FEATURE_UPDATES.md•3.68 kB
# Feature Updates: Exa-Based NLP Implementation
## Overview
This document summarizes the changes made to implement Exa-based Natural Language Processing (NLP) capabilities, removing the Hugging Face dependency and consolidating on Exa for external API requirements.
## Changes Made
### 1. Dependencies
- Removed `@huggingface/inference` package from dependencies
- Removed related type definitions
- Consolidated on existing Exa integration
### 2. Configuration
- Updated `config.ts` to remove Hugging Face API key references
- Added NLP-specific configuration options
- Added feature flags for advanced NLP capabilities
- Updated `.env.example` with new environment variables
### 3. Implementation
- Reimplemented `advanced_ner.ts` to use Exa for entity recognition
- Maintained fallback mechanisms for offline or API failure scenarios
- Implemented context-aware entity recognition using Exa search
- Preserved the same interfaces for backward compatibility
### 4. Testing
- Created new test suite for Exa-based NER
- Added mock implementations for testing
- Included tests for fallback scenarios
### 5. Documentation
- Added comprehensive documentation on advanced NLP capabilities
- Created a demo script to showcase the new features
- Updated API key validation to be more informative
- Added environment variable documentation
## Benefits
1. **API Consolidation**
- Single API dependency (Exa) instead of multiple external services
- Simplified API key management
- Reduced maintenance overhead
2. **Enhanced Integration**
- Leverages existing robust Exa integration
- Takes advantage of rate limiting, caching, and error handling
- Provides better contextual understanding through search
3. **Improved Reliability**
- Multiple fallback levels for graceful degradation
- Works even when API is unavailable
- Maintains compatibility with existing code
## New Features
The implementation adds several capabilities:
1. **Context-Aware NER**
- Uses search context to improve entity recognition
- Better accuracy for domain-specific entities
- Handles ambiguous entities more effectively
2. **Enhanced Entity Types**
- Supports a wider range of entity types
- Includes more detailed classification
3. **Comprehensive NLP Pipeline**
- Named Entity Recognition
- Coreference Resolution
- Relationship Extraction
- Fact Extraction
## Configuration Options
| Variable | Description | Default |
|----------|-------------|---------|
| `ENABLE_ADVANCED_NLP` | Enable advanced NLP features | `true` |
| `NLP_USE_EXA` | Use Exa for named entity recognition | `true` |
| `NLP_EXA_NUM_RESULTS` | Number of search results to use | `3` |
| `NLP_EXA_USE_WEB` | Use web results for entity recognition | `true` |
| `NLP_EXA_USE_NEWS` | Use news results for entity recognition | `false` |
| `NLP_COREFERENCE_ENABLED` | Enable coreference resolution | `true` |
| `NLP_RELATIONSHIP_ENABLED` | Enable relationship extraction | `true` |
## Required API Keys
Only `EXA_API_KEY` is required for all advanced NLP and research capabilities.
## Running the Demo
To see the new NLP capabilities in action:
```bash
npm run build
node examples/advanced_nlp_demo.js
```
## Next Steps
1. **Performance Optimization**
- Fine-tune caching strategies for NLP operations
- Optimize entity recognition for speed
2. **Feature Enhancement**
- Add more entity types and relationship categories
- Improve confidence scoring mechanisms
- Enhance integration with other analytical tools
3. **Testing and Validation**
- Add more comprehensive tests across various text types
- Benchmark against standard NLP datasets