Merge branch 'main' into openai-vector-store/qdrant

docs/source/apis/external.md

@@ -355,7 +355,7 @@ server:
 8. Run the server:
 
 ```bash
-python -m llama_stack.distribution.server.server --yaml-config ~/.llama/run-byoa.yaml
+python -m llama_stack.core.server.server --yaml-config ~/.llama/run-byoa.yaml
 ```
 
 9. Test the API:

docs/source/building_applications/playground/index.md

@@ -103,5 +103,5 @@ llama stack run together
 
 2. Start Streamlit UI
 ```bash
-uv run --with ".[ui]" streamlit run llama_stack/distribution/ui/app.py
+uv run --with ".[ui]" streamlit run llama_stack.core/ui/app.py
 ```

docs/source/deploying/kubernetes_deployment.md

@@ -174,7 +174,7 @@ spec:
       - name: llama-stack
         image: localhost/llama-stack-run-k8s:latest
         imagePullPolicy: IfNotPresent
-        command: ["python", "-m", "llama_stack.distribution.server.server", "--config", "/app/config.yaml"]
+        command: ["python", "-m", "llama_stack.core.server.server", "--config", "/app/config.yaml"]
         ports:
           - containerPort: 5000
         volumeMounts:

docs/source/distributions/building_distro.md

@@ -59,7 +59,7 @@ Build a Llama stack container
 
 options:
   -h, --help            show this help message and exit
-  --config CONFIG       Path to a config file to use for the build. You can find example configs in llama_stack/distributions/**/build.yaml. If this argument is not provided, you will
+  --config CONFIG       Path to a config file to use for the build. You can find example configs in llama_stack.cores/**/build.yaml. If this argument is not provided, you will
                         be prompted to enter information interactively (default: None)
   --template TEMPLATE   Name of the example template config to use for build. You may use `llama stack build --list-templates` to check out the available templates (default: None)
   --list-templates      Show the available templates for building a Llama Stack distribution (default: False)

docs/source/distributions/importing_as_library.md

@@ -10,7 +10,7 @@ llama stack build --template starter --image-type venv
 ```
 
 ```python
-from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
+from llama_stack.core.library_client import LlamaStackAsLibraryClient
 
 client = LlamaStackAsLibraryClient(
     "starter",

docs/source/distributions/k8s/stack-k8s.yaml.template

@@ -52,7 +52,7 @@ spec:
           value: "${SAFETY_MODEL}"
         - name: TAVILY_SEARCH_API_KEY
           value: "${TAVILY_SEARCH_API_KEY}"
-        command: ["python", "-m", "llama_stack.distribution.server.server", "--config", "/etc/config/stack_run_config.yaml", "--port", "8321"]
+        command: ["python", "-m", "llama_stack.core.server.server", "--config", "/etc/config/stack_run_config.yaml", "--port", "8321"]
         ports:
           - containerPort: 8321
         volumeMounts:

docs/source/providers/external/external-providers-guide.md

@@ -1,9 +1,4 @@
-# External Providers Guide
-
-Llama Stack supports external providers that live outside of the main codebase. This allows you to:
-- Create and maintain your own providers independently
-- Share providers with others without contributing to the main codebase
-- Keep provider-specific code separate from the core Llama Stack code
+# Creating External Providers
 
 ## Configuration
 
@@ -55,17 +50,6 @@ Llama Stack supports two types of external providers:
 1. **Remote Providers**: Providers that communicate with external services (e.g., cloud APIs)
 2. **Inline Providers**: Providers that run locally within the Llama Stack process
 
-## Known External Providers
-
-Here's a list of known external providers that you can use with Llama Stack:
-
-| Name | Description | API | Type | Repository |
-|------|-------------|-----|------|------------|
-| KubeFlow Training | Train models with KubeFlow | Post Training | Remote | [llama-stack-provider-kft](https://github.com/opendatahub-io/llama-stack-provider-kft) |
-| KubeFlow Pipelines | Train models with KubeFlow Pipelines | Post Training | Inline **and** Remote | [llama-stack-provider-kfp-trainer](https://github.com/opendatahub-io/llama-stack-provider-kfp-trainer) |
-| RamaLama | Inference models with RamaLama | Inference | Remote | [ramalama-stack](https://github.com/containers/ramalama-stack) |
-| TrustyAI LM-Eval | Evaluate models with TrustyAI LM-Eval | Eval | Remote | [llama-stack-provider-lmeval](https://github.com/trustyai-explainability/llama-stack-provider-lmeval) |
-
 ### Remote Provider Specification
 
