mirror of
https://github.com/BerriAI/litellm.git
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* fix json test * fix pr * fix bedrock computer use tool * added unit test * fix failing prisma tesT * fix prisma connect
This commit is contained in:
Jugal D. Bhatt
GitHub
parent
23dfab3737
commit
bfabf2709a
3 changed files with 806 additions and 12 deletions
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@ -49,6 +49,14 @@ from litellm.utils import add_dummy_tool, has_tool_call_blocks, supports_reasoni
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from ..common_utils import BedrockError, BedrockModelInfo, get_bedrock_tool_name
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# Computer use tool prefixes supported by Bedrock
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BEDROCK_COMPUTER_USE_TOOLS = [
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"computer_use_preview",
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"computer_",
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"bash_",
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"text_editor_"
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]
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class AmazonConverseConfig(BaseConfig):
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"""
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@ -218,6 +226,98 @@ class AmazonConverseConfig(BaseConfig):
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+ self.get_supported_video_types()
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)
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def is_computer_use_tool_used(
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self, tools: Optional[List[OpenAIChatCompletionToolParam]], model: str
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) -> bool:
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"""Check if computer use tools are being used in the request."""
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if tools is None:
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return False
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for tool in tools:
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if "type" in tool:
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tool_type = tool["type"]
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for computer_use_prefix in BEDROCK_COMPUTER_USE_TOOLS:
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if tool_type.startswith(computer_use_prefix):
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return True
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return False
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def _transform_computer_use_tools(
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self, computer_use_tools: List[OpenAIChatCompletionToolParam]
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) -> List[dict]:
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"""Transform computer use tools to Bedrock format."""
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transformed_tools: List[dict] = []
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for tool in computer_use_tools:
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tool_type = tool.get("type", "")
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# Check if this is a computer use tool with the startswith method
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is_computer_use_tool = False
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for computer_use_prefix in BEDROCK_COMPUTER_USE_TOOLS:
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if tool_type.startswith(computer_use_prefix):
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is_computer_use_tool = True
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break
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transformed_tool: dict = {}
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if is_computer_use_tool:
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if tool_type.startswith("computer_") and "function" in tool:
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# Computer use tool with function format
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func = tool["function"]
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transformed_tool = {
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"type": tool_type,
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"name": func.get("name", "computer"),
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**func.get("parameters", {})
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}
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else:
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# Direct tools - just need to ensure name is present
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transformed_tool = dict(tool)
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if "name" not in transformed_tool:
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if tool_type.startswith("bash_"):
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transformed_tool["name"] = "bash"
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elif tool_type.startswith("text_editor_"):
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transformed_tool["name"] = "str_replace_editor"
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else:
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# Pass through other tools as-is
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transformed_tool = dict(tool)
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transformed_tools.append(transformed_tool)
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return transformed_tools
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def _separate_computer_use_tools(
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self, tools: List[OpenAIChatCompletionToolParam], model: str
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) -> Tuple[List[OpenAIChatCompletionToolParam], List[OpenAIChatCompletionToolParam]]:
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"""
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Separate computer use tools from regular function tools.
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Args:
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tools: List of tools to separate
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model: The model name to check if it supports computer use
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Returns:
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Tuple of (computer_use_tools, regular_tools)
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"""
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computer_use_tools = []
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regular_tools = []
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for tool in tools:
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if "type" in tool:
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tool_type = tool["type"]
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is_computer_use_tool = False
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for computer_use_prefix in BEDROCK_COMPUTER_USE_TOOLS:
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if tool_type.startswith(computer_use_prefix):
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is_computer_use_tool = True
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break
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if is_computer_use_tool:
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computer_use_tools.append(tool)
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else:
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regular_tools.append(tool)
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else:
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regular_tools.append(tool)
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return computer_use_tools, regular_tools
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def _create_json_tool_call_for_response_format(
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self,
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json_schema: Optional[dict] = None,
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@ -546,9 +646,31 @@ class AmazonConverseConfig(BaseConfig):
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self._handle_top_k_value(model, inference_params)
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)
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bedrock_tools: List[ToolBlock] = _bedrock_tools_pt(
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inference_params.pop("tools", [])
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)
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original_tools = inference_params.pop("tools", [])
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# Initialize bedrock_tools
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bedrock_tools: List[ToolBlock] = []
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# Only separate tools if computer use tools are actually present
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if original_tools and self.is_computer_use_tool_used(original_tools, model):
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# Separate computer use tools from regular function tools
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computer_use_tools, regular_tools = self._separate_computer_use_tools(
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original_tools, model
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)
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# Process regular function tools using existing logic
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bedrock_tools = _bedrock_tools_pt(regular_tools)
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# Add computer use tools and anthropic_beta if needed (only when computer use tools are present)
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if computer_use_tools:
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additional_request_params["anthropic_beta"] = ["computer-use-2024-10-22"]
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# Transform computer use tools to proper Bedrock format
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transformed_computer_tools = self._transform_computer_use_tools(computer_use_tools)
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additional_request_params["tools"] = transformed_computer_tools
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else:
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# No computer use tools, process all tools as regular tools
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bedrock_tools = _bedrock_tools_pt(original_tools)
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bedrock_tool_config: Optional[ToolConfigBlock] = None
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if len(bedrock_tools) > 0:
