docs: Improvements on provider_codegen for type hints and multi-line yaml descriptions

docs/docs/providers/agents/index.mdx

@@ -1,7 +1,8 @@
 ---
-description: "Agents
+description: |
+  Agents
 
-    APIs for creating and interacting with agentic systems."
+  APIs for creating and interacting with agentic systems.
 sidebar_label: Agents
 title: Agents
 ---
@@ -12,6 +13,6 @@ title: Agents
 
 Agents
 
-    APIs for creating and interacting with agentic systems.
+APIs for creating and interacting with agentic systems.
 
 This section contains documentation for all available providers for the **agents** API.

docs/docs/providers/agents/inline_meta-reference.mdx

@@ -14,7 +14,7 @@ Meta's reference implementation of an agent system that can use tools, access ve
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `persistence` | `<class 'inline.agents.meta_reference.config.AgentPersistenceConfig'>` | No |  |  |
+| `persistence` | `AgentPersistenceConfig` | No |  |  |
 
 ## Sample Configuration
 

docs/docs/providers/batches/index.mdx

@@ -1,14 +1,15 @@
 ---
-description: "The Batches API enables efficient processing of multiple requests in a single operation,
-    particularly useful for processing large datasets, batch evaluation workflows, and
-    cost-effective inference at scale.
+description: |
+  The Batches API enables efficient processing of multiple requests in a single operation,
+  particularly useful for processing large datasets, batch evaluation workflows, and
+  cost-effective inference at scale.
 
-    The API is designed to allow use of openai client libraries for seamless integration.
+  The API is designed to allow use of openai client libraries for seamless integration.
 
-    This API provides the following extensions:
-     - idempotent batch creation
+  This API provides the following extensions:
+   - idempotent batch creation
 
-    Note: This API is currently under active development and may undergo changes."
+  Note: This API is currently under active development and may undergo changes.
 sidebar_label: Batches
 title: Batches
 ---
@@ -18,14 +19,14 @@ title: Batches
 ## Overview
 
 The Batches API enables efficient processing of multiple requests in a single operation,
-    particularly useful for processing large datasets, batch evaluation workflows, and
-    cost-effective inference at scale.
+particularly useful for processing large datasets, batch evaluation workflows, and
+cost-effective inference at scale.
 
-    The API is designed to allow use of openai client libraries for seamless integration.
+The API is designed to allow use of openai client libraries for seamless integration.
 
-    This API provides the following extensions:
-     - idempotent batch creation
+This API provides the following extensions:
+ - idempotent batch creation
 
-    Note: This API is currently under active development and may undergo changes.
+Note: This API is currently under active development and may undergo changes.
 
 This section contains documentation for all available providers for the **batches** API.

docs/docs/providers/batches/inline_reference.mdx

@@ -14,9 +14,9 @@ Reference implementation of batches API with KVStore persistence.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `kvstore` | `<class 'llama_stack.core.storage.datatypes.KVStoreReference'>` | No |  | Configuration for the key-value store backend. |
-| `max_concurrent_batches` | `<class 'int'>` | No | 1 | Maximum number of concurrent batches to process simultaneously. |
-| `max_concurrent_requests_per_batch` | `<class 'int'>` | No | 10 | Maximum number of concurrent requests to process per batch. |
+| `kvstore` | `KVStoreReference` | No |  | Configuration for the key-value store backend. |
+| `max_concurrent_batches` | `int` | No | 1 | Maximum number of concurrent batches to process simultaneously. |
+| `max_concurrent_requests_per_batch` | `int` | No | 10 | Maximum number of concurrent requests to process per batch. |
 
 ## Sample Configuration
 

docs/docs/providers/datasetio/inline_localfs.mdx

@@ -14,7 +14,7 @@ Local filesystem-based dataset I/O provider for reading and writing datasets to
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `kvstore` | `<class 'llama_stack.core.storage.datatypes.KVStoreReference'>` | No |  |  |
+| `kvstore` | `KVStoreReference` | No |  |  |
 
 ## Sample Configuration
 

docs/docs/providers/datasetio/remote_huggingface.mdx

@@ -14,7 +14,7 @@ HuggingFace datasets provider for accessing and managing datasets from the Huggi
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `kvstore` | `<class 'llama_stack.core.storage.datatypes.KVStoreReference'>` | No |  |  |
+| `kvstore` | `KVStoreReference` | No |  |  |
 
