structure saas with tools

.venv/lib/python3.10/site-packages/google/adk/tools/base_tool.py

@@ -0,0 +1,144 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from abc import ABC
+import os
+from typing import Any
+from typing import Optional
+from typing import TYPE_CHECKING
+
+from deprecated import deprecated
+from google.genai import types
+
+from .tool_context import ToolContext
+
+if TYPE_CHECKING:
+  from ..models.llm_request import LlmRequest
+
+
+class BaseTool(ABC):
+  """The base class for all tools."""
+
+  name: str
+  """The name of the tool."""
+  description: str
+  """The description of the tool."""
+
+  is_long_running: bool = False
+  """Whether the tool is a long running operation, which typically returns a
+  resource id first and finishes the operation later."""
+
+  def __init__(self, *, name, description, is_long_running: bool = False):
+    self.name = name
+    self.description = description
+    self.is_long_running = is_long_running
+
+  def _get_declaration(self) -> Optional[types.FunctionDeclaration]:
+    """Gets the OpenAPI specification of this tool in the form of a FunctionDeclaration.
+
+    NOTE
+    - Required if subclass uses the default implementation of
+      `process_llm_request` to add function declaration to LLM request.
+    - Otherwise, can be skipped, e.g. for a built-in GoogleSearch tool for
+      Gemini.
+
+    Returns:
+      The FunctionDeclaration of this tool, or None if it doesn't need to be
+      added to LlmRequest.config.
+    """
+    return None
+
+  async def run_async(
+      self, *, args: dict[str, Any], tool_context: ToolContext
+  ) -> Any:
+    """Runs the tool with the given arguments and context.
+
+    NOTE
+    - Required if this tool needs to run at the client side.
+    - Otherwise, can be skipped, e.g. for a built-in GoogleSearch tool for
+      Gemini.
+
+    Args:
+      args: The LLM-filled arguments.
+      tool_context: The context of the tool.
+
+    Returns:
+      The result of running the tool.
+    """
+    raise NotImplementedError(f'{type(self)} is not implemented')
+
+  async def process_llm_request(
+      self, *, tool_context: ToolContext, llm_request: LlmRequest
+  ) -> None:
+    """Processes the outgoing LLM request for this tool.
+
+    Use cases:
+    - Most common use case is adding this tool to the LLM request.
+    - Some tools may just preprocess the LLM request before it's sent out.
+
+    Args:
+      tool_context: The context of the tool.
+      llm_request: The outgoing LLM request, mutable this method.
+    """
+    if (function_declaration := self._get_declaration()) is None:
+      return
+
+    llm_request.tools_dict[self.name] = self
+    if tool_with_function_declarations := _find_tool_with_function_declarations(
+        llm_request
+    ):
+      if tool_with_function_declarations.function_declarations is None:
+        tool_with_function_declarations.function_declarations = []
+      tool_with_function_declarations.function_declarations.append(
+          function_declaration
+      )
+    else:
+      llm_request.config = (
+          types.GenerateContentConfig()
+          if not llm_request.config
+          else llm_request.config
+      )
+      llm_request.config.tools = (
+          [] if not llm_request.config.tools else llm_request.config.tools
+      )
+      llm_request.config.tools.append(
+          types.Tool(function_declarations=[function_declaration])
+      )
+
+  @property
+  def _api_variant(self) -> str:
+    use_vertexai = os.environ.get('GOOGLE_GENAI_USE_VERTEXAI', '0').lower() in [
+        'true',
+        '1',
+    ]
+    return 'VERTEX_AI' if use_vertexai else 'GOOGLE_AI'
+
+
+def _find_tool_with_function_declarations(
+    llm_request: LlmRequest,
+) -> Optional[types.Tool]:
+  # TODO: add individual tool with declaration and merge in google_llm.py
+  if not llm_request.config or not llm_request.config.tools:
+    return None
+
+  return next(
+      (
+          tool
+          for tool in llm_request.config.tools
+          if isinstance(tool, types.Tool) and tool.function_declarations
+      ),
+      None,
+  )