b8e9a80d93
* wait I forgot to comit locally * cp the entire core directory and then rm the .git subdir
55 lines
2.6 KiB
Plaintext
55 lines
2.6 KiB
Plaintext
---
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title: Introduction to Stateful Agents
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slug: stateful-agents
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---
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<img className="light" src="/images/stateful_agents.png" />
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<img className="dark" src="/images/stateful_agents_dark.png" />
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Large Language Models have given us powerful building blocks for intelligent systems.
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By connecting these models to external tools, we can create AI agents that take actions and affect the real world.
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Most LLM agents today are held back by a fundamental limitation: while LLMs provide the intelligence, they are inherently stateless - processing each input without memory of past interactions.
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Simply accumulating conversation history leads to agents that lose track of important information or need their memory regularly cleared to continue functioning.
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Building truly intelligent agents requires sophisticated context management - the missing piece that transforms stateless LLMs into agents that can intelligently process vast knowledge bases and continuously learn from their experiences.
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## Stateful Agents
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When an LLM agent interacts with the world, it accumulates state - learned behaviors, facts about its environment, and memories of past interactions.
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A stateful agent is one that can effectively manage this growing knowledge, maintaining consistent behavior while incorporating new experiences.
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```mermaid
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graph TD
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subgraph basic["Basic Agent"]
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direction LR
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c1["Context Window:
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Growing History → Context Limit!"] --> llm1[LLM]
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llm1 --> action1[/"Agent Action"/]
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action1 -->|"Append to History"| c1
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end
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basic --> stateful
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subgraph stateful["Stateful Agent"]
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direction LR
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db[(Persistent State
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All Memory & History)] --> cms["Context Management
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System"]
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cms -->|"Compile Context"| cw["Context Window
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---------------
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Relevant State"]
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cw --> llm2[LLM]
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llm2 --> action2[/"Agent Action"/]
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action2 -->|"Persist New State"| db
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end
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class c1,cw context
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class action1,action2 action
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```
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Stateful agents use intelligent context management to organize and prioritize information, enabling them to process large amounts of data while maintaining focus on what's relevant.
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This is a fundamental shift from traditional approaches that simply accumulate information until the agent becomes overwhelmed.
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Letta provides the foundation for building stateful agents through its context management system.
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By handling the complexity of state management, Letta lets you (the developer) focus on building agents that can truly learn and evolve through their interactions with the world.
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