shared_state is a centralized Python dictionary accessible by all tools and agents. It allows you to control execution flow, share data, and provide instructions to the agents based on certain conditions or actions performed by other agents.
Shared state is only available when tools are deployed together with agents (see Deployment to Production guide). If tools are deployed as separate APIs, they won’t share the same state, and you’ll need to implement your own state management solution.

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Understanding Shared State

Shared state is particularly useful when your agents interact with multiple tools that need to exchange information. Here’s why:
  • Without Shared State: Suppose Tool A collects data that Tool B needs. The agent must explicitly pass this data as a parameter to Tool B.
Without Shared State
  • With Shared State: Tool A can store the required data in the shared state, and Tool B can get it without needing direct parameter passing. This approach reduces complexity and minimizes the risk of errors.
With Shared State

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Using Shared State

The two basic operations are:
  • Setting a value in the shared state: shared_state.set('key', value)
  • Getting a value from the shared state: shared_state.get('key')
You can use shared state in your tools and agents. Here’s how:
To set a value in the shared state within a tool, use the self._shared_state.set inside your tool. For example, you can store the context retrieved from a database in the shared state:
class QueryDatabase(BaseTool):
    """
    Retrieves data from the database and stores it in the shared state.
    """
    question: str = Field(..., description="The query to execute.")

    def run(self):
        # Fetch data based on the question
        context = query_database(self.question)
        # Store the context in shared state
        self._shared_state.set('context', context)
        return "Context has been retrieved and stored successfully."