docs: fix broken links

docs/docs/advanced_apis/post_training.mdx

@@ -302,4 +302,4 @@ customizer_url: ${env.NVIDIA_CUSTOMIZER_URL:=http://nemo.test}
 
 - Check out the [Building Applications - Fine-tuning](../building_applications/index.mdx) guide for application-level examples
 - See the [Providers](../providers/post_training/index.mdx) section for detailed provider documentation
-- Review the [API Reference](../api_reference/post_training.mdx) for complete API documentation
+- Review the [API Reference](../advanced_apis/post_training.mdx) for complete API documentation

docs/docs/advanced_apis/scoring.mdx

@@ -189,5 +189,5 @@ The Scoring API works closely with the [Evaluation](./evaluation.mdx) API to pro
 
 - Check out the [Evaluation](./evaluation.mdx) guide for running complete evaluations
 - See the [Building Applications - Evaluation](../building_applications/evals.mdx) guide for application examples
-- Review the [Evaluation Reference](../references/evals_reference.mdx) for comprehensive scoring function usage
+- Review the [Evaluation Reference](../references/evals_reference/) for comprehensive scoring function usage
 - Explore the [Evaluation Concepts](../concepts/evaluation_concepts.mdx) for detailed conceptual information

docs/docs/building_applications/index.mdx

@@ -20,23 +20,23 @@ The best way to get started is to look at this comprehensive notebook which walk
 Here are the key topics that will help you build effective AI applications:
 
 ### 🤖 **Agent Development**
-- **[Agent Framework](./agent)** - Understand the components and design patterns of the Llama Stack agent framework
-- **[Agent Execution Loop](./agent_execution_loop)** - How agents process information, make decisions, and execute actions
-- **[Agents vs Responses API](./responses_vs_agents)** - Learn when to use each API for different use cases
+- **[Agent Framework](./agent.mdx)** - Understand the components and design patterns of the Llama Stack agent framework
+- **[Agent Execution Loop](./agent_execution_loop.mdx)** - How agents process information, make decisions, and execute actions
+- **[Agents vs Responses API](./responses_vs_agents.mdx)** - Learn when to use each API for different use cases
 
 ### 📚 **Knowledge Integration**
-- **[RAG (Retrieval-Augmented Generation)](./rag)** - Enhance your agents with external knowledge through retrieval mechanisms
+- **[RAG (Retrieval-Augmented Generation)](./rag.mdx)** - Enhance your agents with external knowledge through retrieval mechanisms
 
 ### 🛠️ **Capabilities & Extensions**
-- **[Tools](./tools)** - Extend your agents' capabilities by integrating with external tools and APIs
+- **[Tools](./tools.mdx)** - Extend your agents' capabilities by integrating with external tools and APIs
 
 ### 📊 **Quality & Monitoring**
-- **[Evaluations](./evals)** - Evaluate your agents' effectiveness and identify areas for improvement
-- **[Telemetry](./telemetry)** - Monitor and analyze your agents' performance and behavior
-- **[Safety](./safety)** - Implement guardrails and safety measures to ensure responsible AI behavior
+- **[Evaluations](./evals.mdx)** - Evaluate your agents' effectiveness and identify areas for improvement
+- **[Telemetry](./telemetry.mdx)** - Monitor and analyze your agents' performance and behavior
+- **[Safety](./safety.mdx)** - Implement guardrails and safety measures to ensure responsible AI behavior
 
 ### 🎮 **Interactive Development**
-- **[Playground](./playground)** - Interactive environment for testing and developing applications
+- **[Playground](./playground.mdx)** - Interactive environment for testing and developing applications
 
 ## Application Patterns
 
@@ -77,7 +77,7 @@ Build production-ready systems with:
 
 ## Related Resources
 
-- **[Getting Started](/docs/getting-started/)** - Basic setup and concepts
+- **[Getting Started](/docs/getting-started/quickstart)** - Basic setup and concepts
 - **[Providers](/docs/providers/)** - Available AI service providers
 - **[Distributions](/docs/distributions/)** - Pre-configured deployment packages
-- **[API Reference](/docs/api/)** - Complete API documentation
+- **[API Reference](/docs/api/llama-stack-specification)** - Complete API documentation

docs/docs/building_applications/playground.mdx

@@ -291,9 +291,9 @@ llama stack run meta-reference
 
 ## Related Resources
 
-- **[Getting Started Guide](/docs/getting-started)** - Complete setup and introduction
+- **[Getting Started Guide](/docs/getting-started/quickstart)** - Complete setup and introduction
 - **[Core Concepts](/docs/concepts)** - Understanding Llama Stack fundamentals
 - **[Agents](./agent)** - Building intelligent agents
 - **[RAG (Retrieval Augmented Generation)](./rag)** - Knowledge-enhanced applications
 - **[Evaluations](./evals)** - Comprehensive evaluation framework
-- **[API Reference](/docs/api-reference)** - Complete API documentation
+- **[API Reference](/docs/api/llama-stack-specification)** - Complete API documentation

docs/docs/concepts/apis/external.mdx

@@ -2,7 +2,7 @@
 title: External APIs
 description: Understanding external APIs in Llama Stack
 sidebar_label: External APIs
-sidebar_position: 4
+sidebar_position: 3
 ---
 # External APIs
 

docs/docs/concepts/distributions.mdx

@@ -2,7 +2,7 @@
 title: Distributions
 description: Pre-packaged provider configurations for different deployment scenarios
 sidebar_label: Distributions
-sidebar_position: 5
+sidebar_position: 3
 ---
 
