> ## Documentation Index > Fetch the complete documentation index at: https://docs.ag2.ai/llms.txt > Use this file to discover all available pages before exploring further. # Portkey Integration Portkey Metrics Visualization [Portkey](https://portkey.ai) is a 2-line upgrade to make your AG2 agents reliable, cost-efficient, and fast. Portkey adds 4 core production capabilities to any AG2 agent: 1. Routing to 200+ LLMs 2. Making each LLM call more robust 3. Full-stack tracing & cost, performance analytics 4. Real-time guardrails to enforce behavior ## Getting Started 1. **Install Required Packages:** 2. ```bash theme={null} pip install -qU ag2 portkey-ai ``` **Configure AG2 with Portkey:** ```python theme={null} from autogen import AssistantAgent, UserProxyAgent, LLMConfig from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders llm_config = LLMConfig( api_key="OPENAI_API_KEY", model="gpt-3.5-turbo", base_url=PORTKEY_GATEWAY_URL, api_type="openai", default_headers=createHeaders( api_key="YOUR_PORTKEY_API_KEY", provider="openai", ) ) ``` Generate your API key in the [Portkey Dashboard](https://app.portkey.ai/). And, that's it! With just this, you can start logging all of your AutoGen requests and make them reliable. 3. **Let's Run your Agent** ```python theme={null} import autogen # Create user proxy agent, coder, product manager user_proxy = autogen.UserProxyAgent( name="User_proxy", system_message="A human admin who will give the idea and run the code provided by Coder.", code_execution_config={"last_n_messages": 2, "work_dir": "groupchat"}, human_input_mode="ALWAYS", ) with llm_config: coder = autogen.AssistantAgent( name="Coder", system_message = "You are a Python developer who is good at developing games. You work with Product Manager.", ) # Create groupchat groupchat = autogen.GroupChat( agents=[user_proxy, coder], messages=[]) manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config) # Start the conversation user_proxy.initiate_chat( manager, message="Build a classic & basic pong game with 2 players in python") ```
Here’s the output from your Agent’s run on Portkey's dashboard
Portkey Dashboard ## Key Features Portkey offers a range of advanced features to enhance your AG2 agents. Here’s an overview | Feature | Description | | -------------------------------------------------------- | ------------------------------------------------------------------ | | 🌐 [Multi-LLM Integration](#interoperability) | Access 200+ LLMs with simple configuration changes | | πŸ›‘οΈ [Enhanced Reliability](#reliability) | Implement fallbacks, load balancing, retries, and much more | | πŸ“Š [Advanced Metrics](#metrics) | Track costs, tokens, latency, and 40+ custom metrics effortlessly | | πŸ” [Detailed Traces and Logs](#comprehensive-logging) | Gain insights into every agent action and decision | | 🚧 [Guardrails](#guardrails) | Enforce agent behavior with real-time checks on inputs and outputs | | πŸ”„ [Continuous Optimization](#continuous-improvement) | Capture user feedback for ongoing agent improvements | | πŸ’Ύ [Smart Caching](#caching) | Reduce costs and latency with built-in caching mechanisms | | πŸ” [Enterprise-Grade Security](#security-and-compliance) | Set budget limits and implement fine-grained access controls | ## Colab Notebook For a hands-on example of integrating Portkey with AG2, check out our notebook

[![Google Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://git.new/Portkey-Autogen) . ## Advanced Features ### Interoperability Easily switch between **200+ LLMs** by changing the `provider` and API key in your configuration. #### Example: Switching from OpenAI to Azure OpenAI ```python theme={null} config = [ { "api_key": "api-key", "model": "gpt-3.5-turbo", "base_url": PORTKEY_GATEWAY_URL, "api_type": "openai", "default_headers": createHeaders( api_key="YOUR_PORTKEY_API_KEY", provider="azure-openai", virtual_key="AZURE_VIRTUAL_KEY" ) } ] ``` Note: AG2 messages will go through Portkey's AI Gateway following OpenAI's API signature. Some language models may not work properly because messages need to be in a specific role order. ### Reliability Implement fallbacks, load balancing, and automatic retries to make your agents more resilient. ```python theme={null} { "strategy": { "mode": "fallback" # Options: "loadbalance" or "fallback" }, "targets": [ { "provider": "openai", "api_key": "openai-api-key", "override_params": { "top_k": "0.4", "max_tokens": "100" } }, { "provider": "anthropic", "api_key": "anthropic-api-key", "override_params": { "top_p": "0.6", "model": "claude-3-5-sonnet-20240620" } } ] } ``` Learn more about [Portkey Config object here](https://docs.portkey.ai/docs/product/ai-gateway-streamline-llm-integrations/configs). Be Careful to Load-Balance/Fallback to providers that don't support tool calling when the request contains a function call. ### Metrics Agent runs are complex. Portkey automatically logs **40+ comprehensive metrics** for your AI agents, including cost, tokens used, latency, etc. Whether you need a broad overview or granular insights into your agent runs, Portkey's customizable filters provide the metrics you need. [![Portkey's Observability Dashboard](https://github.com/siddharthsambharia-portkey/Portkey-Product-Images/blob/main/Portkey-Dashboard.png?raw=true)](https://app.portkey.ai/) ### Comprehensive Logging Access detailed logs and traces of agent activities, function calls, and errors. Filter logs based on multiple parameters for in-depth analysis. ![Portkey Traces](https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Traces.png) [![Portkey Logs](https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Logs.png)](https://app.portkey.ai/) ### Guardrails AG2 agents, while powerful, can sometimes produce unexpected or undesired outputs. Portkey's Guardrails feature helps enforce agent behavior in real-time, ensuring your AG2 agents operate within specified parameters. Verify both the **inputs** to and *outputs* from your agents to ensure they adhere to specified formats and content guidelines. Learn more about Portkey's Guardrails [here](https://portkey.ai/docs/product/guardrails) ### Continuous Improvement Capture qualitative and quantitative user feedback on your requests to continuously enhance your agent performance. ### Caching Reduce costs and latency with Portkey's built-in caching system. ```python theme={null} portkey_config = { "cache": { "mode": "semantic" # Options: "simple" or "semantic" } } ``` ### Security and Compliance Set budget limits on provider API keys and implement fine-grained user roles and permissions for both your application and the Portkey APIs. ## Additional Resources * [πŸ“˜ Portkey Documentation](https://docs.portkey.ai) * [🐦 Twitter](https://twitter.com/portkeyai) * [πŸ’¬ Discord Community](https://discord.gg/JHPt4C7r) * [πŸ“Š Portkey App](https://app.portkey.ai) For more information on using these features and setting up your Config, please refer to the [Portkey documentation](https://docs.portkey.ai).
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