# Task-02: Configure Nomic Matryoshka Embeddings

**Status:** 🟠 Implemented
**Priority:** High
**Created:** 2025-01-12
**Parent:** [Goal 02: Semantic Transcript Search](../scratchpad.md)

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## Objective

Configure and test NomicEmbeddings with Matryoshka dimensionality support, ensuring the embedding model works correctly in local inference mode.

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## Implementation Plan

1. [x] Test NomicEmbeddings initialization with default config
2. [x] Verify local inference mode works (Embed4All)
3. [x] Test embedding generation with sample text
4. [x] Verify Matryoshka dimensionality produces correct vector sizes
5. [x] Add unit tests for embeddings module
6. [x] Handle potential errors (model download, GPU availability)

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## Key Configuration

From `config.py`:
- `embedding_model`: "nomic-embed-text-v1.5"
- `embedding_dimensionality`: 512 (Matryoshka: 64, 128, 256, 512, 768)
- `embedding_inference_mode`: "local" (uses Embed4All)

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## Test Cases

1. **Basic embedding generation:**
   - Embed single query text
   - Embed multiple documents
   - Verify vector dimensions match config

2. **Matryoshka dimensionality:**
   - Test 512-dim (default)
   - Verify other dimensions work (256, 768)

3. **Error handling:**
   - Invalid model name
   - Network unavailable for model download

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## Acceptance Criteria

- [x] `get_embeddings()` returns working NomicEmbeddings instance
- [x] `embed_query()` produces vectors of correct dimensionality (512-dim verified)
- [x] `embed_documents()` works for batch embedding (3 docs tested)
- [x] Unit tests added with mocking for CI (16 tests in test_semantic_config.py)
- [x] Local inference mode verified (CPU fallback works, CUDA 11.0 warning expected)

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## Notes

- First run may download model (~250MB for nomic-embed-text-v1.5)
- Local mode uses Embed4All (gpt4all backend)
- No API key needed for local inference

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## References

- [langchain-nomic source](https://github.com/langchain-ai/langchain/tree/master/libs/partners/nomic)
- [Nomic Embed Text v1.5](https://huggingface.co/nomic-ai/nomic-embed-text-v1.5)

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## Completion Notes (2025-01-12)

### What Was Done

1. **Added `nomic[local]` dependency** for Embed4All local inference
2. **Tested embeddings successfully:**
   - Model downloads automatically (~274MB)
   - embed_query returns 512-dim vectors
   - embed_documents handles batch embedding (3 docs @ 40 inputs/sec)
   - CPU fallback works (CUDA 11.0 not available, but RTX 3080 Ti detected)

3. **Fixed config for env var loading:**
   - Added validator to convert string dimensionality to int
   - Validates Matryoshka dimensions: {64, 128, 256, 512, 768}

4. **Added comprehensive tests:**
   - `tests/test_semantic_config.py` with 16 unit tests + 4 slow integration tests
   - Registered `slow` pytest marker in pyproject.toml
   - Tests cover: config defaults, custom values, bounds validation, env vars, caching

5. **All tests pass:** 194 passed, linting clean

### GPU Note

System has RTX 3080 Ti with CUDA 13.0, but gpt4all/Embed4All expects CUDA 11.0.
CPU fallback is working fine (~40 embeddings/sec). GPU optimization deferred.

### Awaiting User Validation

Task is marked 🟠 Implemented. Awaiting user validation before marking 🟢 Complete.