 # Distributions

docs/docs/concepts/evaluation_concepts.mdx

@@ -0,0 +1,78 @@
+---
+title: Evaluation Concepts
+description: Running evaluations on Llama Stack
+sidebar_label: Evaluation Concepts
+sidebar_position: 5
+---
+
+# Evaluation Concepts
+
+The Llama Stack Evaluation flow allows you to run evaluations on your GenAI application datasets or pre-registered benchmarks.
+
+We introduce a set of APIs in Llama Stack for supporting running evaluations of LLM applications:
+- `/datasetio` + `/datasets` API
+- `/scoring` + `/scoring_functions` API
+- `/eval` + `/benchmarks` API
+
+This guide goes over the sets of APIs and developer experience flow of using Llama Stack to run evaluations for different use cases. Checkout our Colab notebook on working examples with evaluations [here](https://colab.research.google.com/drive/10CHyykee9j2OigaIcRv47BKG9mrNm0tJ?usp=sharing).
+
+The Evaluation APIs are associated with a set of Resources. Please visit the Resources section in our [Core Concepts](./index.mdx) guide for better high-level understanding.
+
+- **DatasetIO**: defines interface with datasets and data loaders.
+  - Associated with `Dataset` resource.
+- **Scoring**: evaluate outputs of the system.
+  - Associated with `ScoringFunction` resource. We provide a suite of out-of-the box scoring functions and also the ability for you to add custom evaluators. These scoring functions are the core part of defining an evaluation task to output evaluation metrics.
+- **Eval**: generate outputs (via Inference or Agents) and perform scoring.
+  - Associated with `Benchmark` resource.
+
+## Open-benchmark Eval
+
+### List of open-benchmarks Llama Stack support
+
+Llama stack pre-registers several popular open-benchmarks to easily evaluate model perfomance via CLI.
+
+The list of open-benchmarks we currently support:
+- [MMLU-COT](https://arxiv.org/abs/2009.03300) (Measuring Massive Multitask Language Understanding): Benchmark designed to comprehensively evaluate the breadth and depth of a model's academic and professional understanding
+- [GPQA-COT](https://arxiv.org/abs/2311.12022) (A Graduate-Level Google-Proof Q&A Benchmark): A challenging benchmark of 448 multiple-choice questions written by domain experts in biology, physics, and chemistry.
+- [SimpleQA](https://openai.com/index/introducing-simpleqa/): Benchmark designed to access models to answer short, fact-seeking questions.
+- [MMMU](https://arxiv.org/abs/2311.16502) (A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI)]: Benchmark designed to evaluate multimodal models.
+
+You can follow this [contributing guide](../references/evals_reference.mdx#open-benchmark-contributing-guide) to add more open-benchmarks to Llama Stack
+
+### Run evaluation on open-benchmarks via CLI
+
+We have built-in functionality to run the supported open-benckmarks using llama-stack-client CLI
+
+#### Spin up Llama Stack server
+
+Spin up llama stack server with 'open-benchmark' template
+```bash
+llama stack run llama_stack/distributions/open-benchmark/run.yaml
+```
+
+#### Run eval CLI
+There are 3 necessary inputs to run a benchmark eval
+- `list of benchmark_ids`: The list of benchmark ids to run evaluation on
+- `model-id`: The model id to evaluate on
+- `output_dir`: Path to store the evaluate results
+
+```bash
+llama-stack-client eval run-benchmark <benchmark_id_1> <benchmark_id_2> ... \
+--model_id <model id to evaluate on> \
+--output_dir <directory to store the evaluate results>
+```
+
+You can run
+```bash
+llama-stack-client eval run-benchmark help
+```
+to see the description of all the flags that eval run-benchmark has
+
+In the output log, you can find the file path that has your evaluation results. Open that file and you can see you aggregate
+evaluation results over there.
+
+## What's Next?
+
+- Check out our Colab notebook on working examples with running benchmark evaluations [here](https://colab.research.google.com/github/meta-llama/llama-stack/blob/main/docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb#scrollTo=mxLCsP4MvFqP).
+- Check out our [Building Applications - Evaluation](../building_applications/evals.mdx) guide for more details on how to use the Evaluation APIs to evaluate your applications.
+- Check out our [Evaluation Reference](../references/evals_reference.mdx) for more details on the APIs.

docs/docs/concepts/index.mdx

@@ -1,4 +1,9 @@
-# Core Concepts
+---
+title: Core Concepts
+description: Understanding Llama Stack's service-oriented philosophy and key concepts
+sidebar_label: Overview
+sidebar_position: 1
+---
 
 Given Llama Stack's service-oriented philosophy, a few concepts and workflows arise which may not feel completely natural in the LLM landscape, especially if you are coming with a background in other frameworks.
 
@@ -6,38 +11,21 @@ Given Llama Stack's service-oriented philosophy, a few concepts and workflows ar
 
 This section covers the fundamental concepts of Llama Stack:
 
-- **[Architecture](./architecture.md)** - Learn about Llama Stack's architectural design and principles
-- **[APIs](./apis/index.mdx)** - Understanding the core APIs and their stability levels
-  - [API Overview](./apis/index.mdx) - Core APIs available in Llama Stack
-  - [API Providers](./apis/api_providers.mdx) - How providers implement APIs
-  - [API Stability Leveling](./apis/api_leveling.mdx) - API stability and versioning
-- **[Distributions](./distributions.md)** - Pre-configured deployment packages
-- **[Resources](./resources.md)** - Understanding Llama Stack resources and their lifecycle
-- **[External Integration](./external.md)** - Integrating with external services and providers
+- **[Architecture](architecture.mdx)** - Learn about Llama Stack's architectural design and principles
+- **[APIs](apis)** - Understanding the core APIs and their stability levels
+  - [API Overview](apis/index.mdx) - Core APIs available in Llama Stack
+  - [API Providers](apis/api_providers.mdx) - How providers implement APIs
+  - [External APIs](apis/external.mdx) - External APIs available in Llama Stack
+  - [API Stability Leveling](apis/api_leveling.mdx) - API stability and versioning
+- **[Distributions](distributions.mdx)** - Pre-configured deployment packages
+- **[Resources](resources.mdx)** - Understanding Llama Stack resources and their lifecycle
 
 ## Getting Started
 
 If you're new to Llama Stack, we recommend starting with:
 
