localmodel / app.py
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import gradio as gr
from huggingface_hub import hf_hub_download
from llama_cpp import Llama
MODEL_REPO = "bartowski/Phi-3-mini-4k-instruct-GGUF"
MODEL_FILE = "Phi-3-mini-4k-instruct-Q4_K_M.gguf"
print("Downloading model...")
model_path = hf_hub_download(
repo_id=MODEL_REPO,
filename=MODEL_FILE
)
print("Loading model...")
llm = Llama(
model_path=model_path,
n_ctx=2048,
n_threads=4,
verbose=False
)
SYSTEM_PROMPT = """
You are a senior software engineer.
You specialize in:
- Python
- JavaScript
- TypeScript
- PHP
- Pawn/OpenMP
- SQL
- C++
- Rust
Always:
- Explain clearly
- Generate complete code
- Follow best practices
"""
def chat(message, history):
conversation = ""
for user, assistant in history:
conversation += f"User: {user}\n"
conversation += f"Assistant: {assistant}\n"
prompt = f"""
{SYSTEM_PROMPT}
{conversation}
User: {message}
Assistant:
"""
output = llm(
prompt,
max_tokens=256,
temperature=0.2,
top_p=0.95,
stop=["User:"]
)
return output["choices"][0]["text"].strip()
demo = gr.ChatInterface(
fn=chat,
title="AI Coding Assistant",
description="Running locally on Hugging Face CPU Basic"
)
demo.launch()