feat: Add a new template for dell (#978)

- Added new template `dell` and its documentation 
- Update docs 
- [minor] uv fix i came across 
- codegen for all templates 

Tested with 

```bash
export INFERENCE_PORT=8181
export DEH_URL=http://0.0.0.0:$INFERENCE_PORT
export INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
export CHROMADB_HOST=localhost
export CHROMADB_PORT=6601
export CHROMA_URL=[http://$CHROMADB_HOST:$CHROMADB_PORT](about:blank)
export CUDA_VISIBLE_DEVICES=0
export LLAMA_STACK_PORT=8321

# build the stack template 
llama stack build --template=dell 

# start the TGI inference server 
podman run --rm -it --network host -v $HOME/.cache/huggingface:/data -e HF_TOKEN=$HF_TOKEN -p $INFERENCE_PORT:$INFERENCE_PORT --gpus $CUDA_VISIBLE_DEVICES [ghcr.io/huggingface/text-generation-inference](http://ghcr.io/huggingface/text-generation-inference) --dtype bfloat16 --usage-stats off --sharded false --cuda-memory-fraction 0.7 --model-id $INFERENCE_MODEL --port $INFERENCE_PORT --hostname 0.0.0.0

# start chroma-db for vector-io ( aka RAG )
podman run --rm -it --network host --name chromadb -v .:/chroma/chroma -e IS_PERSISTENT=TRUE chromadb/chroma:latest --port $CHROMADB_PORT --host $(hostname)

# build docker 
llama stack build --template=dell --image-type=container

# run llama stack server ( via docker )
podman run -it \
--network host \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ~/.llama:/root/.llama \
# NOTE: mount the llama-stack / llama-model directories if testing local changes 
-v /home/hjshah/git/llama-stack:/app/llama-stack-source -v /home/hjshah/git/llama-models:/app/llama-models-source \ localhost/distribution-dell:dev \
--port $LLAMA_STACK_PORT  \
--env INFERENCE_MODEL=$INFERENCE_MODEL \
--env DEH_URL=$DEH_URL \
--env CHROMA_URL=$CHROMA_URL

# test the server 
cd <PATH_TO_LLAMA_STACK_REPO>
LLAMA_STACK_BASE_URL=http://0.0.0.0:$LLAMA_STACK_PORT pytest -s -v tests/client-sdk/agents/test_agents.py

```

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>

docs/source/distributions/remote_hosted_distro/nvidia.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 # NVIDIA Distribution
 
 The `llamastack/distribution-nvidia` distribution consists of the following provider configurations.