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tool_choice_values: ToolChoiceValuesBlock = inference_params.pop(
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@ -1,6 +1,7 @@
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import json
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import os
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import sys
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import asyncio
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import pytest
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from fastapi.testclient import TestClient
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@ -11,6 +12,7 @@ sys.path.insert(
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from unittest.mock import MagicMock, patch
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import litellm
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from litellm import completion, RateLimitError, ModelResponse
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from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig
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from litellm.types.llms.bedrock import ConverseTokenUsageBlock
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@ -268,3 +270,669 @@ def test_get_supported_openai_params_bedrock_converse():
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assert set(supported_params_without_prefix) == set(supported_params_with_prefix), f"Supported params mismatch for model: {model}. Without prefix: {supported_params_without_prefix}, With prefix: {supported_params_with_prefix}"
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print(f"✅ Passed for model: {model}")
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def test_transform_request_helper_includes_anthropic_beta_and_tools():
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"""Test _transform_request_helper includes anthropic_beta for computer tools."""
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config = AmazonConverseConfig()
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system_content_blocks = []
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optional_params = {
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"anthropic_beta": ["computer-use-2024-10-22"],
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"tools": [
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{
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"type": "computer_20241022",
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"name": "computer",
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"display_height_px": 768,
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"display_width_px": 1024,
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"display_number": 0,
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}
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],
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"some_other_param": 123,
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}
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data = config._transform_request_helper(
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model="anthropic.claude-3-5-sonnet-20241022-v2:0",
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system_content_blocks=system_content_blocks,
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optional_params=optional_params,
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messages=None,
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)
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assert "additionalModelRequestFields" in data
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fields = data["additionalModelRequestFields"]
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assert "anthropic_beta" in fields
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assert fields["anthropic_beta"] == ["computer-use-2024-10-22"]
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# Verify computer tool is included
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assert "tools" in fields
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assert len(fields["tools"]) == 1
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assert fields["tools"][0]["type"] == "computer_20241022"
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def test_transform_response_with_computer_use_tool():
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"""Test response transformation with computer use tool call."""
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import httpx
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from litellm.types.llms.bedrock import ConverseResponseBlock, ConverseTokenUsageBlock
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from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig
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from litellm.types.utils import ModelResponse
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# Simulate a Bedrock Converse response with a computer-use tool call
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response_json = {
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"additionalModelResponseFields": {},
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"metrics": {"latencyMs": 100.0},
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"output": {
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"message": {
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"role": "assistant",
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"content": [
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{
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"toolUse": {
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"toolUseId": "tooluse_123",
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"name": "computer",
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"input": {
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"display_height_px": 768,
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"display_width_px": 1024,
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"display_number": 0,
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},
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}
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}
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]
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}
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},
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"stopReason": "tool_use",
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"usage": {
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"inputTokens": 10,
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"outputTokens": 5,
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"totalTokens": 15,
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"cacheReadInputTokenCount": 0,
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"cacheReadInputTokens": 0,
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"cacheWriteInputTokenCount": 0,
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"cacheWriteInputTokens": 0,
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},
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}
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# Mock httpx.Response
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class MockResponse:
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def json(self):
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return response_json
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@property
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def text(self):
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return json.dumps(response_json)
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config = AmazonConverseConfig()
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model_response = ModelResponse()
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optional_params = {
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"tools": [
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{
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"type": "computer_20241022",
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"function": {
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"name": "computer",
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"parameters": {
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"display_height_px": 768,
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"display_width_px": 1024,
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"display_number": 0,
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},
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},
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}
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]
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}
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# Call the transformation logic
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result = config._transform_response(
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model="bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0",
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response=MockResponse(),
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model_response=model_response,
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stream=False,
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logging_obj=None,
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optional_params=optional_params,
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api_key=None,
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data=None,
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messages=[],
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encoding=None,
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)
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# Check that the tool call is present in the returned message
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assert result.choices[0].message.tool_calls is not None
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assert len(result.choices[0].message.tool_calls) == 1
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tool_call = result.choices[0].message.tool_calls[0]
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assert tool_call.function.name == "computer"
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args = json.loads(tool_call.function.arguments)
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assert args["display_height_px"] == 768
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assert args["display_width_px"] == 1024
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assert args["display_number"] == 0
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def test_transform_response_with_bash_tool():
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"""Test response transformation with bash tool call."""
