Document Parser by Contextual AI
Rank a list of documents according to their relevance to a query primarily and your custom instructions secondarily. We evaluated the model on instructions for recency, document type, source, and metadata, and it can generalize to other instructions as well. The reranker supports multilinguality. Th
Document Parser by Contextual AI launched on May 14, 2025 with 118 votes, #387 of 7,905 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
A document parser designed for RAG use cases, which achieves superior accuracy and reliability by excelling in the following areas: 1. Document-level understanding 2. Minimized hallucinations 3. Superior handling of complex modalities
Parse a file into a structured Markdown and/or JSON. Files must be less than 300MB and 2000 pages. We use LibreOffice to convert DOC(X) and PPT(X) files to PDF, which may affect page count. See our blog post and code examples. Email [email protected] with any feedback or questions.
Use this file to discover all available pages before exploring further. curl --request POST \ --url https://api.contextual.ai/v1/parse \ --header 'Authorization: Bearer <token>' \ --header 'Content-Type: multipart/form-data' \ --form raw_file='@example-file' \ --form parse_mode=standard \ --form enable_document_hierarchy= true \ --form enable_split_tables= false import requests url = "https://api.contextual.ai/v1/parse" files = { "raw_file": ("example-file", open("example-file", "rb")) } payload = { "parse_mode": "standard", "enable_document_hierarchy": "true", "enable_split_tables": "false" } headers = {"Authorization": "Bearer <token>"} response = requests.post(url, data=payload,…from docs.contextual.ai
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