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