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docling

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更新时间2026年1月15日 19:24

Expert guidance on document processing with Docling and audio transcription with Whisper.

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来源

FullFran

FullFran/Hybrid-RAG-example

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在 Manus 中运行

Docling & Ingestion Expert Skill

This skill provides patterns for processing diverse document formats and audio files.

📝 Document Processing

Multi-format support: Use docling for converting PDF, DOCX, PPTX, XLSX, HTML, and Markdown to a clean Markdown representation.
HybridChunker: Always use Docling's HybridChunker to preserve document structure (headings, lists, tables).
Token Awareness: Configure chunker with max_tokens=512 to align with embedding models (e.g., text-embedding-3-small).

🔊 Audio Transcription

Whisper ASR: Use docling's integration with Whisper Turbo for transcribing audio files (.mp3, .wav, .m4a, .flac).
Path Handling: Pass pathlib.Path objects to DocumentConverter for audio files.

🏗️ Pipeline Architecture

Ingestion Pipeline: Centralize logic in src/ingestion/ingest.py.
Metadata Extraction: Extract YAML frontmatter and standard document properties.
Batching: Use batch embedding generation and insert_many for chunks to optimize performance.

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name	docling
description	Expert guidance on document processing with Docling and audio transcription with Whisper.

Docling & Ingestion Expert Skill

This skill provides patterns for processing diverse document formats and audio files.

📝 Document Processing

Multi-format support: Use docling for converting PDF, DOCX, PPTX, XLSX, HTML, and Markdown to a clean Markdown representation.
HybridChunker: Always use Docling's HybridChunker to preserve document structure (headings, lists, tables).
Token Awareness: Configure chunker with max_tokens=512 to align with embedding models (e.g., text-embedding-3-small).

🔊 Audio Transcription

Whisper ASR: Use docling's integration with Whisper Turbo for transcribing audio files (.mp3, .wav, .m4a, .flac).
Path Handling: Pass pathlib.Path objects to DocumentConverter for audio files.

🏗️ Pipeline Architecture

Ingestion Pipeline: Centralize logic in src/ingestion/ingest.py.
Metadata Extraction: Extract YAML frontmatter and standard document properties.
Batching: Use batch embedding generation and insert_many for chunks to optimize performance.