Interactive Simulation · v1.0.0

Anatomy of an AI Agent & ReAct Loop

// Thought → Action → Observation → Repeat //

⚡ Active Scenario
OBJECTIVE: Monitor the market and send a panic alert if Bitcoin is around $60,000 and the news is bad.
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The Brain
Core LLM · Reasoning Engine
The central inference engine. Processes context, applies fuzzy reasoning, and decides actions. The seat of thought and decision.
GPT-4o Claude Gemini Inference
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Memory · Short-Term
Context Window · RAG
The current conversation, system instructions, and observations from the current round.
Context Tokens
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Memory · Long-Term
Qdrant Vector DB · Notebook
Vector database with past lessons, semantic embeddings, and persistent notes.
Qdrant Embeddings
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Planning
Chain of Thought · ReAct Cycles
Breaks the objective into steps, generates chains of thought (CoT), and orchestrates ReAct cycles.
CoT ReAct Tree-of-Thought
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Tools
Functions · APIs · Scripts
External functions called by the agent: web search, Python script, email API, calculator, browser.
web_search send_email Python APIs
// The ReAct Cycle
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THOUGHT
ACTION
👁️
OBS
// Simulation Progress
Step 0 of 6
agent · runtime · log
// Agent AI · ReAct Engine v2.1
// Initialization complete. Awaiting command...
 
agent@core:~$
TASK COMPLETED SUCCESSFULLY
ReAct cycle finished.