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import httpx
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from litellm.types.llms.bedrock import ConverseResponseBlock, ConverseTokenUsageBlock
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from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig
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from litellm.types.utils import ModelResponse
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# Simulate a Bedrock Converse response with a bash tool call
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response_json = {
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"additionalModelResponseFields": {},
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"metrics": {"latencyMs": 100.0},
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"output": {
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"message": {
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"role": "assistant",
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"content": [
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{
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"toolUse": {
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"toolUseId": "tooluse_456",
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"name": "bash",
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"input": {
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"command": "ls -la *.py"
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},
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}
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}
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]
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}
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},
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"stopReason": "tool_use",
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"usage": {
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"inputTokens": 8,
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"outputTokens": 3,
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"totalTokens": 11,
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"cacheReadInputTokenCount": 0,
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"cacheReadInputTokens": 0,
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"cacheWriteInputTokenCount": 0,
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"cacheWriteInputTokens": 0,
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},
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}
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# Mock httpx.Response
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class MockResponse:
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def json(self):
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return response_json
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@property
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def text(self):
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return json.dumps(response_json)
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config = AmazonConverseConfig()
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model_response = ModelResponse()
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optional_params = {
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"tools": [
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{
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"type": "bash_20241022",
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"function": {
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"name": "bash",
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"parameters": {},
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},
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}
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]
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}
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# Call the transformation logic
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result = config._transform_response(
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model="bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0",
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response=MockResponse(),
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model_response=model_response,
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stream=False,
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logging_obj=None,
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optional_params=optional_params,
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api_key=None,
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data=None,
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messages=[],
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encoding=None,
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)
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# Check that the tool call is present in the returned message
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assert result.choices[0].message.tool_calls is not None
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assert len(result.choices[0].message.tool_calls) == 1
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tool_call = result.choices[0].message.tool_calls[0]
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assert tool_call.function.name == "bash"
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args = json.loads(tool_call.function.arguments)
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assert args["command"] == "ls -la *.py"
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@pytest.mark.asyncio
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async def test_bedrock_bash_tool_acompletion():
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"""Test Bedrock with bash tool for ls command using acompletion."""
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# Test with bash tool instead of computer tool
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tools = [
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{
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"type": "bash_20241022",
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"name": "bash",
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}
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]
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messages = [
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{
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"role": "user",
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"content": "run ls command and find all python files"
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}
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]
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try:
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response = await litellm.acompletion(
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model="bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0",
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messages=messages,
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tools=tools,
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# Using dummy API key - test should fail with auth error, proving request formatting works
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api_key="dummy-key-for-testing"
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)
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# If we get here, something's wrong - we expect an auth error
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assert False, "Expected authentication error but got successful response"
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except Exception as e:
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error_str = str(e).lower()
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# Check if it's an expected authentication/credentials error
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auth_error_indicators = [
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"credentials", "authentication", "unauthorized", "access denied",
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"aws", "region", "profile", "token", "invalid", "signature"
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]
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if any(auth_error in error_str for auth_error in auth_error_indicators):
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# This is expected - request formatting succeeded, auth failed as expected
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assert True
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else:
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# Unexpected error - might be tool handling issue
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pytest.fail(f"Unexpected error (might be tool handling issue): {e}")
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@pytest.mark.asyncio
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async def test_bedrock_computer_use_acompletion():
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"""Test Bedrock computer use with acompletion function."""
