chore: import upstream snapshot with attribution

contributing/samples/multimodal/static_non_text_content/agent.py

@@ -0,0 +1,226 @@
+# Copyright 2026 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.
+
+"""Static non-text content sample agent demonstrating static instructions with non-text parts."""
+
+import base64
+
+from dotenv import load_dotenv
+from google.adk.agents.llm_agent import Agent
+from google.genai import types
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Sample image data (a simple 1x1 yellow pixel PNG)
+SAMPLE_IMAGE_DATA = base64.b64decode(
+    "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg=="
+)
+
+# Sample document content (simplified contributing guide)
+SAMPLE_DOCUMENT = """# Contributing Guide
+
+## Best Practices
+
+1. **Code Quality**: Always write clean, well-documented code
+2. **Testing**: Include comprehensive tests for new features
+3. **Documentation**: Update documentation when adding new functionality
+4. **Review Process**: Submit pull requests for code review
+5. **Conventions**: Follow established coding conventions and style guides
+
+## Guidelines
+
+- Use meaningful variable and function names
+- Write descriptive commit messages
+- Keep functions small and focused
+- Handle errors gracefully
+- Consider performance implications
+- Maintain backward compatibility when possible
+
+This guide helps ensure consistent, high-quality contributions to the project.
+"""
+
+
+def create_static_instruction_with_file_upload():
+  """Create static instruction content with both inline_data and file_data.
+
+  This function creates a static instruction that demonstrates both inline_data
+  (for images) and file_data (for documents). Always includes Files API upload,
+  and adds additional GCS file reference when using Vertex AI.
+  """
+  import os
+  import tempfile
+
+  from google.adk.utils.variant_utils import get_google_llm_variant
+  from google.adk.utils.variant_utils import GoogleLLMVariant
+
+  from google import genai
+
+  # Determine API variant
+  api_variant = get_google_llm_variant()
+  print(f"Using API variant: {api_variant}")
+
+  # Prepare file data parts based on API variant
+  file_data_parts = []
+
+  if api_variant == GoogleLLMVariant.VERTEX_AI:
+    print("Using Vertex AI - adding GCS URI and HTTPS URL references")
+
+    # Add GCS file reference
+    file_data_parts.append(
+        types.Part(
+            file_data=types.FileData(
+                file_uri=(
+                    "gs://cloud-samples-data/generative-ai/pdf/2403.05530.pdf"
+                ),
+                mime_type="application/pdf",
+                display_name="Gemma Research Paper",
+            )
+        )
+    )
+
+    # Add the same document via HTTPS URL to demonstrate both access methods
+    file_data_parts.append(
+        types.Part(
+            file_data=types.FileData(
+                file_uri="https://storage.googleapis.com/cloud-samples-data/generative-ai/pdf/2403.05530.pdf",
+                mime_type="application/pdf",
+                display_name="AI Research Paper (HTTPS)",
+            )
+        )
+    )
+
+    additional_text = (
+        " You also have access to a Gemma research paper from GCS"
+        " and an AI research paper from HTTPS URL."
+    )
+
+  else:
+    print("Using Gemini Developer API - uploading to Files API")
+    client = genai.Client()
+
+    # Check if file already exists
+    display_name = "Contributing Guide"
+    uploaded_file = None
+
+    # List existing files to see if we already uploaded this document
+    existing_files = client.files.list()
+    for file in existing_files:
+      if file.display_name == display_name:
+        uploaded_file = file
+        print(f"Reusing existing file: {file.name} ({file.display_name})")
+        break
+
+    # If file doesn't exist, upload it
+    if uploaded_file is None:
+      # Create a temporary file with the sample document
+      with tempfile.NamedTemporaryFile(
+          mode="w", suffix=".md", delete=False
+      ) as f:
+        f.write(SAMPLE_DOCUMENT)
+        temp_file_path = f.name
+
+      try:
+        # Upload the file to Gemini Files API
+        uploaded_file = client.files.upload(file=temp_file_path)
+        print(
+            "Uploaded new file:"
+            f" {uploaded_file.name} ({uploaded_file.display_name})"
+        )
+      finally:
+        # Clean up temporary file
+        if os.path.exists(temp_file_path):
+          os.unlink(temp_file_path)
+
+    # Add Files API file data part
+    file_data_parts.append(
+        types.Part(
+            file_data=types.FileData(
+                file_uri=uploaded_file.uri,
+                mime_type="text/markdown",
+                display_name="Contributing Guide",
+            )
+        )
+    )
+
+    additional_text = (
+        " You also have access to the contributing guide document."
+    )
+
+  # Create static instruction with mixed content
+  parts = [
+      types.Part.from_text(
+          text=(
+              "You are an AI assistant that analyzes images and documents."
+              " You have access to the following reference materials:"
+          )
+      ),
+      # Add a sample image as inline_data
+      types.Part(
+          inline_data=types.Blob(
+              data=SAMPLE_IMAGE_DATA,
+              mime_type="image/png",
+              display_name="sample_chart.png",
+          )
+      ),
+      types.Part.from_text(
+          text=f"This is a sample chart showing color data.{additional_text}"
+      ),
+  ]
+
+  # Add all file_data parts
+  parts.extend(file_data_parts)
+
+  # Add instruction text
+  if api_variant == GoogleLLMVariant.VERTEX_AI:
+    instruction_text = """
+When users ask questions, you should:
+1. Use the reference chart above to provide context when discussing visual data or charts
+2. Reference the Gemma research paper (from GCS) when discussing AI research, model architectures, or technical details
+3. Reference the AI research paper (from HTTPS) when discussing research topics
+4. Be helpful and informative in your responses
+5. Explain how the provided reference materials relate to their questions"""
+  else:
+    instruction_text = """
+When users ask questions, you should:
+1. Use the reference chart above to provide context when discussing visual data or charts
+2. Reference the contributing guide document when explaining best practices and guidelines
+3. Be helpful and informative in your responses
+4. Explain how the provided reference materials relate to their questions"""
+
+  instruction_text += """
+
+Remember: The reference materials above are available to help you provide better answers."""
+
+  parts.append(types.Part.from_text(text=instruction_text))
+
+  static_instruction_content = types.Content(parts=parts)
+
+  return static_instruction_content
+
+
+# Create the root agent with Files API integration
+root_agent = Agent(
+    name="static_non_text_content_demo_agent",
+    description=(
+        "Demonstrates static instructions with non-text content (inline_data"
+        " and file_data features)"
+    ),
+    static_instruction=create_static_instruction_with_file_upload(),
+    instruction=(
+        "Please analyze the user's question and provide helpful insights."
+        " Reference the materials provided in your static instructions when"
+        " relevant."
+    ),
+)