-1. **[Architecture](./architecture.md)** - Understand the overall system design
-2. **[APIs](./apis/index.mdx)** - Learn about the available APIs and their purpose
-3. **[Distributions](./distributions.md)** - Choose a pre-configured setup for your use case
+1. **[Architecture](architecture.mdx)** - Understand the overall system design
+2. **[APIs](apis/index.mdx)** - Learn about the available APIs and their purpose
+3. **[Distributions](distributions.mdx)** - Choose a pre-configured setup for your use case
 
-Each concept builds upon the previous ones to give you a comprehensive understanding of how Llama Stack works and how to use it effectively.---
-title: Core Concepts
-description: Understanding Llama Stack's service-oriented philosophy and key concepts
-sidebar_label: Overview
-sidebar_position: 1
----
-
-# Core Concepts
-
-Given Llama Stack's service-oriented philosophy, a few concepts and workflows arise which may not feel completely natural in the LLM landscape, especially if you are coming with a background in other frameworks.
-
-This section covers the key concepts you need to understand to work effectively with Llama Stack:
-
-- **[Architecture](./architecture)** - Llama Stack's service-oriented design and benefits
-- **[APIs](./apis)** - Available REST APIs and planned capabilities
-- **[API Providers](./api_providers)** - Remote vs inline provider implementations
-- **[Distributions](./distributions)** - Pre-packaged provider configurations
-- **[Resources](./resources)** - Resource federation and registration
+Each concept builds upon the previous ones to give you a comprehensive understanding of how Llama Stack works and how to use it effectively.

docs/docs/distributions/self_hosted_distro/starter.md

@@ -36,25 +36,25 @@ The starter distribution includes a comprehensive set of inference providers:
 
 ### Hosted Providers
 - **[OpenAI](https://openai.com/api/)**: GPT-4, GPT-3.5, O1, O3, O4 models and text embeddings -
-  provider ID: `openai` - reference documentation: [openai](../../providers/inference/remote_openai.md)
+  provider ID: `openai` - reference documentation: [openai](../../providers/inference/remote_openai)
 - **[Fireworks](https://fireworks.ai/)**: Llama 3.1, 3.2, 3.3, 4 Scout, 4 Maverick models and
-  embeddings - provider ID: `fireworks` - reference documentation: [fireworks](../../providers/inference/remote_fireworks.md)
+  embeddings - provider ID: `fireworks` - reference documentation: [fireworks](../../providers/inference/remote_fireworks)
 - **[Together](https://together.ai/)**: Llama 3.1, 3.2, 3.3, 4 Scout, 4 Maverick models and
-  embeddings - provider ID: `together` - reference documentation: [together](../../providers/inference/remote_together.md)
-- **[Anthropic](https://www.anthropic.com/)**: Claude 3.5 Sonnet, Claude 3.7 Sonnet, Claude 3.5 Haiku, and Voyage embeddings - provider ID: `anthropic` - reference documentation: [anthropic](../../providers/inference/remote_anthropic.md)
-- **[Gemini](https://gemini.google.com/)**: Gemini 1.5, 2.0, 2.5 models and text embeddings - provider ID: `gemini` - reference documentation: [gemini](../../providers/inference/remote_gemini.md)
-- **[Groq](https://groq.com/)**: Fast Llama models (3.1, 3.2, 3.3, 4 Scout, 4 Maverick) - provider ID: `groq` - reference documentation: [groq](../../providers/inference/remote_groq.md)
-- **[SambaNova](https://www.sambanova.ai/)**: Llama 3.1, 3.2, 3.3, 4 Scout, 4 Maverick models - provider ID: `sambanova` - reference documentation: [sambanova](../../providers/inference/remote_sambanova.md)
-- **[Cerebras](https://www.cerebras.ai/)**: Cerebras AI models - provider ID: `cerebras` - reference documentation: [cerebras](../../providers/inference/remote_cerebras.md)
-- **[NVIDIA](https://www.nvidia.com/)**: NVIDIA NIM - provider ID: `nvidia` - reference documentation: [nvidia](../../providers/inference/remote_nvidia.md)
-- **[HuggingFace](https://huggingface.co/)**: Serverless and endpoint models - provider ID: `hf::serverless` and `hf::endpoint` - reference documentation: [huggingface-serverless](../../providers/inference/remote_hf_serverless.md) and [huggingface-endpoint](../../providers/inference/remote_hf_endpoint.md)
-- **[Bedrock](https://aws.amazon.com/bedrock/)**: AWS Bedrock models - provider ID: `bedrock` - reference documentation: [bedrock](../../providers/inference/remote_bedrock.md)
+  embeddings - provider ID: `together` - reference documentation: [together](../../providers/inference/remote_together)
+- **[Anthropic](https://www.anthropic.com/)**: Claude 3.5 Sonnet, Claude 3.7 Sonnet, Claude 3.5 Haiku, and Voyage embeddings - provider ID: `anthropic` - reference documentation: [anthropic](../../providers/inference/remote_anthropic)
+- **[Gemini](https://gemini.google.com/)**: Gemini 1.5, 2.0, 2.5 models and text embeddings - provider ID: `gemini` - reference documentation: [gemini](../../providers/inference/remote_gemini)
+- **[Groq](https://groq.com/)**: Fast Llama models (3.1, 3.2, 3.3, 4 Scout, 4 Maverick) - provider ID: `groq` - reference documentation: [groq](../../providers/inference/remote_groq)
+- **[SambaNova](https://www.sambanova.ai/)**: Llama 3.1, 3.2, 3.3, 4 Scout, 4 Maverick models - provider ID: `sambanova` - reference documentation: [sambanova](../../providers/inference/remote_sambanova)
+- **[Cerebras](https://www.cerebras.ai/)**: Cerebras AI models - provider ID: `cerebras` - reference documentation: [cerebras](../../providers/inference/remote_cerebras)
+- **[NVIDIA](https://www.nvidia.com/)**: NVIDIA NIM - provider ID: `nvidia` - reference documentation: [nvidia](../../providers/inference/remote_nvidia)
+- **[HuggingFace](https://huggingface.co/)**: Serverless and endpoint models - provider ID: `hf::serverless` and `hf::endpoint` - reference documentation: [huggingface-serverless](../../providers/inference/remote_hf_serverless) and [huggingface-endpoint](../../providers/inference/remote_hf_endpoint)
+- **[Bedrock](https://aws.amazon.com/bedrock/)**: AWS Bedrock models - provider ID: `bedrock` - reference documentation: [bedrock](../../providers/inference/remote_bedrock)
 
