Document Ingestion Pipeline
by AaaS · open-source · Last verified 2026-03-01
Automated pipeline for ingesting documents from multiple sources (files, URLs, APIs) into a vector store. Handles format detection, text extraction, chunking, deduplication, metadata enrichment, and incremental updates for growing knowledge bases.
https://aaas.blog/script/document-ingestion-pipeline ↗C+
C+—Average
Adoption: BQuality: B+Freshness: ACitations: C+Engagement: F
Specifications
- License
- MIT
- Pricing
- open-source
- Capabilities
- format-detection, text-extraction, deduplication, metadata-enrichment, incremental-updates
- Integrations
- unstructured, langchain, pinecone-client, openai, tiktoken
- Use Cases
- knowledge-base-building, document-processing, data-pipeline, content-indexing
- API Available
- No
- Language
- python
- Dependencies
- unstructured, langchain, pinecone-client, openai, tiktoken, pypdf
- Environment
- Python 3.11+ with poppler-utils for PDF processing
- Est. Runtime
- 5-30 minutes depending on document volume
- Tags
- script, automation, ingestion, documents, preprocessing
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
57.3Adoption
68
Quality
78
Freshness
80
Citations
58
Engagement
0