feat: add auto-generated CI documentation pre-commit hook (#2890)

Our CI is entirely undocumented, this commit adds a README.md file with
a table of the current CI and what is does

---------

Signed-off-by: Nathan Weinberg <nweinber@redhat.com>

llama_stack/providers/inline/inference/meta_reference/inference.py

@@ -73,11 +73,12 @@ from .config import MetaReferenceInferenceConfig
 from .generators import LlamaGenerator
 from .model_parallel import LlamaModelParallelGenerator
 
-log = get_logger(__name__, category="inference")
 # there's a single model parallel process running serving the model. for now,
 # we don't support multiple concurrent requests to this process.
 SEMAPHORE = asyncio.Semaphore(1)
 
+logger = get_logger(__name__, category="inference")
+
 
 def llama_builder_fn(config: MetaReferenceInferenceConfig, model_id: str, llama_model: Model) -> LlamaGenerator:
     return LlamaGenerator(config, model_id, llama_model)
@@ -144,7 +145,7 @@ class MetaReferenceInferenceImpl(
         return model
 
     async def load_model(self, model_id, llama_model) -> None:
-        log.info(f"Loading model `{model_id}`")
+        logger.info(f"Loading model `{model_id}`")
 
         builder_params = [self.config, model_id, llama_model]
 
@@ -166,7 +167,7 @@ class MetaReferenceInferenceImpl(
         self.model_id = model_id
         self.llama_model = llama_model
 
-        log.info("Warming up...")
+        logger.info("Warming up...")
         await self.completion(
             model_id=model_id,
             content="Hello, world!",
@@ -177,7 +178,7 @@ class MetaReferenceInferenceImpl(
             messages=[UserMessage(content="Hi how are you?")],
             sampling_params=SamplingParams(max_tokens=20),
         )
-        log.info("Warmed up!")
+        logger.info("Warmed up!")
 
     def check_model(self, request) -> None:
         if self.model_id is None or self.llama_model is None:

llama_stack/providers/inline/inference/meta_reference/parallel_utils.py

@@ -12,7 +12,6 @@
 
 import copy
 import json
-import logging
 import multiprocessing
 import os
 import tempfile
@@ -32,13 +31,14 @@ from fairscale.nn.model_parallel.initialize import (
 from pydantic import BaseModel, Field
 from torch.distributed.launcher.api import LaunchConfig, elastic_launch
 
+from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import GenerationResult
 from llama_stack.providers.utils.inference.prompt_adapter import (
     ChatCompletionRequestWithRawContent,
     CompletionRequestWithRawContent,
 )
 
-log = logging.getLogger(__name__)
+log = get_logger(name=__name__, category="inference")
 
 
 class ProcessingMessageName(str, Enum):
@@ -236,7 +236,7 @@ def worker_process_entrypoint(
         except StopIteration:
             break
 
-    log.info("[debug] worker process done")
+            log.info("[debug] worker process done")
 
 
 def launch_dist_group(

llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers.py

@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import logging
 from collections.abc import AsyncGenerator
 
 from llama_stack.apis.inference import (
@@ -32,8 +31,6 @@ from llama_stack.providers.utils.inference.openai_compat import (
 
 from .config import SentenceTransformersInferenceConfig
 
-log = logging.getLogger(__name__)
-
 
 class SentenceTransformersInferenceImpl(
     OpenAIChatCompletionToLlamaStackMixin,