 ### Local/Remote Providers
-- **[Ollama](https://ollama.ai/)**: Local Ollama models - provider ID: `ollama` - reference documentation: [ollama](../../providers/inference/remote_ollama.md)
-- **[vLLM](https://docs.vllm.ai/en/latest/)**: Local or remote vLLM server - provider ID: `vllm` - reference documentation: [vllm](../../providers/inference/remote_vllm.md)
-- **[TGI](https://github.com/huggingface/text-generation-inference)**: Text Generation Inference server - Dell Enterprise Hub's custom TGI container too (use `DEH_URL`) - provider ID: `tgi` - reference documentation: [tgi](../../providers/inference/remote_tgi.md)
-- **[Sentence Transformers](https://www.sbert.net/)**: Local embedding models - provider ID: `sentence-transformers` - reference documentation: [sentence-transformers](../../providers/inference/inline_sentence-transformers.md)
+- **[Ollama](https://ollama.ai/)**: Local Ollama models - provider ID: `ollama` - reference documentation: [ollama](../../providers/inference/remote_ollama)
+- **[vLLM](https://docs.vllm.ai/en/latest/)**: Local or remote vLLM server - provider ID: `vllm` - reference documentation: [vllm](../../providers/inference/remote_vllm)
+- **[TGI](https://github.com/huggingface/text-generation-inference)**: Text Generation Inference server - Dell Enterprise Hub's custom TGI container too (use `DEH_URL`) - provider ID: `tgi` - reference documentation: [tgi](../../providers/inference/remote_tgi)
+- **[Sentence Transformers](https://www.sbert.net/)**: Local embedding models - provider ID: `sentence-transformers` - reference documentation: [sentence-transformers](../../providers/inference/inline_sentence-transformers)
 
 All providers are disabled by default. So you need to enable them by setting the environment variables.
 

docs/docs/getting_started/detailed_tutorial.mdx

@@ -216,7 +216,7 @@ OpenAIChatCompletion(
 
 ### Step 4: Run the Demos
 
-Note that these demos show the [Python Client SDK](../references/python_sdk_reference/index.md).
+Note that these demos show the [Python Client SDK](../references/python_sdk_reference/index).
 Other SDKs are also available, please refer to the [Client SDK](../index.md#client-sdks) list for the complete options.
 
 <Tabs>

docs/docs/providers/agents/index.mdx

@@ -25,7 +25,3 @@ Agents API for creating and interacting with agentic systems.
     - Agents can also use Memory to retrieve information from knowledge bases. See the RAG Tool and Vector IO APIs for more details.
 
 This section contains documentation for all available providers for the **agents** API.
-
-## Providers
-
-- [Meta-Reference](./inline_meta-reference)

docs/docs/providers/batches/index.mdx

@@ -29,7 +29,3 @@ The Batches API enables efficient processing of multiple requests in a single op
     Note: This API is currently under active development and may undergo changes.
 
 This section contains documentation for all available providers for the **batches** API.
-
-## Providers
-
-- [Reference](./inline_reference)

docs/docs/providers/datasetio/index.md

@@ -1,16 +0,0 @@
----
-sidebar_label: Datasetio
-title: Datasetio
----
-
-# Datasetio
-
-## Overview
-
-This section contains documentation for all available providers for the **datasetio** API.
-
-## Providers
-
-- [Localfs](./inline_localfs)
-- [Remote - Huggingface](./remote_huggingface)
-- [Remote - Nvidia](./remote_nvidia)

docs/docs/providers/datasetio/index.mdx

@@ -8,9 +8,3 @@ title: Datasetio
 ## Overview
 
 This section contains documentation for all available providers for the **datasetio** API.
-
-## Providers
-
-- [Localfs](./inline_localfs)
-- [Remote - Huggingface](./remote_huggingface)
-- [Remote - Nvidia](./remote_nvidia)

docs/docs/providers/eval/index.mdx

@@ -11,8 +11,3 @@ title: Eval
 Llama Stack Evaluation API for running evaluations on model and agent candidates.
 
 This section contains documentation for all available providers for the **eval** API.
-
-## Providers
-
-- [Meta-Reference](./inline_meta-reference)
-- [Remote - Nvidia](./remote_nvidia)

docs/docs/providers/files/index.mdx

@@ -8,8 +8,3 @@ title: Files
 ## Overview
 
 This section contains documentation for all available providers for the **files** API.
-
-## Providers
-
-- [Localfs](./inline_localfs)
-- [Remote - S3](./remote_s3)

docs/docs/providers/index.mdx

@@ -21,13 +21,13 @@ Importantly, Llama Stack always strives to provide at least one fully inline pro
 
