# TGI Distribution

The `llamastack/distribution-tgi` distribution consists of the following provider configurations.


| **API**         	| **Inference** 	| **Agents**     	| **Memory**                                       	| **Safety**     	| **Telemetry**  	|
|-----------------	|---------------	|----------------	|--------------------------------------------------	|----------------	|----------------	|
| **Provider(s)** 	| remote::tgi   	| meta-reference 	| meta-reference, remote::pgvector, remote::chroma 	| meta-reference 	| meta-reference 	|


### Start the Distribution (Single Node GPU)

> [!NOTE]
> This assumes you have access to GPU to start a TGI server with access to your GPU.


```
$ cd llama_stack/distribution/docker/tgi
$ ls
compose.yaml  tgi-run.yaml
$ docker compose up
```

The script will first start up TGI server, then start up Llama Stack distribution server hooking up to the remote TGI provider for inference. You should be able to see the following outputs --
```
[text-generation-inference] | 2024-10-15T18:56:33.810397Z  INFO text_generation_router::server: router/src/server.rs:1813: Using config Some(Llama)
[text-generation-inference] | 2024-10-15T18:56:33.810448Z  WARN text_generation_router::server: router/src/server.rs:1960: Invalid hostname, defaulting to 0.0.0.0
[text-generation-inference] | 2024-10-15T18:56:33.864143Z  INFO text_generation_router::server: router/src/server.rs:2353: Connected
INFO:     Started server process [1]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
INFO:     Uvicorn running on http://[::]:5000 (Press CTRL+C to quit)
```

To kill the server
```
docker compose down
```

### Start the Distribution (Single Node CPU)

> [!NOTE]
> This assumes you have an hosted endpoint compatible with TGI server.

```
$ cd llama-stack/distribution/tgi/cpu
$ ls
compose.yaml  run.yaml
$ docker compose up
```

Replace <ENTER_YOUR_TGI_HOSTED_ENDPOINT> in `run.yaml` file with your TGI endpoint.
```
inference:
  - provider_id: tgi0
    provider_type: remote::tgi
    config:
      url: <ENTER_YOUR_TGI_HOSTED_ENDPOINT>
```

### (Alternative) TGI server + llama stack run (Single Node GPU)

If you wish to separately spin up a TGI server, and connect with Llama Stack, you may use the following commands.

#### (optional) Start TGI server locally
- Please check the [TGI Getting Started Guide](https://github.com/huggingface/text-generation-inference?tab=readme-ov-file#get-started) to get a TGI endpoint.

```
docker run --rm -it -v $HOME/.cache/huggingface:/data -p 5009:5009 --gpus all ghcr.io/huggingface/text-generation-inference:latest --dtype bfloat16 --usage-stats on --sharded false --model-id meta-llama/Llama-3.1-8B-Instruct --port 5009
```


#### Start Llama Stack server pointing to TGI server

```
docker run --network host -it -p 5000:5000 -v ./run.yaml:/root/my-run.yaml --gpus=all llamastack-local-cpu --yaml_config /root/my-run.yaml
```

Make sure in you `run.yaml` file, you inference provider is pointing to the correct TGI server endpoint. E.g.
```
inference:
  - provider_id: tgi0
    provider_type: remote::tgi
    config:
      url: http://127.0.0.1:5009
```

**Via Conda**

```bash
llama stack build --config ./build.yaml
# -- start a TGI server endpoint
llama stack run ./gpu/run.yaml
```