File size: 1,735 Bytes
5fa76ab 63b4fe7 5fa76ab d1a0a0d 5fa76ab 79c2343 5fa76ab 63b4fe7 79c2343 5fa76ab 63b4fe7 79c2343 63b4fe7 79c2343 5fa76ab 79c2343 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
from fastapi import FastAPI
from pydantic import BaseModel
from huggingface_hub import InferenceClient
from fastapi.responses import StreamingResponse
import uvicorn
app = FastAPI()
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
class Item(BaseModel):
prompt: str
history: list
system_prompt: str
temperature: float = 0.0
max_new_tokens: int = 1048
top_p: float = 0.15
repetition_penalty: float = 1.0
def format_prompt(message, history):
print("````")
print(message)
print("++++")
print(history)
print("````")
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
async def generate_stream(item: Item):
temperature = float(item.temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(item.top_p)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=item.max_new_tokens,
top_p=top_p,
repetition_penalty=item.repetition_penalty,
do_sample=True,
seed=42,
)
formatted_prompt = format_prompt(f"{item.system_prompt} [/INST] Ok..! </s> [INST] {item.prompt}", item.history)
print(formatted_prompt)
print("=======")
print(item.history)
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
for response in stream:
yield response.token.text # Stream each token as it's received
@app.post("/generate/")
async def generate_text(item: Item):
return StreamingResponse(generate_stream(item), media_type="text/plain")
|