68 lines
1.6 KiB
Markdown
68 lines
1.6 KiB
Markdown
# Deep Search Agent – LangChain Implementation
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This repository contains a minimal implementation of a **search agent** built with LangChain, following the “Deep Agents from Scratch” template.
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The agent can answer arbitrary questions by performing a web search and reasoning over the results.
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## Features
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- Uses **OpenAI GPT‑4o‑mini** as the language model.
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- Performs web searches via **SerpAPI** (Google/SerpAPI).
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- Maintains conversation context with a memory buffer.
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- Implements the **Zero‑Shot React** agent pattern.
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- Simple command‑line interface for interactive use.
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## Prerequisites
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- Python 3.10+
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- An OpenAI API key.
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- A SerpAPI key (free tier available).
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## Setup
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```bash
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# Clone the repository
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git clone https://git.brojs.ru/kuzakhmetovartur/8.-samopisnyy-poiskovyy-agent-na-osnove-<repo>.git
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cd <repo>
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# Create a virtual environment (optional but recommended)
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python -m venv .venv
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source .venv/bin/activate # On Windows: .venv\\Scripts\\activate
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# Install dependencies
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pip install -r requirements.txt
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```
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Create a `.env` file in the project root with your credentials:
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```
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OPENAI_API_KEY=sk-...
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SERPAPI_KEY=your-serpapi-key
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```
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## Usage
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Run the agent interactively:
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```bash
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python -m src.agent
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```
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You will be prompted to enter a question. The agent will search the web and return a concise answer.
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## Example
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```
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Enter your question: What is the capital of France?
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Processing...
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=== Answer ===
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The capital of France is Paris.
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```
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## Testing
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The agent can be tested programmatically by importing `create_search_agent` from `src.agent` and calling `agent.run("your question")`.
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## License
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MIT License |