 Remote providers are used when you need to communicate with external services. Here's an example for a custom Ollama provider:
@@ -119,9 +103,9 @@ container_image: custom-vector-store:latest  # optional
 - `provider_data_validator`: Optional validator for provider data
 - `container_image`: Optional container image to use instead of pip packages
 
-## Required Implementation
+## Required Fields
 
-## All Providers
+### All Providers
 
 All providers must contain a `get_provider_spec` function in their `provider` module. This is a standardized structure that Llama Stack expects and is necessary for getting things such as the config class. The `get_provider_spec` method returns a structure identical to the `adapter`. An example function may look like:
 
@@ -146,7 +130,7 @@ def get_provider_spec() -> ProviderSpec:
     )
 ```
 
-### Remote Providers
+#### Remote Providers
 
 Remote providers must expose a `get_adapter_impl()` function in their module that takes two arguments:
 1. `config`: An instance of the provider's config class
@@ -162,7 +146,7 @@ async def get_adapter_impl(
     return OllamaInferenceAdapter(config)
 ```
 
-### Inline Providers
+#### Inline Providers
 
 Inline providers must expose a `get_provider_impl()` function in their module that takes two arguments:
 1. `config`: An instance of the provider's config class
@@ -189,7 +173,40 @@ Version: 0.1.0
 Location: /path/to/venv/lib/python3.10/site-packages
 ```
 
-## Example using `external_providers_dir`: Custom Ollama Provider
+## Best Practices
+
+1. **Package Naming**: Use the prefix `llama-stack-provider-` for your provider packages to make them easily identifiable.
+
+2. **Version Management**: Keep your provider package versioned and compatible with the Llama Stack version you're using.
+
+3. **Dependencies**: Only include the minimum required dependencies in your provider package.
+
+4. **Documentation**: Include clear documentation in your provider package about:
+   - Installation requirements
+   - Configuration options
+   - Usage examples
+   - Any limitations or known issues
+
+5. **Testing**: Include tests in your provider package to ensure it works correctly with Llama Stack.
+You can refer to the [integration tests
+guide](https://github.com/meta-llama/llama-stack/blob/main/tests/integration/README.md) for more
+information. Execute the test for the Provider type you are developing.
+
+## Troubleshooting
+
+If your external provider isn't being loaded:
+
+1. Check that `module` points to a published pip package with a top level `provider` module including `get_provider_spec`.
+1. Check that the `external_providers_dir` path is correct and accessible.
+2. Verify that the YAML files are properly formatted.
+3. Ensure all required Python packages are installed.
+4. Check the Llama Stack server logs for any error messages - turn on debug logging to get more
+   information using `LLAMA_STACK_LOGGING=all=debug`.
+5. Verify that the provider package is installed in your Python environment if using `external_providers_dir`.
+
+## Examples
+
+### Example using `external_providers_dir`: Custom Ollama Provider
 
 Here's a complete example of creating and using a custom Ollama provider:
 
@@ -241,7 +258,7 @@ external_providers_dir: ~/.llama/providers.d/
 The provider will now be available in Llama Stack with the type `remote::custom_ollama`.
 
 
-## Example using `module`: ramalama-stack
+### Example using `module`: ramalama-stack
 
 [ramalama-stack](https://github.com/containers/ramalama-stack) is a recognized external provider that supports installation via module.
 
@@ -266,35 +283,4 @@ additional_pip_packages:
 
 No other steps are required other than `llama stack build` and `llama stack run`. The build process will use `module` to install all of the provider dependencies, retrieve the spec, etc.
 
-The provider will now be available in Llama Stack with the type `remote::ramalama`.
