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Update app.py
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import os
from transformers import pipeline
import gradio as gr
from fastapi import FastAPI
from pydantic import BaseModel
import threading
import uvicorn
# =======================
# Load Secrets
# =======================
# SYSTEM_PROMPT (with the flag) must be added in HF Space secrets
SYSTEM_PROMPT = os.environ.get(
"prompt",
"You are a placeholder Sovereign. No secrets found in environment."
)
# MODEL_ID = "tiiuae/Falcon3-3B-Instruct"
# tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
# # =======================
# # Initialize Falcon-3B
# # =======================
# pipe = pipeline(
# "text-generation",
# model="tiiuae/Falcon3-3B-Instruct",
# tokenizer=tokenizer,
# device_map="auto",
# return_full_text=False,
# max_new_tokens=256,
# do_sample=True,
# temperature=0.8,
# top_p=0.9,
# eos_token_id=tokenizer.eos_token_id
# )
pipe = pipeline(
"text-generation",
model="tiiuae/Falcon3-3B-Instruct",
torch_dtype="auto",
device_map="auto",
)
# =======================
# Core Chat Function
# =======================
def chat_fn(user_input: str) -> str:
"""
Concatenate system and user messages, run the model,
and strip the system prompt from the output.
"""
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": f"User: {user_input}"}
]
# Falcon is not chat-native; we just join roles with newlines
prompt_text = "\n".join(f"{m['role'].capitalize()}: {m['content']}" for m in messages)
result = pipe(prompt_text, max_new_tokens=256, do_sample=False)
generated_text = result[0]["generated_text"]
return generated_text[len(prompt_text):].strip()
# =======================
# Gradio UI
# =======================
def gradio_chat(user_input: str) -> str:
return chat_fn(user_input)
iface = gr.Interface(
fn=gradio_chat,
inputs=gr.Textbox(lines=5, placeholder="Enter your prompt…"),
outputs="text",
title="Prompt cracking challenge",
description="Does he really think he is the king?"
)
# =======================
# FastAPI for API access
# =======================
app = FastAPI(title="Prompt cracking challenge API")
class Request(BaseModel):
prompt: str
@app.post("/generate")
def generate(req: Request):
return {"response": chat_fn(req.prompt)}
# =======================
# Launch Both Servers
# =======================
if __name__ == "__main__":
iface.launch(server_name="0.0.0.0", share=True)