 ## Sample Configuration
 

docs/docs/providers/datasetio/remote_nvidia.mdx

@@ -17,7 +17,7 @@ NVIDIA's dataset I/O provider for accessing datasets from NVIDIA's data platform
 | `api_key` | `str \| None` | No |  | The NVIDIA API key. |
 | `dataset_namespace` | `str \| None` | No | default | The NVIDIA dataset namespace. |
 | `project_id` | `str \| None` | No | test-project | The NVIDIA project ID. |
-| `datasets_url` | `<class 'str'>` | No | http://nemo.test | Base URL for the NeMo Dataset API |
+| `datasets_url` | `str` | No | http://nemo.test | Base URL for the NeMo Dataset API |
 
 ## Sample Configuration
 

docs/docs/providers/eval/index.mdx

@@ -1,7 +1,8 @@
 ---
-description: "Evaluations
+description: |
+  Evaluations
 
-    Llama Stack Evaluation API for running evaluations on model and agent candidates."
+  Llama Stack Evaluation API for running evaluations on model and agent candidates.
 sidebar_label: Eval
 title: Eval
 ---
@@ -12,6 +13,6 @@ title: Eval
 
 Evaluations
 
-    Llama Stack Evaluation API for running evaluations on model and agent candidates.
+Llama Stack Evaluation API for running evaluations on model and agent candidates.
 
 This section contains documentation for all available providers for the **eval** API.

docs/docs/providers/eval/inline_meta-reference.mdx

@@ -14,7 +14,7 @@ Meta's reference implementation of evaluation tasks with support for multiple la
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `kvstore` | `<class 'llama_stack.core.storage.datatypes.KVStoreReference'>` | No |  |  |
+| `kvstore` | `KVStoreReference` | No |  |  |
 
 ## Sample Configuration
 

docs/docs/providers/eval/remote_nvidia.mdx

@@ -14,7 +14,7 @@ NVIDIA's evaluation provider for running evaluation tasks on NVIDIA's platform.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `evaluator_url` | `<class 'str'>` | No | http://0.0.0.0:7331 | The url for accessing the evaluator service |
+| `evaluator_url` | `str` | No | http://0.0.0.0:7331 | The url for accessing the evaluator service |
 
 ## Sample Configuration
 

docs/docs/providers/files/index.mdx

@@ -1,7 +1,8 @@
 ---
-description: "Files
+description: |
+  Files
 
-    This API is used to upload documents that can be used with other Llama Stack APIs."
+  This API is used to upload documents that can be used with other Llama Stack APIs.
 sidebar_label: Files
 title: Files
 ---
@@ -12,6 +13,6 @@ title: Files
 
 Files
 
-    This API is used to upload documents that can be used with other Llama Stack APIs.
+This API is used to upload documents that can be used with other Llama Stack APIs.
 
 This section contains documentation for all available providers for the **files** API.

docs/docs/providers/files/inline_localfs.mdx

@@ -14,9 +14,9 @@ Local filesystem-based file storage provider for managing files and documents lo
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `storage_dir` | `<class 'str'>` | No |  | Directory to store uploaded files |
-| `metadata_store` | `<class 'llama_stack.core.storage.datatypes.SqlStoreReference'>` | No |  | SQL store configuration for file metadata |
-| `ttl_secs` | `<class 'int'>` | No | 31536000 |  |
+| `storage_dir` | `str` | No |  | Directory to store uploaded files |
+| `metadata_store` | `SqlStoreReference` | No |  | SQL store configuration for file metadata |
+| `ttl_secs` | `int` | No | 31536000 |  |
 
 ## Sample Configuration
 

docs/docs/providers/files/remote_openai.mdx

@@ -14,8 +14,8 @@ OpenAI Files API provider for managing files through OpenAI's native file storag
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `api_key` | `<class 'str'>` | No |  | OpenAI API key for authentication |
-| `metadata_store` | `<class 'llama_stack.core.storage.datatypes.SqlStoreReference'>` | No |  | SQL store configuration for file metadata |
+| `api_key` | `str` | No |  | OpenAI API key for authentication |
+| `metadata_store` | `SqlStoreReference` | No |  | SQL store configuration for file metadata |
 
