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Simplify install paths around app setup

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“BeeRad”
2026-05-02 14:15:53 +10:00
parent 0481435ca6
commit 3c46991a2e
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@@ -9,7 +9,7 @@
╚═╝ ╚═╝╚═╝ ╚═╝ ╚═╝ ╚═╝ ╚═╝ ╚═╝╚═╝ ╚═╝ ╚═╝ ╚═╝
``` ```
**TL;DR:** Use the MCP quick install if you want Claude Code, Cursor, Codex, or another agent to read and write your local graph. Clone this repository only if you also want the local browser UI. If you clone the repo, choose **OpenAI** or **local Qwen** before setup creates the vector tables. **TL;DR:** Clone this repository, choose where the models run, then start the local app. Your SQLite database stays on your device in every setup. Choose **OpenAI** if you want the easiest model setup. Choose **local Qwen** through Ollama or llama.cpp if you want the utility model and embedding model running on your own machine.
[![Watch the setup walkthrough](https://img.youtube.com/vi/YyUCGigZIZE/hqdefault.jpg)](https://youtu.be/YyUCGigZIZE?si=USYgvmwtdGpgGdwu) [![Watch the setup walkthrough](https://img.youtube.com/vi/YyUCGigZIZE/hqdefault.jpg)](https://youtu.be/YyUCGigZIZE?si=USYgvmwtdGpgGdwu)
@@ -48,68 +48,34 @@ Current contract:
## Install ## Install
### Which install should I use? ### Choose One Model Path
Every path uses a local SQLite database. The choice is only about where the two AI models run:
| You want... | Use this path | | You want... | Use this path |
|-------------|---------------| |-------------|---------------|
| Your AI coding agent can read/write your RA-H graph | **Option A: MCP-only quick install** | | The simplest setup and strongest default model quality | **Local DB + OpenAI models** |
| A browser UI at `localhost:3000` with OpenAI models | **Option B1: Full local app with OpenAI** | | No model calls leaving your computer | **Local DB + local Qwen models** |
| A browser UI at `localhost:3000` with local Qwen models through Ollama | **Option B2: Full local app with local Qwen/Ollama** | | A clean test that does not touch your normal graph | **Demo-safe isolated install** |
| A browser UI at `localhost:3000` with local Qwen models through llama.cpp | **Option B3: Full local app with local Qwen/llama.cpp** |
| A clean demo that does not touch your real graph | **Demo-safe isolated install** |
### Option A: MCP-only quick install What "OpenAI models" means:
- Your database is local.
- Your notes, graph, chunks, and vectors are stored in SQLite on your device.
- RA-H sends utility-model requests and embedding requests to the OpenAI API after you add an API key.
- The utility model helps with descriptions and summaries. The embedding model powers semantic search.
- Choose this if you want the easiest setup and do not want to manage local model runtimes.
If you mainly want Claude Code, Cursor, Codex, or another coding agent to use RA-H, start here. What "local Qwen models" means:
- Your database is local.
- The utility model runs locally.
- The embedding model runs locally.
- Those model requests go to Ollama or llama.cpp on your device, not to OpenAI or another hosted model API.
- The utility model helps with descriptions and summaries. The embedding model powers semantic search.
- Choose this if you care most about local control, privacy, offline operation, or avoiding API usage. It requires more setup and enough local hardware.
For Claude Code: ### Option 1: Local DB + OpenAI Models
```bash Use this if you want RA-H running quickly and are comfortable using OpenAI for descriptions, embeddings, and semantic search.
npx -y ra-h-mcp-server@latest setup --client claude-code --yes
```
Then fully restart Claude Code. On Mac, use **Cmd+Q**, then reopen it.
Verify:
```bash
npx -y ra-h-mcp-server@latest doctor
```
Then ask your agent:
```text
Do you have RA-H tools available?
```
You should see tools like `queryNodes`, `retrieveQueryContext`, `createNode`, and `readSkill`.
Other clients:
```bash
npx -y ra-h-mcp-server@latest setup --client cursor --yes
npx -y ra-h-mcp-server@latest setup --client codex --yes
```
Multiple clients can be installed in one pass. This is the best path if you use both Claude Code and Codex:
```bash
npx -y ra-h-mcp-server@latest setup --client claude-code,codex --yes
```
Notes:
- `--yes` lets the installer write supported client config automatically.
- Codex uses TOML config, so the installer writes `CODEX_HOME/config.toml` or `~/.codex/config.toml`.
- The MCP-only path does not clone this repo and does not start the browser UI.
- The installer defaults to the latest published MCP package. For release/debug reproducibility, pin an exact version intentionally.
```bash
npx -y ra-h-mcp-server@latest setup --client claude-code --yes --pin current
```
### Option B1: Full local app with OpenAI
Use this if you want the browser UI at `localhost:3000` and want RA-H to use OpenAI for descriptions, embeddings, and semantic search.
