robocorp: rm package (now langchain-sema4) (#26471)

2025-08-14 15:16:21 +00:00 · 2024-09-13 15:54:00 -07:00 · 2024-09-13 15:54:00 -07:00 · ca304ae046
commit ca304ae046
parent 537f6924dc
24 changed files with 0 additions and 4527 deletions
--- a/libs/partners/robocorp/.gitignore
+++ b/libs/partners/robocorp/.gitignore
@ -1 +0,0 @@
 __pycache__
--- a/libs/partners/robocorp/LICENSE
+++ b/libs/partners/robocorp/LICENSE
@ -1,21 +0,0 @@
 MIT License
 Copyright (c) 2023 LangChain, Inc.
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
 in the Software without restriction, including without limitation the rights
 to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 copies of the Software, and to permit persons to whom the Software is
 furnished to do so, subject to the following conditions:
 The above copyright notice and this permission notice shall be included in all
 copies or substantial portions of the Software.
 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
--- a/libs/partners/robocorp/Makefile
+++ b/libs/partners/robocorp/Makefile
@ -1,59 +0,0 @@
 .PHONY: all format lint test tests integration_tests docker_tests help extended_tests
 # Default target executed when no arguments are given to make.
 all: help
 # Define a variable for the test file path.
 TEST_FILE ?= tests/unit_tests/
 integration_test integration_tests: TEST_FILE=tests/integration_tests/
 test tests integration_test integration_tests:
 	poetry run pytest $(TEST_FILE)
 test_watch:
 	poetry run ptw --snapshot-update --now . -- -vv $(TEST_FILE)
 ######################
 # LINTING AND FORMATTING
 ######################
 # Define a variable for Python and notebook files.
 PYTHON_FILES=.
 MYPY_CACHE=.mypy_cache
 lint format: PYTHON_FILES=.
 lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/action-server --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
 lint_package: PYTHON_FILES=langchain_robocorp
 lint_tests: PYTHON_FILES=tests
 lint_tests: MYPY_CACHE=.mypy_cache_test
 lint lint_diff lint_package lint_tests:
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES)
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
 format format_diff:
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES)
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES)
 spell_check:
 	poetry run codespell --toml pyproject.toml
 spell_fix:
 	poetry run codespell --toml pyproject.toml -w
 check_imports: $(shell find langchain_robocorp -name '*.py')
 	poetry run python ./scripts/check_imports.py $^
 ######################
 # HELP
 ######################
 help:
 	@echo '----'
 	@echo 'check_imports				- check imports'
 	@echo 'format                       - run code formatters'
 	@echo 'lint                         - run linters'
 	@echo 'test                         - run unit tests'
 	@echo 'tests                        - run unit tests'
 	@echo 'test TEST_FILE=<test_file>   - run all tests in file'
--- a/libs/partners/robocorp/README.md
+++ b/libs/partners/robocorp/README.md
@ -1,17 +0,0 @@
 # langchain-robocorp
 | Note: this package is deprecated in favor of the renamed `langchain-sema4` package ([repo](https://github.com/langchain-ai/langchain-sema4), [package](https://pypi.org/project/langchain-sema4/)). |
 |-|
 This package contains the LangChain integrations for [Robocorp Action Server](https://github.com/robocorp/robocorp).
 Action Server enables an agent to execute actions in the real world. 
 ## Installation
 ```bash
 pip install -U langchain-robocorp
 ```
 ## Action Server Toolkit
 See [ActionServerToolkit](https://python.langchain.com/docs/integrations/tools/robocorp) for detailed documentation.
--- a/libs/partners/robocorp/langchain_robocorp/init.py
+++ b/libs/partners/robocorp/langchain_robocorp/init.py
@ -1,5 +0,0 @@
 from langchain_robocorp.toolkits import ActionServerToolkit
 __all__ = [
    "ActionServerToolkit",
 ]
--- a/libs/partners/robocorp/langchain_robocorp/_common.py
+++ b/libs/partners/robocorp/langchain_robocorp/_common.py
@ -1,175 +0,0 @@
 import time
 from dataclasses import dataclass
 from typing import Any, Dict, List, Set, Tuple, Union, cast
 from langchain_core.utils.json_schema import dereference_refs
 from langchain_core.utils.pydantic import is_basemodel_instance
 from pydantic import (
    BaseModel,
    Field,
    create_model,
 )
@dataclass(frozen=True)
 class ReducedOpenAPISpec:
    """A reduced OpenAPI spec.
    This is reduced representation for OpenAPI specs.
    Attributes:
        servers: The servers in the spec.
        description: The description of the spec.
        endpoints: The endpoints in the spec.
    """
    servers: List[dict]
    description: str
    endpoints: List[Tuple[str, dict]]
 def reduce_openapi_spec(url: str, spec: dict) -> ReducedOpenAPISpec:
    """Simplify OpenAPI spec to only required information for the agent"""
    # 1. Consider only GET and POST
    endpoints = [
        (route, docs)
        for route, operation in spec["paths"].items()
        for operation_name, docs in operation.items()
        if operation_name in ["get", "post"]
    ]
