lwangverizon
8e69a58df4
feature/auto-create-new-session Merge https://github.com/google/adk-python/pull/4072 **Please ensure you have read the [contribution guide](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) before creating a pull request.** ### Link to Issue or Description of Change **2. Or, if no issue exists, describe the change:** **Problem:** When building frontend applications with ADK, there's a limitation where frontends cannot always guarantee that `create_session` is called before initiating a conversation. This creates friction in the user experience because: - Users may refresh the page or navigate directly to a conversation URL with a specific session_id - Frontend state management may lose track of whether a session was already created - Mobile apps or single-page applications have complex lifecycle management where ensuring `create_session` is called first adds unnecessary complexity - This forces developers to implement additional logic to check session existence before every conversation Currently, if `get_session` is called with a non-existent session_id, it returns `None`, requiring the frontend to explicitly handle this case and call `create_session` separately. **Solution:** Modified the `get_session` method in `DatabaseSessionService` to automatically create a session if it doesn't exist in the database. This "get or create" pattern is common in many frameworks and provides a more developer-friendly API. The implementation: 1. Attempts to fetch the session from the database 2. If the session doesn't exist (returns `None`), automatically calls `create_session` with the provided parameters 3. Retrieves and returns the newly created session 4. Maintains backward compatibility - existing code continues to work without changes This allows frontends to simply call `get_session` with a session_id and be confident that the session will be available, regardless of whether it was previously created. **Benefits:** - Simplifies frontend integration by removing the need to track session creation state - Reduces API calls (no need to check existence before calling get_session) - Follows the principle of least surprise - getting a session with an ID should work reliably - No breaking changes to existing code that checks for `None` return values ### Testing Plan **Unit Tests:** - [x] I have added or updated unit tests for my change. - [x] All unit tests pass locally. **pytest results:** COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/4072 from lwangverizon:feature/auto-create-new-session 5475c6ae91d12332598d521302736eb1db79a8be PiperOrigin-RevId: 856019482
Agent Development Kit (ADK)
An open-source, code-first Python framework for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Important Links: Docs, Samples, Java ADK, Go ADK & ADK Web.
</html>Agent Development Kit (ADK) is a flexible and modular framework that applies software development principles to AI agent creation. It is designed to simplify building, deploying, and orchestrating agent workflows, from simple tasks to complex systems. While optimized for Gemini, ADK is model-agnostic, deployment-agnostic, and compatible with other frameworks.
π₯ What's new
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Custom Service Registration: Add a service registry to provide a generic way to register custom service implementations to be used in FastAPI server. See short instruction. (391628f)
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Rewind: Add the ability to rewind a session to before a previous invocation (9dce06f).
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New CodeExecutor: Introduces a new AgentEngineSandboxCodeExecutor class that supports executing agent-generated code using the Vertex AI Code Execution Sandbox API (ee39a89)
β¨ Key Features
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Rich Tool Ecosystem: Utilize pre-built tools, custom functions, OpenAPI specs, MCP tools or integrate existing tools to give agents diverse capabilities, all for tight integration with the Google ecosystem.
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Code-First Development: Define agent logic, tools, and orchestration directly in Python for ultimate flexibility, testability, and versioning.
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Agent Config: Build agents without code. Check out the Agent Config feature.
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Tool Confirmation: A tool confirmation flow(HITL) that can guard tool execution with explicit confirmation and custom input.
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Modular Multi-Agent Systems: Design scalable applications by composing multiple specialized agents into flexible hierarchies.
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Deploy Anywhere: Easily containerize and deploy agents on Cloud Run or scale seamlessly with Vertex AI Agent Engine.
π Installation
Stable Release (Recommended)
You can install the latest stable version of ADK using pip:
pip install google-adk
The release cadence is roughly bi-weekly.
This version is recommended for most users as it represents the most recent official release.
Development Version
Bug fixes and new features are merged into the main branch on GitHub first. If you need access to changes that haven't been included in an official PyPI release yet, you can install directly from the main branch:
pip install git+https://github.com/google/adk-python.git@main
Note: The development version is built directly from the latest code commits. While it includes the newest fixes and features, it may also contain experimental changes or bugs not present in the stable release. Use it primarily for testing upcoming changes or accessing critical fixes before they are officially released.
π€ Agent2Agent (A2A) Protocol and ADK Integration
For remote agent-to-agent communication, ADK integrates with the A2A protocol. See this example for how they can work together.
π Documentation
Explore the full documentation for detailed guides on building, evaluating, and deploying agents:
π Feature Highlight
Define a single agent:
from google.adk.agents import Agent
from google.adk.tools import google_search
root_agent = Agent(
name="search_assistant",
model="gemini-2.5-flash", # Or your preferred Gemini model
instruction="You are a helpful assistant. Answer user questions using Google Search when needed.",
description="An assistant that can search the web.",
tools=[google_search]
)
Define a multi-agent system:
Define a multi-agent system with coordinator agent, greeter agent, and task execution agent. Then ADK engine and the model will guide the agents works together to accomplish the task.
from google.adk.agents import LlmAgent, BaseAgent
# Define individual agents
greeter = LlmAgent(name="greeter", model="gemini-2.5-flash", ...)
task_executor = LlmAgent(name="task_executor", model="gemini-2.5-flash", ...)
# Create parent agent and assign children via sub_agents
coordinator = LlmAgent(
name="Coordinator",
model="gemini-2.5-flash",
description="I coordinate greetings and tasks.",
sub_agents=[ # Assign sub_agents here
greeter,
task_executor
]
)
Development UI
A built-in development UI to help you test, evaluate, debug, and showcase your agent(s).
Evaluate Agents
adk eval \
samples_for_testing/hello_world \
samples_for_testing/hello_world/hello_world_eval_set_001.evalset.json
π€ Contributing
We welcome contributions from the community! Whether it's bug reports, feature requests, documentation improvements, or code contributions, please see our
- General contribution guideline and flow.
- Then if you want to contribute code, please read Code Contributing Guidelines to get started.
Community Repo
We have adk-python-community repo that is home to a growing ecosystem of community-contributed tools, third-party service integrations, and deployment scripts that extend the core capabilities of the ADK.
Vibe Coding
If you want to develop agent via vibe coding the llms.txt and the llms-full.txt can be used as context to LLM. While the former one is a summarized one and the later one has the full information in case your LLM has big enough context window.
Community Events
- [Completed] ADK's 1st community meeting on Wednesday, October 15, 2025. Remember to join our group to get access to the recording, and deck.
π License
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Happy Agent Building!