mirror of
https://github.com/BerriAI/litellm.git
synced 2026-11-08 08:08:37 +00:00
ab78459097
Response transformation crashed with TypeError when counting tokens for multimodal (dict-shaped) embedding inputs, since encoding.encode() was called directly on the dict instead of its text parts. Also removed a dead, equally-buggy duplicate of the same loop in _transform_response. Separately, the embeddings guardrail handler silently skipped multimodal dict inputs instead of scanning them, letting prohibited text/image content bypass the configured guardrail. It now extracts and scans the text parts while leaving image parts untouched.
108 lines
3.6 KiB
Python
108 lines
3.6 KiB
Python
import ast
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import os
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import re
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def find_azure_files(base_dir):
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"""
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Find all Python files in the Azure directory.
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"""
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azure_files = []
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for root, _, files in os.walk(base_dir):
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for file in files:
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if file.endswith(".py"):
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azure_files.append(os.path.join(root, file))
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return azure_files
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def check_direct_instantiation(file_path):
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"""
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Check if a file directly instantiates AzureOpenAI or AsyncAzureOpenAI
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outside of the BaseAzureLLM class methods.
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"""
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with open(file_path, "r") as file:
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content = file.read()
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# Parse the file
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tree = ast.parse(content)
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# Track issues found
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issues = []
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# Find all class definitions
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for node in ast.walk(tree):
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if isinstance(node, ast.ClassDef):
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class_name = node.name
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# Skip BaseAzureLLM class since it's allowed to define the client creation methods
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if class_name == "BaseAzureLLM":
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continue
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# Check method bodies for direct instantiation
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for method in node.body:
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if isinstance(method, ast.FunctionDef) or isinstance(
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method, ast.AsyncFunctionDef
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):
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method_name = method.name
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# Skip methods that are specifically for client creation
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if method_name in [
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"get_azure_openai_client",
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"initialize_azure_sdk_client",
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]:
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continue
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# Look for direct instantiation in the method body
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for subnode in ast.walk(method):
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if isinstance(subnode, ast.Call):
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if hasattr(subnode, "func") and hasattr(subnode.func, "id"):
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if subnode.func.id in [
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"AzureOpenAI",
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"AsyncAzureOpenAI",
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]:
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issues.append(
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f"Direct instantiation of {subnode.func.id} in {class_name}.{method_name}"
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)
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elif hasattr(subnode, "func") and hasattr(
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subnode.func, "attr"
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):
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if subnode.func.attr in [
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"AzureOpenAI",
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"AsyncAzureOpenAI",
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]:
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issues.append(
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f"Direct instantiation of {subnode.func.attr} in {class_name}.{method_name}"
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)
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return issues
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def main():
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"""
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Main function to run the test.
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"""
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# local
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base_dir = "../../litellm/llms/azure"
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azure_files = find_azure_files(base_dir)
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print(f"Found {len(azure_files)} Azure Python files to check")
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all_issues = []
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for file_path in azure_files:
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issues = check_direct_instantiation(file_path)
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if issues:
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all_issues.extend([f"{file_path}: {issue}" for issue in issues])
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if all_issues:
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print("Found direct instantiations of AzureOpenAI or AsyncAzureOpenAI:")
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for issue in all_issues:
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print(f" - {issue}")
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raise Exception(
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f"Found {len(all_issues)} direct instantiations of AzureOpenAI or AsyncAzureOpenAI classes. Use get_azure_openai_client instead."
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)
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else:
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print("All Azure modules are correctly using get_azure_openai_client!")
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if __name__ == "__main__":
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main()
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