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)