 ## Provider Categories
 
-- **[External Providers](./external/)** - Guide for building and using external providers
-- **[OpenAI Compatibility](./openai)** - OpenAI API compatibility layer
-- **[Inference](./inference/)** - LLM and embedding model providers
-- **[Agents](./agents/)** - Agentic system providers
-- **[DatasetIO](./datasetio/)** - Dataset and data loader providers
-- **[Safety](./safety/)** - Content moderation and safety providers
-- **[Telemetry](./telemetry/)** - Monitoring and observability providers
-- **[Vector IO](./vector-io/)** - Vector database providers
-- **[Tool Runtime](./tool-runtime/)** - Tool and protocol providers
-- **[Files](./files/)** - File system and storage providers
+- **[External Providers](external/index.mdx)** - Guide for building and using external providers
+- **[OpenAI Compatibility](./openai.mdx)** - OpenAI API compatibility layer
+- **[Inference](inference/index.mdx)** - LLM and embedding model providers
+- **[Agents](agents/index.mdx)** - Agentic system providers
+- **[DatasetIO](datasetio/index.mdx)** - Dataset and data loader providers
+- **[Safety](safety/index.mdx)** - Content moderation and safety providers
+- **[Telemetry](telemetry/index.mdx)** - Monitoring and observability providers
+- **[Vector IO](vector_io/index.mdx)** - Vector database providers
+- **[Tool Runtime](tool_runtime/index.mdx)** - Tool and protocol providers
+- **[Files](files/index.mdx)** - File system and storage providers

docs/docs/providers/inference/index.mdx

@@ -19,30 +19,3 @@ Llama Stack Inference API for generating completions, chat completions, and embe
     - Embedding models: these models generate embeddings to be used for semantic search.
 
 This section contains documentation for all available providers for the **inference** API.
-
-## Providers
-
-- [Meta-Reference](./inline_meta-reference)
-- [Sentence-Transformers](./inline_sentence-transformers)
-- [Remote - Anthropic](./remote_anthropic)
-- [Remote - Azure](./remote_azure)
-- [Remote - Bedrock](./remote_bedrock)
-- [Remote - Cerebras](./remote_cerebras)
-- [Remote - Databricks](./remote_databricks)
-- [Remote - Fireworks](./remote_fireworks)
-- [Remote - Gemini](./remote_gemini)
-- [Remote - Groq](./remote_groq)
-- [Remote - Hf - Endpoint](./remote_hf_endpoint)
-- [Remote - Hf - Serverless](./remote_hf_serverless)
-- [Remote - Llama-Openai-Compat](./remote_llama-openai-compat)
-- [Remote - Nvidia](./remote_nvidia)
-- [Remote - Ollama](./remote_ollama)
-- [Remote - Openai](./remote_openai)
-- [Remote - Passthrough](./remote_passthrough)
-- [Remote - Runpod](./remote_runpod)
-- [Remote - Sambanova](./remote_sambanova)
-- [Remote - Tgi](./remote_tgi)
-- [Remote - Together](./remote_together)
-- [Remote - Vertexai](./remote_vertexai)
-- [Remote - Vllm](./remote_vllm)
-- [Remote - Watsonx](./remote_watsonx)

docs/docs/providers/openai.mdx

@@ -1,3 +1,8 @@
+title: OpenAI Compatibility
+description: OpenAI API Compatibility
+sidebar_label: OpenAI Compatibility
+sidebar_position: 1
+---
 ## OpenAI API Compatibility
 
 ### Server path

docs/docs/providers/post_training/index.mdx

@@ -8,10 +8,3 @@ title: Post_Training
 ## Overview
 
 This section contains documentation for all available providers for the **post_training** API.
-
-## Providers
-
-- [Huggingface-Gpu](./inline_huggingface-gpu)
-- [Torchtune-Cpu](./inline_torchtune-cpu)
-- [Torchtune-Gpu](./inline_torchtune-gpu)
-- [Remote - Nvidia](./remote_nvidia)

docs/docs/providers/safety/index.mdx

@@ -8,12 +8,3 @@ title: Safety
 ## Overview
 
 This section contains documentation for all available providers for the **safety** API.
-
-## Providers
-
-- [Code-Scanner](./inline_code-scanner)
-- [Llama-Guard](./inline_llama-guard)
-- [Prompt-Guard](./inline_prompt-guard)
-- [Remote - Bedrock](./remote_bedrock)
-- [Remote - Nvidia](./remote_nvidia)
-- [Remote - Sambanova](./remote_sambanova)

docs/docs/providers/scoring/index.mdx

@@ -8,9 +8,3 @@ title: Scoring
 ## Overview
 
 This section contains documentation for all available providers for the **scoring** API.
-
-## Providers
-
-- [Basic](./inline_basic)
-- [Braintrust](./inline_braintrust)
-- [Llm-As-Judge](./inline_llm-as-judge)

docs/docs/providers/telemetry/index.mdx

@@ -8,7 +8,3 @@ title: Telemetry
 ## Overview
 
 This section contains documentation for all available providers for the **telemetry** API.
-
-## Providers
-
-- [Meta-Reference](./inline_meta-reference)

docs/docs/providers/tool_runtime/index.mdx

@@ -8,12 +8,3 @@ title: Tool_Runtime
 ## Overview
 
 This section contains documentation for all available providers for the **tool_runtime** API.
-
-## Providers
-
-- [Rag-Runtime](./inline_rag-runtime)
-- [Remote - Bing-Search](./remote_bing-search)
-- [Remote - Brave-Search](./remote_brave-search)
-- [Remote - Model-Context-Protocol](./remote_model-context-protocol)
-- [Remote - Tavily-Search](./remote_tavily-search)
-- [Remote - Wolfram-Alpha](./remote_wolfram-alpha)

docs/docs/providers/vector_io/index.mdx

@@ -8,18 +8,3 @@ title: Vector_Io
 ## Overview
 
 This section contains documentation for all available providers for the **vector_io** API.
-
-## Providers
-
-- [Chromadb](./inline_chromadb)
-- [Faiss](./inline_faiss)
-- [Meta-Reference](./inline_meta-reference)
-- [Milvus](./inline_milvus)
-- [Qdrant](./inline_qdrant)
-- [Sqlite-Vec](./inline_sqlite-vec)
-- [Sqlite Vec](./inline_sqlite_vec)
-- [Remote - Chromadb](./remote_chromadb)
-- [Remote - Milvus](./remote_milvus)
-- [Remote - Pgvector](./remote_pgvector)
-- [Remote - Qdrant](./remote_qdrant)
-- [Remote - Weaviate](./remote_weaviate)

docs/docs/references/llama_cli_reference/index.md

@@ -29,7 +29,7 @@ You have two ways to install Llama Stack:
 ## `llama` subcommands
 1. `download`: Supports downloading models from Meta or Hugging Face.  [Downloading models](#downloading-models)
 2. `model`: Lists available models and their properties. [Understanding models](#understand-the-models)
-3. `stack`: Allows you to build a stack using the `llama stack` distribution and run a Llama Stack server. You can read more about how to build a Llama Stack distribution in the [Build your own Distribution](../../distributions/building_distro) documentation.
+3. `stack`: Allows you to build a stack using the `llama stack` distribution and run a Llama Stack server. You can read more about how to build a Llama Stack distribution in the [Build your own Distribution](../distributions/building_distro) documentation.
 
