cloudshell/career_conversation

1from dotenv import load_dotenv2from openai import OpenAI3import json4import os5import requests6from pypdf import PdfReader7import gradio as gr8 9 10load_dotenv(override=True)11 12def push(text):13    requests.post(14        "https://api.pushover.net/1/messages.json",15        data={16            "token": os.getenv("PUSHOVER_TOKEN"),17            "user": os.getenv("PUSHOVER_USER"),18            "message": text,19        }20    )21 22 23def record_user_details(email, name="Name not provided", notes="not provided"):24    push(f"Recording {name} with email {email} and notes {notes}")25    return {"recorded": "ok"}26 27def record_unknown_question(question):28    push(f"Recording {question}")29    return {"recorded": "ok"}30 31record_user_details_json = {32    "name": "record_user_details",33    "description": "Use this tool to record that a user is interested in being in touch and provided an email address",34    "parameters": {35        "type": "object",36        "properties": {37            "email": {38                "type": "string",39                "description": "The email address of this user"40            },41            "name": {42                "type": "string",43                "description": "The user's name, if they provided it"44            }45            ,46            "notes": {47                "type": "string",48                "description": "Any additional information about the conversation that's worth recording to give context"49            }50        },51        "required": ["email"],52        "additionalProperties": False53    }54}55 56record_unknown_question_json = {57    "name": "record_unknown_question",58    "description": "Always use this tool to record any question that couldn't be answered as you didn't know the answer",59    "parameters": {60        "type": "object",61        "properties": {62            "question": {63                "type": "string",64                "description": "The question that couldn't be answered"65            },66        },67        "required": ["question"],68        "additionalProperties": False69    }70}71 72tools = [{"type": "function", "function": record_user_details_json},73        {"type": "function", "function": record_unknown_question_json}]74 75 76class Me:77 78    def __init__(self):79        self.openai = OpenAI()80        self.name = "Ed Donner"81        reader = PdfReader("me/linkedin.pdf")82        self.linkedin = ""83        for page in reader.pages:84            text = page.extract_text()85            if text:86                self.linkedin += text87        with open("me/summary.txt", "r", encoding="utf-8") as f:88            self.summary = f.read()89 90 91    def handle_tool_call(self, tool_calls):92        results = []93        for tool_call in tool_calls:94            tool_name = tool_call.function.name95            arguments = json.loads(tool_call.function.arguments)96            print(f"Tool called: {tool_name}", flush=True)97            tool = globals().get(tool_name)98            result = tool(**arguments) if tool else {}99            results.append({"role": "tool","content": json.dumps(result),"tool_call_id": tool_call.id})100        return results101    102    def system_prompt(self):103        system_prompt = f"You are acting as {self.name}. You are answering questions on {self.name}'s website, \104particularly questions related to {self.name}'s career, background, skills and experience. \105Your responsibility is to represent {self.name} for interactions on the website as faithfully as possible. \106You are given a summary of {self.name}'s background and LinkedIn profile which you can use to answer questions. \107Be professional and engaging, as if talking to a potential client or future employer who came across the website. \108If 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. \109If 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. "110 111        system_prompt += f"\n\n## Summary:\n{self.summary}\n\n## LinkedIn Profile:\n{self.linkedin}\n\n"112        system_prompt += f"With this context, please chat with the user, always staying in character as {self.name}."113        return system_prompt114    115    def chat(self, message, history):116        messages = [{"role": "system", "content": self.system_prompt()}] + history + [{"role": "user", "content": message}]117        done = False118        while not done:119            response = self.openai.chat.completions.create(model="gpt-4o-mini", messages=messages, tools=tools)120            if response.choices[0].finish_reason=="tool_calls":121                message = response.choices[0].message122                tool_calls = message.tool_calls123                results = self.handle_tool_call(tool_calls)124                messages.append(message)125                messages.extend(results)126            else:127                done = True128        return response.choices[0].message.content129    130 131if __name__ == "__main__":132    me = Me()133    gr.ChatInterface(me.chat, type="messages").launch()134