    # 2. Replace any refs so that complete docs are retrieved.
    # Note: probably want to do this post-retrieval, it blows up the size of the spec.
    # 3. Strip docs down to required request args + happy path response.
    def reduce_endpoint_docs(docs: dict) -> dict:
        out = {}
        if docs.get("summary"):
            out["summary"] = docs.get("summary")
        if docs.get("operationId"):
            out["operationId"] = docs.get("operationId")
        if docs.get("description"):
            out["description"] = docs.get("description")
        if docs.get("parameters"):
            out["parameters"] = [
                parameter
                for parameter in docs.get("parameters", [])
                if parameter.get("required")
            ]
        if "200" in docs["responses"]:
            out["responses"] = docs["responses"]["200"]
        if docs.get("requestBody"):
            out["requestBody"] = docs.get("requestBody")
        return out
    endpoints = [
        (name, reduce_endpoint_docs(dereference_refs(docs, full_schema=spec)))
        for name, docs in endpoints
    ]
    return ReducedOpenAPISpec(
        servers=[
            {
                "url": url,
            }
        ],
        description=spec["info"].get("description", ""),
        endpoints=endpoints,
    )
 type_mapping = {
    "string": str,
    "integer": int,
    "number": float,
    "object": dict,
    "array": list,
    "boolean": bool,
    "null": type(None),
 }
 def get_schema(endpoint_spec: dict) -> dict:
    return (
        endpoint_spec.get("requestBody", {})
        .get("content", {})
        .get("application/json", {})
        .get("schema", {})
    )
 def create_field(
    schema: dict, required: bool, created_model_names: Set[str]
 ) -> Tuple[Any, Any]:
    """
    Creates a Pydantic field based on the schema definition.
    """
    if "anyOf" in schema:
        field_types = [
            create_field(sub_schema, required, created_model_names)[0]
            for sub_schema in schema["anyOf"]
        ]
        if len(field_types) == 1:
            field_type = field_types[0]  # Simplified handling
        else:
            field_type = Union[tuple(field_types)]
    else:
        field_type = type_mapping.get(schema.get("type", "string"), str)
    description = schema.get("description", "")
    # Handle nested objects
    if schema.get("type") == "object":
        nested_fields = {
            k: create_field(v, k in schema.get("required", []), created_model_names)
            for k, v in schema.get("properties", {}).items()
        }
        model_name = schema.get("title", f"NestedModel{time.time()}")
        if model_name in created_model_names:
            # needs to be unique
            model_name = model_name + str(time.time())
        nested_model = create_model(model_name, **nested_fields)  # type: ignore
        created_model_names.add(model_name)
        return nested_model, Field(... if required else None, description=description)
    # Handle arrays
    elif schema.get("type") == "array":
        item_type, _ = create_field(
            schema["items"], required=True, created_model_names=created_model_names
        )
        return List[item_type], Field(  # type: ignore
            ... if required else None, description=description
        )
    # Other types
    return field_type, Field(... if required else None, description=description)
 def get_param_fields(endpoint_spec: dict) -> dict:
    """Get an OpenAPI endpoint parameter details"""
    schema = get_schema(endpoint_spec)
    properties = schema.get("properties", {})
    required_fields = schema.get("required", [])
    fields = {}
    created_model_names: Set[str] = set()
    for key, value in properties.items():
        is_required = key in required_fields
        field_info = create_field(value, is_required, created_model_names)
        fields[key] = field_info
    return fields
 def model_to_dict(
    item: Union[BaseModel, List, Dict[str, Any]],
 ) -> Any:
    if is_basemodel_instance(item):
        return cast(BaseModel, item).dict()
    elif isinstance(item, dict):
        return {key: model_to_dict(value) for key, value in item.items()}
    elif isinstance(item, list):
        return [model_to_dict(element) for element in item]
    else:
        return item
--- a/libs/partners/robocorp/langchain_robocorp/_prompts.py
+++ b/libs/partners/robocorp/langchain_robocorp/_prompts.py
@ -1,18 +0,0 @@
 API_CONTROLLER_PROMPT = (
    "You are turning user input into a json query"
    """ for an API request tool.
 The final output to the tool should be a json string with a single key "data".
 The value of "data" should be a dictionary of key-value pairs you want """
    """to POST to the url.
 Always use double quotes for strings in the json string.
 Always respond only with the json object and nothing else.
 Here is documentation on the API:
 Base url: {api_url}
 Endpoint documentation:
 {api_docs}
 User Input: {input}
 """
 )
--- a/libs/partners/robocorp/langchain_robocorp/py.typed
+++ b/libs/partners/robocorp/langchain_robocorp/py.typed
--- a/libs/partners/robocorp/langchain_robocorp/toolkits.py
+++ b/libs/partners/robocorp/langchain_robocorp/toolkits.py
@ -1,249 +0,0 @@
 """Robocorp Action Server toolkit."""
 from __future__ import annotations
 import json
 from typing import Any, Callable, Dict, List, Optional, TypedDict
 from urllib.parse import urljoin
 import requests
 from langchain_core.callbacks import CallbackManagerForToolRun
 from langchain_core.callbacks.base import BaseCallbackHandler
 from langchain_core.callbacks.manager import CallbackManager
 from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import PromptTemplate
 from langchain_core.runnables import Runnable, RunnablePassthrough
 from langchain_core.tools import BaseTool, StructuredTool, Tool
 from langchain_core.tracers.context import _tracing_v2_is_enabled
 from langsmith import Client
 from pydantic import BaseModel, ConfigDict, Field, PrivateAttr, create_model
 from langchain_robocorp._common import (
    get_param_fields,
    model_to_dict,
    reduce_openapi_spec,
 )
 from langchain_robocorp._prompts import (
    API_CONTROLLER_PROMPT,
 )
 LLM_TRACE_HEADER = "X-action-trace"
 class RunDetailsCallbackHandler(BaseCallbackHandler):
    """Callback handler to add run details to the run."""
    def __init__(self, run_details: dict) -> None:
        """Initialize the callback handler.
        Args:
            run_details (dict): Run details.