 ### Sample Usage
 

docs/static/src/components/HomepageFeatures/index.js

@@ -1,64 +0,0 @@
-import React from 'react';
-import clsx from 'clsx';
-import styles from './styles.module.css';
-
-const FeatureList = [
-  {
-    title: 'Easy to Use',
-    Svg: require('@site/static/img/undraw_docusaurus_mountain.svg').default,
-    description: (
-      <>
-        Docusaurus was designed from the ground up to be easily installed and
-        used to get your website up and running quickly.
-      </>
-    ),
-  },
-  {
-    title: 'Focus on What Matters',
-    Svg: require('@site/static/img/undraw_docusaurus_tree.svg').default,
-    description: (
-      <>
-        Docusaurus lets you focus on your docs, and we&apos;ll do the chores. Go
-        ahead and move your docs into the <code>docs</code> directory.
-      </>
-    ),
-  },
-  {
-    title: 'Powered by React',
-    Svg: require('@site/static/img/undraw_docusaurus_react.svg').default,
-    description: (
-      <>
-        Extend or customize your website layout by reusing React. Docusaurus can
-        be extended while reusing the same header and footer.
-      </>
-    ),
-  },
-];
-
-function Feature({Svg, title, description}) {
-  return (
-    <div className={clsx('col col--4')}>
-      <div className="text--center">
-        <Svg className={styles.featureSvg} role="img" />
-      </div>
-      <div className="text--center padding-horiz--md">
-        <h3>{title}</h3>
-        <p>{description}</p>
-      </div>
-    </div>
-  );
-}
-
-export default function HomepageFeatures() {
-  return (
-    <section className={styles.features}>
-      <div className="container">
-        <div className="row">
-          {FeatureList.map((props, idx) => (
-            <Feature key={idx} {...props} />
-          ))}
-        </div>
-      </div>
-    </section>
-  );
-}

docs/static/src/components/HomepageFeatures/styles.module.css

@@ -1,11 +0,0 @@
-.features {
-  display: flex;
-  align-items: center;
-  padding: 2rem 0;
-  width: 100%;
-}
-
-.featureSvg {
-  height: 200px;
-  width: 200px;
-}

docs/static/src/css/custom.css

@@ -1,191 +0,0 @@
-/**
- * Any CSS included here will be global. The classic template
- * bundles Infima by default. Infima is a CSS framework designed to
- * work well for content-centric websites.
- */
-
-/* You can override the default Infima variables here. */
-:root {
-  /* Llama Stack Original Theme - Based on llamastack.github.io */
-  --ifm-color-primary: #4a4a68;
-  --ifm-color-primary-dark: #3a3a52;
-  --ifm-color-primary-darker: #332735;
-  --ifm-color-primary-darkest: #2b2129;
-  --ifm-color-primary-light: #5a5a7e;
-  --ifm-color-primary-lighter: #6a6a94;
-  --ifm-color-primary-lightest: #8080aa;
-
-  /* Additional theme colors */
-  --ifm-color-secondary: #1b263c;
-  --ifm-color-info: #2980b9;
-  --ifm-color-success: #16a085;
-  --ifm-color-warning: #f39c12;
-  --ifm-color-danger: #e74c3c;
-
-  /* Background colors */
-  --ifm-background-color: #ffffff;
-  --ifm-background-surface-color: #f8f9fa;
-
-  /* Code and syntax highlighting */
-  --ifm-code-font-size: 95%;
-  --ifm-pre-background: #1b263c;
-  --ifm-pre-color: #e1e5e9;
-  --docusaurus-highlighted-code-line-bg: rgba(51, 39, 53, 0.1);
-
-  /* Link colors */
-  --ifm-link-color: var(--ifm-color-primary);
-  --ifm-link-hover-color: var(--ifm-color-primary-darker);
-
-  /* Navbar */
-  --ifm-navbar-background-color: rgba(255, 255, 255, 0.95);
-  --ifm-navbar-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
-
-  /* Hero section gradient - matching original theme */
-  --hero-gradient: linear-gradient(90deg, #332735 0%, #1b263c 100%);
-
-  /* OpenAPI method colors */
-  --openapi-code-blue: #2980b9;
-  --openapi-code-green: #16a085;
-  --openapi-code-orange: #f39c12;
-  --openapi-code-red: #e74c3c;
-  --openapi-code-purple: #332735;
-}
-
-/* For readability concerns, you should choose a lighter palette in dark mode. */
-[data-theme='dark'] {
-  /* Dark theme primary colors - lighter versions of original theme */
-  --ifm-color-primary: #8080aa;
-  --ifm-color-primary-dark: #6a6a94;
-  --ifm-color-primary-darker: #5a5a7e;
-  --ifm-color-primary-darkest: #4a4a68;
-  --ifm-color-primary-light: #9090ba;
-  --ifm-color-primary-lighter: #a0a0ca;
-  --ifm-color-primary-lightest: #b0b0da;
-
-  /* Dark theme background colors */
-  --ifm-background-color: #1a1a1a;
-  --ifm-background-surface-color: #2a2a2a;
-
-  /* Dark theme navbar */
-  --ifm-navbar-background-color: rgba(26, 26, 26, 0.95);
-
-  /* Dark theme code highlighting */
-  --docusaurus-highlighted-code-line-bg: rgba(51, 39, 53, 0.3);
-
-  /* Dark theme text colors */
-  --ifm-font-color-base: #e1e5e9;
-  --ifm-font-color-secondary: #a0a6ac;
-}
-
-/* Sidebar Method labels */
-.api-method>.menu__link {
-  align-items: center;
-  justify-content: start;
-}
-
-.api-method>.menu__link::before {
-  width: 50px;
-  height: 20px;
-  font-size: 12px;
-  line-height: 20px;
-  text-transform: uppercase;
-  font-weight: 600;
-  border-radius: 0.25rem;
-  border: 1px solid;
-  margin-right: var(--ifm-spacing-horizontal);
-  text-align: center;
-  flex-shrink: 0;
-  border-color: transparent;
-  color: white;
-}
-
-.get>.menu__link::before {
-  content: "get";
-  background-color: var(--ifm-color-primary);
-}
-
-.put>.menu__link::before {
-  content: "put";
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-
-.post>.menu__link::before {
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-.delete>.menu__link::before {
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-.patch>.menu__link::before {
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-.footer--dark {
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-
-.footer--dark .footer__link-item {
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-
-.footer--dark .footer__title {
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-
-/* OpenAPI theme fixes for light mode readability */
-/* Version badge fixes */
-.openapi__version-badge,
-.theme-doc-version-badge,
-[class*="version-badge"],
-[class*="versionBadge"] {
-  background-color: #ffffff !important;
-  color: #333333 !important;
-  border: 1px solid #d1d5db !important;
-}
-
-/* OpenAPI method badges in light mode */
-.openapi__method-badge,
-[class*="method-badge"] {
-  color: #ffffff !important;
-}
-
-/* Button fixes for light mode */
-.openapi__button,
-.theme-api-docs-demo-panel button,
-[class*="api-docs"] button,
-button[class*="button"],
-.openapi-explorer__response-schema button,
-.openapi-tabs__operation button {
-  color: #ffffff !important;
-}
-
-.openapi__button:hover,
-.theme-api-docs-demo-panel button:hover,
-[class*="api-docs"] button:hover,
-button[class*="button"]:hover,
-.openapi-explorer__response-schema button:hover,
-.openapi-tabs__operation button:hover {
-  color: #ffffff !important;
-}
-
-/* Navigation buttons (Next/Previous) */
-.pagination-nav__link,
-.pagination-nav__label {
-  color: #333333 !important;
-}
-
-.pagination-nav__link--next,
-.pagination-nav__link--prev {
-  background-color: #ffffff !important;
-  border: 1px solid #d1d5db !important;
-}
-
-.pagination-nav__link--next:hover,
-.pagination-nav__link--prev:hover {
-  background-color: #f3f4f6 !important;
-}

