style: remove prints in codebase (#1146)

# What does this PR do?
- replace prints in codebase with logger
- update print_table to use rich Table

## Test Plan
- library client script in
https://github.com/meta-llama/llama-stack/pull/1145

```
llama stack list-providers
```
<img width="1407" alt="image"
src="https://github.com/user-attachments/assets/906b4f54-9e42-4e55-8968-7e3aa45525b2"
/>


[//]: # (## Documentation)

llama_stack/cli/table.py

@@ -4,75 +4,36 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-import re
-import textwrap
 from typing import Iterable
 
-from termcolor import cprint
+from rich.console import Console
-
+from rich.table import Table
-
-def strip_ansi_colors(text):
-    ansi_escape = re.compile(r"\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])")
-    return ansi_escape.sub("", text)
-
-
-def format_row(row, col_widths):
-    def wrap(text, width):
-        lines = []
-        for line in text.split("\n"):
-            if line.strip() == "":
-                lines.append("")
-            else:
-                lines.extend(textwrap.wrap(line, width, break_long_words=False, replace_whitespace=False))
-        return lines
-
-    wrapped = [wrap(item, width) for item, width in zip(row, col_widths, strict=False)]
-    max_lines = max(len(subrow) for subrow in wrapped)
-
-    lines = []
-    for i in range(max_lines):
-        line = []
-        for cell_lines, width in zip(wrapped, col_widths, strict=False):
-            value = cell_lines[i] if i < len(cell_lines) else ""
-            line.append(value + " " * (width - len(strip_ansi_colors(value))))
-        lines.append("| " + (" | ".join(line)) + " |")
-
-    return "\n".join(lines)
 
 
 def print_table(rows, headers=None, separate_rows: bool = False, sort_by: Iterable[int] = tuple()):
-    def itemlen(item):
+    # Convert rows and handle None values
-        return max([len(line) for line in strip_ansi_colors(item).split("\n")])
-
     rows = [[x or "" for x in row] for row in rows]
 
+    # Sort rows if sort_by is specified
     if sort_by:
         rows.sort(key=lambda x: tuple(x[i] for i in sort_by))
 
-    if not headers:
+    # Create Rich table
-        col_widths = [max(itemlen(item) for item in col) for col in zip(*rows, strict=False)]
+    table = Table(show_lines=separate_rows)
-    else:
-        col_widths = [
-            max(
-                itemlen(header),
-                max(itemlen(item) for item in col),
-            )
-            for header, col in zip(headers, zip(*rows, strict=False), strict=False)
-        ]
-    col_widths = [min(w, 80) for w in col_widths]
-
-    header_line = "+".join("-" * (width + 2) for width in col_widths)
-    header_line = f"+{header_line}+"
 
+    # Add headers if provided
     if headers:
-        print(header_line)
+        for header in headers:
-        cprint(format_row(headers, col_widths), "white", attrs=["bold"])
+            table.add_column(header, style="bold white")
+    else:
+        # Add unnamed columns based on first row
+        for _ in range(len(rows[0]) if rows else 0):
+            table.add_column()
 
-    print(header_line)
+    # Add rows
     for row in rows:
-        print(format_row(row, col_widths))
+        table.add_row(*row)
-        if separate_rows:
-            print(header_line)
 
-    if not separate_rows:
+    # Print table
-        print(header_line)
+    console = Console()
+    console.print(table)

llama_stack/distribution/library_client.py

@@ -47,6 +47,8 @@ from llama_stack.providers.utils.telemetry.tracing import (
     start_trace,
 )
 
+logger = logging.getLogger(__name__)
+
 T = TypeVar("T")
 
 
@@ -87,7 +89,7 @@ def convert_to_pydantic(annotation: Any, value: Any) -> Any:
         try:
             return [convert_to_pydantic(item_type, item) for item in value]
         except Exception:
-            print(f"Error converting list {value} into {item_type}")
+            logger.error(f"Error converting list {value} into {item_type}")
             return value
 
     elif origin is dict:
@@ -95,7 +97,7 @@ def convert_to_pydantic(annotation: Any, value: Any) -> Any:
         try:
             return {k: convert_to_pydantic(val_type, v) for k, v in value.items()}
         except Exception:
-            print(f"Error converting dict {value} into {val_type}")
+            logger.error(f"Error converting dict {value} into {val_type}")
             return value
 
     try:
@@ -111,9 +113,8 @@ def convert_to_pydantic(annotation: Any, value: Any) -> Any:
                     return convert_to_pydantic(union_type, value)
                 except Exception:
                     continue
-            cprint(
+            logger.warning(
                 f"Warning: direct client failed to convert parameter {value} into {annotation}: {e}",
-                "yellow",
             )
         return value
 
@@ -152,7 +153,7 @@ class LlamaStackAsLibraryClient(LlamaStackClient):
 
         for handler in root_logger.handlers[:]:
             root_logger.removeHandler(handler)
-            print(f"Removed handler {handler.__class__.__name__} from root logger")
+            logger.info(f"Removed handler {handler.__class__.__name__} from root logger")
 
     def request(self, *args, **kwargs):
         if kwargs.get("stream"):

llama_stack/providers/remote/inference/nvidia/nvidia.py

@@ -4,6 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import logging
 import warnings
 from typing import AsyncIterator, List, Optional, Union
 
@@ -25,7 +26,12 @@ from llama_stack.apis.inference import (
     ToolChoice,
     ToolConfig,
 )
-from llama_stack.models.llama.datatypes import CoreModelId, SamplingParams, ToolDefinition, ToolPromptFormat
+from llama_stack.models.llama.datatypes import (
+    CoreModelId,
+    SamplingParams,
+    ToolDefinition,
+    ToolPromptFormat,
+)
 from llama_stack.providers.utils.inference.model_registry import (
     ModelRegistryHelper,
     build_model_alias,
@@ -43,6 +49,8 @@ from .openai_utils import (
 )
 from .utils import _is_nvidia_hosted, check_health
 
+logger = logging.getLogger(__name__)
+
 _MODEL_ALIASES = [
     build_model_alias(
         "meta/llama3-8b-instruct",
@@ -90,7 +98,7 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
         # TODO(mf): filter by available models
         ModelRegistryHelper.__init__(self, model_aliases=_MODEL_ALIASES)
 
-        print(f"Initializing NVIDIAInferenceAdapter({config.url})...")
+        logger.info(f"Initializing NVIDIAInferenceAdapter({config.url})...")
 
         if _is_nvidia_hosted(config):
             if not config.api_key:

llama_stack/providers/remote/inference/nvidia/utils.py

@@ -4,12 +4,15 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import logging
 from typing import Tuple
 
 import httpx
 
 from . import NVIDIAConfig
 
+logger = logging.getLogger(__name__)
+
 
 def _is_nvidia_hosted(config: NVIDIAConfig) -> bool:
     return "integrate.api.nvidia.com" in config.url
@@ -42,7 +45,7 @@ async def check_health(config: NVIDIAConfig) -> None:
         RuntimeError: If the server is not running or ready
     """
     if not _is_nvidia_hosted(config):
-        print("Checking NVIDIA NIM health...")
+        logger.info("Checking NVIDIA NIM health...")
         try:
             is_live, is_ready = await _get_health(config.url)
             if not is_live: