ToolkitUpdated: 2024-02-01

RAG Pipeline Blueprint

A production-grade architecture for Retrieval-Augmented Generation systems.

Description

Don't start from scratch. This blueprint provides the exact architecture used in enterprise RAG systems. It covers advanced chunking strategies (semantic vs. fixed), vector database selection criteria, and a hybrid search ranking algorithm. Includes Python pseudocode for the critical ingestion pipeline.

Use Case

Perfect for: AI Engineers and Technical Architects building internal knowledge bases.

Included Files

Architecture_Diagrams.fig (Figma)
Ingestion_Pipeline_Pseudocode.py
Chunking_Strategy_Guide.pdf
Evaluation_Checklist.md

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€89EUR

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License: Commercial Team License

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### Component: Hybrid Search Ranker

```python
def weighted_rank(keyword_score, semantic_score, current_weight=0.7):
    # Implements Reciprocal Rank Fusion (RRF)
    # Priority given to semantic match unless exact keyword exists in title
    if keyword_score > 0.9:
        return (keyword_score * 0.8) + (semantic_score * 0.2)
    return (keyword_score * (1 - current_weight)) + (semantic_score * current_weight)
```
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