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fix: add the missing required tool parameters for Anthropic models
Fixes #1692 PiperOrigin-RevId: 795125801
This commit is contained in:
Xuan Yang
committed by
Copybara-Service
Copybara-Service
parent
9ba8eec220
commit
e63e2a7106
@@ -216,25 +216,31 @@ def _update_type_string(value_dict: dict[str, Any]):
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def function_declaration_to_tool_param(
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function_declaration: types.FunctionDeclaration,
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) -> anthropic_types.ToolParam:
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"""Converts a function declaration to an Anthropic tool param."""
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assert function_declaration.name
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properties = {}
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if (
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function_declaration.parameters
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and function_declaration.parameters.properties
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):
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for key, value in function_declaration.parameters.properties.items():
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value_dict = value.model_dump(exclude_none=True)
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_update_type_string(value_dict)
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properties[key] = value_dict
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required_params = []
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if function_declaration.parameters:
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if function_declaration.parameters.properties:
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for key, value in function_declaration.parameters.properties.items():
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value_dict = value.model_dump(exclude_none=True)
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_update_type_string(value_dict)
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properties[key] = value_dict
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if function_declaration.parameters.required:
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required_params = function_declaration.parameters.required
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input_schema = {
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"type": "object",
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"properties": properties,
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}
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if required_params:
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input_schema["required"] = required_params
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return anthropic_types.ToolParam(
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name=function_declaration.name,
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description=function_declaration.description or "",
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input_schema={
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"type": "object",
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"properties": properties,
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},
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input_schema=input_schema,
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)
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@@ -20,6 +20,7 @@ from anthropic import types as anthropic_types
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from google.adk import version as adk_version
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from google.adk.models import anthropic_llm
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from google.adk.models.anthropic_llm import Claude
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from google.adk.models.anthropic_llm import function_declaration_to_tool_param
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from google.adk.models.llm_request import LlmRequest
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from google.adk.models.llm_response import LlmResponse
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from google.genai import types
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@@ -96,6 +97,200 @@ def test_supported_models():
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assert models[1] == r"claude-.*-4.*"
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function_declaration_test_cases = [
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(
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"function_with_no_parameters",
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types.FunctionDeclaration(
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name="get_current_time",
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description="Gets the current time.",
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),
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anthropic_types.ToolParam(
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name="get_current_time",
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description="Gets the current time.",
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input_schema={"type": "object", "properties": {}},
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),
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),
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(
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"function_with_one_optional_parameter",
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types.FunctionDeclaration(
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name="get_weather",
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description="Gets weather information for a given location.",
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"location": types.Schema(
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type=types.Type.STRING,
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description="City and state, e.g., San Francisco, CA",
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)
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},
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),
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),
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anthropic_types.ToolParam(
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name="get_weather",
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description="Gets weather information for a given location.",
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input_schema={
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": (
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"City and state, e.g., San Francisco, CA"
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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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(
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"function_with_one_required_parameter",
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types.FunctionDeclaration(
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name="get_stock_price",
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description="Gets the current price for a stock ticker.",
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"ticker": types.Schema(
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type=types.Type.STRING,
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description="The stock ticker, e.g., AAPL",
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)
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},
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required=["ticker"],
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),
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),
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anthropic_types.ToolParam(
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name="get_stock_price",
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description="Gets the current price for a stock ticker.",
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input_schema={
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"type": "object",
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"properties": {
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"ticker": {
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"type": "string",
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"description": "The stock ticker, e.g., AAPL",
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}
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},
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"required": ["ticker"],
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},
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),
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),
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(
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"function_with_multiple_mixed_parameters",
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types.FunctionDeclaration(
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name="submit_order",
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description="Submits a product order.",
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"product_id": types.Schema(
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type=types.Type.STRING, description="The product ID"
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),
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"quantity": types.Schema(
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type=types.Type.INTEGER,
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description="The order quantity",
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),
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"notes": types.Schema(
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type=types.Type.STRING,
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description="Optional order notes",
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),
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},
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required=["product_id", "quantity"],
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),
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),
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anthropic_types.ToolParam(
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name="submit_order",
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description="Submits a product order.",
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input_schema={
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"type": "object",
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"properties": {
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"product_id": {
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"type": "string",
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"description": "The product ID",
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},
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"quantity": {
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"type": "integer",
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"description": "The order quantity",
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},
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"notes": {
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"type": "string",
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"description": "Optional order notes",
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},
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},
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"required": ["product_id", "quantity"],
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},
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),
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),
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(
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"function_with_complex_nested_parameter",
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types.FunctionDeclaration(
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name="create_playlist",
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description="Creates a playlist from a list of songs.",
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"playlist_name": types.Schema(
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type=types.Type.STRING,
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description="The name for the new playlist",
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),
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"songs": types.Schema(
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type=types.Type.ARRAY,
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description="A list of songs to add to the playlist",
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items=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"title": types.Schema(type=types.Type.STRING),
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"artist": types.Schema(type=types.Type.STRING),
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},
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required=["title", "artist"],
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),
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),
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},
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required=["playlist_name", "songs"],
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),
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),
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anthropic_types.ToolParam(
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name="create_playlist",
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description="Creates a playlist from a list of songs.",
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input_schema={
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"type": "object",
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"properties": {
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"playlist_name": {
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"type": "string",
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"description": "The name for the new playlist",
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},
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"songs": {
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"type": "array",
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"description": "A list of songs to add to the playlist",
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"items": {
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"type": "object",
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"properties": {
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"title": {"type": "string"},
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"artist": {"type": "string"},
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},
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"required": ["title", "artist"],
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},
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},
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},
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"required": ["playlist_name", "songs"],
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},
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),
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),
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]
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@pytest.mark.parametrize(
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"_, function_declaration, expected_tool_param",
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function_declaration_test_cases,
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ids=[case[0] for case in function_declaration_test_cases],
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)
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async def test_function_declaration_to_tool_param(
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_, function_declaration, expected_tool_param
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):
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"""Test function_declaration_to_tool_param."""
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assert (
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function_declaration_to_tool_param(function_declaration)
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== expected_tool_param
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)
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@pytest.mark.asyncio
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async def test_generate_content_async(
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claude_llm, llm_request, generate_content_response, generate_llm_response
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