chore: remove --env from llama stack run

# What does this PR do?


## Test Plan

docs/docs/building_applications/tools.mdx

@@ -219,13 +219,10 @@ group_tools = client.tools.list_tools(toolgroup_id="search_tools")
 <TabItem value="setup" label="Setup & Configuration">
 
 1. Start by registering a Tavily API key at [Tavily](https://tavily.com/).
-2. [Optional] Provide the API key directly to the Llama Stack server
+2. [Optional] Set the API key in your environment before starting the Llama Stack server
 ```bash
 export TAVILY_SEARCH_API_KEY="your key"
 ```
-```bash
---env TAVILY_SEARCH_API_KEY=${TAVILY_SEARCH_API_KEY}
-```
 
 </TabItem>
 <TabItem value="implementation" label="Implementation">
@@ -273,9 +270,9 @@ for log in EventLogger().log(response):
 <TabItem value="setup" label="Setup & Configuration">
 
 1. Start by registering for a WolframAlpha API key at [WolframAlpha Developer Portal](https://developer.wolframalpha.com/access).
-2. Provide the API key either when starting the Llama Stack server:
+2. Provide the API key either by setting it in your environment before starting the Llama Stack server:
     ```bash
-    --env WOLFRAM_ALPHA_API_KEY=${WOLFRAM_ALPHA_API_KEY}
+    export WOLFRAM_ALPHA_API_KEY="your key"
     ```
     or from the client side:
     ```python

docs/docs/contributing/new_api_provider.mdx

@@ -76,7 +76,7 @@ Integration tests are located in [tests/integration](https://github.com/meta-lla
 Consult [tests/integration/README.md](https://github.com/meta-llama/llama-stack/blob/main/tests/integration/README.md) for more details on how to run the tests.
 
 Note that each provider's `sample_run_config()` method (in the configuration class for that provider)
- typically references some environment variables for specifying API keys and the like. You can set these in the environment or pass these via the `--env` flag to the test command.
+ typically references some environment variables for specifying API keys and the like. You can set these in the environment before running the test command.
 
 
 ### 2. Unit Testing

docs/docs/distributions/building_distro.mdx

@@ -289,10 +289,10 @@ After this step is successful, you should be able to find the built container im
 docker run -d \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
+  -e INFERENCE_MODEL=$INFERENCE_MODEL \
+  -e OLLAMA_URL=http://host.docker.internal:11434 \
   localhost/distribution-ollama:dev \
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
-  --env OLLAMA_URL=http://host.docker.internal:11434
+  --port $LLAMA_STACK_PORT
 ```
 
 Here are the docker flags and their uses:
@@ -305,12 +305,12 @@ Here are the docker flags and their uses:
 
 * `localhost/distribution-ollama:dev`: The name and tag of the container image to run
 
+* `-e INFERENCE_MODEL=$INFERENCE_MODEL`: Sets the INFERENCE_MODEL environment variable in the container
+
+* `-e OLLAMA_URL=http://host.docker.internal:11434`: Sets the OLLAMA_URL environment variable in the container
+
 * `--port $LLAMA_STACK_PORT`: Port number for the server to listen on
 
-* `--env INFERENCE_MODEL=$INFERENCE_MODEL`: Sets the model to use for inference
-
-* `--env OLLAMA_URL=http://host.docker.internal:11434`: Configures the URL for the Ollama service
-
 </TabItem>
 </Tabs>
 
@@ -320,7 +320,7 @@ Now, let's start the Llama Stack Distribution Server. You will need the YAML con
 
 ```
 llama stack run -h
-usage: llama stack run [-h] [--port PORT] [--image-name IMAGE_NAME] [--env KEY=VALUE]
+usage: llama stack run [-h] [--port PORT] [--image-name IMAGE_NAME]
                        [--image-type {venv}] [--enable-ui]
                        [config | template]
 
@@ -334,7 +334,6 @@ options:
   --port PORT           Port to run the server on. It can also be passed via the env var LLAMA_STACK_PORT. (default: 8321)
   --image-name IMAGE_NAME
                         Name of the image to run. Defaults to the current environment (default: None)
-  --env KEY=VALUE       Environment variables to pass to the server in KEY=VALUE format. Can be specified multiple times. (default: None)
   --image-type {venv}
                         Image Type used during the build. This should be venv. (default: None)
   --enable-ui           Start the UI server (default: False)

docs/docs/distributions/configuration.mdx

@@ -101,7 +101,7 @@ A few things to note:
 - The id is a string you can choose freely.
 - You can instantiate any number of provider instances of the same type.
 - The configuration dictionary is provider-specific.
-- Notice that configuration can reference environment variables (with default values), which are expanded at runtime. When you run a stack server (via docker or via `llama stack run`), you can specify `--env OLLAMA_URL=http://my-server:11434` to override the default value.
+- Notice that configuration can reference environment variables (with default values), which are expanded at runtime. When you run a stack server, you can set environment variables in your shell before running `llama stack run` to override the default values.
 
