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Babysitter haystack-pipeline

Haystack NLP pipeline configuration for document processing and QA

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/ai-agents-conversational/skills/haystack-pipeline" ~/.claude/skills/a5c-ai-babysitter-haystack-pipeline && rm -rf "$T"
manifest: library/specializations/ai-agents-conversational/skills/haystack-pipeline/SKILL.md
tags
#nlp-pipeline#document-processing#qa-implementation#retrieval-system#pipeline-design
source 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)