Metadata-Version: 2.3
Name: trag-cli
Version: 2.1.3
Summary: Automatic Claude context builder for any coding project
License: MIT
Keywords: claude,ai,context,rag,coding
Author: Hiren
Author-email: trag-cli@example.com
Project-URL: Homepage, https://github.com/trag-cli/trag-cli
Project-URL: Bug Tracker, https://github.com/trag-cli/trag-cli/issues
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: chromadb>=0.4.0
Requires-Dist: pyperclip>=1.8.0

# T-RAG

Automatic Claude context builder for any coding project.

One command → scans your entire project → auto-detects what changed → builds a context summary → paste into Claude.ai → Claude instantly knows your full project state.

**No Git needed. No weekly plan needed. No manual writing. Works for everyone.**

## Install

```bash
pip install trag-cli
```

That's it. No other setup needed.

## Use

Go into any project folder and run:

```bash
trag
```

First time:
- Saves a baseline snapshot of all your files
- Builds full project context

Every time after:
- Automatically shows what changed since last run
- Builds updated context ready to paste into Claude

## Options

```bash
trag                          # scan current folder
trag --project /my/project    # scan a specific folder
trag --plan todo.txt          # use a specific plan/todo file
trag --no-embed               # faster mode (skip ChromaDB)
trag --init                   # create optional notes file
trag --version                # show version
```

## How change tracking works

T-RAG saves a snapshot of your file hashes inside `trag_data/trag_snapshot.json` in your project folder. Next run it compares and finds exactly what changed — no Git needed, fully local.

Each project has its own snapshot because `trag_data/` is created inside each project folder.

## Optional: weekly plan / todo

If you have a `todo.txt`, `weekly_plan.txt`, or `tasks.txt` in your project, T-RAG reads it automatically and includes your plan status in the context.

## Optional: smarter AI reasoning (Ollama)

T-RAG works well without Ollama. For smarter AI-powered project summaries:

```bash
# Install Ollama from https://ollama.com then:
ollama pull qwen2.5-coder:7b
```

T-RAG auto-detects Ollama — nothing else to configure.
