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769ecc0 0333e82 18b7523 769ecc0 0333e82 18b7523 769ecc0 0333e82 769ecc0 0333e82 769ecc0 0333e82 769ecc0 0333e82 | 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 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | import gradio as gr
from huggingface_hub import InferenceClient
from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
import os
# Gradio app + FastAPI mount
app = FastAPI()
client = InferenceClient(
model="HuggingFaceH4/zephyr-7b-beta",
token=os.getenv("huggingface_token"),
)
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response
# Define FastAPI POST endpoint
@app.post("/chat")
async def chat(request: Request):
data = await request.json()
message = data.get("message")
persona = data.get("persona", "You are a friendly Chatbot.")
max_tokens = data.get("max_tokens", 512)
temperature = data.get("temperature", 0.7)
top_p = data.get("top_p", 0.95)
messages = [{"role": "system", "content": persona}, {"role": "user", "content": message}]
full_response = ""
for chunk in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
full_response += chunk.choices[0].delta.content or ""
return JSONResponse({"response": full_response})
# Gradio demo for UI access
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)"),
],
)
# Mount Gradio app at "/"
app = gr.mount_gradio_app(app, demo, path="/") |