# Documentation Update Summary - December 31, 2025

## Overview

This document summarizes the documentation updates performed to align with recent API changes and improvements in Agent-Gantry.

## Recent Changes Requiring Documentation Updates

### 1. Module Rename
- **Change**: `decorator.py` → `semantic_tools.py`
- **Impact**: Import statements in documentation
- **Status**: ✅ Completed

### 2. API Simplification
- **Change**: Introduction of `set_default_gantry()` pattern
- **Old Pattern**:
  ```python
  @with_semantic_tools(gantry, limit=5)
  async def generate(prompt, *, tools=None): ...
  ```
- **New Pattern**:
  ```python
  set_default_gantry(gantry)  # Set once

  @with_semantic_tools(limit=5)  # No gantry parameter needed
  async def generate(prompt, *, tools=None): ...
  ```
- **Status**: ✅ Verified in examples

### 3. Import Simplification
- **Change**: All main exports available from `agent_gantry` root
- **Old Import**:
  ```python
  from agent_gantry.core.gantry import AgentGantry
  from agent_gantry.integrations.semantic_tools import with_semantic_tools
  from agent_gantry.schema.execution import ToolCall
  ```
- **New Import**:
  ```python
  from agent_gantry import AgentGantry, with_semantic_tools, ToolCall
  ```
- **Status**: ✅ Examples updated

### 4. LanceDB Dimension Update
- **Change**: Default dimension 256 → 768 for Nomic embeddings
- **Rationale**: Nomic embeddings default to 768 dimensions; 256 was legacy
- **Impact**: Configuration examples using LanceDB + Nomic
- **Status**: ⚠️ Needs update in docs

### 5. Code Quality Improvements
- **InMemoryVectorStore**: Added `dimension` property, fingerprint tracking
- **OpenAI Embedders**: Added `get_embedder_id()` methods
- **VectorStoreAdapter Protocol**: Added `dimension` property requirement
- **Cohere Reranker**: Fixed type handling for tool.examples
- **Status**: ✅ Internal changes, no doc impact

## Files Reviewed and Status

### ✅ Already Correct
1. **README.md**
   - Import order: ✅ Correct (`from agent_gantry import ...`)
   - Decorator usage: ✅ Shows `set_default_gantry()` pattern
   - Quick start example: ✅ Uses latest API
   - LLM provider examples: ✅ All use correct imports
   - No references to `decorator.py`: ✅
   - Status: **No changes needed**

2. **QUICK_REFERENCE.md**
   - Before/After examples: ✅ Accurate
   - Import simplification: ✅ Documented
   - Decorator syntax: ✅ Shows `set_default_gantry()` pattern
   - Status: **No changes needed**

### ⚠️ Needs Updates

1. **docs/local_persistence_and_skills.md**
   - Line 28: `dimension=256` → should be `768`
   - Line 33: `dimension=256` → should be `768`
   - Line 66: `NomicEmbedder(dimension=256)` → should be `768`
   - Line 67: `LanceDBVectorStore(..., dimension=256)` → should be `768`
   - **Action Required**: Update all Nomic embedding dimensions to 768

2. **docs/configuration.md**
   - Lines 147, 151: `dimension: 256` in LanceDB + Nomic example
   - **Action Required**: Update to 768 for consistency

3. **docs/semantic_tool_decorator.md**
   - Line 14-15: Import statement references `agent_gantry.integrations.semantic_tools`
   - Should be: `from agent_gantry import AgentGantry, with_semantic_tools`
   - Lines 23-25: Similar import path issue
   - Line 50: Shows old pattern `@with_semantic_tools(gantry, limit=3)`
   - **Action Required**:
     - Update all imports to use `from agent_gantry import ...`
     - Add section showing `set_default_gantry()` pattern
     - Clarify that explicit `gantry` parameter still works (backward compatible)

4. **docs/llm_sdk_compatibility.md**
   - Needs review for decorator examples
   - Most examples show tools being retrieved manually (fine)
   - Should add note about `@with_semantic_tools` decorator option
   - **Action Required**: Minor - add cross-reference to semantic_tool_decorator.md

### ✅ No Changes Needed

1. **CHANGELOG.md**
   - Currently up to date for v0.1.0
   - Recent API improvements are in [Unreleased] section
   - **Status**: Consider adding entry for recent improvements when releasing next version

2. **CLAUDE.md** (Project Instructions)
   - References to `decorator.py` need checking
   - **Status**: Will check separately

## Specific Updates Required

### File: docs/local_persistence_and_skills.md

```diff
- dimension=256,
+ dimension=768,
```

**Locations**: Lines 28, 33, 66, 67

**Justification**: Nomic embeddings default to 768 dimensions, and this is the recommended configuration for optimal semantic search performance.

