From 4aa1bf6a60bef73930c74876a482ce908d3619f6 Mon Sep 17 00:00:00 2001 From: Ashwin Bharambe Date: Mon, 28 Oct 2024 23:07:32 -0700 Subject: [PATCH] Kill --name from llama stack build (#340) --- docs/building_distro.md | 26 +++++------ docs/cli_reference.md | 26 +++++------ docs/getting_started.ipynb | 1 - docs/getting_started.md | 1 - docs/source/cli_reference.md | 30 ++++++------- docs/source/getting_started.md | 29 ++++++------- llama_stack/cli/stack/build.py | 62 ++++----------------------- llama_stack/cli/stack/configure.py | 19 +------- llama_stack/distribution/configure.py | 7 +++ 9 files changed, 71 insertions(+), 130 deletions(-) diff --git a/docs/building_distro.md b/docs/building_distro.md index 05e5c09bb..234c553da 100644 --- a/docs/building_distro.md +++ b/docs/building_distro.md @@ -58,15 +58,15 @@ llama stack build --list-templates You may then pick a template to build your distribution with providers fitted to your liking. ``` -llama stack build --template local-tgi --name my-tgi-stack +llama stack build --template tgi ``` ``` -$ llama stack build --template local-tgi --name my-tgi-stack +$ llama stack build --template tgi ... ... -Build spec configuration saved at ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml -You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml` +Build spec configuration saved at ~/.conda/envs/llamastack-tgi/tgi-build.yaml +You may now run `llama stack configure tgi` or `llama stack configure ~/.conda/envs/llamastack-tgi/tgi-build.yaml` ``` #### Building from config file @@ -75,9 +75,9 @@ You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~ - The config file will be of contents like the ones in `llama_stack/distributions/templates/`. ``` -$ cat llama_stack/distribution/templates/local-ollama-build.yaml +$ cat llama_stack/templates/ollama/build.yaml -name: local-ollama +name: ollama distribution_spec: description: Like local, but use ollama for running LLM inference providers: @@ -90,7 +90,7 @@ image_type: conda ``` ``` -llama stack build --config llama_stack/distribution/templates/local-ollama-build.yaml +llama stack build --config llama_stack/templates/ollama/build.yaml ``` #### How to build distribution with Docker image @@ -101,7 +101,7 @@ llama stack build --config llama_stack/distribution/templates/local-ollama-build To build a docker image, you may start off from a template and use the `--image-type docker` flag to specify `docker` as the build image type. ``` -llama stack build --template local --image-type docker --name docker-0 +llama stack build --template local --image-type docker ``` Alternatively, you may use a config file and set `image_type` to `docker` in our `-build.yaml` file, and run `llama stack build -build.yaml`. The `-build.yaml` will be of contents like: @@ -136,14 +136,14 @@ Build spec configuration saved at ~/.llama/distributions/docker/docker-local-bui ## Step 2. Configure After our distribution is built (either in form of docker or conda environment), we will run the following command to ``` -llama stack configure [ | | ] +llama stack configure [ | ] ``` - For `conda` environments: would be the generated build spec saved from Step 1. - For `docker` images downloaded from Dockerhub, you could also use as the argument. - Run `docker images` to check list of available images on your machine. ``` -$ llama stack configure 8b-instruct +$ llama stack configure tgi Configuring API: inference (meta-reference) Enter value for model (existing: Meta-Llama3.1-8B-Instruct) (required): @@ -172,10 +172,10 @@ Enter value for wolfram_api_key (optional): Configuring API: telemetry (console) -YAML configuration has been written to ~/.llama/builds/conda/8b-instruct-run.yaml +YAML configuration has been written to ~/.llama/builds/conda/tgi-run.yaml ``` -After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/8b-instruct-run.yaml` with the following contents. You may edit this file to change the settings. +After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/tgi-run.yaml` with the following contents. You may edit this file to change the settings. As you can see, we did basic configuration above and configured: - inference to run on model `Meta-Llama3.1-8B-Instruct` (obtained from `llama model list`) @@ -228,7 +228,7 @@ INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit) ``` > [!NOTE] -> Configuration is in `~/.llama/builds/local/conda/8b-instruct-run.yaml`. Feel free to increase `max_seq_len`. +> Configuration is in `~/.llama/builds/local/conda/tgi-run.yaml`. Feel free to increase `max_seq_len`. > [!IMPORTANT] > The "local" distribution inference server currently only supports CUDA. It will not work on Apple Silicon machines. diff --git a/docs/cli_reference.md b/docs/cli_reference.md index ddc8e6b3e..39ac99615 100644 --- a/docs/cli_reference.md +++ b/docs/cli_reference.md @@ -229,8 +229,8 @@ You will be shown a Markdown formatted description of the model interface and ho - Please see our [Getting Started](getting_started.md) guide for more details on how to build and start a Llama Stack distribution. ### Step 3.1 Build -In the following steps, imagine we'll be working with a `Llama3.1-8B-Instruct` model. We will name our build `8b-instruct` to help us remember the config. We will start build our distribution (in the form of a Conda environment, or Docker image). In this step, we will specify: -- `name`: the name for our distribution (e.g. `8b-instruct`) +In the following steps, imagine we'll be working with a `Llama3.1-8B-Instruct` model. We will name our build `tgi` to help us remember the config. We will start build our distribution (in the form of a Conda environment, or Docker image). In this step, we will specify: +- `name`: the name for our distribution (e.g. `tgi`) - `image_type`: our build image type (`conda | docker`) - `distribution_spec`: our distribution specs for specifying API providers - `description`: a short description of the configurations for the distribution @@ -279,15 +279,15 @@ llama stack build --list-templates You may then pick a template to build your distribution with providers fitted to your liking. ``` -llama stack build --template local-tgi --name my-tgi-stack --image-type conda +llama stack build --template tgi --image-type conda ``` ``` -$ llama stack build --template local-tgi --name my-tgi-stack --image-type conda +$ llama stack build --template tgi --image-type conda ... ... -Build spec configuration saved at ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml -You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml` +Build spec configuration saved at ~/.conda/envs/llamastack-tgi/tgi-build.yaml +You may now run `llama stack configure tgi` or `llama stack configure ~/.conda/envs/llamastack-tgi/tgi-build.yaml` ``` #### Building from config file @@ -298,7 +298,7 @@ You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~ ``` $ cat build.yaml -name: local-ollama +name: ollama distribution_spec: description: Like local, but use ollama for running LLM inference providers: @@ -319,7 +319,7 @@ llama stack build --config build.yaml To build a docker image, you may start off from a template and use the `--image-type docker` flag to specify `docker` as the build image type. ``` -llama stack build --template local --image-type docker --name docker-0 +llama stack build --template tgi --image-type docker ``` Alternatively, you may use a config file and set `image_type` to `docker` in our `-build.yaml` file, and run `llama stack build -build.yaml`. The `-build.yaml` will be of contents like: @@ -354,14 +354,14 @@ Build spec configuration saved at ~/.llama/distributions/docker/docker-local-bui ### Step 3.2 Configure After our distribution is built (either in form of docker or conda environment), we will run the following command to ``` -llama stack configure [ | | ] +llama stack configure [ | ] ``` - For `conda` environments: would be the generated build spec saved from Step 1. - For `docker` images downloaded from Dockerhub, you could also use as the argument. - Run `docker images` to check list of available images on your machine. ``` -$ llama stack configure ~/.llama/distributions/conda/8b-instruct-build.yaml +$ llama stack configure ~/.llama/distributions/conda/tgi-build.yaml Configuring API: inference (meta-reference) Enter value for model (existing: Llama3.1-8B-Instruct) (required): @@ -409,13 +409,13 @@ Note that all configurations as well as models are stored in `~/.llama` Now, let's start the Llama Stack Distribution Server. You will need the YAML configuration file which was written out at the end by the `llama stack