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import os
import gradio as gr
from dotenv import load_dotenv
from openai import OpenAI
from fastapi import FastAPI
import threading
import uvicorn
from prompts.initial_prompt import INITIAL_PROMPT
from prompts.main_prompt import MAIN_PROMPT
# ✅ Load OpenAI API Key
if os.path.exists(".env"):
load_dotenv(".env")
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
client = OpenAI(api_key=OPENAI_API_KEY)
# ✅ FastAPI App for Serving Prompts
fastapi_app = FastAPI()
@fastapi_app.get("/initial_prompt")
async def get_initial_prompt():
return {"prompt": INITIAL_PROMPT}
@fastapi_app.get("/main_prompt")
async def get_main_prompt():
return {"prompt": MAIN_PROMPT}
# ✅ Chatbot Function
def gpt_call(history, user_message,
model="gpt-4o-mini",
max_tokens=512,
temperature=0.7,
top_p=0.95):
"""
OpenAI ChatCompletion API call
"""
messages = [{"role": "system", "content": MAIN_PROMPT}]
for user_text, assistant_text in history:
if user_text:
messages.append({"role": "user", "content": user_text})
if assistant_text:
messages.append({"role": "assistant", "content": assistant_text})
messages.append({"role": "user", "content": user_message})
completion = client.chat.completions.create(
model=model,
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p
)
return completion.choices[0].message.content
# ✅ Gradio Chatbot UI
def respond(user_message, history):
if not user_message:
return "", history
assistant_reply = gpt_call(history, user_message)
history.append((user_message, assistant_reply))
return "", history
# ✅ Gradio UI
def launch_gradio():
with gr.Blocks() as gradio_app:
gr.Markdown("## Simple Chat Interface")
chatbot = gr.Chatbot(
value=[{"role": "assistant", "content": INITIAL_PROMPT}],
height=500,
type="messages"
)
state_history = gr.State([("", INITIAL_PROMPT)])
user_input = gr.Textbox(
placeholder="Type your message here...",
label="Your Input"
)
user_input.submit(
respond,
inputs=[user_input, state_history],
outputs=[user_input, chatbot]
).then(
fn=lambda _, h: h,
inputs=[user_input, chatbot],
outputs=[state_history]
)
gradio_app.launch(server_name="0.0.0.0", server_port=7860, show_error=True, enable_queue=True)
# ✅ Run FastAPI and Gradio Separately
if __name__ == "__main__":
threading.Thread(target=launch_gradio, daemon=True).start()
uvicorn.run(fastapi_app, host="0.0.0.0", port=8000)
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