https://github.com/deepset-ai/haystack-rag-agent
https://github.com/deepset-ai/haystack-rag-agent
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/deepset-ai/haystack-rag-agent
- Owner: deepset-ai
- Created: 2024-12-20T10:28:41.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-20T10:41:15.000Z (about 1 year ago)
- Last Synced: 2024-12-20T11:28:53.005Z (about 1 year ago)
- Language: Python
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: Readme.md
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## Prerequisites
Before you begin, ensure you have the following:
- Docker
- Python 3.x
- OpenAI API key
## Setup Instructions
### 1. Add Your OpenAI API Key
A `.env` file already exists in the root directory of the project with the following content:
```plaintext
OPENAI_API_KEY=
```
Replace `` with your actual OpenAI API key. This key will be used by the application to interact with the OpenAI API.
### 2. Start the Docker Containers
To start the application, run the following command from the root directory:
```bash
docker compose up
```
This will start all the required Docker containers for the project.
### 3. Configure the Agent in OpenWebUI
The Agent does not support streaming out of the box, but OpenWebUI has Streaming set as a default. To configure the agent accordingly:
1. Open the OpenWebUI interface in your browser at http://localhost:2000/.
2. Follow the steps demonstrated in the video below to correctly configure the Agent, so that it Streaming is turned off and it therefore properly works in OpenWebUI:
## Customizing the Agent's Tools
The `tools.py` file allows you to customize the tools the agent has access to. You can add new tools simply by creating a Python function with the appropriate annotations.
### Example:
```python
def get_weather(
city: Annotated[str, "The city for which to get the weather"] = "Munich",
unit: Annotated[Literal["Celsius", "Fahrenheit"], "The unit for the temperature"] = "Celsius"
):
"""
A simple function to get the current weather for a location.
"""
return f"22.0 {unit}"
```
Adding a new tool like this enables the agent to perform additional tasks. You can refer to the other example methods already included in `tools.py` for further guidance.
## Haystack Pipeline
The core logic of the Haystack pipeline, powering the agent, is implemented in `agent.py`. Below is a visualization of the pipeline:
