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Ultimate Multimodality

Gemini Embedding 2 is valuable because it does not force your knowledge into a text-only pipeline. This server is designed around that property.

What "Multimodal" Means Here

The server can currently index:

  • Text: .txt, .md, .csv, .docx
  • PDFs: page-by-page visual embeddings with extracted page text
  • Images: .jpg, .jpeg, .png, .webp
  • Audio: .mp3, .wav, .aiff, .aac
  • Video: .mp4

All of these end up in one local semantic memory layer.

Native Media Retrieval

For images, audio, and video, the server sends raw bytes to Gemini Embedding 2 through types.Part.from_bytes(...).

That means the system is not limited to OCR, filenames, or transcripts. A query can retrieve a file because of what the media contains, not only because of text extracted from it.

This is especially useful when your workspace includes:

  • design screenshots
  • exported charts
  • recordings
  • short clips
  • mixed-format project archives

Visual PDF Retrieval

PDFs are handled differently from standard text files.

Instead of flattening the whole document into plain text only, the server:

  1. renders each page as an image
  2. embeds that page visually
  3. stores extracted text as the readable result payload
  4. stores the exact page_number for context retrieval

This gives you two benefits at once:

  • the retrieval quality of a visual page representation
  • the usability of readable page text in the result

Why Page-Aware Metadata Matters

Multimodal retrieval is only genuinely useful if the result can be traced back to a precise local location.

That is why the server now stores metadata such as:

  • modality
  • type
  • page_number
  • extension
  • directory_root
  • filename

This enables:

  • modality filters
  • page-aware citations
  • scoped search
  • context lookups after retrieval

Current Strengths

The strongest parts of the multimodal design today are:

  • one memory layer across multiple modalities
  • visual PDF page indexing
  • direct media embeddings
  • exact file and page reporting

Current Limits

The current implementation still indexes audio and video at the file level, not at fine-grained scene or transcript segment level.

That means:

  • you can retrieve the right file semantically
  • but the system may not yet isolate the exact timestamp inside a long recording

This is a good foundation, but segment-level media enrichment is a later upgrade, not a current claim.