url = f"https://x-access-token:{GH_PAT}@github.com/NitinBot001/Audio-url-new-js.git"
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subprocess.run(
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["git", "clone", repo_url, repo_dir],
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check=True,
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)
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os.chdir(repo_dir)
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# Move instance.json to the repository
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subprocess.run(["mv", "/tmp/instance.json", "."], check=True)
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# Configure Git locally (without --global)
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subprocess.run(["git", "config", "user.email", "[email protected]"], check=True)
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subprocess.run(["git", "config", "user.name", "github-actions"], check=True)
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# Commit and push changes
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subprocess.run(["git", "add", "instance.json"], check=True)
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subprocess.run(["git", "commit", "-m", f"Update tunnel URL to {tunnel_url}"], check=True)
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subprocess.run(["git", "push", "origin", "main"], check=True)
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@app.route("/chat", methods=["POST"])
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def chat():
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data = request.json
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# Construct the prompt without duplicate special tokens
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prompt = (
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f"<|begin_of_text|>"
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f"<|start_header_id|>user<|end_header_id|>\n"
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f"{data.get('message', '')}"
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f"<|eot_id|>\n"
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f"<|start_header_id|>assistant<|end_header_id|>\n"
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)
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output = llm(
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prompt,
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max_tokens=2048,
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stop=["<|eot_id|>"],
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temperature=0.8,
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top_p=0.9,
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)
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return jsonify({"response": output["choices"][0]["text"].strip()})
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if __name__ == "__main__":
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# Download the model
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download_model()
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# Initialize the LLM
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llm = Llama(
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model_path=MODEL_PATH,
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n_ctx=131072, # Set to match the training context length
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n_threads=2,
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n_gpu_layers=0,
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verbose=False,
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)
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# Start the tunnel and push the URL
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tunnel_url = start_tunnel()
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push_tunnel_url_to_repo(tunnel_url)
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# Run the Flask app (for development only)
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app.run(host="0.0.0.0", port=7860)
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