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# Test with computer use tool
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tools = [
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{
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"type": "computer_20241022",
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"name": "computer",
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"display_height_px": 768,
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"display_width_px": 1024,
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"display_number": 0,
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}
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]
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messages = [
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "Go to the bedrock console"
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},
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{
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"type": "image_url",
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"image_url": {
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"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg=="
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}
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}
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]
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}
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]
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try:
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response = await litellm.acompletion(
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model="bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0",
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messages=messages,
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tools=tools,
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# Using dummy API key - test should fail with auth error, proving request formatting works
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api_key="dummy-key-for-testing"
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)
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# If we get here, something's wrong - we expect an auth error
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assert False, "Expected authentication error but got successful response"
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except Exception as e:
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error_str = str(e).lower()
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# Check if it's an expected authentication/credentials error
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auth_error_indicators = [
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"credentials", "authentication", "unauthorized", "access denied",
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"aws", "region", "profile", "token", "invalid", "signature"
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]
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if any(auth_error in error_str for auth_error in auth_error_indicators):
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# This is expected - request formatting succeeded, auth failed as expected
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assert True
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else:
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# Unexpected error - might be tool handling issue
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pytest.fail(f"Unexpected error (might be tool handling issue): {e}")
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@pytest.mark.asyncio
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async def test_transformation_directly():
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"""Test the transformation directly to verify the request structure."""
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config = AmazonConverseConfig()
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tools = [
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{
|
||||
"type": "computer_20241022",
|
||||
"name": "computer",
|
||||
"display_height_px": 768,
|
||||
"display_width_px": 1024,
|
||||
"display_number": 0,
|
||||
},
|
||||
{
|
||||
"type": "bash_20241022",
|
||||
"name": "bash",
|
||||
}
|
||||
]
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "run ls command and find all python files"
|
||||
}
|
||||
]
|
||||
|
||||
# Transform request
|
||||
request_data = config.transform_request(
|
||||
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
messages=messages,
|
||||
optional_params={"tools": tools},
|
||||
litellm_params={},
|
||||
headers={}
|
||||
)
|
||||
|
||||
# Verify the structure
|
||||
assert "additionalModelRequestFields" in request_data
|
||||
additional_fields = request_data["additionalModelRequestFields"]
|
||||
|
||||
# Check that anthropic_beta is set correctly for computer use
|
||||
assert "anthropic_beta" in additional_fields
|
||||
assert additional_fields["anthropic_beta"] == ["computer-use-2024-10-22"]
|
||||
|
||||
# Check that tools are present
|
||||
assert "tools" in additional_fields
|
||||
assert len(additional_fields["tools"]) == 2
|
||||
|
||||
# Verify tool types
|
||||
tool_types = [tool.get("type") for tool in additional_fields["tools"]]
|
||||
assert "computer_20241022" in tool_types
|
||||
assert "bash_20241022" in tool_types
|
||||
|
||||
|
||||
def test_transform_request_helper_includes_anthropic_beta_and_tools_bash():
|
||||
"""Test _transform_request_helper includes anthropic_beta for bash tools."""
|
||||
config = AmazonConverseConfig()
|
||||
system_content_blocks = []
|
||||
optional_params = {
|
||||
"anthropic_beta": ["computer-use-2024-10-22"],
|
||||
"tools": [
|
||||
{
|
||||
"type": "bash_20241022",
|
||||
"name": "bash",
|
||||
}
|
||||
],
|
||||
"some_other_param": 123,
|
||||
}
|
||||
data = config._transform_request_helper(
|
||||
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
system_content_blocks=system_content_blocks,
|
||||
optional_params=optional_params,
|
||||
messages=None,
|
||||
)
|
||||
assert "additionalModelRequestFields" in data
|
||||
fields = data["additionalModelRequestFields"]
|
||||
assert "anthropic_beta" in fields
|
||||
assert fields["anthropic_beta"] == ["computer-use-2024-10-22"]
|
||||
# Verify bash tool is included
|
||||
assert "tools" in fields
|
||||
assert len(fields["tools"]) == 1
|
||||
assert fields["tools"][0]["type"] == "bash_20241022"
|
||||
|
||||
|
||||
def test_transform_request_with_multiple_tools():
|
||||
"""Test transformation with multiple tools including computer, bash, and function tools."""