```bash ```bash
git clone https://github.com/bradwmorris/ra-h_os.git git clone https://github.com/bradwmorris/ra-h_os.git
@@ -121,9 +87,9 @@ npm run dev
Open [localhost:3000](http://localhost:3000). Add your OpenAI API key when the app prompts you, or later in Settings -> API Keys. Open [localhost:3000](http://localhost:3000). Add your OpenAI API key when the app prompts you, or later in Settings -> API Keys.
### Option B2: Full local app with local Qwen/Ollama ### Option 2A: Local DB + Local Qwen/Ollama
Use this if you want the browser UI at `localhost:3000` and want RA-H to call local OpenAI-compatible Ollama endpoints instead of OpenAI. Use this if you want the easiest local-model setup. Ollama runs the local utility and embedding models.
Prerequisites: Prerequisites:
- Ollama is installed and running. - Ollama is installed and running.
@@ -141,9 +107,9 @@ npm run dev
Open [localhost:3000](http://localhost:3000). Settings -> API Keys will show the active local model profile and disable OpenAI key entry. Open [localhost:3000](http://localhost:3000). Settings -> API Keys will show the active local model profile and disable OpenAI key entry.
### Option B3: Full local app with local Qwen/llama.cpp ### Option 2B: Local DB + Local Qwen/llama.cpp
Use this if you want local model calls but prefer managing GGUF files and llama.cpp server processes yourself. Use this if you want local model calls and prefer managing GGUF files and llama.cpp server processes yourself.
Prerequisites: Prerequisites:
- llama.cpp is installed. - llama.cpp is installed.
@@ -169,7 +135,26 @@ npm run dev
Open [localhost:3000](http://localhost:3000). Settings -> API Keys will show the active local model profile and disable OpenAI key entry. Open [localhost:3000](http://localhost:3000). Settings -> API Keys will show the active local model profile and disable OpenAI key entry.
If you also want your coding agent connected to the same default database, run Option A after the app setup. If you override `SQLITE_DB_PATH`, pass the same path to the MCP installer with `--db`. ### Connect MCP After App Setup
MCP lets Claude Code, Codex, Cursor, and other coding agents read and write your RA-H graph. Configure it after the app database exists.
If you used the default database path:
```bash
npx -y ra-h-mcp-server@latest setup --client claude-code,codex --yes
```
If you used a custom `SQLITE_DB_PATH`, pass that exact same path with `--db`:
```bash
npx -y ra-h-mcp-server@latest setup \
--client claude-code,codex \
--yes \
--db "/absolute/path/to/rah.sqlite"
```
Fully restart the agent client after changing MCP config. For Claude Code on Mac, use **Cmd+Q**, then reopen it.
Full install details: Full install details:
- [docs/README.md](./docs/README.md) - [docs/README.md](./docs/README.md)
docs/README.md
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## Start Here ## Start Here
If you just want RA-H OS working: If you just want RA-H OS working:
1. Use the MCP quick install below if you mainly want agent access. 1. Use the OpenAI local app quick start if you want the simplest setup.
2. Use the OpenAI local app quick start if you want the browser UI with OpenAI models. 2. Use the local Qwen/Ollama quick start if you want local models with the least runtime work.
3. Use the local Qwen/Ollama quick start if you want the browser UI with local Ollama models. 3. Use the local Qwen/llama.cpp quick start if you want to manage GGUF files and llama.cpp servers yourself.
4. Use the local Qwen/llama.cpp quick start if you want to manage GGUF files and llama.cpp servers yourself. 4. Connect MCP after the app database exists if you want Claude Code, Codex, Cursor, or another agent to read/write the same graph.
## MCP Quick Install Every app path uses a local SQLite database. OpenAI setup keeps the database local but sends utility-model and embedding requests to OpenAI. Local Qwen setup keeps the database local and runs both model roles on your device through Ollama or llama.cpp, so those model calls do not go to a hosted model API.
```bash
npx -y ra-h-mcp-server@latest setup --client claude-code --yes
```
Run `doctor` after setup or whenever MCP feels stale:
```bash
npx -y ra-h-mcp-server@latest doctor
```
## Local App Quick Start: OpenAI ## Local App Quick Start: OpenAI
@@ -100,7 +90,24 @@ Fresh app setup must choose `--profile openai`, `--profile qwen-local`, or `--pr
## MCP Integration ## MCP Integration
The recommended MCP setup is the CLI command above. Manual config is only for troubleshooting or unsupported clients: Configure MCP after the app database exists. MCP should point at the same SQLite file as the app.
If you used the default database path:
```bash
npx -y ra-h-mcp-server@latest setup --client claude-code,codex --yes
```
If you set `SQLITE_DB_PATH` during app setup, pass that exact same path:
```bash
npx -y ra-h-mcp-server@latest setup \
--client claude-code,codex \
--yes \
--db "/absolute/path/to/rah.sqlite"
```
Manual config is only for troubleshooting or unsupported clients:
```json ```json
{ {