Merge pull request #169 from BrainBlend-AI/feature/docs-improvements

  docs: replace single llms.txt with modular generation system

Author: KennyVaneetvelde

.github/workflows/docs.yml

@@ -42,9 +42,15 @@ jobs:
           poetry run make singlehtml
           poetry run make html
 
-      - name: Generate llms.txt
+      - name: Generate all llms.txt files
         run: |
-          poetry run python scripts/generate_llms_txt.py
+          poetry run python scripts/generate_llms_files.py
+          
+      - name: Copy llms files to build directory
+        run: |
+          cp docs/llms-*.txt docs/_build/html/
+          echo "Generated llms files:"
+          ls -lh docs/_build/html/llms-*.txt
 
       - name: Upload artifact
         uses: actions/upload-pages-artifact@v3

.gitignore

@@ -78,6 +78,9 @@ instance/
 
 # Sphinx documentation
 docs/_build/
+docs/llms-*.txt
+docs/llms.txt
+docs/examples/source/
 
 # PyBuilder
 target/
@@ -150,4 +153,5 @@ debug.log
 # AI tools
 .claude
 CLAUDE.md
+CLAUDE.local.md
 .serena

docs/examples/index.md

@@ -2,6 +2,12 @@
 
 This section contains detailed examples of using Atomic Agents in various scenarios.
 
+```{note}
+All examples are available in optimized formats for AI assistants:
+- **[Examples with documentation](../llms-examples.txt)** - All examples with source code and READMEs
+- **[Full framework package](../llms-full.txt)** - Complete documentation, source, and examples
+```
+
 ## Quickstart Examples
 
 Simple examples to get started with the framework:
@@ -12,7 +18,7 @@ Simple examples to get started with the framework:
 - Custom input/output schemas
 - Multiple provider support
 
-[View Quickstart Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/quickstart)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/quickstart)** - Browse the complete source code and run the examples
 
 ## Basic Multimodal
 
@@ -23,7 +29,7 @@ Examples of working with images and text:
 - Visual content generation
 - Multi-image comparisons
 
-[View Basic Multimodal Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/basic-multimodal)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/basic-multimodal)** - Browse the complete source code and run the examples
 
 ## RAG Chatbot
 
@@ -35,7 +41,7 @@ Build context-aware chatbots with retrieval-augmented generation:
 - Source attribution
 - Follow-up suggestions
 
-[View RAG Chatbot Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/rag-chatbot)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/rag-chatbot)** - Browse the complete source code and run the examples
 
 ## Web Search Agent
 
@@ -47,7 +53,7 @@ Create agents that can search and analyze web content:
 - Multi-source research
 - Citation tracking
 
-[View Web Search Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/web-search-agent)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/web-search-agent)** - Browse the complete source code and run the examples
 
 ## Deep Research
 
@@ -59,7 +65,7 @@ Perform comprehensive research tasks:
 - Structured output generation
 - Citation management
 
-[View Deep Research Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/deep-research)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/deep-research)** - Browse the complete source code and run the examples
 
 ## YouTube Summarizer
 
@@ -71,7 +77,7 @@ Extract and analyze information from videos:
 - Timestamp linking
 - Chapter generation
 
-[View YouTube Summarizer Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/youtube-summarizer)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/youtube-summarizer)** - Browse the complete source code and run the examples
 
 ## YouTube to Recipe
 
@@ -83,7 +89,7 @@ Convert cooking videos into structured recipes:
 - Step-by-step instructions
 - Time and temperature conversion
 
-[View YouTube Recipe Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/youtube-to-recipe)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/youtube-to-recipe)** - Browse the complete source code and run the examples
 
 ## Orchestration Agent
 
@@ -95,7 +101,7 @@ Coordinate multiple agents for complex tasks:
 - Error handling
 - Result aggregation
 
-[View Orchestration Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/orchestration-agent)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/orchestration-agent)** - Browse the complete source code and run the examples
 
 ## MCP Agent
 
@@ -108,4 +114,4 @@ Build intelligent agents using the Model Context Protocol:
 - Extensible tool architecture
 
 [View MCP Agent Documentation](mcp_agent.md)
-[View MCP Agent Examples](https://github.com/BrainBlend-AI/atomic-agents/tree/main/atomic-examples/mcp-agent)
+📂 **[View on GitHub](https://github.com/BrainBlend-AI/atomic-monorepo/tree/main/atomic-examples/mcp-agent)** - Browse the complete source code and run the examples

docs/index.md

@@ -14,6 +14,21 @@ contributing
 
 ![Atomic Agents](_static/logo.png)
 
+```{admonition} AI Assistant Resources
+:class: tip
+
+📥 **Download Documentation for AI Assistants and LLMs**
+
+Choose the resource that best fits your needs:
+
+- **[📚 Full Package](llms-full.txt)** - Complete documentation, source code, and examples in one file
+- **[📖 Documentation Only](llms-docs.txt)** - API documentation, guides, and references
+- **[💻 Source Code Only](llms-source.txt)** - Complete atomic-agents framework source code
+- **[🎯 Examples Only](llms-examples.txt)** - All example implementations with READMEs
+
+All files are optimized for AI assistants and Large Language Models, with clear structure and formatting for easy parsing.
+```
+
 The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability. The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of [Instructor](https://github.com/jxnl/instructor) and leverages the power of [Pydantic](https://docs.pydantic.dev/latest/) for data and schema validation and serialization.
 
 All logic and control flows are written in Python, enabling developers to apply familiar best practices and workflows from traditional software development without compromising flexibility or clarity.