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AI Frontier Explorer - Track, read, and report on cutting-edge AI research using DeepSeek + LangChain

Project description

AI Frontier Explorer ๐Ÿง ๐Ÿ”

Track cutting-edge AI research, deep-read papers, and generate plain-language reports โ€” powered by DeepSeek + LangChain.

License: MIT Python Deep Agents SDK

โœจ Features

  • ๐Ÿ“ก Track โ€” Search arXiv for the latest papers on any AI topic
  • ๐Ÿ“– Deep Read โ€” Fetch full paper content via web scraping
  • ๐Ÿค– Parallel Sub-agents โ€” Delegate paper analysis to sub-agents for concurrent reading
  • ๐Ÿ“ Structured Reports โ€” Auto-generate reports with: summary, key points, plain-language explanation, glossary, impact score
  • ๐Ÿ’พ Persistent Memory โ€” Remembers your preferences across conversations
  • ๐ŸŽฏ Skills System โ€” Built-in AI research methodology

๐Ÿš€ Quick Start

Prerequisites

1. Install

git clone https://github.com/your-username/ai-frontier-explorer
cd ai-frontier-explorer
python -m venv .venv

# Windows
.venv\Scripts\activate

# macOS / Linux
source .venv/bin/activate

pip install -r requirements.txt

2. Configure

Create .env file:

DEEPSEEK_API_KEY=sk-your_deepseek_key
DEEPSEEK_BASE_URL=https://api.deepseek.com
DEEPSEEK_MODEL=deepseek-v4-flash

LANGCHAIN_TRACING_V2=true
LANGCHAIN_API_KEY=lsv2_pt_your_langsmith_key
LANGCHAIN_PROJECT=ai-frontier-explorer

3. Launch

# One-click (Windows)
start.bat

# Or manually
python ai_frontier.py

๐ŸŽฎ Usage

โ•”โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•—
โ•‘    AI Frontier Explorer  v1.0            โ•‘
โ•‘   ่ฟฝ่ธชๅ‰ๆฒฟ ยท ๆทฑๅบฆ็ ”่ฏป ยท ้€šไฟ—ๆŠฅๅ‘Š          โ•‘
โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•

You > /track AI Agent ๆœ€ๆ–ฐ่ฟ›ๅฑ•
You > /track ๅคšๆจกๆ€ๅคงๆจกๅž‹ 2026
You > /search transformer architecture
You > /reports
You > /read 2026-07-30-AI-Agent-ๅ‰ๆฒฟ่ฟ›ๅฑ•่ฟฝ่ธช.md
You > /remember ๆˆ‘ๅ…ณๆณจAIๅฎ‰ๅ…จๆ–นๅ‘

Commands

Command Description
/track <topic> Track frontier research on a topic
/search <query> Quick arXiv search
/reports List generated reports
/read <file> Read a saved report
/remember <info> Save a preference to memory
/tools List available tools
/help Show help
/exit Exit

๐Ÿง  Architecture

ai_frontier.py          # CLI entry point
deep_agent/
  โ”œโ”€โ”€ agent.py          # create_deep_agent() with DeepSeek model
  โ”œโ”€โ”€ config.py         # Settings management
  โ””โ”€โ”€ llm.py            # LLM initialization
tools/
  โ”œโ”€โ”€ arxiv_tools.py    # arXiv paper search
  โ”œโ”€โ”€ web_tools.py      # Web page content extraction
  โ”œโ”€โ”€ report_tools.py   # Save reports to disk
  โ”œโ”€โ”€ search.py         # DuckDuckGo web search
  โ””โ”€โ”€ calculator.py     # Safe calculator
skills/
  โ””โ”€โ”€ ai-research/      # Research methodology skill
memories/               # Persistent memory files
reports/                # Generated reports output

๐Ÿ”ง Tech Stack

  • Agent Framework: Deep Agents SDK (official)
  • Orchestration: LangGraph
  • LLM: DeepSeek via OpenAI-compatible API
  • Memory: LangGraph StoreBackend
  • CLI: Rich terminal UI

๐Ÿ“„ Report Format

Each generated report includes:

  • Name โ€” Paper title
  • Domain โ€” AI subfield (NLP/CV/RL/Agent/LLM...)
  • Summary โ€” What the paper does
  • Key Points โ€” 3-5 core insights
  • Plain Explanation โ€” Easy-to-understand analogy-based explanation
  • Glossary โ€” Technical term definitions
  • Impact Score โ€” 1-10 rating with breakdown

๐Ÿ“ฆ Install as a Package

pip install -e .
ai-frontier     # launch from anywhere

๐Ÿ“œ License

MIT

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