{"library":"unstructured-ingest","type":"library","category":null,"description":"Unstructured Ingest is a Python library that provides local ETL data pipelines to prepare diverse unstructured data (e.g., PDFs, HTML, Word docs) for RAG (Retrieval Augmented Generation) and other AI/LLM applications. It supports various source and destination connectors, enabling batch processing, partitioning, chunking, and embedding of documents. The current version is 1.4.24, and it sees frequent updates with ongoing development and new connector integrations.","language":"python","status":"active","version":"1.4.24","tags":["ETL","RAG","LLM","data-pipeline","unstructured-data","document-processing","connectors"],"install":[{"cmd":"pip install unstructured-ingest","imports":["from unstructured_ingest.pipeline.pipeline import Pipeline","from unstructured_ingest.interfaces import ProcessorConfig","from unstructured_ingest.connector.fsspec.local import LocalIndexerConfig"]},{"cmd":"pip install \"unstructured-ingest[pdf,s3]\"","imports":[]}],"homepage":"https://unstructured.io","github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/unstructured-ingest/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":55,"avg_install_s":22,"avg_import_s":1.87,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/unstructured-ingest/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}