> ## Documentation Index
> Fetch the complete documentation index at: https://docs.negentro.tech/llms.txt
> Use this file to discover all available pages before exploring further.

# Multimodal Memory Support

> Store, index, and retrieve memories across images, documents, audio transcripts, and structured tables.

## Supported Modalities

> **Images & Diagrams**
>
> Ingest system diagrams, error screenshots, and UI mockups. Extracted into structured visual descriptions and CLIP vector representations.

> **PDFs & Documents**
>
> Extract tabular data and contextual paragraphs while preserving source page coordinates for grounded citations.

> **Audio & Voice**
>
> Ingest multi-speaker audio transcripts with speaker diarization tags and temporal boundaries.

> **Structured Data**
>
> Seamlessly index JSON payloads, database rows, and spreadsheets alongside conversational context.

## Ingesting Image Memories

```python multimodal_example.py theme={null}
# Store an image with automatic vision fact extraction
m.add(
    "Architecture diagram showing Kubernetes cluster with 3 worker nodes and Istio service mesh.",
    user_id="usr_9918",
    metadata={
        "type": "image",
        "image_url": "https://storage.internal/diagrams/k8s_mesh.png"
    }
)

# Natural language query retrieves image memory
results = m.search("How many worker nodes are in our Kubernetes cluster?", user_id="usr_9918")
```


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