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Core concepts
Letta SDK Reference for AI Agents
Agents
Building stateful agents
Context hierarchy
Image inputs
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Multi-agent systems
Multi-agent patterns
The supervisor-worker pattern
Parallel execution with shared memory
The producer-reviewer pattern
The round-robin pattern
AgentFile (.af)
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Model Context Protocol
What is MCP?
Connect Letta to MCP
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Multi-agent tools
Creating tool rules
Using tool variables
Parallel tool calling
Deploy and scale
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Claude Code memory proxy
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Letta ADE
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lettactl
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Core concepts
Core concepts
Suites
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Suite YAML reference
Graders
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Multi-metric evaluation
Extractors
Built-in extractors
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Advanced
Custom Graders
Multi-turn conversations
CLI reference
CLI commands
Results & metrics
Understanding results
Troubleshooting
Troubleshooting
Templates & versioning
Intro to templates
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Memory variables
Self-hosting
Overview
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Collecting traces
Model providers
OpenAI
Anthropic
Google AI (Gemini)
LM Studio
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OpenAI-compatible
DeepSeek
AWS Bedrock
Groq
xAI (Grok)
Together
Google Vertex AI
Azure OpenAI
Ollama
vLLM
Advanced configuration
Database configuration
Performance tuning
Inspecting DB
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Voice agents
LiveKit integration
Vapi integration
Additional resources
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Research background
MemGPT
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Legacy agent types
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Creating Agents in the ADE
Create new agents in the Agent Development Environment with templates and configuration.