        """
        self.run_details = run_details
    def on_tool_start(
        self,
        serialized: Dict[str, Any],
        input_str: str,
        **kwargs: Any,
    ) -> None:
        if "parent_run_id" in kwargs:
            self.run_details["run_id"] = kwargs["parent_run_id"]
        else:
            if "run_id" in self.run_details:
                self.run_details.pop("run_id")
 class ToolInputSchema(BaseModel):
    """Tool input schema."""
    question: str = Field(...)
 class ToolArgs(TypedDict):
    """Tool arguments."""
    name: str
    description: str
    callback_manager: CallbackManager
 class ActionServerRequestTool(BaseTool):
    """Requests POST tool with LLM-instructed extraction of truncated responses."""
    name: str = "action_server_request"
    """Tool name."""
    description: str = "Useful to make requests to Action Server API"
    """Tool description."""
    endpoint: str
    """"Action API endpoint"""
    action_request: Callable[[str], str]
    """Action request execution"""
    def _run(
        self, query: str, run_manager: Optional[CallbackManagerForToolRun] = None
    ) -> str:
        try:
            json_text = query[query.find("{") : query.rfind("}") + 1]
            payload = json.loads(json_text)
        except json.JSONDecodeError as e:
            raise e
        return self.action_request(self.endpoint, **payload["data"])
    async def _arun(self, text: str) -> str:
        raise NotImplementedError()
 class ActionServerToolkit(BaseModel):
    """Toolkit exposing Robocorp Action Server provided actions as individual tools."""
    url: str = Field(exclude=True)
    """Action Server URL"""
    api_key: str = Field(exclude=True, default="")
    """Action Server request API key"""
    additional_headers: dict = Field(exclude=True, default_factory=dict)
    """Additional headers to be passed to the Action Server"""
    report_trace: bool = Field(exclude=True, default=False)
    """Enable reporting Langsmith trace to Action Server runs"""
    _run_details: dict = PrivateAttr({})
    model_config = ConfigDict(
        arbitrary_types_allowed=True,
    )
    def get_tools(
        self,
        llm: Optional[BaseChatModel] = None,
        callback_manager: Optional[CallbackManager] = None,
    ) -> List[BaseTool]:
        """
        Get Action Server actions as a toolkit
        :param llm: Optionally pass a model to return single input tools
        :param callback_manager: Callback manager to be passed to tools
        """
        # Fetch and format the API spec
        try:
            spec_url = urljoin(self.url, "openapi.json")
            response = requests.get(spec_url)
            json_spec = response.json()
            api_spec = reduce_openapi_spec(self.url, json_spec)
        except Exception:
            raise ValueError(
                f"Failed to fetch OpenAPI schema from Action Server - {self.url}"
            )
        # Prepare request tools
        self._run_details: dict = {}
        # Prepare callback manager
        if callback_manager is None:
            callback_manager = CallbackManager([])
        callbacks: List[BaseCallbackHandler] = []
        if _tracing_v2_is_enabled():
            callbacks.append(RunDetailsCallbackHandler(self._run_details))
        for callback in callbacks:
            callback_manager.add_handler(callback)
        toolkit: List[BaseTool] = []
        # Prepare tools
        for endpoint, docs in api_spec.endpoints:
            if not endpoint.startswith("/api/actions"):
                continue
            tool_args: ToolArgs = {
                "name": docs["operationId"],
                "description": docs["description"],
                "callback_manager": callback_manager,
            }
            if llm:
                tool = self._get_unstructured_tool(endpoint, docs, tool_args, llm)
            else:
                tool = self._get_structured_tool(endpoint, docs, tool_args)
            toolkit.append(tool)
        return toolkit
    def _get_unstructured_tool(
        self,
        endpoint: str,
        docs: dict,
        tool_args: ToolArgs,
        llm: BaseChatModel,
    ) -> BaseTool:
        request_tool = ActionServerRequestTool(
            action_request=self._action_request, endpoint=endpoint
        )
        prompt_variables = {
            "api_url": self.url,
        }
        tool_name = tool_args["name"]
        tool_docs = json.dumps(docs, indent=4)
        prompt_variables["api_docs"] = f"{tool_name}: \n{tool_docs}"
        prompt = PromptTemplate(
            template=API_CONTROLLER_PROMPT,
            input_variables=["input"],
            partial_variables=prompt_variables,
        )
        chain: Runnable = (
            {"input": RunnablePassthrough()}
            | prompt
            | llm
            | StrOutputParser()
            | request_tool
        )
        return Tool(func=chain.invoke, args_schema=ToolInputSchema, **tool_args)
    def _get_structured_tool(
        self, endpoint: str, docs: dict, tools_args: ToolArgs
    ) -> BaseTool:
        fields = get_param_fields(docs)
        _DynamicToolInputSchema = create_model("DynamicToolInputSchema", **fields)
