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from fastapi import FastAPI, HTTPException | |
from pydantic import BaseModel | |
from huggingface_hub import InferenceClient | |
app = FastAPI() | |
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2") | |
class PromptRequest(BaseModel): | |
prompt: str | |
history: list | |
def format_prompt(message, history): | |
system_prompt = "You are Mistral, a gentle and a useful AI assistant. My input is " | |
prompt = "<s>" | |
prompt += f"[INST] {system_prompt} [/INST]" | |
for user_prompt, bot_response in history: | |
prompt += f"[INST] {user_prompt} [/INST]" | |
prompt += f" {bot_response}</s> " | |
prompt += f"[INST] {message} [/INST]" | |
return prompt | |
def generate(prompt, history): | |
formatted_prompt = format_prompt(prompt, history) | |
stream = client.text_generation(formatted_prompt, stream=True, details=True, return_full_text=False) | |
output = "" | |
for response in stream: | |
output += response.token.text | |
yield output | |
async def generate_response(request: PromptRequest): | |
try: | |
responses = [] | |
async for response in generate(request.prompt, request.history): | |
responses.append(response) | |
return {"responses": responses} | |
except Exception as e: | |
raise HTTPException(status_code=500, detail=str(e)) | |