docs/source/distributions/self_hosted_distro/bedrock.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 # Bedrock Distribution
 
 ```{toctree}

docs/source/distributions/self_hosted_distro/cerebras.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 # Cerebras Distribution
 
 The `llamastack/distribution-cerebras` distribution consists of the following provider configurations.

docs/source/distributions/self_hosted_distro/dell.md

@@ -0,0 +1,186 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
+---
+orphan: true
+---
+
+# Dell Distribution of Llama Stack
+
+```{toctree}
+:maxdepth: 2
+:hidden:
+
+self
+```
+
+The `llamastack/distribution-dell` distribution consists of the following provider configurations.
+
+| API | Provider(s) |
+|-----|-------------|
+| agents | `inline::meta-reference` |
+| datasetio | `remote::huggingface`, `inline::localfs` |
+| eval | `inline::meta-reference` |
+| inference | `remote::tgi` |
+| safety | `inline::llama-guard` |
+| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
+| telemetry | `inline::meta-reference` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
+
+
+You can use this distribution if you have GPUs and want to run an independent TGI or Dell Enterprise Hub container for running inference.
+
+### Environment Variables
+
+The following environment variables can be configured:
+
+- `DEH_URL`: URL for the Dell inference server (default: `http://0.0.0.0:8181`)
+- `DEH_SAFETY_URL`: URL for the Dell safety inference server (default: `http://0.0.0.0:8282`)
+- `CHROMA_URL`: URL for the Chroma server (default: `http://localhost:6601`)
+- `INFERENCE_MODEL`: Inference model loaded into the TGI server (default: `meta-llama/Llama-3.2-3B-Instruct`)
+- `SAFETY_MODEL`: Name of the safety (Llama-Guard) model to use (default: `meta-llama/Llama-Guard-3-1B`)
+
+
+## Setting up Inference server using Dell Enterprise Hub's custom TGI container.
+
+NOTE: This is a placeholder to run inference with TGI. This will be updated to use [Dell Enterprise Hub's containers](https://dell.huggingface.co/authenticated/models) once verified.
+
+```bash
+export INFERENCE_PORT=8181
+export DEH_URL=http://0.0.0.0:$INFERENCE_PORT
+export INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
+export CHROMADB_HOST=localhost
+export CHROMADB_PORT=6601
+export CHROMA_URL=http://$CHROMADB_HOST:$CHROMADB_PORT
+export CUDA_VISIBLE_DEVICES=0
+export LLAMA_STACK_PORT=8321
+
+docker run --rm -it \
+  --network host \
+  -v $HOME/.cache/huggingface:/data \
+  -e HF_TOKEN=$HF_TOKEN \
+  -p $INFERENCE_PORT:$INFERENCE_PORT \
+  --gpus $CUDA_VISIBLE_DEVICES \
+  ghcr.io/huggingface/text-generation-inference \
+  --dtype bfloat16 \
+  --usage-stats off \
+  --sharded false \
+  --cuda-memory-fraction 0.7 \
+  --model-id $INFERENCE_MODEL \
+  --port $INFERENCE_PORT --hostname 0.0.0.0
+```
+
+If you are using Llama Stack Safety / Shield APIs, then you will need to also run another instance of a TGI with a corresponding safety model like `meta-llama/Llama-Guard-3-1B` using a script like:
+
+```bash
+export SAFETY_INFERENCE_PORT=8282
+export DEH_SAFETY_URL=http://0.0.0.0:$SAFETY_INFERENCE_PORT
+export SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
+export CUDA_VISIBLE_DEVICES=1
+
+docker run --rm -it \
+  --network host \
+  -v $HOME/.cache/huggingface:/data \
+  -e HF_TOKEN=$HF_TOKEN \
+  -p $SAFETY_INFERENCE_PORT:$SAFETY_INFERENCE_PORT \
+  --gpus $CUDA_VISIBLE_DEVICES \
+  ghcr.io/huggingface/text-generation-inference \
+  --dtype bfloat16 \
+  --usage-stats off \
+  --sharded false \
+  --cuda-memory-fraction 0.7 \
+  --model-id $SAFETY_MODEL \
+  --hostname 0.0.0.0 \
+  --port $SAFETY_INFERENCE_PORT
+```
+
+## Dell distribution relies on ChromaDB for vector database usage
+
+You can start a chroma-db easily using docker.
+```bash
+# This is where the indices are persisted
+mkdir -p $HOME/chromadb
+
+podman run --rm -it \
+  --network host \
+  --name chromadb \
+  -v $HOME/chromadb:/chroma/chroma \
+  -e IS_PERSISTENT=TRUE \
+  chromadb/chroma:latest \
+  --port $CHROMADB_PORT \
+  --host $CHROMADB_HOST
+```
+
+## Running Llama Stack
+
+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
+docker run -it \
+  --network host \
+  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+  -v $HOME/.llama:/root/.llama \
+  # NOTE: mount the llama-stack / llama-model directories if testing local changes else not needed
+  -v /home/hjshah/git/llama-stack:/app/llama-stack-source -v /home/hjshah/git/llama-models:/app/llama-models-source \
+  # localhost/distribution-dell:dev if building / testing locally
+  llamastack/distribution-dell\
+  --port $LLAMA_STACK_PORT  \
+  --env INFERENCE_MODEL=$INFERENCE_MODEL \
+  --env DEH_URL=$DEH_URL \
+  --env CHROMA_URL=$CHROMA_URL
+
+```
+
+If you are using Llama Stack Safety / Shield APIs, use:
+
+```bash
+# You need a local checkout of llama-stack to run this, get it using
+# git clone https://github.com/meta-llama/llama-stack.git
+cd /path/to/llama-stack
+
+export SAFETY_INFERENCE_PORT=8282
+export DEH_SAFETY_URL=http://0.0.0.0:$SAFETY_INFERENCE_PORT
+export SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
+
+docker run \
+  -it \
+  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+  -v $HOME/.llama:/root/.llama \
+  -v ./llama_stack/templates/tgi/run-with-safety.yaml:/root/my-run.yaml \
+  llamastack/distribution-dell \
+  --yaml-config /root/my-run.yaml \
+  --port $LLAMA_STACK_PORT \
+  --env INFERENCE_MODEL=$INFERENCE_MODEL \
+  --env DEH_URL=$DEH_URL \
+  --env SAFETY_MODEL=$SAFETY_MODEL \
+  --env DEH_SAFETY_URL=$DEH_SAFETY_URL \
+  --env CHROMA_URL=$CHROMA_URL
+```
+
+### Via Conda
+
+Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
+
+```bash
+llama stack build --template dell --image-type conda
+llama stack run dell
+  --port $LLAMA_STACK_PORT \
+  --env INFERENCE_MODEL=$INFERENCE_MODEL \
+  --env DEH_URL=$DEH_URL \
+  --env CHROMA_URL=$CHROMA_URL
+```
+
+If you are using Llama Stack Safety / Shield APIs, use:
+
+```bash
+llama stack run ./run-with-safety.yaml \
+  --port $LLAMA_STACK_PORT \
+  --env INFERENCE_MODEL=$INFERENCE_MODEL \
+  --env DEH_URL=$DEH_URL \
+  --env SAFETY_MODEL=$SAFETY_MODEL \
+  --env DEH_SAFETY_URL=$DEH_SAFETY_URL \
+  --env CHROMA_URL=$CHROMA_URL
+```

docs/source/distributions/self_hosted_distro/fireworks.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---

docs/source/distributions/self_hosted_distro/meta-reference-gpu.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---
@@ -82,7 +83,7 @@ docker run \
 
 ### Via Conda
 
-Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
+Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
 
