import gradio as gr
from threading import Thread

err = None
try:
    import torch
    from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer
except ModuleNotFoundError as e:
    err = e

MODEL = "yava-code/kimi-coder-135m"
tok = None
model = None

if err is None:
    tok = AutoTokenizer.from_pretrained(MODEL)
    model = AutoModelForCausalLM.from_pretrained(
        MODEL,
        torch_dtype=torch.bfloat16,
        device_map="auto",
    )
    model.eval()

def respond(msg, history, max_new, temp):
    if err is not None:
        yield (
            f"missing dependency: `{err.name}`\n\n"
            "add it to requirements.txt and rebuild the space."
        )
        return

    chat = []
    for u, a in history:
        chat += [{"role": "user", "content": u}, {"role": "assistant", "content": a}]
    chat.append({"role": "user", "content": msg})

    input_ids = tok.apply_chat_template(chat, return_tensors="pt", add_generation_prompt=True).to(model.device)

    streamer = TextIteratorStreamer(tok, skip_prompt=True, skip_special_tokens=True)
    gen_kwargs = dict(
        input_ids=input_ids,
        streamer=streamer,
        max_new_tokens=max_new,
        temperature=temp,
        do_sample=temp > 0,
    )
    Thread(target=model.generate, kwargs=gen_kwargs).start()

    out = ""
    for token in streamer:
        out += token
        yield out

EXAMPLES = [
    ["Write a Python function to find all prime numbers up to n using the Sieve of Eratosthenes."],
    ["Implement a binary search tree with insert and search methods in Python."],
    ["Write a decorator that caches function results (memoization)."],
]

with gr.Blocks(title="kimi-coder-135m") as demo:
    gr.Markdown(
        """
## 🤖 kimi-coder-135m
SmolLM2-135M fine-tuned on 15k coding samples distilled from KIMI-K2.5.  
Model: [yava-code/kimi-coder-135m](https://huggingface.co/yava-code/kimi-coder-135m)
        """
    )
    if err is not None:
        gr.Markdown(
            f"### startup warning\n"
            f"missing dependency: `{err.name}`\n\n"
            f"current requirements include `torch`, so this usually means the build failed.\n"
            f"try restarting/rebuilding the space."
        )
    else:
        chatbot = gr.ChatInterface(
            respond,
            additional_inputs=[
                gr.Slider(64, 1024, value=512, label="Max new tokens"),
                gr.Slider(0, 1, value=0.3, step=0.05, label="Temperature"),
            ],
            examples=EXAMPLES,
            title="",
        )

demo.launch()