Merge pull request #1052 from harshalmore31/qdrant-integration

[Fix] Docs

docs/swarms/RAG/qdrant_rag.md

@@ -383,30 +383,45 @@ print(result)
 
 ## Best Practices
 
-1. **Document Processing Strategy**:
+### Document Processing Strategy
-   - **Chunking**: Split large documents into 200-500 token chunks for optimal retrieval
+
-   - **Overlap**: Use 20-50 token overlap between chunks to maintain context
+| Practice | Recommendation | Details |
-   - **Preprocessing**: Clean and normalize text before indexing
+|----------|----------------|---------|
-
+| **Chunking** | 200-500 tokens | Split large documents into optimal chunks for retrieval |
-2. **Collection Organization**:
+| **Overlap** | 20-50 tokens | Maintain context between consecutive chunks |
-   - Use separate collections for different document types (technical docs, policies, etc.)
+| **Preprocessing** | Clean & normalize | Remove noise and standardize text format |
-   - Implement consistent naming conventions for collections
+
-   - Consider document lifecycle and update strategies
+### Collection Organization
-
+
-3. **Embedding Model Selection**:
+| Practice | Recommendation | Details |
-   - **Development**: Use `all-MiniLM-L6-v2` for fast iteration
+|----------|----------------|---------|
-   - **Production**: Use `text-embedding-3-small` or `text-embedding-3-large` for quality
+| **Separation** | Type-based collections | Use separate collections for docs, policies, code, etc. |
-   - **Specialized Domains**: Consider domain-specific embedding models
+| **Naming** | Consistent conventions | Follow clear, descriptive naming patterns |
-
+| **Lifecycle** | Update strategies | Plan for document versioning and updates |
-4. **Performance Optimization**:
+
-   - **Retrieval Count**: Start with 3-5 results, adjust based on performance testing
+### Embedding Model Selection
-   - **Batch Operations**: Use `batch_add()` for efficient bulk document ingestion
+
-   - **Metadata Strategy**: Store relevant metadata for enhanced filtering and context
+| Environment | Recommended Model | Use Case |
-
+|-------------|-------------------|----------|
-5. **Production Deployment**:
+| **Development** | `all-MiniLM-L6-v2` | Fast iteration and testing |
-   - Use Qdrant Cloud or self-hosted server for persistent storage
+| **Production** | `text-embedding-3-small/large` | High-quality production deployment |
-   - Implement proper error handling and retry mechanisms
+| **Specialized** | Domain-specific models | Industry or domain-focused applications |
-   - Monitor performance metrics and embedding quality
+
+### Performance Optimization
+
+| Setting | Recommendation | Rationale |
+|---------|----------------|-----------|
+| **Retrieval Count** | Start with 3-5 results | Balance relevance with performance |
+| **Batch Operations** | Use `batch_add()` | Efficient bulk document processing |
+| **Metadata** | Strategic storage | Enable filtering and enhanced context |
+
+### Production Deployment
+
+| Component | Best Practice | Implementation |
+|-----------|---------------|----------------|
+| **Storage** | Persistent server | Use Qdrant Cloud or self-hosted server |
+| **Error Handling** | Robust mechanisms | Implement retry logic and graceful failures |
+| **Monitoring** | Performance tracking | Monitor metrics and embedding quality |
 
 ## Performance Tips