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docs: add LLMs.txt references to documentation
Updates: - Added LLMs.txt card in docs/index.md Learn More section - Created docs/llms-txt.md with complete guide about LLMs.txt - Updated README.md with LLMs.txt reference - Added llms-txt.md to mkdocs.yml navigation LLMs.txt provides 800+ lines of complete framework documentation optimized for LLM consumption (v0.1.0 to v0.12.0)
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‎docs/index.md‎

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[:octicons-arrow-right-24: Examples](examples/basic-usage.md)
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- :material-robot: __LLMs.txt__
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---
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Complete documentation for LLM consumption (800+ lines)
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[:octicons-arrow-right-24: LLMs.txt](https://github.com/marcosf63/react-agent-framework/blob/main/LLMs.txt)
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‎docs/llms-txt.md‎

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# LLMs.txt - Complete Documentation for AI Models
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The **LLMs.txt** file contains the complete framework documentation optimized for Large Language Model consumption.
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---
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## Overview
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LLMs.txt is a comprehensive, structured documentation file designed specifically for AI models to understand and use the ReAct Agent Framework effectively.
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**File Location**: [`LLMs.txt`](https://github.com/marcosf63/react-agent-framework/blob/main/LLMs.txt)
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**Size**: 800+ lines
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**Format**: Plain text with clear structure
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**Coverage**: All versions from v0.1.0 to v0.12.0
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---
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## What's Included
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### 1. Overview & Quick Start
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Complete introduction with working examples
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### 2. Installation
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All installation methods and options
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### 3. Core Concepts
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ReAct pattern, agent creation, tool registration
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### 4. Memory Systems (v0.10.0+)
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- ChatMemory (SimpleChatMemory, SQLiteChatMemory)
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- KnowledgeMemory (ChromaKnowledgeMemory, FAISSKnowledgeMemory)
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- Complete API and examples
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### 5. Multi-Provider Support
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OpenAI, Anthropic, Google, Ollama configuration
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### 6. Built-in Tools
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Search, filesystem, computation tools
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### 7. Objectives System
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Goal tracking and management
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### 8. Reasoning Strategies
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ReAct, ReWOO, Reflection, Plan-Execute
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### 9. Environments
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Web, CLI, File environment interaction
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### 10. MCP Integration
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Model Context Protocol server setup
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### 11. Layer 4: Infrastructure (v0.11.0)
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Complete production infrastructure:
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- **Monitoring**: Metrics, logging, telemetry
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- **Resilience**: Retry, circuit breaker, fallback, timeout
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- **Security**: RBAC, sandbox, audit, secrets
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- **Cost Control**: Budget, rate limiting, quotas
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- **Human-in-the-Loop**: Approval, intervention, feedback
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### 12. Layer 3: Multi-Agent Systems (v0.12.0)
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Complete multi-agent capabilities:
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- **Communication**: Messages, protocols, channels
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- **Orchestration**: Orchestrator, workflows, task delegation
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- **Coordination**: Shared state, consensus, locking
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- **Collaboration**: Teams, patterns, negotiation
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### 13. Complete API Reference
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All classes, methods, parameters, and return types
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### 14. Examples & Use Cases
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5 complete, production-ready examples:
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1. Simple Q&A Agent
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2. Research Agent with Memory
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3. Production Agent with Infrastructure
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4. Multi-Agent System
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5. Complete Enterprise System
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---
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## Why LLMs.txt?
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### For AI Models
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- **Structured format** optimized for AI consumption
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- **Complete coverage** of all features in one file
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- **Working examples** with full context
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- **No navigation required** - everything in sequence
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- **Version tracking** - clear indication of feature versions
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### For Developers
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- **Quick reference** for AI pair programming
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- **Copy-paste ready** code examples
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- **Architecture overview** in one place
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- **Version history** and migration paths
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---
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## How to Use
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### As a Developer
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**1. Share with AI assistants:**
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```bash
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# Copy to clipboard
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cat LLMs.txt | pbcopy # macOS
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cat LLMs.txt | xclip # Linux
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```
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**2. Reference in prompts:**
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```
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"Using the ReAct Agent Framework as described in LLMs.txt,
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create an agent that..."
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```
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**3. Quick lookup:**
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```bash
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# Find specific topics
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grep -A 10 "Multi-Agent" LLMs.txt
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grep -A 20 "Memory Systems" LLMs.txt
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```
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### As an AI Model
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The file is structured with clear section markers:
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```
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================================================================================
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SECTION NAME
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================================================================================
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```
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Each section includes:
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- Concept explanation
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- Code examples
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- API signatures
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- Best practices
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- Common patterns
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---
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## Example Content Structure
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```text
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================================================================================
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4. MEMORY SYSTEMS (v0.10.0+)
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================================================================================
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IMPORTANT: v0.10.0 separated memory into TWO types:
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- Chat Memory: Sequential conversation history
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- Knowledge Memory: Semantic knowledge base (RAG)
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CHAT MEMORY:
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------------
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SimpleChatMemory (Development):
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```python
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from react_agent_framework.core.memory.chat import SimpleChatMemory
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agent = ReactAgent(
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name="Agent",
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chat_memory=SimpleChatMemory(max_messages=100)
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)
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```
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[... complete examples and API ...]
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```
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---
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## Keeping Updated
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The LLMs.txt file is updated with each release:
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- **v0.12.0**: Added Layer 3 (Multi-Agent Systems)
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- **v0.11.0**: Added Layer 4 (Infrastructure)
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- **v0.10.0**: Added Memory System Refactoring
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- **v0.9.0**: Initial LLMs.txt creation
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---
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## Download
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**Direct link**: [LLMs.txt on GitHub](https://github.com/marcosf63/react-agent-framework/blob/main/LLMs.txt)
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**Raw file**: [Raw LLMs.txt](https://raw.githubusercontent.com/marcosf63/react-agent-framework/main/LLMs.txt)
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```bash
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# Download with curl
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curl -O https://raw.githubusercontent.com/marcosf63/react-agent-framework/main/LLMs.txt
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# Download with wget
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wget https://raw.githubusercontent.com/marcosf63/react-agent-framework/main/LLMs.txt
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```
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---
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## Contribute
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Found an issue or want to improve LLMs.txt?
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1. [Open an issue](https://github.com/marcosf63/react-agent-framework/issues)
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2. [Submit a PR](https://github.com/marcosf63/react-agent-framework/pulls)
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The file is located at the repository root: `/LLMs.txt`
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---
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## See Also
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- [Documentation Home](../index.md)
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- [API Reference](../api-reference/react-agent.md)
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- [Examples](../examples/basic-usage.md)
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- [GitHub Repository](https://github.com/marcosf63/react-agent-framework)

‎mkdocs.yml‎

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- Development:
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- contributing.md
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- changelog.md
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- llms-txt.md
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# Extra
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