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Kristopher Overholt
58 lines
3.6 KiB
Markdown
58 lines
3.6 KiB
Markdown
# Introduction to Conversational Context: Session, State, and Memory
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## Why Context Matters
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Meaningful, multi-turn conversations require agents to understand context. Just like humans, they need to recall what's been said and done to maintain continuity and avoid repetition. The Agent Development Kit (ADK) provides structured ways to manage this context through `Session`, `State`, and `Memory`.
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## Core Concepts
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Think of interacting with your agent as having distinct **conversation threads**, potentially drawing upon **long-term knowledge**.
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1. **`Session`**: The Current Conversation Thread
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* Represents a *single, ongoing interaction* between a user and your agent system.
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* Contains the chronological sequence of messages and actions (`Events`) for *that specific interaction*.
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* A `Session` can also hold temporary data (`State`) relevant only *during this conversation*.
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2. **`State` (`session.state`)**: Data Within the Current Conversation
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* Data stored within a specific `Session`.
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* Used to manage information relevant *only* to the *current, active* conversation thread (e.g., items in a shopping cart *during this chat*, user preferences mentioned *in this session*).
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3. **`Memory`**: Searchable, Cross-Session Information
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* Represents a store of information that might span *multiple past sessions* or include external data sources.
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* It acts as a knowledge base the agent can *search* to recall information or context beyond the immediate conversation.
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## Managing Context: Services
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ADK provides services to manage these concepts:
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1. **`SessionService`**: Manages Conversation Threads (`Session` objects)
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* Handles the lifecycle: creating, retrieving, updating (appending `Events`, modifying `State`), and deleting individual `Session` threads.
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* Ensures the agent has the right history and state for the current turn.
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2. **`MemoryService`**: Manages the Long-Term Knowledge Store (`Memory`)
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* Handles ingesting information (often from completed `Session`s) into the long-term store.
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* Provides methods to search this stored knowledge based on queries.
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**Implementations**: ADK offers different implementations for both `SessionService` and `MemoryService`, allowing you to choose the storage backend that best fits your application's needs. Notably, **in-memory implementations** are provided for both services; these are designed specifically for **local quick testing and development**. It's important to remember that **all data stored using these in-memory options (sessions, state, or long-term knowledge) is lost when your application restarts**. For persistence and scalability beyond local testing, ADK also offers database and cloud-based service options.
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**In Summary:**
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* **`Session` & `State`**: Focus on the **here and now** – the history and temporary data of the *single, active conversation*. Managed primarily by `SessionService`.
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* **Memory**: Focuses on the **past and external information** – a *searchable archive* potentially spanning across conversations. Managed by `MemoryService`.
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## What's Next?
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In the following sections, we'll dive deeper into each of these components:
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* **`Session`**: Understanding its structure and `Events`.
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* **`State`**: How to effectively read, write, and manage session-specific data.
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* **`SessionService`**: Choosing the right storage backend for your sessions.
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* **`MemoryService`**: Exploring options for storing and retrieving broader context.
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Understanding these concepts is fundamental to building agents that can engage in complex, stateful, and context-aware conversations.
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