use logging instead of prints (#499)

# What does this PR do?

This PR moves all print statements to use logging. Things changed:
- Had to add `await start_trace("sse_generator")` to server.py to
actually get tracing working. else was not seeing any logs
- If no telemetry provider is provided in the run.yaml, we will write to
stdout
- by default, the logs are going to be in JSON, but we expose an option
to configure to output in a human readable way.

llama_stack/providers/utils/inference/prompt_adapter.py

@@ -7,14 +7,13 @@
 import base64
 import io
 import json
+import logging
 from typing import Tuple
 
 import httpx
 
 from llama_models.llama3.api.chat_format import ChatFormat
 from PIL import Image as PIL_Image
-from termcolor import cprint
-
 from llama_models.llama3.api.datatypes import *  # noqa: F403
 from llama_stack.apis.inference import *  # noqa: F403
 from llama_models.datatypes import ModelFamily
@@ -29,6 +28,8 @@ from llama_models.sku_list import resolve_model
 
 from llama_stack.providers.utils.inference import supported_inference_models
 
+log = logging.getLogger(__name__)
+
 
 def content_has_media(content: InterleavedTextMedia):
     def _has_media_content(c):
@@ -175,13 +176,13 @@ def chat_completion_request_to_messages(
     """
     model = resolve_model(llama_model)
     if model is None:
-        cprint(f"Could not resolve model {llama_model}", color="red")
+        log.error(f"Could not resolve model {llama_model}")
         return request.messages
 
     allowed_models = supported_inference_models()
     descriptors = [m.descriptor() for m in allowed_models]
     if model.descriptor() not in descriptors:
-        cprint(f"Unsupported inference model? {model.descriptor()}", color="red")
+        log.error(f"Unsupported inference model? {model.descriptor()}")
         return request.messages
 
     if model.model_family == ModelFamily.llama3_1 or (