        def dynamic_func(**data: dict[str, Any]) -> str:
            return self._action_request(endpoint, **model_to_dict(data))
        dynamic_func.__name__ = tools_args["name"]
        dynamic_func.__doc__ = tools_args["description"]
        return StructuredTool(
            func=dynamic_func,
            args_schema=_DynamicToolInputSchema,
            **tools_args,
        )
    def _action_request(self, endpoint: str, **data: dict[str, Any]) -> str:
        headers = {
            "Authorization": f"Bearer {self.api_key}",
            "Content-Type": "application/json",
            **self.additional_headers,
        }
        try:
            if self.report_trace and "run_id" in self._run_details:
                client = Client()
                run = client.read_run(self._run_details["run_id"])
                if run.url:
                    headers[LLM_TRACE_HEADER] = run.url
        except Exception:
            pass
        url = urljoin(self.url, endpoint)
        response = requests.post(url, headers=headers, data=json.dumps(data))
        return response.text
--- a/libs/partners/robocorp/poetry.lock
+++ b/libs/partners/robocorp/poetry.lock
@ -1,872 +0,0 @@
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 zstd = ["zstandard (>=0.18.0)"]
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 [package.extras]
 watchmedo = ["PyYAML (>=3.10)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
 content-hash = "a684f0e24648e9106bbb7d79554a71fca47235b61961159872a5d72267406aab"
--- a/libs/partners/robocorp/pyproject.toml
+++ b/libs/partners/robocorp/pyproject.toml
@ -1,86 +0,0 @@
 [build-system]
 requires = ["poetry-core>=1.0.0"]
 build-backend = "poetry.core.masonry.api"
 [tool.poetry]
 name = "langchain-robocorp"
 version = "0.0.10"
 description = "An integration package connecting Robocorp Action Server and LangChain"
 authors = []
 readme = "README.md"
 repository = "https://github.com/langchain-ai/langchain"
 license = "MIT"
 [tool.mypy]
 disallow_untyped_defs = "True"
 [tool.poetry.urls]
 "Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/robocorp"
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
 langchain-core = "^0.3.0.dev"
 requests = "^2.31.0"
 types-requests = "^2.31.0.6"
 pydantic = ">=2,<3"
 [tool.ruff.lint]
 select = ["E", "F", "I", "T201"]
 [tool.coverage.run]
 omit = ["tests/*"]
 [tool.pytest.ini_options]
 addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5"
 markers = [
    "requires: mark tests as requiring a specific library",
    "asyncio: mark tests as requiring asyncio",
    "compile: mark placeholder test used to compile integration tests without running them",
 ]
 asyncio_mode = "auto"
 [tool.poetry.group.test]
 optional = true
 [tool.poetry.group.codespell]
 optional = true
 [tool.poetry.group.test_integration]
 optional = true
 [tool.poetry.group.lint]
 optional = true
 [tool.poetry.group.dev]
 optional = true
 [tool.poetry.group.test.dependencies]
 pytest = "^7.3.0"
 freezegun = "^1.2.2"
 pytest-mock = "^3.10.0"
 syrupy = "^4.0.2"
 pytest-watcher = "^0.3.4"
 pytest-asyncio = "^0.21.1"
 [tool.poetry.group.codespell.dependencies]
 codespell = "^2.2.0"
 [tool.poetry.group.test_integration.dependencies]
 [tool.poetry.group.lint.dependencies]
 ruff = "^0.5"
 [tool.poetry.group.typing.dependencies]
 mypy = "^1.10"
 [tool.poetry.group.test.dependencies.langchain-core]
 path = "../../core"
 develop = true
 [tool.poetry.group.dev.dependencies.langchain-core]
 path = "../../core"
 develop = true
 [tool.poetry.group.typing.dependencies.langchain-core]
 path = "../../core"
 develop = true
--- a/libs/partners/robocorp/scripts/check_imports.py
+++ b/libs/partners/robocorp/scripts/check_imports.py
@ -1,17 +0,0 @@
 import sys
 import traceback
 from importlib.machinery import SourceFileLoader
 if __name__ == "__main__":
    files = sys.argv[1:]
    has_failure = False
    for file in files:
        try:
            SourceFileLoader("x", file).load_module()
        except Exception:
            has_failure = True
            print(file)  # noqa: T201
            traceback.print_exc()
            print()  # noqa: T201
    sys.exit(1 if has_failure else 0)
--- a/libs/partners/robocorp/scripts/lint_imports.sh
+++ b/libs/partners/robocorp/scripts/lint_imports.sh
@ -1,17 +0,0 @@
 #!/bin/bash
 set -eu
 # Initialize a variable to keep track of errors
 errors=0
 # make sure not importing from langchain or langchain_experimental
 git --no-pager grep '^from langchain\.' . && errors=$((errors+1))
 git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1))
 # Decide on an exit status based on the errors
 if [ "$errors" -gt 0 ]; then
    exit 1
 else
    exit 0
 fi
--- a/libs/partners/robocorp/tests/init.py
+++ b/libs/partners/robocorp/tests/init.py
--- a/libs/partners/robocorp/tests/integration_tests/init.py
+++ b/libs/partners/robocorp/tests/integration_tests/init.py
--- a/libs/partners/robocorp/tests/integration_tests/test_compile.py
+++ b/libs/partners/robocorp/tests/integration_tests/test_compile.py
@ -1,7 +0,0 @@
 import pytest
@pytest.mark.compile
 def test_placeholder() -> None:
    """Used for compiling integration tests without running any real tests."""