configure` step. ``` -llama stack run ~/.llama/builds/conda/8b-instruct-run.yaml +llama stack run ~/.llama/builds/conda/tgi-run.yaml ``` You should see the Llama Stack server start and print the APIs that it is supporting ``` -$ llama stack run ~/.llama/builds/local/conda/8b-instruct.yaml +$ llama stack run ~/.llama/builds/local/conda/tgi-run.yaml > initializing model parallel with size 1 > initializing ddp with size 1 @@ -446,7 +446,7 @@ INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit) ``` > [!NOTE] -> Configuration is in `~/.llama/builds/local/conda/8b-instruct-run.yaml`. Feel free to increase `max_seq_len`. +> Configuration is in `~/.llama/builds/local/conda/tgi-run.yaml`. Feel free to increase `max_seq_len`. > [!IMPORTANT] > The "local" distribution inference server currently only supports CUDA. It will not work on Apple Silicon machines. diff --git a/docs/getting_started.ipynb b/docs/getting_started.ipynb index 00633b1d3..c8fc63e5d 100644 --- a/docs/getting_started.ipynb +++ b/docs/getting_started.ipynb @@ -68,7 +68,6 @@ "```\n", "$ llama stack configure llamastack-local-gpu\n", "\n", - "Could not find llamastack-local-gpu. Trying conda build name instead...\n", "Could not find /home/hjshah/.conda/envs/llamastack-llamastack-local-gpu/llamastack-local-gpu-build.yaml. Trying docker image name instead...\n", "+ podman run --network host -it -v /home/hjshah/.llama/builds/docker:/app/builds llamastack-local-gpu llama stack configure ./llamastack-build.yaml --output-dir /app/builds\n", "\n", diff --git a/docs/getting_started.md b/docs/getting_started.md index bb4e76cf2..49c7cd5a0 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -97,7 +97,6 @@ docker run -it -p 5000:5000 -v ~/.llama:/root/.llama -v ./run.yaml:/root/my-run. ``` $ llama stack configure my-local-stack - Could not find my-local-stack. Trying conda build name instead... Configuring API `inference`... === Configuring provider `meta-reference` for API inference... Enter value for model (default: Llama3.1-8B-Instruct) (required): diff --git a/docs/source/cli_reference.md b/docs/source/cli_reference.md index a5ea03673..81da1a773 100644 --- a/docs/source/cli_reference.md +++ b/docs/source/cli_reference.md @@ -279,15 +279,15 @@ llama stack build --list-templates You may then pick a template to build your distribution with providers fitted to your liking. ``` -llama stack build --template local-tgi --name my-tgi-stack +llama stack build --template tgi ``` ``` -$ llama stack build --template local-tgi --name my-tgi-stack +$ llama stack build --template tgi ... ... -Build spec configuration saved at ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml -You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml` +Build spec configuration saved at ~/.conda/envs/llamastack-tgi/tgi-build.yaml +You may now run `llama stack configure tgi` or `llama stack configure ~/.conda/envs/llamastack-tgi/tgi-build.yaml` ``` #### Building from config file @@ -296,9 +296,9 @@ You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~ - The config file will be of contents like the ones in `llama_stack/distributions/templates/`. ``` -$ cat llama_stack/distribution/templates/local-ollama-build.yaml +$ cat llama_stack/templates/ollama/build.yaml -name: local-ollama +name: ollama distribution_spec: description: Like local, but use ollama for running LLM inference providers: @@ -311,7 +311,7 @@ image_type: conda ``` ``` -llama stack build --config llama_stack/distribution/templates/local-ollama-build.yaml +llama stack build --config llama_stack/templates/ollama/build.yaml ``` #### How to build distribution with Docker image @@ -319,7 +319,7 @@ llama stack build --config llama_stack/distribution/templates/local-ollama-build To build a docker image, you may start off from a template and use the `--image-type docker` flag to specify `docker` as the build image type. ``` -llama stack build --template local --image-type docker --name docker-0 +llama stack build --template local --image-type docker ``` Alternatively, you may use a config file and set `image_type` to `docker` in our `-build.yaml` file, and run `llama stack build -build.yaml`. The `-build.yaml` will be of contents like: @@ -354,14 +354,14 @@ Build spec configuration saved at ~/.llama/distributions/docker/docker-local-bui ### Step 3.2 