mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
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5a4b18d9b1
Major improvements to smart-search, chain-search cascade, ranking pipeline, reranker factory, CLI history store, codex-lens integration, and uv-manager. Simplify command-generator skill by inlining phases. Add comprehensive tests. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
110 lines
2.7 KiB
Markdown
110 lines
2.7 KiB
Markdown
# CodexLens
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CodexLens is a multi-modal code analysis platform designed to provide comprehensive code understanding and analysis capabilities.
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## Features
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- **Multi-language Support**: Analyze code in Python, JavaScript, TypeScript and more using Tree-sitter parsers
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- **Semantic Search**: Find relevant code snippets using semantic understanding with fastembed and HNSWLIB
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- **Code Parsing**: Advanced code structure parsing with tree-sitter
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- **Flexible Architecture**: Modular design for easy extension and customization
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## Installation
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### Basic Installation
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```bash
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pip install codex-lens
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```
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### With Semantic Search
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```bash
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pip install codex-lens[semantic]
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```
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### With GPU Acceleration (NVIDIA CUDA)
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```bash
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pip install codex-lens[semantic-gpu]
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```
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### With DirectML (Windows - NVIDIA/AMD/Intel)
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```bash
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pip install codex-lens[semantic-directml]
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```
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### With All Optional Features
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```bash
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pip install codex-lens[full]
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```
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### Local ONNX Reranker Bootstrap
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Use the pinned bootstrap flow when you want the local-only reranker backend in an
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existing CodexLens virtual environment without asking pip to resolve the whole
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project extras set at once.
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1. Start from the CodexLens repo root and create or activate the project venv.
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2. Review the pinned install manifest in `scripts/requirements-reranker-local.txt`.
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3. Render the deterministic setup plan:
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```bash
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python scripts/bootstrap_reranker_local.py --dry-run
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```
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The bootstrap script always targets the selected venv Python, installs the local
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ONNX reranker stack in a fixed order, and keeps the package set pinned to the
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validated Python 3.13-compatible combination:
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- `numpy==2.4.0`
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- `onnxruntime==1.23.2`
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- `huggingface-hub==0.36.2`
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- `transformers==4.53.3`
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- `optimum[onnxruntime]==2.1.0`
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When you are ready to apply it to the CodexLens venv, use:
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```bash
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python scripts/bootstrap_reranker_local.py --apply
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```
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To pre-download the default local reranker model (`Xenova/ms-marco-MiniLM-L-6-v2`)
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into the repo-local Hugging Face cache, use:
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```bash
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python scripts/bootstrap_reranker_local.py --apply --download-model
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```
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The dry-run plan also prints the equivalent explicit model download command. On
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Windows PowerShell with the default repo venv, it looks like:
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```bash
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.venv/Scripts/hf.exe download Xenova/ms-marco-MiniLM-L-6-v2 --local-dir .cache/huggingface/models/Xenova--ms-marco-MiniLM-L-6-v2
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```
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After installation, probe the backend from the same venv:
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```bash
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python scripts/bootstrap_reranker_local.py --apply --probe
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```
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## Requirements
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- Python >= 3.10
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- See `pyproject.toml` for detailed dependency list
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## Development
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This project uses setuptools for building and packaging.
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## License
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MIT License
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## Authors
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CodexLens Contributors
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