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# CodeRecall Heres a polished `README.md` for your project **CodeRecall**:
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# 🧠 CodeRecall
> Context-aware local AI assistant for developers using Ollama, ChromaDB, and VS Codes Continue extension.
CodeRecall ingests your entire codebase — including Git history and diffs — into a local vector database (ChromaDB), enabling RAG-augmented queries via Ollama models right inside VS Code.
No cloud APIs. No latency. Full control.
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## 🚀 Features
- 🔍 **Semantic code search** across multiple languages
- 📜 **Git commit + diff embedding** for code evolution awareness
- 🤖 **RAG integration** with local Ollama models (e.g. LLaMA 3)
- 💻 **VS Code Continue extension support**
- ⚙️ Configurable with a simple `config.ini`
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## 🧩 Project Structure
```
CodeRecall/
├── chroma_ingest.py # Ingest codebase + Git into ChromaDB
├── chroma_context_provider.py # VS Code Continue context provider
├── config.ini # Ollama + Chroma settings
├── chroma-db/ # ChromaDB persistence directory
└── config.json # Continue extension config
```
---
## 🔧 Setup
### 1. Install dependencies
```bash
pip install chromadb requests
```
Make sure you have:
- 🦙 [Ollama](https://ollama.com/) installed and running
- ✅ [Continue Extension](https://marketplace.visualstudio.com/items?itemName=Continue.continue) for VS Code
- 🐙 Git repo initialized (optional but recommended)
### 2. Configure `config.ini`
```ini
[ollama]
url = http://localhost:11434
[chroma]
persist_directory = ./chroma-db
```
---
## 📥 Ingest your project
```bash
python chroma_ingest.py
```
This loads:
- Source code in common languages
- Markdown and text docs
- Git commit messages and full diffs
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## 🧠 Add as a VS Code Context Provider
### `config.json` for Continue
```json
{
"models": [
{
"title": "LLaMA 3 (Ollama)",
"provider": "ollama",
"model": "llama3",
"apiBase": "http://localhost:11434"
}
],
"contextProviders": [
{
"title": "ChromaDB Search",
"provider": "custom",
"path": "./chroma_context_provider.py"
}
]
}
```
---
## ✨ Usage
1. Launch VS Code.
2. Open the Continue sidebar.
3. Set `"ChromaDB Search"` as your context provider.
4. Ask your model questions about your codebase, architecture, or commits.
Example prompt:
> _“How does the Git ingestion pipeline work?”_
---
## 📌 Notes
- Default embedding model is `nomic-embed-text` (via Ollama).
- Change `n_results` in `chroma_context_provider.py` for broader/narrower context.
- Works offline, no API keys required.
---
## 🧪 Roadmap Ideas
- [ ] Add OpenAPI spec ingestion
- [ ] Enable full-text search fallback
- [ ] Support for multi-repo ingestion
- [ ] Optional chunking for large diffs or files
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## 🛡 License
MIT — free for personal + commercial use.
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Want me to auto-generate a logo, badge set, or GitHub Actions to auto-ingest on commit?