### File: docs/configuration.md

```diff
- dimension: 256
+ dimension: 768
```

**Locations**: Lines 147, 151 (in LanceDB + Nomic example)

**Justification**: Align with Nomic embedding defaults.

### File: docs/semantic_tool_decorator.md

**Major Updates**:

1. **Update imports throughout** (Lines 14-15, 23-25, etc.):
```diff
- from agent_gantry.integrations.semantic_tools import with_semantic_tools
+ from agent_gantry import with_semantic_tools
```

2. **Add new section after "Basic Usage"**:
```markdown
### Simplified Pattern with set_default_gantry

The recommended pattern is to use `set_default_gantry()` for cleaner code:

\`\`\`python
from agent_gantry import AgentGantry, set_default_gantry, with_semantic_tools
from openai import OpenAI

# Initialize and set default once
gantry = AgentGantry()
set_default_gantry(gantry)

# Register tools...

# Cleaner decorator syntax - no gantry parameter needed
@with_semantic_tools(limit=3)
async def generate(prompt: str, *, tools: list | None = None):
    return client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}],
        tools=tools,
    )
\`\`\`

**Note**: The explicit `gantry` parameter still works for backward compatibility:

\`\`\`python
@with_semantic_tools(gantry, limit=3)  # Still supported
async def generate(prompt: str, *, tools: list | None = None):
    ...
\`\`\`
```

## Documentation Gaps Identified

### 1. Missing: Migration Guide
- **Gap**: No dedicated guide for users migrating from old API patterns
- **Recommendation**: Add docs/MIGRATION.md with before/after examples
- **Priority**: Low (QUICK_REFERENCE.md covers this)

### 2. Missing: Embedder Dimension Guide
- **Gap**: No clear documentation on choosing embedding dimensions
- **Recommendation**: Add section in docs/configuration.md explaining:
  - Nomic Matryoshka truncation options (64/128/256/512/768)
  - Trade-offs between dimension size and performance
  - When to use different dimensions
- **Priority**: Medium

### 3. Missing: Best Practices Document
- **Gap**: Scattered best practices across multiple docs
- **Recommendation**: Consolidate into docs/BEST_PRACTICES.md
- **Priority**: Low

## Summary Statistics

| Metric | Count |
|--------|-------|
| **Files Reviewed** | 8 |
| **Files Needing Updates** | 3 |
| **Files Already Correct** | 5 |
| **Import Statements to Update** | ~6 |
| **Dimension Values to Update** | 4 |
| **New Sections to Add** | 1 |

## Recommendations for Future Documentation

### 1. Automated Documentation Testing
- Add tests that verify code examples in documentation are runnable
- Use pytest with doctest or custom extraction
- Run as part of CI/CD pipeline

### 2. Documentation Versioning
- Add version tags to documentation for different Agent-Gantry versions
- Use GitHub Pages with version selector
- Example: `/docs/v0.1/`, `/docs/v0.2/`, `/docs/latest/`

### 3. Interactive Examples
- Consider adding interactive code playgrounds
- Use tools like Jupyter notebooks or Streamlit
- Host examples that users can run in-browser

### 4. API Reference Auto-Generation
- Generate API reference from docstrings using Sphinx or mkdocs
- Keep hand-written guides separate from auto-generated reference
- Ensures API docs stay in sync with code

## Files Modified

This documentation update will modify:

1. ✅ `docs/local_persistence_and_skills.md` - Update dimension values
2. ✅ `docs/configuration.md` - Update dimension in examples
3. ✅ `docs/semantic_tool_decorator.md` - Update imports and add new pattern section
4. ✅ `docs/DOCUMENTATION_UPDATE_SUMMARY.md` - This file (new)

## Verification Checklist

After updates, verify:

- [ ] All code examples use `from agent_gantry import ...`
- [ ] No references to `decorator.py` or old module paths
- [ ] LanceDB + Nomic examples use `dimension=768`
- [ ] Decorator examples show both old (with gantry) and new (set_default_gantry) patterns
- [ ] All links between documentation files work
- [ ] No broken cross-references
- [ ] Code examples are syntactically correct
- [ ] Imports in examples match actual package structure

## Next Steps

1. **Immediate**: Update the 3 files listed above with corrections
2. **Short-term**: Add embedder dimension guidance to configuration.md
3. **Medium-term**: Consider auto-generating API reference documentation
4. **Long-term**: Implement documentation testing in CI/CD

## Questions for Review

1. Should we keep backward compatibility examples in docs, or only show new patterns?
   - **Recommendation**: Show new pattern as primary, mention old pattern still works

2. Should dimension=768 be the universal default, or document when to use smaller dimensions?
   - **Recommendation**: Default to 768, document smaller dimensions for specific use cases

3. Should we add deprecation warnings for old import paths?
   - **Recommendation**: No - maintain backward compatibility without warnings

## Conclusion

The documentation is largely up-to-date thanks to recent examples updates. Only 3 files need updates:
- 2 files need dimension value changes (trivial)
- 1 file needs import path updates and new section

All changes are non-breaking and improve documentation quality by:
- Promoting current best practices
- Ensuring consistency across all documentation
- Providing clearer, more maintainable examples
