Portkey Integration with Autogen

website/docs/ecosystem/portkey.md

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+# Portkey Integration with Autogen
+ <img src="https://github.com/siddharthsambharia-portkey/Portkey-Product-Images/blob/main/Portkey-Autogen.png?raw=true" alt="Portkey Metrics Visualization" width=70% />
+
+[Portkey](https://portkey.ai) is a 2-line upgrade to make your Autogen agents reliable, cost-efficient, and fast.
+
+Portkey adds 4 core production capabilities to any Autogen 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:**
+
+   ```bash
+   pip install -qU pyautogen portkey-ai
+   ```
+
+2. **Configure Autogen with Portkey:**
+
+   ```python
+   from autogen import AssistantAgent, UserProxyAgent, config_list_from_json
+   from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders
+
+   config = [
+       {
+           "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
+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",
+)
+
+
+coder = autogen.AssistantAgent(
+    name="Coder",
+    system_message = "You are a Python developer who is good at developing games. You work with Product Manager."
+    llm_config={"config_list": config},
+)
+
+# Create groupchat
+groupchat = autogen.GroupChat(
+    agents=[user_proxy, coder], messages=[])
+manager = autogen.GroupChatManager(groupchat=groupchat, llm_config={"config_list": config})
+
+
+
+# Start the conversation
+user_proxy.initiate_chat(
+    manager, message="Build a classic & basic pong game with 2 players in python")
+
+```
+<br>
+Here’s the output from your Agent’s run on Portkey's dashboard<br>
+<img src=https://github.com/siddharthsambharia-portkey/Portkey-Product-Images/blob/main/Portkey-Dashboard.png?raw=true width=70%" alt="Portkey Dashboard" />
+
+
+
+
+
+
+## Key Features
+Portkey offers a range of advanced features to enhance your Autogen agents. Here’s an overview
+
+| Feature | Description |
+|---------|-------------|
+| 🌐 [Multi-LLM Integration](#interoperability) | Access 200+ LLMs with simple configuration changes |
+| 🛡️ [Enhanced Reliability](#reliability) | Implement fallbacks, load balancing, retries, and much more |
+| 📊 [Advanced Metrics](#metrics) | Track costs, tokens, latency, and 40+ custom metrics effortlessly |
+| 🔍 [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 |
+| 🔄 [Continuous Optimization](#continuous-improvement) | Capture user feedback for ongoing agent improvements |
+| 💾 [Smart Caching](#caching) | Reduce costs and latency with built-in caching mechanisms |
+| 🔐 [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 Autogen, check out our notebook<br> <br>[![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
+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"
+        )
+    }
+]
+```
+
+### Reliability
+
+Implement fallbacks, load balancing, and automatic retries to make your agents more resilient.
+
+```python
+portkey_config = {
+  "retry": {
+    "attempts": 5
+  },
+  "strategy": {
+    "mode": "loadbalance"  # Options: "loadbalance" or "fallback"
+  },
+  "targets": [
+    {
+      "provider": "openai",
+      "api_key": "OpenAI_API_Key"
+    },
+    {
+      "provider": "anthropic",
+      "api_key": "Anthropic_API_Key"
+    }
+  ]
+}
+```
+
+### 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.
+
+<details>
+  <summary><b>Portkey's Observability Dashboard</b></summary>
+<img src=https://github.com/siddharthsambharia-portkey/Portkey-Product-Images/blob/main/Portkey-Dashboard.png?raw=true width=70%" alt="Portkey Dashboard" />
+</details>
+
+### Comprehensive Logging
+
+Access detailed logs and traces of agent activities, function calls, and errors. Filter logs based on multiple parameters for in-depth analysis.
+
+<details>
+  <summary><b>Traces</b></summary>
+  <img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Traces.png" alt="Portkey Logging Interface" width=70% />
+</details>
+
+<details>
+  <summary><b>Logs</b></summary>
+  <img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Logs.png" alt="Portkey Metrics Visualization" width=70% />
+</details>
+
+### Guardrails
+Autogen agents, while powerful, can sometimes produce unexpected or undesired outputs. Portkey's Guardrails feature helps enforce agent behavior in real-time, ensuring your Autogen 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://docs.portkey.ai/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
+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
+
+- [📘 Portkey Documentation](https://docs.portkey.ai)
+- [🐦 Twitter](https://twitter.com/portkeyai)
+- [💬 Discord Community](https://discord.gg/JHPt4C7r)
+- [📊 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).