docs/static/src/pages/index.js

@@ -1,163 +0,0 @@
-import React from 'react';
-import clsx from 'clsx';
-import Layout from '@theme/Layout';
-import Link from '@docusaurus/Link';
-import useDocusaurusContext from '@docusaurus/useDocusaurusContext';
-import styles from './index.module.css';
-
-function HomepageHeader() {
-  const {siteConfig} = useDocusaurusContext();
-  return (
-    <header className={clsx('hero hero--primary', styles.heroBanner)}>
-      <div className="container">
-        <div className={styles.heroContent}>
-          <h1 className={styles.heroTitle}>Build AI Applications with Llama Stack</h1>
-          <p className={styles.heroSubtitle}>
-            Unified APIs for Inference, RAG, Agents, Tools, Safety, and Telemetry
-          </p>
-          <div className={styles.buttons}>
-            <Link
-              className={clsx('button button--primary button--lg', styles.getStartedButton)}
-              to="/docs/getting-started">
-              🚀 Get Started
-            </Link>
-            <Link
-              className={clsx('button button--primary button--lg', styles.apiButton)}
-              to="/docs/category/llama-stack-api">
-              📚 API Reference
-            </Link>
-          </div>
-        </div>
-      </div>
-    </header>
-  );
-}
-
-function QuickStart() {
-  return (
-    <section className={styles.quickStart}>
-      <div className="container">
-        <div className="row">
-          <div className="col col--6">
-            <h2 className={styles.sectionTitle}>Quick Start</h2>
-            <p className={styles.sectionDescription}>
-              Get up and running with Llama Stack in just a few commands. Build your first RAG application locally.
-            </p>
-            <div className={styles.codeBlock}>
-              <pre><code>{`# Install uv and start Ollama
-ollama run llama3.2:3b --keepalive 60m
-
-# Run Llama Stack server
-OLLAMA_URL=http://localhost:11434 \\
-  uv run --with llama-stack \\
-  llama stack build --distro starter \\
-  --image-type venv --run
-
-# Try the Python SDK
-from llama_stack_client import LlamaStackClient
-
-client = LlamaStackClient(
-  base_url="http://localhost:8321"
-)
-
-response = client.inference.chat_completion(
-  model="Llama3.2-3B-Instruct",
-  messages=[{
-    "role": "user",
-    "content": "What is machine learning?"
-  }]
-)`}</code></pre>
-            </div>
-          </div>
-          <div className="col col--6">
-            <h2 className={styles.sectionTitle}>Why Llama Stack?</h2>
-            <div className={styles.features}>
-              <div className={styles.feature}>
-                <div className={styles.featureIcon}>🔗</div>
-                <div>
-                  <h4>Unified APIs</h4>
-                  <p>One consistent interface for all your AI needs - inference, safety, agents, and more.</p>
-                </div>
-              </div>
-              <div className={styles.feature}>
-                <div className={styles.featureIcon}>🔄</div>
-                <div>
-                  <h4>Provider Flexibility</h4>
-                  <p>Swap between providers without code changes. Start local, deploy anywhere.</p>
-                </div>
-              </div>
-              <div className={styles.feature}>
-                <div className={styles.featureIcon}>🛡️</div>
-                <div>
-                  <h4>Production Ready</h4>
-                  <p>Built-in safety, monitoring, and evaluation tools for enterprise applications.</p>
-                </div>
-              </div>
-              <div className={styles.feature}>
-                <div className={styles.featureIcon}>📱</div>
-                <div>
-                  <h4>Multi-Platform</h4>
-                  <p>SDKs for Python, Node.js, iOS, Android, and REST APIs for any language.</p>
-                </div>
-              </div>
-            </div>
-          </div>
-        </div>
-      </div>
-    </section>
-  );
-}
-
-function CommunityLinks() {
-  return (
-    <section className={styles.community}>
-      <div className="container">
-        <div className={styles.communityContent}>
-          <h2 className={styles.sectionTitle}>Join the Community</h2>
-          <p className={styles.sectionDescription}>
-            Connect with developers building the future of AI applications
-          </p>
-          <div className={styles.communityLinks}>
-            <a
-              href="https://github.com/llamastack/llama-stack"
-              className={clsx('button button--outline button--lg', styles.communityButton)}
-              target="_blank"
-              rel="noopener noreferrer">
-              <span className={styles.communityIcon}>⭐</span>
-              Star on GitHub
-            </a>
-            <a
-              href="https://discord.gg/llama-stack"
-              className={clsx('button button--outline button--lg', styles.communityButton)}
-              target="_blank"
-              rel="noopener noreferrer">
-              <span className={styles.communityIcon}>💬</span>
-              Join Discord
-            </a>
-            <Link
-              to="/docs/intro"
-              className={clsx('button button--outline button--lg', styles.communityButton)}>
-              <span className={styles.communityIcon}>📚</span>
-              Read Docs
-            </Link>
-          </div>
-        </div>
-      </div>
-    </section>
-  );
-}
-
-export default function Home() {
-  const {siteConfig} = useDocusaurusContext();
-  return (
-    <Layout
-      title="Build AI Applications"
-      description="The open-source framework for building generative AI applications with unified APIs for Inference, RAG, Agents, Tools, Safety, and Telemetry.">
-      <HomepageHeader />
-      <main>
-        <QuickStart />
-        <CommunityLinks />
-      </main>
-    </Layout>
-  );
-}