    pass
--- a/libs/partners/robocorp/tests/unit_tests/init.py
+++ b/libs/partners/robocorp/tests/unit_tests/init.py
--- a/libs/partners/robocorp/tests/unit_tests/_fixtures.py
+++ b/libs/partners/robocorp/tests/unit_tests/_fixtures.py
@ -1,73 +0,0 @@
 from typing import Any, List, Optional
 from langchain_core.callbacks.manager import CallbackManagerForLLMRun
 from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_core.messages import AIMessage, BaseMessage
 from langchain_core.outputs import ChatGeneration, ChatResult
 class FakeChatLLMT(BaseChatModel):
    @property
    def _llm_type(self) -> str:
        return "fake-openai-chat-model"
    def _generate(
        self,
        messages: List[BaseMessage],
        stop: Optional[List[str]] = None,
        run_manager: Optional[CallbackManagerForLLMRun] = None,
        **kwargs: Any,
    ) -> ChatResult:
        return ChatResult(
            generations=[
                ChatGeneration(
                    message=AIMessage(
                        content="",
                        additional_kwargs={
                            "function_call": {
                                "name": "accept",
                                "arguments": '{\n  "draft": "turtles"\n}',
                            }
                        },
                    )
                )
            ]
        )
 openapi_endpoint_doc_mock = {
    "summary": "Test Action",
    "operationId": "test_action",
    "description": "Greets an employee",
    "responses": {
        "description": "Successful Response",
        "content": {
            "application/json": {
                "schema": {
                    "type": "string",
                    "title": "Response Test Action",
                    "description": "The greeting",
                }
            }
        },
    },
    "requestBody": {
        "content": {
            "application/json": {
                "schema": {
                    "properties": {
                        "name": {
                            "type": "string",
                            "title": "Name",
                            "description": "Name of the employee",
                        }
                    },
                    "type": "object",
                    "required": ["name"],
                    "title": "TestActionInput",
                }
            }
        },
        "required": True,
    },
 }
--- a/libs/partners/robocorp/tests/unit_tests/_openapi.fixture.json
+++ b/libs/partners/robocorp/tests/unit_tests/_openapi.fixture.json
@ -1,411 +0,0 @@
 {
  "openapi": "3.1.0",
  "info": {
    "title": "Robocorp Actions Server",
    "description": "Robocorp Actions Server",
    "version": "0.1.0"
  },
  "paths": {
    "/api/actions/test/test-action/run": {
      "post": {
        "summary": "Test Action",
        "description": "Greets an employee",
        "operationId": "test_action",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": { "$ref": "#/components/schemas/TestActionInput" }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "string",
                  "title": "Response Test Action",
                  "description": "The greeting"
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
              }
            }
          }
        }
      }
    },
    "/api/runs": {
      "get": {
        "summary": "List Runs",
        "operationId": "list_runs_api_runs_get",
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "items": { "$ref": "#/components/schemas/Run" },
                  "type": "array",
                  "title": "Response List Runs Api Runs Get"
                }
              }
            }
          }
        }
      }
    },
    "/api/runs/{run_id}": {
      "get": {
        "summary": "Show Run",
        "operationId": "show_run_api_runs__run_id__get",
        "parameters": [
          {
            "name": "run_id",
            "in": "path",
            "required": true,
            "schema": { "type": "string", "title": "ID for run" }
          }
        ],
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": { "$ref": "#/components/schemas/Run" }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
              }
            }
          }
        }
      }
    },
    "/api/runs/{run_id}/artifacts": {
      "get": {
        "summary": "Get Run Artifacts",
        "operationId": "get_run_artifacts_api_runs__run_id__artifacts_get",
        "parameters": [
          {
            "name": "run_id",
            "in": "path",
            "required": true,
            "schema": { "type": "string", "title": "ID for run" }
          }
        ],
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "array",
                  "items": { "$ref": "#/components/schemas/ArtifactInfo" },
                  "description": "Provides a list with the artifacts available\nfor a given run (i.e.: [{'name': '__action_server_output.txt', 'size_in_bytes': 22}])\n",
                  "title": "Response Get Run Artifacts Api Runs  Run Id  Artifacts Get"
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
              }
            }
          }
        }
      }
    },
    "/api/runs/{run_id}/log.html": {
      "get": {
        "summary": "Get Run Log Html",
        "operationId": "get_run_log_html_api_runs__run_id__log_html_get",
        "parameters": [
          {
            "name": "run_id",
            "in": "path",
            "required": true,
            "schema": { "type": "string", "title": "ID for run" }
          }
        ],
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": { "application/json": { "schema": {} } }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
              }
            }
          }
        }
      }
    },
    "/api/runs/{run_id}/artifacts/text-content": {
      "get": {
        "summary": "Get Run Artifact Text",
        "operationId": "get_run_artifact_text_api_runs__run_id__artifacts_text_content_get",
        "parameters": [
          {
            "name": "run_id",
            "in": "path",
            "required": true,
            "schema": { "type": "string", "title": "ID for run" }
          },
          {
            "name": "artifact_names",
            "in": "query",
            "required": false,
            "schema": {
              "anyOf": [
                { "type": "array", "items": { "type": "string" } },
                { "type": "null" }
              ],
              "title": "Artifact names for which the content should be gotten."
            }
          },
          {
            "name": "artifact_name_regexp",
            "in": "query",
            "required": false,
            "schema": {
              "anyOf": [{ "type": "string" }, { "type": "null" }],
              "title": "A regexp to match artifact names."
            }
          }
        ],
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "object",
                  "additionalProperties": { "type": "string" },
                  "title": "Response Get Run Artifact Text Api Runs  Run Id  Artifacts Text Content Get"
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
              }
            }
          }
        }
      }
    },
    "/api/runs/{run_id}/artifacts/binary-content": {
      "get": {
        "summary": "Get Run Artifact Binary",
        "operationId": "get_run_artifact_binary_api_runs__run_id__artifacts_binary_content_get",
        "parameters": [
          {
            "name": "run_id",
            "in": "path",
            "required": true,
            "schema": { "type": "string", "title": "ID for run" }
          },
          {
            "name": "artifact_name",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string",
              "title": "Artifact name for which the content should be gotten."
