feat: solution for '8. Самописный поисковый агент на основе deep agents from scratch'

README.md

@@ -1,76 +1,87 @@
-# Deep Agent Search with Virtual File System
+# Deep Agents from Scratch – Search Agent
 
-This project demonstrates a simple deep agent search system that operates on **virtual files** stored entirely in memory. It uses **PyTorch**, **scikit-learn**, and **NumPy** to perform TF‑IDF vectorization and cosine similarity ranking.
+This project implements a simple web‑search agent using the **LangChain** framework, following the “Deep Agents from Scratch” template.  
+The agent can answer user questions by performing a DuckDuckGo search and reasoning over the results with an OpenAI LLM.
 
 ## Features
 
-- **Virtual File System**: Create, read, write, unload, and delete virtual files.
-- **Search Agent**: Rank lines from a virtual file based on a query using TF‑IDF and cosine similarity.
-- **Deep Learning Integration**: Uses PyTorch tensors for similarity calculations.
-- **Easy to Extend**: Replace the search logic with more sophisticated models (e.g., transformers) without changing the file system.
+- **Zero‑shot React** agent powered by LangChain.
+- Uses **DuckDuckGo** for web search (no API key required).
+- Powered by **OpenAI** (requires an API key).
+- Conversation memory to keep context across turns.
+- Simple command‑line interface.
+
+## Prerequisites
+
+- Python 3.10+
+- An OpenAI API key (set in `OPENAI_API_KEY` environment variable).
 
 ## Installation
 
 ```bash
 # Clone the repository
-git clone https://git.brojs.ru/kuzakhmetovartur/8.-samopisnyy-poiskovyy-agent-na-osnove-
-cd 8.-samopisnyy-poiskovyy-agent-na-osnove-
+git clone https://git.brojs.ru/kuzakhmetovartur/8.-samopisnyy-poiskovyy-agent-na-osnove.git
+cd 8.-samopisnyy-poiskovyy-agent-na-osnove
 
-# Create a virtual environment (optional but recommended)
-python -m venv venv
-source venv/bin/activate  # On Windows: venv\Scripts\activate
+# Create a virtual environment (recommended)
+python -m venv .venv
+source .venv/bin/activate   # On Windows use `.venv\Scripts\activate`
 
 # Install dependencies
 pip install -r requirements.txt
 ```
 
+## Configuration
+
+Create a `.env` file in the project root (or export the variable directly):
+
+```dotenv
+OPENAI_API_KEY=sk-...
+```
+
+> **Note**: The DuckDuckGo search tool does not require any API key.
+
 ## Usage
 
-Run the example script:
+Run the agent from the command line:
 
 ```bash
-python src/main.py
+python main.py "What is the capital of France?"
 ```
 
-You should see output similar to:
+You should see the agent perform a search and return an answer.
 
-```
-Search results for query: 'neural networks'
-1. Neural networks can approximate complex functions.
-2. Deep learning has revolutionized many fields.
-3. PyTorch provides dynamic computation graphs.
-After unload: Cannot read from unloaded file 'sample.txt'.
+## Example
+
+```bash
+$ python main.py "Who is the current CEO of Tesla?"
+=== Agent Response ===
+Elon Musk is the current CEO of Tesla. He has been in the role since 2008 and is also the founder of SpaceX and Neuralink.
 ```
 
 ## Project Structure
 
 ```
 ├── src
-│   ├── main.py                # Entry point and demo
-│   └── virtual_file_system.py # Virtual file system implementation
-├── requirements.txt           # Dependencies
-└── README.md                  # Documentation
+│   └── agent.py          # Agent implementation
+├── main.py               # CLI entry point
+├── requirements.txt      # Dependencies
+├── README.md             # Documentation
+└── .env                  # (Optional) Environment variables
 ```
 
-## Extending the Search Agent
+## Extending the Agent
 
-The `SearchAgent` class in `src/main.py` can be replaced with any model that accepts a query and returns ranked results. For example, you could:
+- **Add more tools**: Import additional tools from `langchain_community.tools` and add them to the `tools` list in `src/agent.py`.
+- **Change the LLM**: Replace `ChatOpenAI` with another LLM provider (e.g., Anthropic, Gemini) by adjusting the import and initialization.
+- **Adjust temperature**: Modify the `temperature` parameter in `ChatOpenAI` to control creativity.
 
-- Load a pre‑trained transformer (e.g., BERT) and compute embeddings.
-- Use a neural ranking model trained on relevance data.
-- Integrate with external search APIs.
+## Troubleshooting
 
-Just ensure that the agent receives a `VirtualFileSystem` instance and uses `VirtualFile.read()` to access data.
-
-## Testing
-
-Unit tests are not included in this minimal example, but you can add tests using `pytest` to verify:
-
-- Virtual file read/write/unload behavior.
-- Search agent ranking correctness.
-- Integration of the virtual file system with the agent.
+- **Missing OpenAI key**: Ensure `OPENAI_API_KEY` is set in your environment or `.env` file.
+- **Network errors**: Check your internet connection and retry.
+- **Agent hangs**: Increase the `timeout` in the DuckDuckGo tool or switch to a different search provider.
 
 ## License
 
-MIT License
-```
+MIT License.