 ### Environment Variable Substitution
 
@@ -173,13 +173,10 @@ optional_token: ${env.OPTIONAL_TOKEN:+}
 
 #### Runtime Override
 
-You can override environment variables at runtime when starting the server:
+You can override environment variables at runtime by setting them in your shell before starting the server:
 
 ```bash
-# Override specific environment variables
-llama stack run --config run.yaml --env API_KEY=sk-123 --env BASE_URL=https://custom-api.com
-
-# Or set them in your shell
+# Set environment variables in your shell
 export API_KEY=sk-123
 export BASE_URL=https://custom-api.com
 llama stack run --config run.yaml

docs/docs/distributions/remote_hosted_distro/watsonx.md

@@ -69,10 +69,10 @@ docker run \
   -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ./run.yaml:/root/my-run.yaml \
+  -e WATSONX_API_KEY=$WATSONX_API_KEY \
+  -e WATSONX_PROJECT_ID=$WATSONX_PROJECT_ID \
+  -e WATSONX_BASE_URL=$WATSONX_BASE_URL \
   llamastack/distribution-watsonx \
   --config /root/my-run.yaml \
-  --port $LLAMA_STACK_PORT \
-  --env WATSONX_API_KEY=$WATSONX_API_KEY \
-  --env WATSONX_PROJECT_ID=$WATSONX_PROJECT_ID \
-  --env WATSONX_BASE_URL=$WATSONX_BASE_URL
+  --port $LLAMA_STACK_PORT
 ```

docs/docs/distributions/self_hosted_distro/dell.md

@@ -129,11 +129,11 @@ docker run -it \
   # NOTE: mount the llama-stack / llama-model directories if testing local changes else not needed
   -v $HOME/git/llama-stack:/app/llama-stack-source -v $HOME/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
+  -e INFERENCE_MODEL=$INFERENCE_MODEL \
+  -e DEH_URL=$DEH_URL \
+  -e CHROMA_URL=$CHROMA_URL \
+  llamastack/distribution-dell \
+  --port $LLAMA_STACK_PORT
 
 ```
 
@@ -154,14 +154,14 @@ docker run \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v $HOME/.llama:/root/.llama \
   -v ./llama_stack/distributions/tgi/run-with-safety.yaml:/root/my-run.yaml \
+  -e INFERENCE_MODEL=$INFERENCE_MODEL \
+  -e DEH_URL=$DEH_URL \
+  -e SAFETY_MODEL=$SAFETY_MODEL \
+  -e DEH_SAFETY_URL=$DEH_SAFETY_URL \
+  -e CHROMA_URL=$CHROMA_URL \
   llamastack/distribution-dell \
   --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
+  --port $LLAMA_STACK_PORT
 ```
 
 ### Via venv
@@ -170,21 +170,21 @@ Make sure you have done `pip install llama-stack` and have the Llama Stack CLI a
 
 ```bash
 llama stack build --distro dell --image-type venv
-llama stack run dell
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL \
-  --env DEH_URL=$DEH_URL \
-  --env CHROMA_URL=$CHROMA_URL
+INFERENCE_MODEL=$INFERENCE_MODEL \
+DEH_URL=$DEH_URL \
+CHROMA_URL=$CHROMA_URL \
+llama stack run dell \
+  --port $LLAMA_STACK_PORT
 ```
 
 If you are using Llama Stack Safety / Shield APIs, use:
 
 ```bash
+INFERENCE_MODEL=$INFERENCE_MODEL \
+DEH_URL=$DEH_URL \
+SAFETY_MODEL=$SAFETY_MODEL \
+DEH_SAFETY_URL=$DEH_SAFETY_URL \
+CHROMA_URL=$CHROMA_URL \
 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
+  --port $LLAMA_STACK_PORT
 ```

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

@@ -84,9 +84,9 @@ docker run \
   --gpu all \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
+  -e INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
   llamastack/distribution-meta-reference-gpu \
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
+  --port $LLAMA_STACK_PORT
 ```
 
 If you are using Llama Stack Safety / Shield APIs, use:
@@ -98,10 +98,10 @@ docker run \
   --gpu all \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
+  -e INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
+  -e SAFETY_MODEL=meta-llama/Llama-Guard-3-1B \
   llamastack/distribution-meta-reference-gpu \
-  --port $LLAMA_STACK_PORT \
-  --env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
-  --env SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
+  --port $LLAMA_STACK_PORT
 ```
 
