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AI Agent that researches the lives of historical figures and extracts events into structured JSON timelines using LangGraph multi-agent orchestration.
| Date | Stars |
|---|---|
| 2026-07-31 | 250 |
| 2026-08-06 | 251 |
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# Event Deep Research
AI Agent that researchs the lifes of historical figures and extracts the events into a structured JSON timeline.
<img src="media/event-deep-research.webp" alt="Event Deep Research" width="600"/>
## Table of Contents
- [Event Deep Research](#event-deep-research)
- [Table of Contents](#table-of-contents)
- [Features](#features)
- [Demo / Example](#demo--example)
- [🚀 Installation](#-installation)
- [Prerequisites](#prerequisites)
- [Setup](#setup)
- [Usage](#usage)
- [Via LangGraph Studio (Recommended)](#via-langgraph-studio-recommended)
- [Configuration (configuration.py)](#configuration-configurationpy)
- [Architecture / Internals](#architecture--internals)
- [Roadmap / Future Work](#roadmap--future-work)
- [Contributing](#contributing)
- [License](#license)
- [Acknowledgments](#acknowledgments)
---
## Features
- Supervisor Agent with multiple tools (Research, think, Finish)
- Merge Workflow to incorporate and deduplicate events from multiple sources
- Support for OpenAI, Anthropic, Google, or Local models (Ollama)
## Demo / Example
https://github.com/user-attachments/assets/ebda1625-fdf6-4f3b-a5d2-319d6db40ec2
**Input:**
```json
{
"person_to_research": "Albert Einstein"
}
```
**Output:**
```json
{
"structured_events": [
{
"name": "Birth in Ulm",
"description": "Albert Einstein was born in Ulm, Germany to Hermann and Pauline Einstein",
"date": {"year": 1879, "note": "March 14"},
"location": "Ulm, German Empire",
"id": "time-1879-03-14T00:00:00Z"
},
{
"name": "Zurich Polytechnic",
"description": "Entered the Swiss Federal Polytechnic School in Zurich to study physics and mathematics",
"date": {"year": 1896, "note": ""},
"location": "Zurich, Switzerland",
"id": "time-1896-01-01T00:00:00Z"
},
{
"name": "Miracle Year Papers",
"description": "Published four groundbreaking papers on photoelectric effect, Brownian motion, special relativity, and mass-energy equivalence",
"date": {"year": 1905, "note": ""},
"location": "Bern, Switzerland",
"id": "time-1905-01-01T00:00:00Z"
},
{
"name": "Nobel Prize in Physics",
"description": "Awarded Nobel Prize for his discovery of the law of the photoelectric effect",
"date": {"year": 1921, "note": ""},
"location": "Stockholm, Sweden",
"id": "time-1921-01-01T00:00:00Z"
},
{
"name": "Death in Princeton",
"description": "Albert Einstein died at Princeton Hospital after refusing surgery for an abdominal aortic aneurysm",
"date": {"year": 1955, "note": "April 18"},
"location": "Princeton, New Jersey, USA",
"id": "time-1955-04-18T00:00:00Z"
}
]
}
```
## 🚀 Installation
### Prerequisites
- **Python 3.12+**
- **uv** (Python package manager)
### Setup
```bash
# 1. Clone the repository
git clone https://github.com/bernatsampera/event-deep-research.git
cd event-deep-research
# 2. Create virtual environment and install dependencies
uv venv && source .venv/bin/activate
uv sync
# 3. Set up environment variables
cp .env.example .env
# Edit .env with your API keys:
# FIRECRAWL_BASE_URL (https://api.firecrawl.com/v1)
# - FIRECRAWL_API_KEY (required for production, optional for local testing)
# - TAVILY_API_KEY (required)
# - OPENAI_API_KEY, ANTHROPIC_API_KEY, or GOOGLE_API_KEY (Change model in configuration.py)
# 4. Start the development server
uvx --refresh --from "langgraph-cli[inmem]" --with-editable . --python 3.12 langgraph dev --allow-blocking
# Open http://localhost:2024 to access LangGraph Studio
```
## Usage
### Via LangGraph Studio (Recommended)
1. Start the developExcerpt of 8,058 characters
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