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from fastapi import FastAPI, Request, Body
from huggingface_hub import InferenceClient
import random
API_URL = "https://api-inference.huggingface.co/models/"
client = InferenceClient(
"mistralai/Mistral-7B-Instruct-v0.1"
)
app = FastAPI()
def format_prompt(message, history):
prompt = "<s>"
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
@app.post("/api/v1/generate_text")
def generate_text(request: Request, prompt: str = Body()):
history = [] # You might need to handle this based on your actual usage
print(f"request + {request}")
temperature = request.headers.get("temperature", 0.5)
# print(f"temperature + {temperature}")
top_p = request.headers.get("top_p", 0.95)
# print(f"top_p + {top_p}")
repetition_penalty = request.headers.get("repetition_penalty", 1.0)
# print(f"repetition_penalty + {repetition_penalty}")
formatted_prompt = format_prompt(prompt, history)
print(f"formatted_prompt + {formatted_prompt}")
stream = client.text_generation(
formatted_prompt,
temperature=temperature,
max_new_tokens=512,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=random.randint(0, 10**7),
stream=False,
details=True,
return_full_text=True
)
# output = ""
# for response in stream:
# output += response.token.text
# yield output
# return output[len(output) - 1]
return stream |