            }
          }
        ],
        "responses": {
          "200": { "description": "Successful Response" },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
              }
            }
          }
        }
      }
    },
    "/api/actionPackages": {
      "get": {
        "summary": "List Action Packages",
        "operationId": "list_action_packages_api_actionPackages_get",
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "items": { "$ref": "#/components/schemas/ActionPackageApi" },
                  "type": "array",
                  "title": "Response List Action Packages Api Actionpackages Get"
                }
              }
            }
          }
        }
      }
    }
  },
  "components": {
    "schemas": {
      "Action": {
        "properties": {
          "id": { "type": "string", "title": "Id" },
          "action_package_id": {
            "type": "string",
            "title": "Action Package Id"
          },
          "name": { "type": "string", "title": "Name" },
          "docs": { "type": "string", "title": "Docs" },
          "file": { "type": "string", "title": "File" },
          "lineno": { "type": "integer", "title": "Lineno" },
          "input_schema": { "type": "string", "title": "Input Schema" },
          "output_schema": { "type": "string", "title": "Output Schema" },
          "enabled": { "type": "boolean", "title": "Enabled", "default": true },
          "is_consequential": {
            "anyOf": [{ "type": "boolean" }, { "type": "null" }],
            "title": "Is Consequential"
          }
        },
        "type": "object",
        "required": [
          "id",
          "action_package_id",
          "name",
          "docs",
          "file",
          "lineno",
          "input_schema",
          "output_schema"
        ],
        "title": "Action"
      },
      "ActionPackageApi": {
        "properties": {
          "id": { "type": "string", "title": "Id" },
          "name": { "type": "string", "title": "Name" },
          "actions": {
            "items": { "$ref": "#/components/schemas/Action" },
            "type": "array",
            "title": "Actions"
          }
        },
        "type": "object",
        "required": ["id", "name", "actions"],
        "title": "ActionPackageApi"
      },
      "ArtifactInfo": {
        "properties": {
          "name": { "type": "string", "title": "Name" },
          "size_in_bytes": { "type": "integer", "title": "Size In Bytes" }
        },
        "type": "object",
        "required": ["name", "size_in_bytes"],
        "title": "ArtifactInfo"
      },
      "HTTPValidationError": {
        "properties": {
          "errors": {
            "items": { "$ref": "#/components/schemas/ValidationError" },
            "type": "array",
            "title": "Errors"
          }
        },
        "type": "object",
        "title": "HTTPValidationError"
      },
      "Run": {
        "properties": {
          "id": { "type": "string", "title": "Id" },
          "status": { "type": "integer", "title": "Status" },
          "action_id": { "type": "string", "title": "Action Id" },
          "start_time": { "type": "string", "title": "Start Time" },
          "run_time": {
            "anyOf": [{ "type": "number" }, { "type": "null" }],
            "title": "Run Time"
          },
          "inputs": { "type": "string", "title": "Inputs" },
          "result": {
            "anyOf": [{ "type": "string" }, { "type": "null" }],
            "title": "Result"
          },
          "error_message": {
            "anyOf": [{ "type": "string" }, { "type": "null" }],
            "title": "Error Message"
          },
          "relative_artifacts_dir": {
            "type": "string",
            "title": "Relative Artifacts Dir"
          },
          "numbered_id": { "type": "integer", "title": "Numbered Id" }
        },
        "type": "object",
        "required": [
          "id",
          "status",
          "action_id",
          "start_time",
          "run_time",
          "inputs",
          "result",
          "error_message",
          "relative_artifacts_dir",
          "numbered_id"
        ],
        "title": "Run"
      },
      "TestActionInput": {
        "properties": {
          "name": {
            "type": "string",
            "title": "Name",
            "description": "Name of the employee"
          }
        },
        "type": "object",
        "required": ["name"],
        "title": "TestActionInput"
      },
      "ValidationError": {
        "properties": {
          "loc": {
            "items": { "anyOf": [{ "type": "string" }, { "type": "integer" }] },
            "type": "array",
            "title": "Location"
          },
          "msg": { "type": "string", "title": "Message" },
          "type": { "type": "string", "title": "Error Type" }
        },
        "type": "object",
        "required": ["loc", "msg", "type"],
        "title": "ValidationError"
      }
    }
  }
 }
--- a/libs/partners/robocorp/tests/unit_tests/_openapi2.fixture.json
+++ b/libs/partners/robocorp/tests/unit_tests/_openapi2.fixture.json
@ -1,387 +0,0 @@
 {
  "openapi": "3.1.0",
  "info": {
    "title": "Robocorp Action Server",
    "version": "0.1.0"
  },
  "servers": [
    {
      "url": "https://hosted-actions.onrender.com"
    }
  ],
  "paths": {
    "/api/actions/google-sheet-gmail/get-google-spreadsheet-schema/run": {
      "post": {
        "summary": "Get Google Spreadsheet Schema",
        "description": "Action to get necessary information to be able to work with a Google Sheet Spreadsheets correctly.\nUse this action minimum once before anything else, to learn about the structure\nof the Spreadsheet. Method will return the first few rows of each Sheet as an example.",
        "operationId": "get_google_spreadsheet_schema",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "properties": {},
                "type": "object"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "string",
                  "title": "Response Get Google Spreadsheet Schema",
                  "description": "Names of the sheets, and a couple of first rows from each sheet to explain the context."
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/HTTPValidationError"
                }
              }
            }
          }
        },
        "security": [
          {
            "HTTPBearer": []
          }
        ]
      }
    },
    "/api/actions/google-sheet-gmail/create-new-google-sheet/run": {
      "post": {
        "summary": "Create New Google Sheet",
        "description": "Creates a new empty Sheet in user's Google Spreadsheet.",
        "operationId": "create_new_google_sheet",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "properties": {
                  "name": {
                    "type": "string",
                    "title": "Name",
                    "description": "Name of the Sheet. You must refer to this Sheet name later when adding or reading date from the Sheet."
                  }
                },
                "type": "object",
                "required": [
                  "name"
                ]
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "string",
                  "title": "Response Create New Google Sheet",
                  "description": "True if operation was success, and False if it failed."
