app.py

import gradio as gr
from huggingface_hub import InferenceClient

# ←–– set this to the exact name of your HF repo
HF_MODEL_ID = "rieon/DeepCoder-14B-Preview-Suger"

# explicitly tell the client you want text-generation
client = InferenceClient(model=HF_MODEL_ID)

# def respond(
#     message: str,
#     history: list[dict],       # [{"role":"user"/"assistant","content":…}, …]
#     system_message: str,
#     max_tokens: int,
#     temperature: float,
#     top_p: float,
# ):
#     # 1️⃣ Build one raw-text prompt from system + chat history + new user turn
#     prompt = system_message.strip() + "\n"
#     for msg in history:
#         role = msg["role"]
#         content = msg["content"]
#         if role == "user":
#             prompt += f"User: {content}\n"
#         elif role == "assistant":
#             prompt += f"Assistant: {content}\n"
#     prompt += f"User: {message}\nAssistant:"

#     # 2️⃣ Stream tokens from the text-generation endpoint
#     generated = ""
#     for chunk in client.text_generation(
#         prompt,                     # first positional arg
#         max_new_tokens=max_tokens,
#         temperature=temperature,
#         top_p=top_p,
#         stream=True,
#     ):
#         generated += chunk.generated_text
#         yield generated

def respond(
    message: str,
    history: list[dict],
    system_message: str,
    max_tokens: int,
    temperature: float,
    top_p: float,
):
    # assemble a single prompt from system message + history
    prompt = system_message.strip() + "\n"
    # for user, bot in history:
    #     prompt += f"User: {user}\nAssistant: {bot}\n"
    prompt += f"User: {message}\nAssistant:"

    # stream back tokens
    generated = ""
    for chunk in client.text_generation(
        prompt,
        max_new_tokens=max_tokens,
        temperature=temperature,
        top_p=top_p,
        stream=True,
    ):
        # the API returns a small JSON with .generated_text
        generated += chunk.generated_text
        yield generated

demo = gr.ChatInterface(
    fn=respond,
    type="messages",
    title="DeepCoder with Suger",
    description="Upload any text or pdf files and ask questions about them!",
    additional_inputs=[
        gr.Textbox(value="You are a helpful coding assistant.", label="System message"),
        gr.Slider(1, 2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(0.1, 4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p"),
    ],
)

if __name__ == "__main__":
    demo.launch()