app.py

import os
import json
import requests
from pypdf import PdfReader
from openai import OpenAI
import gradio as gr

OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
BASE_URL = "https://integrate.api.nvidia.com/v1"
MODEL = "meta/llama3-8b-instruct"

PUSHOVER_TOKEN = os.environ.get("PUSHOVER_TOKEN")
PUSHOVER_USER = os.environ.get("PUSHOVER_USER")

client = OpenAI(api_key=OPENAI_API_KEY, base_url=BASE_URL)

def push(text):
    try:
        if not PUSHOVER_TOKEN or not PUSHOVER_USER:
            return
        requests.post(
            "https://api.pushover.net/1/messages.json",
            data={"token": PUSHOVER_TOKEN, "user": PUSHOVER_USER, "message": text},
            timeout=5
        )
    except:
        pass

def record_user_details(email, name="Name not provided", notes="not provided"):
    push(f"Lead → {name} | {email} | {notes}")
    return {"status": "ok"}

def record_unknown_question(question):
    push(f"Unknown → {question}")
    return {"status": "ok"}

globals()["record_user_details"] = record_user_details
globals()["record_unknown_question"] = record_unknown_question

tools = [
    {
        "type": "function",
        "function": {
            "name": "record_user_details",
            "description": "Record user's interest and email.",
            "parameters": {
                "type": "object",
                "properties": {
                    "email": {"type": "string"},
                    "name": {"type": "string"},
                    "notes": {"type": "string"}
                },
                "required": ["email"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "record_unknown_question",
            "description": "Record unknown question.",
            "parameters": {
                "type": "object",
                "properties": {"question": {"type": "string"}},
                "required": ["question"]
            }
        }
    }
]

class Me:
    def __init__(self):
        self.name = "Ayush Tyagi"
        self.summary = ""
        self.linkedin = ""

        # Load summary
        if os.path.exists("me/summary.txt"):
            self.summary = open("me/summary.txt", "r", encoding="utf-8").read()

        # Load LinkedIn PDF text
        pdf_path = "me/Ayush_linkdin.pdf"
        if os.path.exists(pdf_path):
            text = []
            reader = PdfReader(pdf_path)
            for page in reader.pages:
                t = page.extract_text()
                if t:
                    text.append(t)
            self.linkedin = "\n\n".join(text)

    def system_prompt(self):
        return f"""
You are acting as {self.name}.
Answer questions about his background, skills, and experience.

STRICT RULES:
- Never reveal personal address or sensitive location information.
- If unsure, call record_unknown_question.
- If user shows interest, ask for email and call record_user_details.

Summary:
{self.summary}

LinkedIn:
{self.linkedin}
"""

    def chat(self, message, history):
        messages = [{"role": "system", "content": self.system_prompt()}]

        for msg in history:
            messages.append(msg)

        messages.append({"role": "user", "content": message})

        while True:
            response = client.chat.completions.create(
                model=MODEL,
                messages=messages,
                tools=tools,
                tool_choice="auto",
                max_tokens=500
            )

            choice = response.choices[0]
            msg = choice.message
            finish = choice.finish_reason

            if finish == "tool_calls":
                for tool_call in msg.tool_calls:
                    func = tool_call.function
                    fname = func.name
                    args = json.loads(func.arguments)
                    result = globals()[fname](**args)
                    messages.append({
                        "role": "tool",
                        "content": json.dumps(result)
                    })
                continue

            return msg.content

me = Me()

def respond(user_message, history):
    bot_reply = me.chat(user_message, history)
    history.append({"role": "user", "content": user_message})
    history.append({"role": "assistant", "content": bot_reply})
    return "", history


# UI
with gr.Blocks(css="""
    body, .gradio-container { 
        background-color: #0d0d0d; 
        color: white;
    }

    .gr-button { 
        background-color: #ff4da6 !important;
        color: black !important; 
        font-weight: 600 !important; 
    }

    .gr-button:hover { 
        background-color: #ff1a8c !important; 
    }

    /* Chatbot background image */
    #chatbot {
        background: url('bg_desktop.jpg') no-repeat center;
        background-size: cover;
        border-radius: 12px;
        padding: 10px;
    }

    /* Mobile-friendly scaling */
    @media (max-width: 600px) {
        #chatbot {
            background-size: contain;
            background-position: top;
        }
    }
""") as ui:

    chatbot = gr.Chatbot(type="messages", height=420, elem_id="chatbot")

    with gr.Row():
        gr.Button("Who are you?").click(lambda: "Who are you?", None, "user_input")
        gr.Button("Contact Info").click(lambda: "What is Ayush Tyagi's contact information?", None, "user_input")
        gr.Button("Latest Projects").click(lambda: "Show Ayush Tyagi’s latest projects.", None, "user_input")

    with gr.Row():
        user_input = gr.Textbox(
            placeholder="Type your message...",
            scale=8
        )
        send_btn = gr.Button("Send", scale=1)

    user_input.submit(respond, [user_input, chatbot], [user_input, chatbot])
    send_btn.click(respond, [user_input, chatbot], [user_input, chatbot])


if __name__ == "__main__":
    ui.launch()