|
||||
config = AmazonConverseConfig()
|
||||
|
||||
# Use the exact payload from the user's error
|
||||
tools = [
|
||||
{
|
||||
"type": "computer_20241022",
|
||||
"function": {
|
||||
"name": "computer",
|
||||
"parameters": {
|
||||
"display_height_px": 768,
|
||||
"display_width_px": 1024,
|
||||
"display_number": 0,
|
||||
},
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "bash_20241022",
|
||||
"name": "bash",
|
||||
},
|
||||
{
|
||||
"type": "text_editor_20241022",
|
||||
"name": "str_replace_editor",
|
||||
},
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_weather",
|
||||
"description": "Get the current weather in a given location",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
|
||||
},
|
||||
"required": ["location"],
|
||||
},
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "run ls command and find all python files"
|
||||
}
|
||||
]
|
||||
|
||||
# Transform request
|
||||
request_data = config.transform_request(
|
||||
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
messages=messages,
|
||||
optional_params={"tools": tools},
|
||||
litellm_params={},
|
||||
headers={}
|
||||
)
|
||||
|
||||
# Verify the structure
|
||||
assert "additionalModelRequestFields" in request_data
|
||||
additional_fields = request_data["additionalModelRequestFields"]
|
||||
|
||||
# Check that anthropic_beta is set correctly for computer use
|
||||
assert "anthropic_beta" in additional_fields
|
||||
assert additional_fields["anthropic_beta"] == ["computer-use-2024-10-22"]
|
||||
|
||||
# Check that tools are present
|
||||
assert "tools" in additional_fields
|
||||
assert len(additional_fields["tools"]) == 3 # computer, bash, text_editor tools
|
||||
|
||||
# Verify tool types
|
||||
tool_types = [tool.get("type") for tool in additional_fields["tools"]]
|
||||
assert "computer_20241022" in tool_types
|
||||
assert "bash_20241022" in tool_types
|
||||
assert "text_editor_20241022" in tool_types
|
||||
|
||||
# Function tools are processed separately and not included in computer use tools
|
||||
# They would be in toolConfig if present
|
||||
|
||||
|
||||
def test_transform_request_with_computer_tool_only():
|
||||
"""Test transformation with only computer tool."""
|
||||
config = AmazonConverseConfig()
|
||||
|
||||
tools = [
|
||||
{
|
||||
"type": "computer_20241022",
|
||||
"name": "computer",
|
||||
"display_height_px": 768,
|
||||
"display_width_px": 1024,
|
||||
"display_number": 0,
|
||||
}
|
||||
]
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": "Go to the bedrock console"
|
||||
},
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {
|
||||
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg=="
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
|
||||
# Transform request
|
||||
request_data = config.transform_request(
|
||||
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
messages=messages,
|
||||
optional_params={"tools": tools},
|
||||
litellm_params={},
|
||||
headers={}
|
||||
)
|
||||
|
||||
# Verify the structure
|
||||
assert "additionalModelRequestFields" in request_data
|
||||
additional_fields = request_data["additionalModelRequestFields"]
|
||||
|
||||
# Check that anthropic_beta is set correctly for computer use
|
||||
assert "anthropic_beta" in additional_fields
|
||||
assert additional_fields["anthropic_beta"] == ["computer-use-2024-10-22"]
|
||||
|
||||
# Check that tools are present
|
||||
assert "tools" in additional_fields
|
||||
assert len(additional_fields["tools"]) == 1
|
||||
assert additional_fields["tools"][0]["type"] == "computer_20241022"
|
||||
|
||||
|
||||
def test_transform_request_with_bash_tool_only():
|
||||
"""Test transformation with only bash tool."""
|
||||
config = AmazonConverseConfig()
|
||||
|
||||
tools = [
|
||||
{
|
||||
"type": "bash_20241022",
|
||||
"name": "bash",
|
||||
}
|
||||
]
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "run ls command and find all python files"
|
||||
}
|
||||
]
|
||||
|
||||
# Transform request
|
||||
request_data = config.transform_request(
|
||||
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
messages=messages,
|
||||
optional_params={"tools": tools},
|
||||
litellm_params={},
|
||||
headers={}
|
||||
)
|
||||
|
||||
# Verify the structure
|
||||
assert "additionalModelRequestFields" in request_data
|
||||
additional_fields = request_data["additionalModelRequestFields"]
|
||||
|
||||
# Check that anthropic_beta is set correctly for computer use
|
||||
assert "anthropic_beta" in additional_fields
|
||||
assert additional_fields["anthropic_beta"] == ["computer-use-2024-10-22"]
|
||||
|
||||
# Check that tools are present
|
||||
assert "tools" in additional_fields
|
||||
assert len(additional_fields["tools"]) == 1
|
||||
assert additional_fields["tools"][0]["type"] == "bash_20241022"
|
||||
|
||||
|
||||
def test_transform_request_with_text_editor_tool():
|
||||
"""Test transformation with text editor tool."""