 ## Sample Configuration
 

docs/docs/providers/files/remote_s3.mdx

@@ -14,13 +14,13 @@ AWS S3-based file storage provider for scalable cloud file management with metad
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `bucket_name` | `<class 'str'>` | No |  | S3 bucket name to store files |
-| `region` | `<class 'str'>` | No | us-east-1 | AWS region where the bucket is located |
+| `bucket_name` | `str` | No |  | S3 bucket name to store files |
+| `region` | `str` | No | us-east-1 | AWS region where the bucket is located |
 | `aws_access_key_id` | `str \| None` | No |  | AWS access key ID (optional if using IAM roles) |
 | `aws_secret_access_key` | `str \| None` | No |  | AWS secret access key (optional if using IAM roles) |
 | `endpoint_url` | `str \| None` | No |  | Custom S3 endpoint URL (for MinIO, LocalStack, etc.) |
-| `auto_create_bucket` | `<class 'bool'>` | No | False | Automatically create the S3 bucket if it doesn't exist |
-| `metadata_store` | `<class 'llama_stack.core.storage.datatypes.SqlStoreReference'>` | No |  | SQL store configuration for file metadata |
+| `auto_create_bucket` | `bool` | No | False | Automatically create the S3 bucket if it doesn't exist |
+| `metadata_store` | `SqlStoreReference` | No |  | SQL store configuration for file metadata |
 
 ## Sample Configuration
 

docs/docs/providers/inference/index.mdx

@@ -1,12 +1,13 @@
 ---
-description: "Inference
+description: |
+  Inference
 
-    Llama Stack Inference API for generating completions, chat completions, and embeddings.
+  Llama Stack Inference API for generating completions, chat completions, and embeddings.
 
-    This API provides the raw interface to the underlying models. Three kinds of models are supported:
-    - LLM models: these models generate \"raw\" and \"chat\" (conversational) completions.
-    - Embedding models: these models generate embeddings to be used for semantic search.
-    - Rerank models: these models reorder the documents based on their relevance to a query."
+  This API provides the raw interface to the underlying models. Three kinds of models are supported:
+  - LLM models: these models generate "raw" and "chat" (conversational) completions.
+  - Embedding models: these models generate embeddings to be used for semantic search.
+  - Rerank models: these models reorder the documents based on their relevance to a query.
 sidebar_label: Inference
 title: Inference
 ---
@@ -17,11 +18,11 @@ title: Inference
 
 Inference
 
-    Llama Stack Inference API for generating completions, chat completions, and embeddings.
+Llama Stack Inference API for generating completions, chat completions, and embeddings.
 
-    This API provides the raw interface to the underlying models. Three kinds of models are supported:
-    - LLM models: these models generate "raw" and "chat" (conversational) completions.
-    - Embedding models: these models generate embeddings to be used for semantic search.
-    - Rerank models: these models reorder the documents based on their relevance to a query.
+This API provides the raw interface to the underlying models. Three kinds of models are supported:
+- LLM models: these models generate "raw" and "chat" (conversational) completions.
+- Embedding models: these models generate embeddings to be used for semantic search.
+- Rerank models: these models reorder the documents based on their relevance to a query.
 
 This section contains documentation for all available providers for the **inference** API.

docs/docs/providers/inference/inline_meta-reference.mdx

@@ -16,12 +16,12 @@ Meta's reference implementation of inference with support for various model form
 |-------|------|----------|---------|-------------|
 | `model` | `str \| None` | No |  |  |
 | `torch_seed` | `int \| None` | No |  |  |
-| `max_seq_len` | `<class 'int'>` | No | 4096 |  |
-| `max_batch_size` | `<class 'int'>` | No | 1 |  |
+| `max_seq_len` | `int` | No | 4096 |  |
+| `max_batch_size` | `int` | No | 1 |  |
 | `model_parallel_size` | `int \| None` | No |  |  |
-| `create_distributed_process_group` | `<class 'bool'>` | No | True |  |
+| `create_distributed_process_group` | `bool` | No | True |  |
 | `checkpoint_dir` | `str \| None` | No |  |  |
-| `quantization` | `Bf16QuantizationConfig \| Fp8QuantizationConfig \| Int4QuantizationConfig, annotation=NoneType, required=True, discriminator='type'` | No |  |  |
+| `quantization` | `Bf16QuantizationConfig \| Fp8QuantizationConfig \| Int4QuantizationConfig \| None` | No |  |  |
 
 ## Sample Configuration
 

docs/docs/providers/inference/remote_anthropic.mdx

@@ -14,9 +14,9 @@ Anthropic inference provider for accessing Claude models and Anthropic's AI serv
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
-| `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically from the provider |
-| `api_key` | `pydantic.types.SecretStr \| None` | No |  | Authentication credential for the provider |
+| `allowed_models` | `list[str] \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
+| `refresh_models` | `bool` | No | False | Whether to refresh models periodically from the provider |
+| `api_key` | `SecretStr \| None` | No |  | Authentication credential for the provider |
 
