# Deep Search Agent – LangChain Implementation

This repository contains a minimal implementation of a **search agent** built with LangChain, following the “Deep Agents from Scratch” template.  
The agent can answer arbitrary questions by performing a web search and reasoning over the results.

## Features

- Uses **OpenAI GPT‑4o‑mini** as the language model.
- Performs web searches via **SerpAPI** (Google/SerpAPI).
- Maintains conversation context with a memory buffer.
- Implements the **Zero‑Shot React** agent pattern.
- Simple command‑line interface for interactive use.

## Prerequisites

- Python 3.10+
- An OpenAI API key.
- A SerpAPI key (free tier available).

## Setup

```bash
# Clone the repository
git clone https://git.brojs.ru/kuzakhmetovartur/8.-samopisnyy-poiskovyy-agent-na-osnove-<repo>.git
cd <repo>

# Create a virtual environment (optional but recommended)
python -m venv .venv
source .venv/bin/activate   # On Windows: .venv\\Scripts\\activate

# Install dependencies
pip install -r requirements.txt
```

Create a `.env` file in the project root with your credentials:

```
OPENAI_API_KEY=sk-...
SERPAPI_KEY=your-serpapi-key
```

## Usage

Run the agent interactively:

```bash
python -m src.agent
```

You will be prompted to enter a question. The agent will search the web and return a concise answer.

## Example

```
Enter your question: What is the capital of France?
Processing...

=== Answer ===
The capital of France is Paris.
```

## Testing

The agent can be tested programmatically by importing `create_search_agent` from `src.agent` and calling `agent.run("your question")`.

## License

MIT License