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from fastapi import FastAPI, Request |
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from fastapi.templating import Jinja2Templates |
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from huggingface_hub import InferenceClient |
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app = FastAPI() |
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templates = Jinja2Templates(directory="templates") |
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client = InferenceClient( |
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"mistralai/Mistral-7B-Instruct-v0.1" |
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) |
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async def format_prompt(message, history): |
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prompt = "<s>" |
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for user_prompt, bot_response in history: |
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prompt += f"[INST] {user_prompt} [/INST]" |
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prompt += f" {bot_response}</s> " |
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prompt += f"[INST] {message} [/INST]" |
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return prompt |
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async def generate( |
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prompt: str, |
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temperature: float = 0.9, |
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max_new_tokens: int = 256, |
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top_p: float = 0.95, |
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repetition_penalty: float = 1.0, |
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): |
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temperature = float(temperature) |
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if temperature < 1e-2: |
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temperature = 1e-2 |
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top_p = float(top_p) |
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generate_kwargs = { |
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"temperature": temperature, |
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"max_new_tokens": max_new_tokens, |
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"top_p": top_p, |
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"repetition_penalty": repetition_penalty, |
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"do_sample": True, |
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"seed": 42, |
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} |
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formatted_prompt = await format_prompt(prompt, []) |
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response = client.text_generation(formatted_prompt, **generate_kwargs, stream=False, details=False, return_full_text=True) |
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return response |
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@app.get("/") |
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async def index(request: Request): |
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return templates.TemplateResponse("index.html", {"request": request}) |
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@app.post("/generate/") |
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async def chatbot_response(prompt: str): |
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response = await generate(prompt) |
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return {"response": response} |
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