docs: update full list of providers with matched APIs and dockerhub images (#2452)

# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->
- add model_type in example
- change "Memory" to "VectorIO" as column name
- update index.md and README.md

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

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

---------

Signed-off-by: Wen Zhou <wenzhou@redhat.com>
Co-authored-by: Sébastien Han <seb@redhat.com>

docs/source/distributions/configuration.md

@@ -77,10 +77,10 @@ Next up is the most critical part: the set of providers that the stack will use
 ```yaml
 providers:
   inference:
-  # provider_id is a string you can choose freely
+    # provider_id is a string you can choose freely
   - provider_id: ollama
     # provider_type is a string that specifies the type of provider.
-    # in this case, the provider for inference is ollama and it is run remotely (outside of the distribution)
+    # in this case, the provider for inference is ollama and it runs remotely (outside of the distribution)
     provider_type: remote::ollama
     # config is a dictionary that contains the configuration for the provider.
     # in this case, the configuration is the url of the ollama server
@@ -88,7 +88,7 @@ providers:
       url: ${env.OLLAMA_URL:=http://localhost:11434}
 ```
 A few things to note:
-- A _provider instance_ is identified with an (id, type, configuration) triplet.
+- A _provider instance_ is identified with an (id, type, config) triplet.
 - The id is a string you can choose freely.
 - You can instantiate any number of provider instances of the same type.
 - The configuration dictionary is provider-specific.
@@ -187,7 +187,7 @@ The environment variable substitution system is type-safe:
 
 ## Resources
 
-Finally, let's look at the `models` section:
+Let's look at the `models` section:
 
 ```yaml
 models:
@@ -195,8 +195,9 @@ models:
   model_id: ${env.INFERENCE_MODEL}
   provider_id: ollama
   provider_model_id: null
+  model_type: llm
 ```
-A Model is an instance of a "Resource" (see [Concepts](../concepts/index)) and is associated with a specific inference provider (in this case, the provider with identifier `ollama`). This is an instance of a "pre-registered" model. While we always encourage the clients to always register models before using them, some Stack servers may come up a list of "already known and available" models.
+A Model is an instance of a "Resource" (see [Concepts](../concepts/index)) and is associated with a specific inference provider (in this case, the provider with identifier `ollama`). This is an instance of a "pre-registered" model. While we always encourage the clients to register models before using them, some Stack servers may come up a list of "already known and available" models.
 
 What's with the `provider_model_id` field? This is an identifier for the model inside the provider's model catalog. Contrast it with `model_id` which is the identifier for the same model for Llama Stack's purposes. For example, you may want to name "llama3.2:vision-11b" as "image_captioning_model" when you use it in your Stack interactions. When omitted, the server will set `provider_model_id` to be the same as `model_id`.
 

docs/source/index.md

@@ -73,17 +73,26 @@ A number of "adapters" are available for some popular Inference and Vector Store
 |  OpenAI  |  Hosted  |
 |  Anthropic  |  Hosted  |
 |  Gemini  |  Hosted  |
+|  WatsonX  |  Hosted  |
 
+**Agents API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  Meta Reference  |  Single Node |
+|  Fireworks  |  Hosted  |
+|  Together  |  Hosted  |
+|  PyTorch ExecuTorch | On-device iOS |
 
 **Vector IO API**
 |  **Provider** |  **Environments** |
 | :----: | :----: |
 |  FAISS | Single Node |
-|  SQLite-Vec| Single Node |
+|  SQLite-Vec | Single Node |
 |  Chroma | Hosted and Single Node |
 |  Milvus | Hosted and Single Node |
 |  Postgres (PGVector) | Hosted and Single Node |
 |  Weaviate | Hosted |
+|  Qdrant  | Hosted and Single Node |
 
 **Safety API**
 |  **Provider** |  **Environments** |
@@ -93,6 +102,30 @@ A number of "adapters" are available for some popular Inference and Vector Store
 |  Code Scanner | Single Node |
 |  AWS Bedrock | Hosted |
 
+**Post Training API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  Meta Reference  |  Single Node |
+|  HuggingFace  |  Single Node |
+|  TorchTune  |  Single Node |
+|  NVIDIA NEMO  |  Hosted |
+
+**Eval API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  Meta Reference  |  Single Node |
+|  NVIDIA NEMO  |  Hosted |
+
+**Telemetry API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  Meta Reference  |  Single Node |
+
+**Tool Runtime API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  Brave Search | Hosted |
+|  RAG Runtime | Single Node |
 
 ```{toctree}
 :hidden:

docs/source/providers/index.md

@@ -1,9 +1,10 @@
 # Providers Overview
 
 The goal of Llama Stack is to build an ecosystem where users can easily swap out different implementations for the same API. Examples for these include:
-- LLM inference providers (e.g., Ollama, Fireworks, Together, AWS Bedrock, Groq, Cerebras, SambaNova, vLLM, etc.),
-- Vector databases (e.g., ChromaDB, Weaviate, Qdrant, Milvus, FAISS, PGVector, SQLite-Vec, etc.),
-- Safety providers (e.g., Meta's Llama Guard, AWS Bedrock Guardrails, etc.)
+- LLM inference providers (e.g., Meta Reference, Ollama, Fireworks, Together, AWS Bedrock, Groq, Cerebras, SambaNova, vLLM, OpenAI, Anthropic, Gemini, WatsonX, etc.),
+- Vector databases (e.g., FAISS, SQLite-Vec, ChromaDB, Weaviate, Qdrant, Milvus, PGVector, etc.),
+- Safety providers (e.g., Meta's Llama Guard, Prompt Guard, Code Scanner, AWS Bedrock Guardrails, etc.),
+- Tool Runtime providers (e.g., RAG Runtime, Brave Search, etc.)
 
 Providers come in two flavors:
 - **Remote**: the provider runs as a separate service external to the Llama Stack codebase. Llama Stack contains a small amount of adapter code.