agentops/examples/README.md

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# AgentOps Examples
This directory contains comprehensive examples demonstrating how to integrate AgentOps with various AI/ML frameworks, libraries, and providers. Each example is provided as a Jupyter notebook and a Python script with detailed explanations and code samples.
## 📁 Directory Structure
- **[`ag2/`](./ag2/)** - Examples for AG2 (AutoGen 2.0) multi-agent conversations
- `agentchat_with_memory` - Agent chat with persistent memory
- `async_human_input` - Asynchronous human input handling
- `tools_wikipedia_search` - Wikipedia search tool integration
- **[`anthropic/`](./anthropic/)** - Anthropic Claude API integration examples
- `agentops-anthropic-understanding-tools` - Deep dive into tool usage
- `anthropic-example-async` - Asynchronous API calls
- `anthropic-example-sync` - Synchronous API calls
- `antrophic-example-tool` - Tool calling examples
- `README.md` - Detailed Anthropic integration guide
- **[`autogen/`](./autogen/)** - Microsoft AutoGen framework examples
- `AgentChat` - Basic agent chat functionality
- `MathAgent` - Mathematical problem-solving agent
- **[`crewai/`](./crewai/)** - CrewAI multi-agent framework examples
- `job_posting` - Job posting automation workflow
- `markdown_validator` - Markdown validation agent
- **[`gemini/`](./gemini/)** - Google Gemini API integration
- `gemini_example` - Basic Gemini API usage with AgentOps
- **[`google_adk/`](./google_adk/)** - Google AI Development Kit examples
- `human_approval` - Human-in-the-loop approval workflows
- **[`langchain/`](./langchain/)** - LangChain framework integration
- `langchain_examples` - Comprehensive LangChain usage examples
- **[`litellm/`](./litellm/)** - LiteLLM proxy integration
- `litellm_example` - Multi-provider LLM access through LiteLLM
- **[`openai/`](./openai/)** - OpenAI API integration examples
- `multi_tool_orchestration` - Complex tool orchestration
- `openai_example_async` - Asynchronous OpenAI API calls
- `openai_example_sync` - Synchronous OpenAI API calls
- `web_search` - Web search functionality
- **[`openai_agents/`](./openai_agents/)** - OpenAI Agents SDK examples
- `agent_patterns` - Common agent design patterns
- `agents_tools` - Agent tool integration
- `customer_service_agent` - Customer service automation
- **[`smolagents/`](./smolagents/)** - SmolAgents framework examples
- `multi_smolagents_system` - Multi-agent system coordination
- `text_to_sql` - Natural language to SQL conversion
- **[`watsonx/`](./watsonx/)** - IBM Watsonx AI integration
- `watsonx-streaming` - Streaming text generation
- `watsonx-text-chat` - Text generation and chat completion
- `watsonx-tokeniation-model` - Tokenization and model details
- `README.md` - Detailed Watsonx integration guide
- **[`xai/`](./xai/)** - xAI (Grok) API integration
- `grok_examples` - Basic Grok API usage
- `grok_vision_examples` - Vision capabilities with Grok
### Utility Scripts
- **[`generate_documentation.py`](./generate_documentation.py)** - Script to convert Jupyter notebooks to MDX documentation files
- Converts notebooks from `examples/` to `docs/v2/examples/`
- Handles frontmatter, GitHub links, and installation sections
- Transforms `%pip install` commands to CodeGroup format
## 📓 Prerequisites
1. **AgentOps Account**: Sign up at [agentops.ai](https://agentops.ai)
2. **Python Environment**: Python 3.10+ recommended
3. **API Keys**: Obtain API keys for the services you want to use
## 📖 Documentation Generation
The `generate_documentation.py` script automatically converts these Jupyter notebook examples into documentation for the AgentOps website. It:
- Extracts notebook content and converts to Markdown
- Adds proper frontmatter and metadata
- Transforms installation commands into user-friendly format
- Generates GitHub links for source notebooks
- Creates MDX files in `docs/v2/examples/`
### Usage
```bash
python examples/generate_documentation.py examples/langchain/langchain_examples.ipynb
```
## 🤝 Contributing
When adding new examples:
1. Create a new subdirectory for the framework/provider
2. Include comprehensive Jupyter notebooks with explanations
3. Add a README.md if the integration is complex
4. Ensure examples are self-contained and runnable
5. Follow the existing naming conventions
6. Use the `generate_documentation.py` script to create documentation files
7. Add the example notebook to the main `README.md` for visibility
8. Add the generated documentation to the `docs/v2/examples/` directory for website visibility
9. Submit a pull request with a clear description of your changes
## 📚 Additional Resources
- [AgentOps Documentation](https://docs.agentops.ai)
- [AgentOps Dashboard](https://app.agentops.ai)
- [GitHub Repository](https://github.com/AgentOps-AI/agentops)
- [Community Discord](https://discord.gg/agentops)
## 📄 License
These examples are provided under the same license as the AgentOps project. See the main repository for license details.