AGENTS.md@docs/other/vec2text git:20260906.82c8031A

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# Vec2Text Documentation Agent

> **📋 Document Metadata**  
> **Type**: Embedding Inversion Integration Agent | **Audience**: Researchers, NLP Engineers | **Complexity**: Advanced  
> **Cross-References**: [README.md](README.md) | [Vec2Text GNN Guide](vec2text_gnn.md) | [LLM Integration](../../gnn/advanced/gnn_llm_neurosymbolic_active_inference.md) | [Main Documentation](../README.md)

## Overview

This directory contains comprehensive documentation, resources, and implementation guides for integrating **Vec2Text** (Embedding Inversion System) with GNN (Generalized Notation Notation). Vec2Text provides advanced text embeddings inversion capabilities, reconstructing original text from dense vector representations, with implications for privacy and interpretability in Active Inference modeling.

**Status**: ✅ Production Ready  
**Version**: 1.0

## Purpose

Vec2Text integration enables:

- **Model Interpretability**: Reconstruct text representations from model embeddings
- **Privacy Analysis**: Analyze privacy implications of embedding-based models
- **Information-Theoretic Insights**: Explore information-theoretic principles in Active Inference
- **Text Representation**: Enhanced text representation capabilities
- **Embedding Inversion**: Two-stage correction architecture for precise inversion

## Contents

**Files**:        2 | **Subdirectories**:        1

## Quick Navigation

- **README.md**: [Directory overview](README.md)
- **GNN Documentation**: [gnn/AGENTS.md](../../gnn/AGENTS.md)
- **Main Documentation**: [doc/README.md](../README.md)
- **Pipeline Reference**: [src/gnn/AGENTS.md](../../../src/gnn/AGENTS.md)

## Documentation Structure

This module is organized as follows:

- **Overview**: High-level description and purpose
- **Contents**: Files and subdirectories
- **Integration**: Connection to the broader pipeline
- **Usage**: How to work with this subsystem

## Integration with Pipeline

This documentation is integrated with the 25-step GNN processing pipeline:

### Core Processing (Steps 0-9)
- **Step 3 (GNN)**: Vec2Text analysis of text representations in GNN files
- **Step 6 (Validation)**: Embedding inversion for model interpretation

### Simulation (Steps 10-16)
- **Step 13 (LLM)**: Vec2Text integration with LLM analysis
- **Step 16 (Analysis)**: Text reconstruction and analysis

### Integration (Steps 17-24)
- **Step 20 (Website)**: Privacy and interpretability analysis
- **Step 23 (Report)**: Embedding inversion results in reports

See [src/gnn/AGENTS.md](../../../src/gnn/AGENTS.md) for complete pipeline documentation.

## Function Signatures and API

### Embedding Inversion Functions

```python
def invert_embedding(embedding: np.ndarray, model: Vec2TextModel) -> str:
    """
    Reconstruct text from embedding using Vec2Text.

    Parameters:
        embedding: Dense vector embedding
        model: Vec2Text model for inversion

    Returns:
        Reconstructed text string
    """


def analyze_privacy_implications(embeddings: List[np.ndarray]) -> PrivacyAnalysis:
    """
    Analyze privacy implications of embedding-based models.

    Parameters:
        embeddings: List of embeddings to analyze

    Returns:
        PrivacyAnalysis with information-theoretic insights
    """
```

## Standards and Guidelines

All documentation in this module adheres to professional standards:

- **Clarity**: Concrete, technical writing
- **Functionality**: Describes actual capabilities
- **Completeness**: Comprehensive coverage
- **Consistency**: Uniform structure and style

## Related Resources

### Main GNN Documentation
- **[GNN Overview](../../gnn/gnn_overview.md)**: Core GNN concepts
- **[GNN Quickstart](../../gnn/tutorials/quickstart_tutorial.md)**: Getting started guide
- **[LLM Integration](../../gnn/advanced/gnn_llm_neurosymbolic_active_inference.md)**: LLM-enhanced analysis

### Embedding Resources
- **[LLM Integration](../../gnn/advanced/gnn_llm_neurosymbolic_active_inference.md)**: LLM-enhanced analysis
- **[Embedding Systems](../../CROSS_REFERENCE_INDEX.md#embedding-systems)**: Text embedding approaches
- **[Privacy and Interpretability](../../CROSS_REFERENCE_INDEX.md#privacy-and-interpretability)**: Privacy considerations

### Pipeline Architecture
- **[Pipeline Documentation](../../gnn/operations/gnn_tools.md)**: Complete pipeline guide
- **[Pipeline AGENTS](../../../src/gnn/AGENTS.md)**: Implementation details
- **[Pipeline README](../../../src/gnn/README.md)**: Pipeline overview

## See Also

- **[Vec2Text Cross-Reference](../../CROSS_REFERENCE_INDEX.md#vec2text)**: Cross-reference index entry
- **[LLM Integration](../../gnn/advanced/gnn_llm_neurosymbolic_active_inference.md)**: LLM-enhanced analysis
- **[Embedding Systems](../../CROSS_REFERENCE_INDEX.md#embedding-systems)**: Text embedding approaches
- **[Main Index](../README.md)**: Return to main documentation

---

**Status**: ✅ Production Ready  
**Compliance**: Professional documentation standards  
**Maintenance**: Regular updates with new Vec2Text features and integration capabilities