docs/static/src/pages/index.module.css

@@ -1,283 +0,0 @@
-/**
- * CSS files with the .module.css suffix will be treated as CSS modules
- * and scoped locally.
- */
-
-.heroBanner {
-  padding: 4rem 0;
-  text-align: center;
-  position: relative;
-  overflow: hidden;
-  background: var(--hero-gradient);
-  color: white;
-  display: flex;
-  align-items: center;
-}
-
-.heroBanner::before {
-  content: '';
-  position: absolute;
-  top: 0;
-  left: 0;
-  right: 0;
-  bottom: 0;
-  background: radial-gradient(circle at 30% 20%, rgba(255, 255, 255, 0.1) 0%, transparent 50%),
-              radial-gradient(circle at 70% 80%, rgba(255, 255, 255, 0.05) 0%, transparent 50%);
-  pointer-events: none;
-}
-
-.heroContent {
-  max-width: 800px;
-  margin: 0 auto;
-}
-
-.heroLogo {
-  height: 48px;
-  width: auto;
-  margin-bottom: 1.5rem;
-}
-
-.heroTitle {
-  font-size: 2.8rem;
-  font-weight: 700;
-  margin-bottom: 1rem;
-  line-height: 1.2;
-}
-
-.heroSubtitle {
-  font-size: 1.1rem;
-  font-weight: 400;
-  margin-bottom: 2rem;
-  opacity: 0.9;
-  line-height: 1.5;
-  max-width: 600px;
-  margin-left: auto;
-  margin-right: auto;
-}
-
-.buttons {
-  display: flex;
-  align-items: center;
-  justify-content: center;
-  gap: 1rem;
-}
-
-.heroBanner .getStartedButton {
-  background: white;
-  color: #332735;
-  border: 2px solid white;
-  font-weight: 600;
-  transition: all 0.3s ease;
-}
-
-.heroBanner .getStartedButton:hover {
-  background: rgba(255, 255, 255, 0.9);
-  color: #2b2129;
-  border-color: rgba(255, 255, 255, 0.9);
-  transform: translateY(-2px);
-  box-shadow: 0 8px 25px rgba(0, 0, 0, 0.15);
-}
-
-.heroBanner .apiButton {
-  background: transparent;
-  color: white;
-  border: 2px solid white;
-  font-weight: 600;
-  transition: all 0.3s ease;
-}
-
-.heroBanner .apiButton:hover {
-  background: white;
-  border-color: white;
-  color: #332735;
-  transform: translateY(-2px);
-}
-
-/* Quick Start Section */
-.quickStart {
-  padding: 4rem 0;
-  background: var(--ifm-background-color);
-}
-
-.sectionTitle {
-  font-size: 2rem;
-  font-weight: 600;
-  margin-bottom: 0.75rem;
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-
-.sectionDescription {
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-
-.codeBlock {
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-
-.codeBlock pre {
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-.codeBlock code {
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-/* Features */
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-.feature {
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-.feature:hover {
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-
-.communityIcon {
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-
-/* Responsive Design */
-@media screen and (max-width: 996px) {
-  .heroBanner {
-    padding: 3rem 2rem;
-  }
-
-  .heroTitle {
-    font-size: 2.2rem;
-  }
-
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-  .communityLinks {
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-  .communityButton {
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-@media screen and (max-width: 768px) {
-  .heroLogo {
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-  }
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-  .heroTitle {
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-  .codeBlock {
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-
-  .codeBlock code {
-    font-size: 0.8rem;
-  }
-
-  .feature {
-    padding: 0.75rem;
-  }
-}

docs/static/src/pages/markdown-page.md

@@ -1,7 +0,0 @@
----
-title: Markdown page example
----
-
-# Markdown page example
-
-You don't need React to write simple standalone pages.