 ## Sample Configuration
 

docs/docs/providers/inference/remote_azure.mdx

@@ -21,10 +21,10 @@ https://learn.microsoft.com/en-us/azure/ai-foundry/openai/overview
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
-| `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically from the provider |
-| `api_key` | `pydantic.types.SecretStr \| None` | No |  | Authentication credential for the provider |
-| `api_base` | `<class 'pydantic.networks.HttpUrl'>` | No |  | Azure API base for Azure (e.g., https://your-resource-name.openai.azure.com) |
+| `allowed_models` | `list[str] \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
+| `refresh_models` | `bool` | No | False | Whether to refresh models periodically from the provider |
+| `api_key` | `SecretStr \| None` | No |  | Authentication credential for the provider |
+| `api_base` | `HttpUrl` | No |  | Azure API base for Azure (e.g., https://your-resource-name.openai.azure.com) |
 | `api_version` | `str \| None` | No |  | Azure API version for Azure (e.g., 2024-12-01-preview) |
 | `api_type` | `str \| None` | No | azure | Azure API type for Azure (e.g., azure) |
 

docs/docs/providers/inference/remote_bedrock.mdx

@@ -14,10 +14,10 @@ AWS Bedrock inference provider using OpenAI compatible endpoint.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
-| `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically from the provider |
-| `api_key` | `pydantic.types.SecretStr \| None` | No |  | Authentication credential for the provider |
-| `region_name` | `<class 'str'>` | No | us-east-2 | AWS Region for the Bedrock Runtime endpoint |
+| `allowed_models` | `list[str] \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
+| `refresh_models` | `bool` | No | False | Whether to refresh models periodically from the provider |
+| `api_key` | `SecretStr \| None` | No |  | Authentication credential for the provider |
+| `region_name` | `str` | No | us-east-2 | AWS Region for the Bedrock Runtime endpoint |
 
 ## Sample Configuration
 

docs/docs/providers/inference/remote_cerebras.mdx

@@ -14,10 +14,10 @@ Cerebras inference provider for running models on Cerebras Cloud platform.
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
-| `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically from the provider |
-| `api_key` | `pydantic.types.SecretStr \| None` | No |  | Authentication credential for the provider |
-| `base_url` | `<class 'str'>` | No | https://api.cerebras.ai | Base URL for the Cerebras API |
+| `allowed_models` | `list[str] \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
+| `refresh_models` | `bool` | No | False | Whether to refresh models periodically from the provider |
+| `api_key` | `SecretStr \| None` | No |  | Authentication credential for the provider |
+| `base_url` | `str` | No | https://api.cerebras.ai | Base URL for the Cerebras API |
 
 ## Sample Configuration
 

docs/docs/providers/inference/remote_databricks.mdx

@@ -14,9 +14,9 @@ Databricks inference provider for running models on Databricks' unified analytic
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
-| `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically from the provider |
-| `api_token` | `pydantic.types.SecretStr \| None` | No |  | The Databricks API token |
+| `allowed_models` | `list[str] \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
+| `refresh_models` | `bool` | No | False | Whether to refresh models periodically from the provider |
+| `api_token` | `SecretStr \| None` | No |  | The Databricks API token |
 | `url` | `str \| None` | No |  | The URL for the Databricks model serving endpoint |
 
 ## Sample Configuration

docs/docs/providers/inference/remote_fireworks.mdx

@@ -14,10 +14,10 @@ Fireworks AI inference provider for Llama models and other AI models on the Fire
 
 | Field | Type | Required | Default | Description |
 |-------|------|----------|---------|-------------|
-| `allowed_models` | `list[str \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
-| `refresh_models` | `<class 'bool'>` | No | False | Whether to refresh models periodically from the provider |
-| `api_key` | `pydantic.types.SecretStr \| None` | No |  | Authentication credential for the provider |
-| `url` | `<class 'str'>` | No | https://api.fireworks.ai/inference/v1 | The URL for the Fireworks server |
+| `allowed_models` | `list[str] \| None` | No |  | List of models that should be registered with the model registry. If None, all models are allowed. |
+| `refresh_models` | `bool` | No | False | Whether to refresh models periodically from the provider |
+| `api_key` | `SecretStr \| None` | No |  | Authentication credential for the provider |
+| `url` | `str` | No | https://api.fireworks.ai/inference/v1 | The URL for the Fireworks server |
 
 ## Sample Configuration