40 lines
1.1 KiB
Markdown
40 lines
1.1 KiB
Markdown
# DeepAgent from Scratch
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## Overview
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This repository contains a minimal implementation of a **DeepAgent** inspired by the *Deep Agents from Scratch* course. The agent can:
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1. Search the web using DuckDuckGo.
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2. Create virtual files in an in‑memory file system.
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3. Persist those virtual files to the real file system when the task is finished.
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The implementation uses:
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- **LangChain OpenAI** (`ChatOpenAI`) for LLM interactions.
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- **DuckDuckGo Search** for web queries.
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- A simple `VirtualFileSystem` class to hold files in memory.
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## Requirements
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```
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langchain-openai>=0.3.0
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langchain>=1.2.10
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langgraph>=0.2.0
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duckduckgo-search
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```
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## Running the Agent
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```bash
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# Install dependencies
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pip install -r requirements.txt
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# Run the agent
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python main.py
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```
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The script will perform a sample search for *"LangChain deep agent"* and create a file named `summary.txt` with the first search result. All virtual files are written to the current directory.
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## Extending the Agent
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- Add more tools by decorating functions with `@tool` and passing them to `DeepAgent`.
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- Modify the `run` method to change the interaction loop or add more sophisticated prompting.
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## License
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MIT
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