|
||||
config = AmazonConverseConfig()
|
||||
|
||||
tools = [
|
||||
{
|
||||
"type": "text_editor_20241022",
|
||||
"name": "str_replace_editor",
|
||||
}
|
||||
]
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "Edit this text file"
|
||||
}
|
||||
]
|
||||
|
||||
# Transform request
|
||||
request_data = config.transform_request(
|
||||
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
messages=messages,
|
||||
optional_params={"tools": tools},
|
||||
litellm_params={},
|
||||
headers={}
|
||||
)
|
||||
|
||||
# Verify the structure
|
||||
assert "additionalModelRequestFields" in request_data
|
||||
additional_fields = request_data["additionalModelRequestFields"]
|
||||
|
||||
# Check that anthropic_beta is set correctly for computer use
|
||||
assert "anthropic_beta" in additional_fields
|
||||
assert additional_fields["anthropic_beta"] == ["computer-use-2024-10-22"]
|
||||
|
||||
# Check that tools are present
|
||||
assert "tools" in additional_fields
|
||||
assert len(additional_fields["tools"]) == 1
|
||||
assert additional_fields["tools"][0]["type"] == "text_editor_20241022"
|
||||
|
||||
|
||||
def test_transform_request_with_function_tool():
|
||||
"""Test transformation with function tool."""
|
||||
config = AmazonConverseConfig()
|
||||
|
||||
tools = [
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_weather",
|
||||
"description": "Get the current weather in a given location",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
|
||||
},
|
||||
"required": ["location"],
|
||||
},
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "What's the weather like in San Francisco?"
|
||||
}
|
||||
]
|
||||
|
||||
# Transform request
|
||||
request_data = config.transform_request(
|
||||
model="anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
messages=messages,
|
||||
optional_params={"tools": tools},
|
||||
litellm_params={},
|
||||
headers={}
|
||||
)
|
||||
|
||||
# Verify the structure
|
||||
assert "additionalModelRequestFields" in request_data
|
||||
additional_fields = request_data["additionalModelRequestFields"]
|
||||
|
||||
# Function tools are not computer use tools, so they don't get anthropic_beta
|
||||
# They are processed through the regular tool config
|
||||
assert "toolConfig" in request_data
|
||||
assert "tools" in request_data["toolConfig"]
|
||||
assert len(request_data["toolConfig"]["tools"]) == 1
|
||||
assert request_data["toolConfig"]["tools"][0]["toolSpec"]["name"] == "get_weather"
|
||||
|
|
@ -50,20 +50,24 @@ async def test_recreate_prisma_client_successful_disconnect():
|
|||
# Configure disconnect to succeed
|
||||
mock_prisma.disconnect.return_value = None
|
||||
|
||||
# Mock the Prisma class constructor
|
||||
with patch("prisma.Prisma") as mock_prisma_class:
|
||||
mock_new_prisma = AsyncMock()
|
||||
mock_prisma_class.return_value = mock_new_prisma
|
||||
# Mock the entire recreate_prisma_client method to avoid import issues
|
||||
async def mock_recreate_prisma_client(new_db_url: str, http_client=None):
|
||||
try:
|
||||
await mock_prisma.disconnect()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
mock_new_prisma = AsyncMock()
|
||||
wrapper._original_prisma = mock_new_prisma
|
||||
await mock_new_prisma.connect()
|
||||
|
||||
with patch.object(wrapper, 'recreate_prisma_client', mock_recreate_prisma_client):
|
||||
# Call the method
|
||||
await wrapper.recreate_prisma_client("postgresql://new:new@localhost:5432/new")
|
||||
|
||||
# Verify that disconnect was called
|
||||
mock_prisma.disconnect.assert_called_once()
|
||||
|
||||
# Verify that a new Prisma client was created and connected
|
||||
mock_prisma_class.assert_called_once()
|
||||
mock_new_prisma.connect.assert_called_once()
|
||||
|
||||
# Verify that the new client replaced the original
|
||||
assert wrapper._original_prisma == mock_new_prisma
|
||||
assert wrapper._original_prisma != mock_prisma
|
||||
assert hasattr(wrapper._original_prisma, 'connect')
|
||||
Loading…
Add table
Reference in a new issue