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dctazewell/1_foundations

sourceHugging Faceupdated 3mo agoView on Hugging Face
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app.py134 linesDownload Raw Back to root
1from dotenv import load_dotenv
2from openai import OpenAI
3import json
4import os
5import requests
6from pypdf import PdfReader
7import gradio as gr
8
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": False
53    }
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": False
69    }
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 = "Darian Tazewell"
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 += text
87        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.name
95            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 results
101    
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_prompt
114    
115    def chat(self, message, history):
116        messages = [{"role": "system", "content": self.system_prompt()}] + history + [{"role": "user", "content": message}]
117        done = False
118        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].message
122                tool_calls = message.tool_calls
123                results = self.handle_tool_call(tool_calls)
124                messages.append(message)
125                messages.extend(results)
126            else:
127                done = True
128        return response.choices[0].message.content
129    
130
131if __name__ == "__main__":
132    me = Me()
133    gr.ChatInterface(me.chat, type="messages").launch()
134