haystack-pipeline

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Haystack 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

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