 ### Via venv
@@ -110,16 +110,16 @@ Make sure you have done `uv pip install llama-stack` and have the Llama Stack CL
 
 ```bash
 llama stack build --distro meta-reference-gpu --image-type venv
+INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
 llama stack run distributions/meta-reference-gpu/run.yaml \
-  --port 8321 \
-  --env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct
+  --port 8321
 ```
 
 If you are using Llama Stack Safety / Shield APIs, use:
 
 ```bash
+INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
+SAFETY_MODEL=meta-llama/Llama-Guard-3-1B \
 llama stack run distributions/meta-reference-gpu/run-with-safety.yaml \
-  --port 8321 \
-  --env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
-  --env SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
+  --port 8321
 ```

docs/docs/distributions/self_hosted_distro/nvidia.md

@@ -129,10 +129,10 @@ docker run \
   --pull always \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ./run.yaml:/root/my-run.yaml \
+  -e NVIDIA_API_KEY=$NVIDIA_API_KEY \
   llamastack/distribution-nvidia \
   --config /root/my-run.yaml \
-  --port $LLAMA_STACK_PORT \
-  --env NVIDIA_API_KEY=$NVIDIA_API_KEY
+  --port $LLAMA_STACK_PORT
 ```
 
 ### Via venv
@@ -142,10 +142,10 @@ If you've set up your local development environment, you can also build the imag
 ```bash
 INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
 llama stack build --distro nvidia --image-type venv
+NVIDIA_API_KEY=$NVIDIA_API_KEY \
+INFERENCE_MODEL=$INFERENCE_MODEL \
 llama stack run ./run.yaml \
-  --port 8321 \
-  --env NVIDIA_API_KEY=$NVIDIA_API_KEY \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL
+  --port 8321
 ```
 
 ## Example Notebooks

docs/docs/getting_started/detailed_tutorial.mdx

@@ -86,9 +86,9 @@ docker run -it \
   --pull always \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
+  -e OLLAMA_URL=http://host.docker.internal:11434 \
   llamastack/distribution-starter \
-  --port $LLAMA_STACK_PORT \
-  --env OLLAMA_URL=http://host.docker.internal:11434
+  --port $LLAMA_STACK_PORT
 ```
 Note to start the container with Podman, you can do the same but replace `docker` at the start of the command with
 `podman`. If you are using `podman` older than `4.7.0`, please also replace `host.docker.internal` in the `OLLAMA_URL`
@@ -106,9 +106,9 @@ docker run -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
   --network=host \
+  -e OLLAMA_URL=http://localhost:11434 \
   llamastack/distribution-starter \
-  --port $LLAMA_STACK_PORT \
-  --env OLLAMA_URL=http://localhost:11434
+  --port $LLAMA_STACK_PORT
 ```
 :::
 You will see output like below:

docs/getting_started_llama4.ipynb

@@ -238,7 +238,7 @@
         "def run_llama_stack_server_background():\n",
         "    log_file = open(\"llama_stack_server.log\", \"w\")\n",
         "    process = subprocess.Popen(\n",
-        "        f\"uv run --with llama-stack llama stack run meta-reference-gpu --image-type venv --env INFERENCE_MODEL={model_id}\",\n",
+        "        f\"INFERENCE_MODEL={model_id} uv run --with llama-stack llama stack run meta-reference-gpu --image-type venv\",\n",
         "        shell=True,\n",
         "        stdout=log_file,\n",
         "        stderr=log_file,\n",

docs/zero_to_hero_guide/README.md

@@ -102,12 +102,12 @@ If you're looking for more specific topics, we have a [Zero to Hero Guide](#next
 3. **Run the Llama Stack**:
    Run the stack using uv:
    ```bash
+   INFERENCE_MODEL=$INFERENCE_MODEL \
+   SAFETY_MODEL=$SAFETY_MODEL \
+   OLLAMA_URL=$OLLAMA_URL \
    uv run --with llama-stack llama stack run starter \
       --image-type venv \
-      --port $LLAMA_STACK_PORT \
-      --env INFERENCE_MODEL=$INFERENCE_MODEL \
-      --env SAFETY_MODEL=$SAFETY_MODEL \
-      --env OLLAMA_URL=$OLLAMA_URL
+      --port $LLAMA_STACK_PORT
    ```
    Note: Every time you run a new model with `ollama run`, you will need to restart the llama stack. Otherwise it won't see the new model.