refactor: remove Conda support from Llama Stack (#2969)

# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
This PR is responsible for removal of Conda support in Llama Stack

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->
Closes #2539

## Test Plan
<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->

docs/source/distributions/self_hosted_distro/dell.md

@@ -114,7 +114,7 @@ podman run --rm -it \
 
 ## 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.
+Now you are ready to run Llama Stack with TGI as the inference provider. You can do this via venv or Docker which has a pre-built image.
 
 ### Via Docker
 
@@ -164,12 +164,12 @@ docker run \
   --env CHROMA_URL=$CHROMA_URL
 ```
 
-### Via Conda
+### Via venv
 
 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 build --template dell --image-type venv
 llama stack run dell
   --port $LLAMA_STACK_PORT \
   --env INFERENCE_MODEL=$INFERENCE_MODEL \

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

@@ -70,7 +70,7 @@ $ llama model list --downloaded
 
 ## Running the Distribution
 
-You can do this via Conda (build code) or Docker which has a pre-built image.
+You can do this via venv or Docker which has a pre-built image.
 
 ### Via Docker
 
@@ -104,12 +104,12 @@ docker run \
   --env SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
 ```
 
-### Via Conda
+### Via venv
 
 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
+llama stack build --template meta-reference-gpu --image-type venv
 llama stack run distributions/meta-reference-gpu/run.yaml \
   --port 8321 \
   --env INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct

docs/source/distributions/self_hosted_distro/nvidia.md

@@ -133,7 +133,7 @@ curl -X DELETE "$NEMO_URL/v1/deployment/model-deployments/meta/llama-3.1-8b-inst
 
 ## Running Llama Stack with NVIDIA
 
-You can do this via Conda or venv (build code), or Docker which has a pre-built image.
+You can do this via venv (build code), or Docker which has a pre-built image.
 
 ### Via Docker
 
@@ -152,17 +152,6 @@ docker run \
   --env NVIDIA_API_KEY=$NVIDIA_API_KEY
 ```
 
-### Via Conda
-
-```bash
-INFERENCE_MODEL=meta-llama/Llama-3.1-8b-Instruct
-llama stack build --template nvidia --image-type conda
-llama stack run ./run.yaml \
-  --port 8321 \
-  --env NVIDIA_API_KEY=$NVIDIA_API_KEY \
-  --env INFERENCE_MODEL=$INFERENCE_MODEL
-```
-
 ### Via venv
 
 If you've set up your local development environment, you can also build the image using your local virtual environment.

docs/source/distributions/self_hosted_distro/starter.md

@@ -145,7 +145,7 @@ This distribution comes with a default "llama-guard" shield that can be enabled
 
 ## Running the Distribution
 
-You can run the starter distribution via Docker, Conda, or venv.
+You can run the starter distribution via Docker or venv.
 
 ### Via Docker
 
@@ -164,12 +164,12 @@ docker run \
   --port $LLAMA_STACK_PORT
 ```
 
-### Via Conda or venv
+### Via venv
 
 Ensure you have configured the starter distribution using the environment variables explained above.
 
 ```bash
-uv run --with llama-stack llama stack build --template starter --image-type <conda|venv> --run
+uv run --with llama-stack llama stack build --template starter --image-type venv --run
 ```
 
 ## Example Usage