Personal AI Assistant – AMA Chatbot

Why this project?

A portfolio chatbot that acts as you — answering questions about your career, background and skills as if you were there. It also captures leads (email + notes) when visitors want to get in touch, and can generate a polished HTML résumé on demand.

---

What makes it technically interesting?

Multi-model agentic pipeline

The résumé generation is handled by a three-stage agent loop where each stage is powered by a different LLM provider:

Stage	Model	Role
Extractor	OpenAI (gpt-5-mini)	Parses your LinkedIn PDF into structured JSON
Planner	Anthropic Claude (claude-sonnet-4-6)	Writes a design brief for the résumé
Developer	Google Gemini (gemini-3.1-flash-lite-preview)	Renders the full single-file HTML résumé

Each agent uses tool calling (create / complete todos) to plan its work before executing, making the reasoning process visible in the UI.

Streaming UI

The Gradio interface streams intermediate steps in real time — you see the agent logs updating as each tool is called, rather than waiting for a final response.

Provider-agnostic agent runner

A single run_agent_stream() dispatcher routes to OpenAI, Anthropic, or Gemini based on the model name, with each backend translating the shared OpenAI-style tool schema into the provider's native format.

---

How to use it

1. Prerequisites

uv pip install -r requirements.txt

2. Environment variables

Create a .env file at the project root (or export the variables):

OPENAI_API_KEY=...
ANTHROPIC_API_KEY=...
GOOGLE_API_KEY=...

# Optional – Pushover notifications for leads
PUSHOVER_TOKEN=...
PUSHOVER_USER=...

3. Personal data

Place your files in a me/ folder next to app.py:

me/
  linkedin.pdf   ← export from LinkedIn
  me.txt         ← a short free-text bio / summary

4. Run

uv run app.py

Then open the Gradio URL printed in the terminal (default: http://localhost:7861).

5. Chat commands

What you say	What happens
Anything about career / skills	Bot answers using your LinkedIn + bio
Provide your email	Email & context are recorded via Pushover
"Show me your resume"	Triggers the 3-stage agent pipeline; HTML résumé appears below the chat