mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-16 22:42:36 +00:00
121 lines
3.6 KiB
Markdown
121 lines
3.6 KiB
Markdown
# TGI Distribution
|
|
|
|
The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations.
|
|
|
|
{{ providers_table }}
|
|
|
|
You can use this distribution if you have GPUs and want to run an independent TGI server container for running inference.
|
|
|
|
{% if run_config_env_vars %}
|
|
### Environment Variables
|
|
|
|
The following environment variables can be configured:
|
|
|
|
{% for var, (default_value, description) in run_config_env_vars.items() %}
|
|
- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
|
|
{% endfor %}
|
|
{% endif %}
|
|
|
|
|
|
## Setting up TGI server
|
|
|
|
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. Here is a sample script to start a TGI server locally via Docker:
|
|
|
|
```bash
|
|
export TGI_INFERENCE_PORT=8080
|
|
export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
|
|
export CUDA_VISIBLE_DEVICES=0
|
|
|
|
docker run --rm -it \
|
|
-v $HOME/.cache/huggingface:/data \
|
|
-p $TGI_INFERENCE_PORT:$TGI_INFERENCE_PORT \
|
|
--gpus $CUDA_VISIBLE_DEVICES \
|
|
ghcr.io/huggingface/text-generation-inference:2.3.1 \
|
|
--dtype bfloat16 \
|
|
--usage-stats off \
|
|
--sharded false \
|
|
--cuda-memory-fraction 0.7 \
|
|
--model-id $INFERENCE_MODEL \
|
|
--port $TGI_INFERENCE_PORT
|
|
```
|
|
|
|
If you are using Llama Stack Safety / Shield APIs, then you will need to also run another instance of a TGI with a corresponding safety model like `meta-llama/Llama-Guard-3-1B` using a script like:
|
|
|
|
```bash
|
|
export TGI_SAFETY_PORT=8081
|
|
export SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
|
|
export CUDA_VISIBLE_DEVICES=1
|
|
|
|
docker run --rm -it \
|
|
-v $HOME/.cache/huggingface:/data \
|
|
-p $TGI_SAFETY_PORT:$TGI_SAFETY_PORT \
|
|
--gpus $CUDA_VISIBLE_DEVICES \
|
|
ghcr.io/huggingface/text-generation-inference:2.3.1 \
|
|
--dtype bfloat16 \
|
|
--usage-stats off \
|
|
--sharded false \
|
|
--model-id $SAFETY_MODEL \
|
|
--port $TGI_SAFETY_PORT
|
|
```
|
|
|
|
## Running Llama Stack with TGI as the inference provider
|
|
|
|
Now you are ready to run Llama Stack with TGI as the inference provider. You can do this via Conda (build code) or Docker which has a pre-built image.
|
|
|
|
### Via Docker
|
|
|
|
This method allows you to get started quickly without having to build the distribution code.
|
|
|
|
```bash
|
|
LLAMA_STACK_PORT=5001
|
|
docker run \
|
|
--network host \
|
|
-it \
|
|
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
|
|
-v ./run.yaml:/root/my-run.yaml \
|
|
llamastack/distribution-{{ name }} \
|
|
/root/my-run.yaml \
|
|
--port $LLAMA_STACK_PORT \
|
|
--env INFERENCE_MODEL=$INFERENCE_MODEL \
|
|
--env TGI_URL=http://host.docker.internal:$TGI_INFERENCE_PORT
|
|
```
|
|
|
|
If you are using Llama Stack Safety / Shield APIs, use:
|
|
|
|
```bash
|
|
docker run \
|
|
--network host \
|
|
-it \
|
|
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
|
|
-v ./run-with-safety.yaml:/root/my-run.yaml \
|
|
llamastack/distribution-{{ name }} \
|
|
/root/my-run.yaml \
|
|
--port $LLAMA_STACK_PORT \
|
|
--env INFERENCE_MODEL=$INFERENCE_MODEL \
|
|
--env TGI_URL=http://host.docker.internal:$TGI_INFERENCE_PORT \
|
|
--env SAFETY_MODEL=$SAFETY_MODEL \
|
|
--env TGI_SAFETY_URL=http://host.docker.internal:$TGI_SAFETY_PORT
|
|
```
|
|
|
|
### Via Conda
|
|
|
|
Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
|
|
|
|
```bash
|
|
llama stack build --template {{ name }} --image-type conda
|
|
llama stack run ./run.yaml
|
|
--port 5001
|
|
--env INFERENCE_MODEL=$INFERENCE_MODEL
|
|
--env TGI_URL=http://127.0.0.1:$TGI_INFERENCE_PORT
|
|
```
|
|
|
|
If you are using Llama Stack Safety / Shield APIs, use:
|
|
|
|
```bash
|
|
llama stack run ./run-with-safety.yaml
|
|
--port 5001
|
|
--env INFERENCE_MODEL=$INFERENCE_MODEL
|
|
--env TGI_URL=http://127.0.0.1:$TGI_INFERENCE_PORT
|
|
--env SAFETY_MODEL=$SAFETY_MODEL
|
|
--env TGI_SAFETY_URL=http://127.0.0.1:$TGI_SAFETY_PORT
|
|
```
|