Merge branch 'meta-llama:main' into feat/litellm_sambanova_usage

docs/source/building_applications/evals.md

@@ -23,9 +23,12 @@ In this example, we will show you how to:
 
 ##### Building a Search Agent
 ```python
+from llama_stack_client import LlamaStackClient
 from llama_stack_client.lib.agents.agent import Agent
 from llama_stack_client.lib.agents.event_logger import EventLogger
 
+client = LlamaStackClient(base_url=f"http://{HOST}:{PORT}")
+
 agent = Agent(
     client,
     model="meta-llama/Llama-3.3-70B-Instruct",
@@ -33,7 +36,7 @@ agent = Agent(
     tools=["builtin::websearch"],
 )
 user_prompts = [
-    "Which teams played in the NBA western conference finals of 2024. Search the web for the answer.",
+    "Which teams played in the NBA Western Conference Finals of 2024. Search the web for the answer.",
     "In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title. Search the web for the answer.",
     "What is the British-American kickboxer Andrew Tate's kickboxing name? Search the web for the answer.",
 ]

docs/source/distributions/building_distro.md

@@ -33,6 +33,8 @@ Can be set to any of the following log levels:
 
 The default global log level is `info`. `all` sets the log level for all components.
 
+A user can also set `LLAMA_STACK_LOG_FILE` which will pipe the logs to the specified path as well as to the terminal. An example would be: `export LLAMA_STACK_LOG_FILE=server.log`
+
 ### Llama Stack Build
 
 In order to build your own distribution, we recommend you clone the `llama-stack` repository.

docs/source/distributions/self_hosted_distro/fireworks.md

@@ -40,7 +40,6 @@ The following models are available by default:
 - `accounts/fireworks/models/llama-v3p1-8b-instruct (aliases: meta-llama/Llama-3.1-8B-Instruct)`
 - `accounts/fireworks/models/llama-v3p1-70b-instruct (aliases: meta-llama/Llama-3.1-70B-Instruct)`
 - `accounts/fireworks/models/llama-v3p1-405b-instruct (aliases: meta-llama/Llama-3.1-405B-Instruct-FP8)`
-- `accounts/fireworks/models/llama-v3p2-1b-instruct (aliases: meta-llama/Llama-3.2-1B-Instruct)`
 - `accounts/fireworks/models/llama-v3p2-3b-instruct (aliases: meta-llama/Llama-3.2-3B-Instruct)`
 - `accounts/fireworks/models/llama-v3p2-11b-vision-instruct (aliases: meta-llama/Llama-3.2-11B-Vision-Instruct)`
 - `accounts/fireworks/models/llama-v3p2-90b-vision-instruct (aliases: meta-llama/Llama-3.2-90B-Vision-Instruct)`

docs/source/distributions/self_hosted_distro/ollama.md

@@ -23,7 +23,7 @@ The `llamastack/distribution-ollama` distribution consists of the following prov
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
 | tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol`, `remote::wolfram-alpha` |
-| vector_io | `inline::sqlite-vec`, `remote::chromadb`, `remote::pgvector` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 You should use this distribution if you have a regular desktop machine without very powerful GPUs. Of course, if you have powerful GPUs, you can still continue using this distribution since Ollama supports GPU acceleration.
@@ -130,7 +130,7 @@ llama stack run ./run-with-safety.yaml \
 ### (Optional) Update Model Serving Configuration
 
 ```{note}
-Please check the [model_entries](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/ollama/ollama.py#L45) for the supported Ollama models.
+Please check the [model_entries](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/ollama/models.py) for the supported Ollama models.
 ```
 
 To serve a new model with `ollama`

docs/source/references/llama_cli_reference/index.md

@@ -1,6 +1,6 @@
 # llama (server-side) CLI Reference
 
-The `llama` CLI tool helps you setup and use the Llama Stack. It should be available on your path after installing the `llama-stack` package.
+The `llama` CLI tool helps you set up and use the Llama Stack. The CLI is available on your path after installing the `llama-stack` package.
 
 ## Installation
 
@@ -27,9 +27,9 @@ You have two ways to install Llama Stack:
 
 
 ## `llama` subcommands
-1. `download`: `llama` cli tools supports downloading the model from Meta or Hugging Face.
-2. `model`: Lists available models and their properties.
-3. `stack`: Allows you to build and run a Llama Stack server. You can read more about this [here](../../distributions/building_distro).
+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.
 
 ### Sample Usage
 
@@ -117,7 +117,7 @@ You should see a table like this:
 +----------------------------------+------------------------------------------+----------------+
 ```
 
-To download models, you can use the llama download command.
+To download models, you can use the `llama download` command.
 
 ### Downloading from [Meta](https://llama.meta.com/llama-downloads/)
 
@@ -191,7 +191,7 @@ You should see a table like this:
 The `llama model` command helps you explore the model’s interface.
 
 1. `download`: Download the model from different sources. (meta, huggingface)
-2. `list`: Lists all the models available for download with hardware requirements to deploy the models.
+2. `list`: Lists all the models available for download with hardware requirements for deploying the models.
 3. `prompt-format`: Show llama model message formats.
 4. `describe`: Describes all the properties of the model.
 
@@ -262,13 +262,12 @@ llama model prompt-format -m Llama3.2-3B-Instruct
 ![alt text](../../../resources/prompt-format.png)
 
 
-
 You will be shown a Markdown formatted description of the model interface and how prompts / messages are formatted for various scenarios.
 
 **NOTE**: Outputs in terminal are color printed to show special tokens.
 
 ### Remove model
-You can run `llama model remove` to remove unecessary model:
+You can run `llama model remove` to remove an unnecessary model:
 
 ```
 llama model remove -m Llama-Guard-3-8B-int8