structure saas with tools

.venv/lib/python3.10/site-packages/google/adk/models/llm_response.py

@@ -0,0 +1,120 @@
+# 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 typing import Any, Optional
+
+from google.genai import types
+from pydantic import BaseModel
+from pydantic import ConfigDict
+
+
+class LlmResponse(BaseModel):
+  """LLM response class that provides the first candidate response from the
+
+  model if available. Otherwise, returns error code and message.
+
+  Attributes:
+    content: The content of the response.
+    grounding_metadata: The grounding metadata of the response.
+    partial: Indicates whether the text content is part of a unfinished text
+      stream. Only used for streaming mode and when the content is plain text.
+    turn_complete: Indicates whether the response from the model is complete.
+      Only used for streaming mode.
+    error_code: Error code if the response is an error. Code varies by model.
+    error_message: Error message if the response is an error.
+    interrupted: Flag indicating that LLM was interrupted when generating the
+      content. Usually it's due to user interruption during a bidi streaming.
+    custom_metadata: The custom metadata of the LlmResponse.
+  """
+
+  model_config = ConfigDict(extra='forbid')
+  """The model config."""
+
+  content: Optional[types.Content] = None
+  """The content of the response."""
+
+  grounding_metadata: Optional[types.GroundingMetadata] = None
+  """The grounding metadata of the response."""
+
+  partial: Optional[bool] = None
+  """Indicates whether the text content is part of a unfinished text stream.
+
+  Only used for streaming mode and when the content is plain text.
+  """
+
+  turn_complete: Optional[bool] = None
+  """Indicates whether the response from the model is complete.
+
+  Only used for streaming mode.
+  """
+
+  error_code: Optional[str] = None
+  """Error code if the response is an error. Code varies by model."""
+
+  error_message: Optional[str] = None
+  """Error message if the response is an error."""
+
+  interrupted: Optional[bool] = None
+  """Flag indicating that LLM was interrupted when generating the content.
+  Usually it's due to user interruption during a bidi streaming.
+  """
+
+  custom_metadata: Optional[dict[str, Any]] = None
+  """The custom metadata of the LlmResponse.
+
+  An optional key-value pair to label an LlmResponse.
+
+  NOTE: the entire dict must be JSON serializable.
+  """
+
+  @staticmethod
+  def create(
+      generate_content_response: types.GenerateContentResponse,
+  ) -> 'LlmResponse':
+    """Creates an LlmResponse from a GenerateContentResponse.
+
+    Args:
+      generate_content_response: The GenerateContentResponse to create the
+        LlmResponse from.
+
+    Returns:
+      The LlmResponse.
+    """
+
+    if generate_content_response.candidates:
+      candidate = generate_content_response.candidates[0]
+      if candidate.content and candidate.content.parts:
+        return LlmResponse(
+            content=candidate.content,
+            grounding_metadata=candidate.grounding_metadata,
+        )
+      else:
+        return LlmResponse(
+            error_code=candidate.finish_reason,
+            error_message=candidate.finish_message,
+        )
+    else:
+      if generate_content_response.prompt_feedback:
+        prompt_feedback = generate_content_response.prompt_feedback
+        return LlmResponse(
+            error_code=prompt_feedback.block_reason,
+            error_message=prompt_feedback.block_reason_message,
+        )
+      else:
+        return LlmResponse(
+            error_code='UNKNOWN_ERROR',
+            error_message='Unknown error.',
+        )