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97f4e58 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 | from dotenv import load_dotenv
from openai import OpenAI
import json
import os
import requests
from pypdf import PdfReader
import gradio as gr
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 unknown question: {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 context"},
},
"required": ["email"],
"additionalProperties": False
}
}
record_unknown_question_json = {
"name": "record_unknown_question",
"description": "Record any question that couldn't be answered",
"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 JoshuaChatBot:
def __init__(self):
self.openai = OpenAI()
self.name = "Joshua Sam Mathew"
# Read resume
reader = PdfReader("JoshuaCh/josh_resume.pdf")
self.josh_resume = "".join(page.extract_text() or "" for page in reader.pages)
# Read LinkedIn
reader = PdfReader("JoshuaCh/josh_linkedin.pdf")
self.josh_linkedin = "".join(page.extract_text() or "" for page in reader.pages)
# Read summary
with open("JoshuaCh/josh_summary.txt", "r", encoding="utf-8") as f:
self.josh_summary = f.read()
def system_prompt(self):
return f"""
You are acting as {self.name}. You are answering questions on {self.name}'s website,
particularly about his career, background, skills, and experience.
Be professional and engaging, as if speaking to a potential client or employer.
Use the summary, resume, and LinkedIn information to answer accurately.
If you don't know an answer, use the record_unknown_question tool. But if its a common question or basic question thats not related to my carear details u can answer it on your own keeping everything proffessional, even if it's about something trivial or unrelated to career.
If a user wants to connect, ask for their email and record it with record_user_details.
## Summary:
{self.josh_summary}
## Resume:
{self.josh_resume}
## LinkedIn:
{self.josh_linkedin}
"""
def handle_tool_call(self, tool_calls):
results = []
for tool_call in tool_calls:
fn = tool_call.function.name
args = json.loads(tool_call.function.arguments)
if fn == "record_user_details":
result = record_user_details(**args)
elif fn == "record_unknown_question":
result = record_unknown_question(**args)
else:
result = {"error": "Unknown tool"}
results.append({"role": "tool", "content": json.dumps(result)})
return results
def chat(self, message, history):
messages = [{"role": "system", "content": self.system_prompt()}] + history + [{"role": "user", "content": message}]
done = False
while not done:
response = self.openai.chat.completions.create(model="gpt-4o-mini", messages=messages, tools=tools)
msg = response.choices[0].message
if hasattr(msg, "tool_calls") and msg.tool_calls:
results = self.handle_tool_call(msg.tool_calls)
messages.append(msg)
messages.extend(results)
else:
done = True
return response.choices[0].message.content
if __name__ == "__main__":
josh = JoshuaChatBot()
gr.ChatInterface(josh.chat, type="messages").launch()
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