import gradio as gr
import os
from huggingface_hub import InferenceClient

# Use Model
model_id = "deepseek-ai/deepseek-coder-33b-instruct"

def respond(message, history, system_message, temperature, request: gr.Request):
    # --- 1. Authentication Logic ---
    token = None
    # Safely access token (handles both Local run and Spaces)
    if request:
        token = getattr(request, "token", None)
    
    if token is None:
        token = os.getenv("HF_TOKEN")

    if token is None:
        yield "Error: No authentication token found. Please add 'HF_TOKEN' to Space Secrets."
        return

    # --- 2. Setup Client ---
    client = InferenceClient(model_id, token=token)
    
    # --- 3. Build Messages (handling history correctly) ---
    messages = [{"role": "system", "content": system_message}]
    
    # We use type="messages" in ChatInterface, so history is already a list of dicts
    for msg in history:
        messages.append(msg)
    
    messages.append({"role": "user", "content": message})

    # --- 4. Generate Response ---
    try:
        stream = client.chat_completion(
            messages, 
            max_tokens=2048, 
            stream=True, 
            temperature=temperature,
            top_p=0.9
        )
        
        response_text = ""
        for chunk in stream:
            # FIX: Check if choices exist before accessing index [0]
            if not chunk.choices:
                continue
            
            content = chunk.choices[0].delta.content
            if content:
                response_text += content
                yield response_text

    except Exception as e:
        yield f"Error: {str(e)}"

# --- 5. Build UI ---
with gr.Blocks(fill_height=True) as demo:
    with gr.Sidebar():
        gr.Markdown("# AI Coding Assistant")
        gr.Markdown(f"Running **{model_id}**")
        gr.LoginButton("Sign in")
    
    gr.ChatInterface(
        respond,
        # 'type="messages"' fixes the deprecation warning and makes parsing easier
        type="messages", 
        additional_inputs=[
            gr.Textbox(value="You are a helpful assistant.", label="System Instruction", lines=2),
            gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.1, label="Temperature")
        ]
    )

demo.launch()