haystack-pipeline
SolidHaystack NLP pipeline configuration for document processing and QA
Data & Documents 814 stars
53 forks Updated today MIT
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Skill Content
# Haystack Pipeline Skill
## Capabilities
- Configure Haystack pipeline components
- Set up document stores and retrievers
- Implement reader/generator models
- Design custom pipeline graphs
- Configure preprocessing pipelines
- Implement evaluation pipelines
## Target Processes
- rag-pipeline-implementation
- intent-classification-system
## Implementation Details
### Core Components
1. **DocumentStores**: Elasticsearch, Weaviate, FAISS, etc.
2. **Retrievers**: BM25, Dense, Hybrid
3. **Readers/Generators**: Extractive and generative QA
4. **Preprocessors**: Document cleaning and splitting
### Pipeline Types
- Retrieval pipelines
- RAG pipelines
- Evaluation pipelines
- Indexing pipelines
### Configuration Options
- Component selection
- Pipeline graph design
- Document store backend
- Model selection
- Preprocessing settings
### Best Practices
- Modular pipeline design
- Proper preprocessing
- Evaluation integration
- Component versioning
### Dependencies
- haystack-ai
- farm-haystack (legacy)
Details
- Author
- a5c-ai
- Repository
- a5c-ai/babysitter
- Created
- 4 months ago
- Last Updated
- today
- Language
- JavaScript
- License
- MIT
Integrates with
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