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/HTTPValidationError"
                }
              }
            }
          }
        },
        "security": [
          {
            "HTTPBearer": []
          }
        ]
      }
    },
    "/api/actions/google-sheet-gmail/add-sheet-rows/run": {
      "post": {
        "summary": "Add Sheet Rows",
        "description": "Action to add multiple rows to the Google sheet. Get the sheets with get_google_spreadsheet_schema if you don't know\nthe names or data structure.  Make sure the values are in correct columns (needs to be ordered the same as in the sample).\nStrictly adhere to the schema.",
        "operationId": "add_sheet_rows",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "properties": {
                  "sheet": {
                    "type": "string",
                    "title": "Sheet",
                    "description": "Name of the sheet where the data is added to"
                  },
                  "rows_to_add": {
                    "properties": {
                      "rows": {
                        "items": {
                          "properties": {
                            "columns": {
                              "items": {
                                "type": "string"
                              },
                              "type": "array",
                              "title": "Columns",
                              "description": "The columns that make up the row"
                            }
                          },
                          "type": "object",
                          "required": [
                            "columns"
                          ],
                          "title": "Row"
                        },
                        "type": "array",
                        "title": "Rows",
                        "description": "The rows that need to be added"
                      }
                    },
                    "type": "object",
                    "required": [
                      "rows"
                    ],
                    "title": "Rows To Add",
                    "description": "the rows to be added to the sheet"
                  }
                },
                "type": "object",
                "required": [
                  "sheet",
                  "rows_to_add"
                ]
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "string",
                  "title": "Response Add Sheet Rows",
                  "description": "The result of the operation."
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/HTTPValidationError"
                }
              }
            }
          }
        },
        "security": [
          {
            "HTTPBearer": []
          }
        ]
      }
    },
    "/api/actions/google-sheet-gmail/get-sheet-contents/run": {
      "post": {
        "summary": "Get Sheet Contents",
        "description": "Get all content from the chosen Google Spreadsheet Sheet.",
        "operationId": "get_sheet_contents",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "properties": {
                  "sheet": {
                    "type": "string",
                    "title": "Sheet",
                    "description": "Name of the sheet from which to get the data"
                  }
                },
                "type": "object",
                "required": [
                  "sheet"
                ]
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "string",
                  "title": "Response Get Sheet Contents",
                  "description": "Sheet data as string, rows separated by newlines"
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/HTTPValidationError"
                }
              }
            }
          }
        },
        "security": [
          {
            "HTTPBearer": []
          }
        ]
      }
    },
    "/api/actions/google-sheet-gmail/send-email-via-gmail/run": {
      "post": {
        "summary": "Send Email Via Gmail",
        "description": "Sends an email using Gmail SMTP with an App Password for authentication.",
        "operationId": "send_email_via_gmail",
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "properties": {
                  "subject": {
                    "type": "string",
                    "title": "Subject",
                    "description": "Email subject"
                  },
                  "body": {
                    "type": "string",
                    "title": "Body",
                    "description": "Email body content"
                  },
                  "recipient": {
                    "type": "string",
                    "title": "Recipient",
                    "description": "Recipient email address"
                  }
                },
                "type": "object",
                "required": [
                  "subject",
                  "body",
                  "recipient"
                ]
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "type": "string",
                  "title": "Response Send Email Via Gmail",
                  "description": "Information if the send was successful or not"
                }
              }
            }
          },
          "422": {
            "description": "Validation Error",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/HTTPValidationError"
                }
              }
            }
          }
        },
        "security": [
          {
            "HTTPBearer": []
          }
        ],
        "x-openai-isConsequential": true
      }
    }
  },
  "components": {
    "securitySchemes": {
      "HTTPBearer": {
        "type": "http",
        "scheme": "bearer"
      }
    },
    "schemas": {
      "HTTPValidationError": {
        "properties": {
          "errors": {
            "items": {
              "$ref": "#/components/schemas/ValidationError"
            },
            "type": "array",
            "title": "Errors"
          }
        },
        "type": "object",
        "title": "HTTPValidationError"
      },
      "ValidationError": {
        "properties": {
          "loc": {
            "items": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "integer"
                }
              ]
            },
            "type": "array",
            "title": "Location"
          },
          "msg": {
            "type": "string",
            "title": "Message"
          },
          "type": {
            "type": "string",
            "title": "Error Type"
          }
        },
        "type": "object",
        "required": [
          "loc",
          "msg",
          "type"
        ],
        "title": "ValidationError"
      }
    }
  }
 }
--- a/libs/partners/robocorp/tests/unit_tests/_openapi3.fixture.json
+++ b/libs/partners/robocorp/tests/unit_tests/_openapi3.fixture.json
--- a/libs/partners/robocorp/tests/unit_tests/test_common.py
+++ b/libs/partners/robocorp/tests/unit_tests/test_common.py
@ -1,25 +0,0 @@
 """Test common functions."""
 import json
 import unittest
 from pathlib import Path
 from langchain_robocorp._common import reduce_openapi_spec
 from ._fixtures import openapi_endpoint_doc_mock
 class TestReduceOpenAPISpec(unittest.TestCase):
    maxDiff = None
    def test_reduce_openapi_spec(self) -> None:
        with Path(__file__).with_name("_openapi.fixture.json").open("r") as file:
            original = json.load(file)
        output = reduce_openapi_spec("https://foo.bar", original)
        self.assertEqual(output.servers, [{"url": "https://foo.bar"}])
        self.assertEqual(output.description, "Robocorp Actions Server")
        self.assertEqual(len(output.endpoints), 8)
        self.assertEqual(output.endpoints[0][1], openapi_endpoint_doc_mock)
--- a/libs/partners/robocorp/tests/unit_tests/test_imports.py
+++ b/libs/partners/robocorp/tests/unit_tests/test_imports.py
@ -1,9 +0,0 @@
 from langchain_robocorp import __all__
 EXPECTED_ALL = [
    "ActionServerToolkit",
 ]
 def test_all_imports() -> None:
    assert sorted(EXPECTED_ALL) == sorted(__all__)
--- a/libs/partners/robocorp/tests/unit_tests/test_toolkits.py
+++ b/libs/partners/robocorp/tests/unit_tests/test_toolkits.py
@ -1,187 +0,0 @@
 """Test toolkit integration."""
 import json
 from pathlib import Path
 from unittest.mock import MagicMock, patch
 from langchain_core.utils.function_calling import (
    convert_to_openai_function,
    convert_to_openai_tool,
 )
 from langchain_robocorp.toolkits import ActionServerToolkit
 from ._fixtures import FakeChatLLMT
 def test_initialization() -> None:
    """Test toolkit initialization."""
