import os from dotenv import load_dotenv from openai import OpenAI import gradio as gr from pydantic import BaseModel import requests import json # Load environment variables load_dotenv(override=True) def push(text): requests.post( "https://api.pushover.net/1/messages.json", data={ "token": os.getenv("PUSHOVER_TOKEN"), "user": os.getenv("PUSHOVER_USER"), "message": text, } ) def record_user_details(email, name="Name not provided", notes="not provided"): push(f"Recording {name} with email {email} and notes {notes}") return {"recorded": "ok"} def record_unknown_question(question): push(f"Recording {question}") return {"recorded": "ok"} record_user_details_json = { "name": "record_user_details", "description": "Use this tool to record that a user is interested in being in touch and provided an email address", "parameters": { "type": "object", "properties": { "email": { "type": "string", "description": "The email address of this user" }, "name": { "type": "string", "description": "The user's name, if they provided it" } , "notes": { "type": "string", "description": "Any additional information about the conversation that's worth recording to give context" } }, "required": ["email"], "additionalProperties": False } } record_unknown_question_json = { "name": "record_unknown_question", "description": "Always use this tool to record any question that couldn't be answered as you didn't know the answer", "parameters": { "type": "object", "properties": { "question": { "type": "string", "description": "The question that couldn't be answered" }, }, "required": ["question"], "additionalProperties": False } } tools = [{"type": "function", "function": record_user_details_json}, {"type": "function", "function": record_unknown_question_json}] class Me: def __init__(self): self.openai = OpenAI() self.name = "Talha Umar" # Handle the case where the resume file might not exist try: with open("me/Resume.txt", "r", encoding="utf-8") as f: self.summary = f.read() except FileNotFoundError: self.summary = "Professional with experience in software development and technology." def handle_tool_call(self, tool_calls): results = [] for tool_call in tool_calls: tool_name = tool_call.function.name arguments = json.loads(tool_call.function.arguments) print(f"Tool called: {tool_name}", flush=True) tool = globals().get(tool_name) result = tool(**arguments) if tool else {} results.append({"role": "tool","content": json.dumps(result),"tool_call_id": tool_call.id}) return results def system_prompt(self): system_prompt = f"You are acting as {self.name}. You are answering questions on {self.name}'s website, \ particularly questions related to {self.name}'s career, background, skills and experience. \ Your responsibility is to represent {self.name} for interactions on the website as faithfully as possible. \ You are given a summary of {self.name}'s background and experience which you can use to answer questions. \ Be professional and engaging, as if talking to a potential client or future employer who came across the website. \ If you don't know the answer to any question, use your record_unknown_question tool to record the question that you couldn't answer, even if it's about something trivial or unrelated to career. \ If the user is engaging in discussion, try to steer them towards getting in touch via email; ask for their email and record it using your record_user_details tool. " system_prompt += f"\n\n## Summary:\n{self.summary}" system_prompt += f"With this context, please chat with the user, always staying in character as {self.name}." return system_prompt def convert_gradio_history_to_openai_messages(self, history): """Convert Gradio history format to OpenAI messages format""" messages = [] for exchange in history: # Gradio history comes as [user_message, assistant_message] pairs if isinstance(exchange, list) and len(exchange) == 2: user_msg, assistant_msg = exchange if user_msg: messages.append({"role": "user", "content": user_msg}) if assistant_msg: messages.append({"role": "assistant", "content": assistant_msg}) elif isinstance(exchange, dict): # If it's already in the right format messages.append(exchange) return messages def chat(self, message, history): # Convert Gradio history to OpenAI format openai_history = self.convert_gradio_history_to_openai_messages(history) # Build the complete message list messages = [{"role": "system", "content": self.system_prompt()}] + openai_history + [{"role": "user", "content": message}] done = False while not done: try: response = self.openai.chat.completions.create( model="gpt-4o-mini", messages=messages, tools=tools ) if response.choices[0].finish_reason == "tool_calls": message_obj = response.choices[0].message tool_calls = message_obj.tool_calls results = self.handle_tool_call(tool_calls) # Add the assistant message with tool calls messages.append({ "role": "assistant", "content": message_obj.content, "tool_calls": [ { "id": tc.id, "type": tc.type, "function": { "name": tc.function.name, "arguments": tc.function.arguments } } for tc in tool_calls ] }) # Add tool results messages.extend(results) else: done = True return response.choices[0].message.content except Exception as e: print(f"Error in chat: {e}") return f"I'm sorry, I encountered an error while processing your message. Please try again." return "Something went wrong. Please try again." if __name__ == "__main__": me = Me() # Create a custom theme that matches the portfolio design custom_theme = gr.themes.Soft( primary_hue="pink", secondary_hue="blue", neutral_hue="gray", font=[gr.themes.GoogleFont("Inter"), "system-ui", "sans-serif"] ).set( body_background_fill="#ffffff", block_background_fill="#f7f7f8", block_border_width="0px", button_primary_background_fill="#ff69b4", button_primary_background_fill_dark="#ff1493", button_primary_text_color="white", block_radius="12px", block_title_text_weight="600", block_label_text_size="14px", block_label_margin="0.5rem" ) # Create the chat interface with custom styling chat_interface = gr.ChatInterface( fn=me.chat, title=f"Chat with {me.name}", description="Ask me anything about my experience, skills, or background!", theme=custom_theme, examples=[ "What's your background in web development?", "Tell me about your experience with UI/UX design", "What are your key skills?" ] ) # Remove share=True since it's not supported on Hugging Face Spaces chat_interface.launch()