pull/1051/head
harshalmore31 6 days ago
parent 5ee7c1e95d
commit 3e17704a12

@ -19,13 +19,13 @@ pip install qdrant-client fastembed swarms-memory litellm
## Tutorial Steps ## Tutorial Steps
1. First, install the latest version of Swarms: 1. **Install Swarms**: First, install the latest version of Swarms:
```bash ```bash
pip3 install -U swarms pip3 install -U swarms
``` ```
2. Set up your environment variables in a `.env` file: 2. **Environment Setup**: Set up your environment variables in a `.env` file:
```plaintext ```plaintext
OPENAI_API_KEY="your-api-key-here" OPENAI_API_KEY="your-api-key-here"
@ -34,16 +34,16 @@ pip install qdrant-client fastembed swarms-memory litellm
WORKSPACE_DIR="agent_workspace" WORKSPACE_DIR="agent_workspace"
``` ```
3. Choose your Qdrant deployment option: 3. **Choose Deployment**: Select your Qdrant deployment option:
- **In-memory**: For testing and development (data is not persisted) - **In-memory**: For testing and development (data is not persisted)
- **Local server**: For production deployments with persistent storage - **Local server**: For production deployments with persistent storage
- **Qdrant Cloud**: Managed cloud service (recommended for production) - **Qdrant Cloud**: Managed cloud service (recommended for production)
4. Configure the vector database wrapper with your preferred embedding model and collection settings 4. **Configure Database**: Set up the vector database wrapper with your preferred embedding model and collection settings
5. Add documents using individual or batch processing methods 5. **Add Documents**: Load documents using individual or batch processing methods
6. Create your agent with RAG capabilities and start querying 6. **Create Agent**: Initialize your agent with RAG capabilities and start querying
## Code ## Code

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