-
-## Best Practices
-
-1. **Package Naming**: Use the prefix `llama-stack-provider-` for your provider packages to make them easily identifiable.
-
-2. **Version Management**: Keep your provider package versioned and compatible with the Llama Stack version you're using.
-
-3. **Dependencies**: Only include the minimum required dependencies in your provider package.
-
-4. **Documentation**: Include clear documentation in your provider package about:
-   - Installation requirements
-   - Configuration options
-   - Usage examples
-   - Any limitations or known issues
-
-5. **Testing**: Include tests in your provider package to ensure it works correctly with Llama Stack.
-You can refer to the [integration tests
-guide](https://github.com/meta-llama/llama-stack/blob/main/tests/integration/README.md) for more
-information. Execute the test for the Provider type you are developing.
-
-## Troubleshooting
-
-If your external provider isn't being loaded:
-
-1. Check that `module` points to a published pip package with a top level `provider` module including `get_provider_spec`.
-1. Check that the `external_providers_dir` path is correct and accessible.
-2. Verify that the YAML files are properly formatted.
-3. Ensure all required Python packages are installed.
-4. Check the Llama Stack server logs for any error messages - turn on debug logging to get more
-   information using `LLAMA_STACK_LOGGING=all=debug`.
-5. Verify that the provider package is installed in your Python environment if using `external_providers_dir`.
+The provider will now be available in Llama Stack with the type `remote::ramalama`.

docs/source/providers/external/external-providers-list.md

@@ -0,0 +1,10 @@
+# Known External Providers
+
+Here's a list of known external providers that you can use with Llama Stack:
+
+| Name | Description | API | Type | Repository |
+|------|-------------|-----|------|------------|
+| KubeFlow Training | Train models with KubeFlow | Post Training | Remote | [llama-stack-provider-kft](https://github.com/opendatahub-io/llama-stack-provider-kft) |
+| KubeFlow Pipelines | Train models with KubeFlow Pipelines | Post Training | Inline **and** Remote | [llama-stack-provider-kfp-trainer](https://github.com/opendatahub-io/llama-stack-provider-kfp-trainer) |
+| RamaLama | Inference models with RamaLama | Inference | Remote | [ramalama-stack](https://github.com/containers/ramalama-stack) |
+| TrustyAI LM-Eval | Evaluate models with TrustyAI LM-Eval | Eval | Remote | [llama-stack-provider-lmeval](https://github.com/trustyai-explainability/llama-stack-provider-lmeval) |

docs/source/providers/external/index.md

@@ -0,0 +1,13 @@
+# External Providers
+
+Llama Stack supports external providers that live outside of the main codebase. This allows you to:
+- Create and maintain your own providers independently
+- Share providers with others without contributing to the main codebase
+- Keep provider-specific code separate from the core Llama Stack code
+
+```{toctree}
+:maxdepth: 1
+
+external-providers-list
+external-providers-guide
+```

docs/source/providers/index.md

@@ -15,7 +15,7 @@ Importantly, Llama Stack always strives to provide at least one fully inline pro
 ```{toctree}
 :maxdepth: 1
 
-external
+external/index
 openai
 inference/index
 agents/index

docs/source/providers/post_training/inline_huggingface.md

@@ -24,6 +24,10 @@ HuggingFace-based post-training provider for fine-tuning models using the Huggin
 | `weight_decay` | `<class 'float'>` | No | 0.01 |  |
 | `dataloader_num_workers` | `<class 'int'>` | No | 4 |  |
 | `dataloader_pin_memory` | `<class 'bool'>` | No | True |  |
+| `dpo_beta` | `<class 'float'>` | No | 0.1 |  |
+| `use_reference_model` | `<class 'bool'>` | No | True |  |
+| `dpo_loss_type` | `Literal['sigmoid', 'hinge', 'ipo', 'kto_pair'` | No | sigmoid |  |
+| `dpo_output_dir` | `<class 'str'>` | No | ./checkpoints/dpo |  |
 
 ## Sample Configuration