Configure After our distribution is built (either in form of docker or conda environment), we will run the following command to ``` -llama stack configure [ | | ] +llama stack configure [ | ] ``` - For `conda` environments: would be the generated build spec saved from Step 1. - For `docker` images downloaded from Dockerhub, you could also use as the argument. - Run `docker images` to check list of available images on your machine. ``` -$ llama stack configure ~/.llama/distributions/conda/8b-instruct-build.yaml +$ llama stack configure ~/.llama/distributions/conda/tgi-build.yaml Configuring API: inference (meta-reference) Enter value for model (existing: Llama3.1-8B-Instruct) (required): @@ -390,10 +390,10 @@ Enter value for wolfram_api_key (optional): Configuring API: telemetry (console) -YAML configuration has been written to ~/.llama/builds/conda/8b-instruct-run.yaml +YAML configuration has been written to ~/.llama/builds/conda/tgi-run.yaml ``` -After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/8b-instruct-run.yaml` with the following contents. You may edit this file to change the settings. +After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/tgi-run.yaml` with the following contents. You may edit this file to change the settings. As you can see, we did basic configuration above and configured: - inference to run on model `Llama3.1-8B-Instruct` (obtained from `llama model list`) @@ -409,13 +409,13 @@ Note that all configurations as well as models are stored in `~/.llama` Now, let's start the Llama Stack Distribution Server. You will need the YAML configuration file which was written out at the end by the `llama stack configure` step. ``` -llama stack run ~/.llama/builds/conda/8b-instruct-run.yaml +llama stack run ~/.llama/builds/conda/tgi-run.yaml ``` You should see the Llama Stack server start and print the APIs that it is supporting ``` -$ llama stack run ~/.llama/builds/local/conda/8b-instruct.yaml +$ llama stack run ~/.llama/builds/conda/tgi-run.yaml > initializing model parallel with size 1 > initializing ddp with size 1 @@ -446,7 +446,7 @@ INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit) ``` > [!NOTE] -> Configuration is in `~/.llama/builds/local/conda/8b-instruct-run.yaml`. Feel free to increase `max_seq_len`. +> Configuration is in `~/.llama/builds/local/conda/tgi-run.yaml`. Feel free to increase `max_seq_len`. > [!IMPORTANT] > The "local" distribution inference server currently only supports CUDA. It will not work on Apple Silicon machines. diff --git a/docs/source/getting_started.md b/docs/source/getting_started.md index 61f8f46c6..b1450cd42 100644 --- a/docs/source/getting_started.md +++ b/docs/source/getting_started.md @@ -86,7 +86,6 @@ llama stack configure ``` $ llama stack configure my-local-stack -Could not find my-local-stack. Trying conda build name instead... Configuring API `inference`... === Configuring provider `meta-reference` for API inference... Enter value for model (default: Llama3.1-8B-Instruct) (required): @@ -218,15 +217,15 @@ llama stack build --list-templates You may then pick a template to build your distribution with providers fitted to your liking. ``` -llama stack build --template local-tgi --name my-tgi-stack +llama stack build --template tgi ``` ``` -$ llama stack build --template local-tgi --name my-tgi-stack +$ llama stack build --template tgi ... ... -Build spec configuration saved at ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml -You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~/.conda/envs/llamastack-my-tgi-stack/my-tgi-stack-build.yaml` +Build spec configuration saved at ~/.conda/envs/llamastack-tgi/tgi-build.yaml +You may now run `llama stack configure tgi` or `llama stack configure ~/.conda/envs/llamastack-tgi/tgi-build.yaml` ``` #### Building from config file @@ -235,9 +234,9 @@ You may now run `llama stack configure my-tgi-stack` or `llama stack configure ~ - The config file will be of contents like the ones in `llama_stack/distributions/templates/`. ``` -$ cat llama_stack/distribution/templates/local-ollama-build.yaml +$ cat llama_stack/templates/ollama/build.yaml -name: local-ollama +name: ollama distribution_spec: description: Like local, but use ollama for running LLM inference providers: @@ -250,7 +249,7 @@ image_type: conda ``` ``` -llama stack build --config llama_stack/distribution/templates/local-ollama-build.yaml +llama stack build --config llama_stack/templates/ollama/build.yaml ``` #### How to build distribution with Docker image @@ -261,7 +260,7 @@ llama stack build --config llama_stack/distribution/templates/local-ollama-build To build a docker image, you may start off from a template and use the `--image-type docker` flag to specify `docker` as the build image type. ``` -llama stack build --template local --image-type docker --name docker-0 +llama stack build --template tgi --image-type docker ``` Alternatively, you may use a config file and set `image_type` to `docker` in our `-build.yaml` file, and run `llama stack build -build.yaml`. The `-build.yaml` will be of contents like: @@ -296,14 +295,14 @@ Build spec configuration saved at ~/.llama/distributions/docker/docker-local-bui ### Step 2. Configure After our distribution is built (either in form of docker or conda environment), we will run the following command to ``` -llama stack configure [ | | ] +llama stack configure [ | ] ``` - For `conda` environments: would be the generated build spec saved from Step 1. - For `docker` images downloaded from Dockerhub, you could also use as the argument. - Run `docker images` to check list of available images on your machine. ``` -$ llama stack configure 8b-instruct +$ llama stack configure tgi Configuring API: inference (meta-reference) Enter value for model (existing: Meta-Llama3.1-8B-Instruct) (required): @@ -332,10 +331,10 @@ Enter value for wolfram_api_key (optional): Configuring API: telemetry (console) -YAML configuration has been written to ~/.llama/builds/conda/8b-instruct-run.yaml +YAML configuration has been written to ~/.llama/builds/conda/tgi-run.yaml ``` -After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/8b-instruct-run.yaml` with the following contents. You may edit this file to change the settings. +After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/tgi-run.yaml` with the following contents. You may edit this file to change the settings. As you can see, we did basic configuration above and configured: - inference to run on model `Meta-Llama3.1-8B-Instruct` (obtained from `llama model list`) @@ -351,13 +350,13 @@ Note that all configurations as well as models are stored in `~/.llama` Now, let's start the Llama Stack Distribution Server. You will need the YAML configuration file which was written out at the end by the `llama stack configure` step. ``` -llama stack run 8b-instruct +llama stack run tgi ``` You should see the Llama Stack server start and print the APIs that it is supporting ``` -$ llama stack run 8b-instruct +$ llama stack run tgi > initializing model parallel with size 1 > initializing ddp with size 1 diff --git a/llama_stack/cli/stack/build.py b/llama_stack/cli/stack/build.py index 40fca4c6d..0ba39265b 100644 --- a/llama_stack/cli/stack/build.py +++ b/llama_stack/cli/stack/build.py @@ -62,17 +62,12 @@ class StackBuild(Subcommand): help="Show the available templates for building a Llama Stack distribution", ) - self.parser.add_argument( - "--name", - type=str, - help="Name of the Llama Stack build to override from template config. This name will be used as paths to store configuration files, build conda environments/docker images. If not specified, will use the name from the template config. ", - ) - self.parser.add_argument( "--image-type", type=str, help="Image Type to use for the build. This can be either conda or docker. If not specified, will use the image type from the template config.", choices=["conda", "docker"], + default="conda", ) def _run_stack_build_command(self, args: argparse.Namespace) -> None: @@ -91,15 +86,9 @@ class StackBuild(Subcommand): return if args.template: - if not args.name: - self.parser.error( - "You must specify a name for the build using --name when using a template" - ) - return available_templates = available_templates_specs() for build_config in available_templates: if build_config.name == args.template: - build_config.name = args.name if args.image_type: build_config.image_type = args.image_type else: @@ -114,30 +103,14 @@ class StackBuild(Subcommand): ) return - # try to see if we can find a pre-existing build config file through name - if args.name: - maybe_build_config = self._get_build_config_from_name(args) - if maybe_build_config: - cprint( - f"Building from existing build config for {args.name} in {str(maybe_build_config)}...", - "green", - ) - with open(maybe_build_config, "r") as f: - build_config = BuildConfig(**yaml.safe_load(f)) - self._run_stack_build_command_from_build_config(build_config) - return - if not args.config and not args.template: - if not args.name: - name = prompt( - "> Enter a name for your Llama Stack (e.g. my-local-stack): ", - validator=Validator.from_callable( - lambda x: len(x) > 0, - error_message="Name cannot be empty, please enter a name", - ), - ) - else: - name = args.name + name = prompt( + "> Enter a name for your Llama Stack (e.g. my-local-stack): ", + validator=Validator.from_callable( + lambda x: len(x) > 0, + error_message="Name cannot be empty, please enter a name", + ), + ) image_type = prompt( "> Enter the image type you want your Llama Stack to be built as (docker or conda): ", @@ -203,25 +176,6 @@ class StackBuild(Subcommand): return self._run_stack_build_command_from_build_config(build_config) - def _get_build_config_from_name(self, args: argparse.Namespace) -> Optional[Path]: - if os.getenv("CONDA_PREFIX", ""): - conda_dir = ( - Path(os.getenv("CONDA_PREFIX")).parent / f"llamastack-{args.name}" - ) - else: - cprint( - "Cannot find CONDA_PREFIX. Trying default conda path ~/.conda/envs...", - color="green", - ) - conda_dir = ( - Path(os.path.expanduser("~/.conda/envs")) / f"llamastack-{args.name}" - ) - build_config_file = Path(conda_dir) / f"{args.name}-build.yaml" - if build_config_file.exists(): - return build_config_file - - return None - def _run_stack_build_command_from_build_config( self, build_config: BuildConfig ) -> None: diff --git a/llama_stack/cli/stack/configure.py b/llama_stack/cli/stack/configure.py index 9ec3b4357..779bb90fc 100644 --- a/llama_stack/cli/stack/configure.py +++ b/llama_stack/cli/stack/configure.py @@ -55,19 +55,12 @@ class StackConfigure(Subcommand): docker_image = None build_config_file = Path(args.config) - if build_config_file.exists(): with open(build_config_file, "r") as f: build_config = BuildConfig(**yaml.safe_load(f)) self._configure_llama_distribution(build_config, args.output_dir) return - # if we get here, we need to try to find the conda build config file - cprint( - f"Could not find {build_config_file}. Trying conda build name instead...", - color="green", - ) - conda_dir = ( Path(os.path.expanduser("~/.conda/envs")) / f"llamastack-{args.config}" ) @@ -80,19 +73,14 @@ class StackConfigure(Subcommand): break build_config_file = Path(conda_dir) / f"{args.config}-build.yaml" - if build_config_file.exists(): with open(build_config_file, "r") as f: build_config = BuildConfig(**yaml.safe_load(f)) + cprint(f"Using {build_config_file}...", "green") self._configure_llama_distribution(build_config, args.output_dir) return - # if we get here, we need to try to find the docker image - cprint( - f"Could not find {build_config_file}. Trying docker image name instead...", - color="green", - ) docker_image = args.config builds_dir = BUILDS_BASE_DIR / ImageType.docker.value if args.output_dir: @@ -105,15 +93,10 @@ class StackConfigure(Subcommand): script_args = [script, docker_image, str(builds_dir)] return_code = run_with_pty(script_args) - - # we have regenerated the build config file with script, now check if it exists if return_code != 0: self.parser.error( f"Failed to configure container {docker_image} with return code {return_code}. Please run `llama stack build` first. " ) - return - - return def _configure_llama_distribution( self, diff --git a/llama_stack/distribution/configure.py b/llama_stack/distribution/configure.py index 7b8c32665..f91fbfc43 100644 --- a/llama_stack/distribution/configure.py +++ b/llama_stack/distribution/configure.py @@ -99,6 +99,13 @@ def configure_api_providers( cprint(f"Configuring API `{api_str}`...", "green", attrs=["bold"]) updated_providers = [] for i, provider_type in enumerate(plist): + if i >= 1: + others = ", ".join(plist[i:]) + print( + f"Not configuring other providers ({others}) interactively. Please edit the resulting YAML directly.\n" + ) + break + print(f"> Configuring provider `({provider_type})`") updated_providers.append( configure_single_provider(