    ActionServerToolkit(url="http://localhost", llm=FakeChatLLMT())  # type: ignore[call-arg]
 def test_get_tools_success() -> None:
    # Setup
    toolkit_instance = ActionServerToolkit(
        url="http://example.com", api_key="dummy_key"
    )
    fixture_path = Path(__file__).with_name("_openapi2.fixture.json")
    with patch(
        "langchain_robocorp.toolkits.requests.get"
    ) as mocked_get, fixture_path.open("r") as f:
        data = json.load(f)  # Using json.load directly on the file object
        mocked_response = MagicMock()
        mocked_response.json.return_value = data
        mocked_response.status_code = 200
        mocked_response.headers = {"Content-Type": "application/json"}
        mocked_get.return_value = mocked_response
        # Execute
        tools = toolkit_instance.get_tools()
        # Verify
        assert len(tools) == 5
        tool = tools[2]
        assert tool.name == "add_sheet_rows"
        assert tool.description == (
            "Action to add multiple rows to the Google sheet. "
            "Get the sheets with get_google_spreadsheet_schema if you don't know"
            "\nthe names or data structure.  Make sure the values are in correct"
            """ columns (needs to be ordered the same as in the sample).
 Strictly adhere to the schema."""
        )
        openai_func_spec = convert_to_openai_function(tool)
        assert isinstance(
            openai_func_spec, dict
        ), "openai_func_spec should be a dictionary."
        assert set(openai_func_spec.keys()) == {
            "description",
            "name",
            "parameters",
        }, "Top-level keys mismatch."
        assert openai_func_spec["description"] == tool.description
        assert openai_func_spec["name"] == tool.name
        assert isinstance(
            openai_func_spec["parameters"], dict
        ), "Parameters should be a dictionary."
        params = openai_func_spec["parameters"]
        assert set(params.keys()) == {
            "type",
            "properties",
            "required",
        }, "Parameters keys mismatch."
        assert params["type"] == "object", "`type` in parameters should be 'object'."
        assert isinstance(
            params["properties"], dict
        ), "`properties` should be a dictionary."
        assert isinstance(params["required"], list), "`required` should be a list."
        assert set(params["required"]) == {
            "sheet",
            "rows_to_add",
        }, "Required fields mismatch."
        assert set(params["properties"].keys()) == {"sheet", "rows_to_add"}
        desc = "The columns that make up the row"
        expected = {
            "description": "the rows to be added to the sheet",
            "allOf": [
                {
                    "title": "Rows To Add",
                    "type": "object",
                    "properties": {
                        "rows": {
                            "title": "Rows",
                            "description": "The rows that need to be added",
                            "type": "array",
                            "items": {
                                "title": "Row",
                                "type": "object",
                                "properties": {
                                    "columns": {
                                        "title": "Columns",
                                        "description": desc,
                                        "type": "array",
                                        "items": {"type": "string"},
                                    }
                                },
                                "required": ["columns"],
                            },
                        }
                    },
                    "required": ["rows"],
                }
            ],
        }
        assert params["properties"]["rows_to_add"] == expected
 def test_get_tools_with_complex_inputs() -> None:
    toolkit_instance = ActionServerToolkit(
        url="http://example.com", api_key="dummy_key"
    )
    fixture_path = Path(__file__).with_name("_openapi3.fixture.json")
    with patch(
        "langchain_robocorp.toolkits.requests.get"
    ) as mocked_get, fixture_path.open("r") as f:
        data = json.load(f)  # Using json.load directly on the file object
        mocked_response = MagicMock()
        mocked_response.json.return_value = data
        mocked_response.status_code = 200
        mocked_response.headers = {"Content-Type": "application/json"}
        mocked_get.return_value = mocked_response
        # Execute
        tools = toolkit_instance.get_tools()
        assert len(tools) == 4
        tool = tools[0]
        assert tool.name == "create_event"
        assert tool.description == "Creates a new event in the specified calendar."
        all_tools_as_openai_tools = [convert_to_openai_tool(t) for t in tools]
        openai_tool_spec = all_tools_as_openai_tools[0]["function"]
        assert isinstance(
            openai_tool_spec, dict
        ), "openai_func_spec should be a dictionary."
        assert set(openai_tool_spec.keys()) == {
            "description",
            "name",
            "parameters",
        }, "Top-level keys mismatch."
        assert openai_tool_spec["description"] == tool.description
        assert openai_tool_spec["name"] == tool.name
        assert isinstance(
            openai_tool_spec["parameters"], dict
        ), "Parameters should be a dictionary."
        params = openai_tool_spec["parameters"]
        assert set(params.keys()) == {
            "type",
            "properties",
            "required",
        }, "Parameters keys mismatch."
        assert params["type"] == "object", "`type` in parameters should be 'object'."
        assert isinstance(
            params["properties"], dict
        ), "`properties` should be a dictionary."
        assert isinstance(params["required"], list), "`required` should be a list."
        assert set(params["required"]) == {
            "event",
        }, "Required fields mismatch."
        assert set(params["properties"].keys()) == {"calendar_id", "event"}