Agent Development Kit(ADK)

An easy-to-use and powerful framework to build AI agents.

src/google/adk/tools/load_artifacts_tool.py

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+# 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
+
+import json
+from typing import Any
+from typing import TYPE_CHECKING
+
+from google.genai import types
+from typing_extensions import override
+
+from .base_tool import BaseTool
+
+if TYPE_CHECKING:
+  from ..models.llm_request import LlmRequest
+  from .tool_context import ToolContext
+
+
+class LoadArtifactsTool(BaseTool):
+  """A tool that loads the artifacts and adds them to the session."""
+
+  def __init__(self):
+    super().__init__(
+        name='load_artifacts',
+        description='Loads the artifacts and adds them to the session.',
+    )
+
+  def _get_declaration(self) -> types.FunctionDeclaration | None:
+    return types.FunctionDeclaration(
+        name=self.name,
+        description=self.description,
+        parameters=types.Schema(
+            type=types.Type.OBJECT,
+            properties={
+                'artifact_names': types.Schema(
+                    type=types.Type.ARRAY,
+                    items=types.Schema(
+                        type=types.Type.STRING,
+                    ),
+                )
+            },
+        ),
+    )
+
+  @override
+  async def run_async(
+      self, *, args: dict[str, Any], tool_context: ToolContext
+  ) -> Any:
+    artifact_names: list[str] = args.get('artifact_names', [])
+    return {'artifact_names': artifact_names}
+
+  @override
+  async def process_llm_request(
+      self, *, tool_context: ToolContext, llm_request: LlmRequest
+  ) -> None:
+    await super().process_llm_request(
+        tool_context=tool_context,
+        llm_request=llm_request,
+    )
+    self._append_artifacts_to_llm_request(
+        tool_context=tool_context, llm_request=llm_request
+    )
+
+  def _append_artifacts_to_llm_request(
+      self, *, tool_context: ToolContext, llm_request: LlmRequest
+  ):
+    artifact_names = tool_context.list_artifacts()
+    if not artifact_names:
+      return
+
+    # Tell the model about the available artifacts.
+    llm_request.append_instructions([f"""You have a list of artifacts:
+  {json.dumps(artifact_names)}
+
+  When the user asks questions about any of the artifacts, you should call the
+  `load_artifacts` function to load the artifact. Do not generate any text other
+  than the function call.
+  """])
+
+    # Attache the content of the artifacts if the model requests them.
+    # This only adds the content to the model request, instead of the session.
+    if llm_request.contents and llm_request.contents[-1].parts:
+      function_response = llm_request.contents[-1].parts[0].function_response
+      if function_response and function_response.name == 'load_artifacts':
+        artifact_names = function_response.response['artifact_names']
+        for artifact_name in artifact_names:
+          artifact = tool_context.load_artifact(artifact_name)
+          llm_request.contents.append(
+              types.Content(
+                  role='user',
+                  parts=[
+                      types.Part.from_text(
+                          text=f'Artifact {artifact_name} is:'
+                      ),
+                      artifact,
+                  ],
+              )
+          )
+
+
+load_artifacts_tool = LoadArtifactsTool()