 ```bash
 llama stack build --template meta-reference-gpu --image-type conda

docs/source/distributions/self_hosted_distro/meta-reference-quantized-gpu.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---
@@ -82,7 +83,7 @@ docker run \
 
 ### Via Conda
 
-Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
+Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
 
 ```bash
 llama stack build --template meta-reference-quantized-gpu --image-type conda

docs/source/distributions/self_hosted_distro/ollama.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---
@@ -103,7 +104,7 @@ docker run \
 
 ### Via Conda
 
-Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
+Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
 
 ```bash
 export LLAMA_STACK_PORT=5001

docs/source/distributions/self_hosted_distro/remote-vllm.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---
@@ -131,7 +132,7 @@ docker run \
 
 ### Via Conda
 
-Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
+Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
 
 ```bash
 export INFERENCE_PORT=8000

docs/source/distributions/self_hosted_distro/sambanova.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---

docs/source/distributions/self_hosted_distro/tgi.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---
@@ -122,7 +123,7 @@ docker run \
 
 ### Via Conda
 
-Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
+Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
 
 ```bash
 llama stack build --template tgi --image-type conda

docs/source/distributions/self_hosted_distro/together.md

@@ -1,3 +1,4 @@
+<!-- This file was auto-generated by distro_codegen.py, please edit source -->
 ---
 orphan: true
 ---