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### General RAG Platform Plan
#### Overview
The goal is to transform the existing RAG system into a versatile, modular platform for building various RAG applications.
#### Architecture
```mermaid
%%{init: {'theme': 'neutral', 'themeVariables': { 'primaryColor': '#e3f2fd', 'edgeLabelBackground':'#fffde7'}}}%%
graph TD
A[General RAG Platform Architecture]
subgraph DataIngestion
A1[Universal Data Loader\n<- Files\n<- Databases\n<- APIs\n<- Cloud Storage]
A2[Smart Document Processor\n<- Format detection\n<- Metadata extraction\n<- Content normalization]
A3[Chunking Strategies\n<- Semantic\n<- Structural\n<- Domain-specific]
end
subgraph CoreServices
B1[Embedding Service\n<- Multi-model support\n<- Batch processing\n<- Cache layer]
B2[VectorDB Orchestrator\n<- Chroma\n<- Pinecone\n<- Weaviate\n<- FAISS]
B3[LLM Gateway\n<- OpenAI\n<- Anthropic\n<- Mistral\n<- Custom models]
end
subgraph QueryEngine
C1[Query Analyzer\n<- Intent detection\n<- Query expansion\n<- Filter generation]
C2[Hybrid Retriever\n<- Vector search\n<- Keyword\n<- Hybrid ranking]
C3[Response Generator\n<- Citation\n<- Formatting\n<- Guardrails]
end
subgraph Management
D1[Config Manager\n<- Tenant isolation\n<- Model configs\n<- Access controls]
D2[Monitoring\n<- Metrics\n<- Logging\n<- Alerting]
D3[API Gateway\n<- REST\n<- GraphQL\n<- gRPC]
end
subgraph Extensibility
E1[Plugin System\n<- Custom loaders\n<- Chunkers\n<- Post-processors]
E2[Workflow Engine\n<- Pipeline designer\n<- Versioning\n<- A/B testing]
end
A --> DataIngestion
A --> CoreServices
A --> QueryEngine
A --> Management
A --> Extensibility
DataIngestion -->|Processed Chunks| CoreServices
CoreServices -->|Vector Index| QueryEngine
QueryEngine -->|Formatted Response| Management
Management -->|APIs| ExternalSystems
```
#### Implementation Plan
1. **Core Abstraction Layer**
- Unified interfaces for:
- Document Loaders (File, DB, API)
- Chunking Strategies
- Embedding Providers
- VectorDB Adapters
- LLM Gateways
2. **Multi-tenancy Features**
- Tenant isolation
- Resource quotas
- Custom pipeline configurations
- Role-based access control
3. **Advanced Retrieval**
- Hybrid search (vector + keyword + custom)
- Query understanding module
- Result reranking layer
- Cache mechanisms
4. **Operational Excellence**
- Observability stack
- Auto-scaling
- CI/CD pipelines
- Health checks
5. **Security**
- Data encryption
- Audit trails
- Content moderation
- PII detection
6. **Developer Ecosystem**
- SDKs (Python/JS)
- CLI tools
- Template repository
- Testing framework
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