78 lines
4.7 KiB
Plaintext
78 lines
4.7 KiB
Plaintext
---
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title: "Introduction"
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description: "AgentOps is the developer favorite platform for testing, debugging, and deploying AI agents and LLM apps."
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mode: "wide"
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---
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<Note title="Open Source">
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The AgentOps app is open source—explore the code in our <a href="https://github.com/AgentOps-AI/agentops/tree/main/app">GitHub app directory</a>.
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</Note>
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## Integrate with developer favorite agent frameworks
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<CardGroup cols={2}>
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<Card title="OpenAI Agents SDK" icon={<img src="https://www.github.com/agentops-ai/agentops/blob/main/docs/images/external/openai/openai-logomark.png?raw=true" alt="OpenAI Agents SDK" />} iconType="image" href="/v1/integrations/agents_sdk" />
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<Card title="CrewAI" icon={<img src="https://www.github.com/agentops-ai/agentops/blob/main/docs/v1/img/docs-icons/crew.png?raw=true" alt="CrewAI"/>} iconType="image" href="/v1/integrations/crewai" />
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<Card title="AG2" icon={<img src="https://www.github.com/agentops-ai/agentops/blob/main/docs/images/external/autogen/ag2.svg?raw=true" alt="AG2"/>} iconType="image" href="/v1/integrations/autogen" />
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<Card title="AutoGen" icon={<img src="https://www.github.com/agentops-ai/agentops/blob/main/docs/images/external/microsoft/microsoft_logo.svg?raw=true" alt="AutoGen" />} iconType="image" href="/v1/integrations/autogen" />
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<Card title="Anthropic" icon={<img src="https://www.github.com/agentops-ai/agentops/blob/main/docs/images/external/anthropic/anthropic_icon_slate.png?raw=true" alt="Anthropic" />} iconType="image" href="/v1/integrations/anthropic" />
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<Card title="Ollama" icon={<img src="https://www.github.com/agentops-ai/agentops/blob/main/docs/images/external/ollama/ollama-icon.png?raw=true" alt="Ollama" />} iconType="image" href="/v1/integrations/ollama" />
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<Card title="Cohere" icon={<img src="https://www.github.com/agentops-ai/agentops/blob/main/docs/images/external/cohere/cohere-logo.svg?raw=true" alt="Cohere" />} iconType="image" href="/v1/integrations/cohere" />
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<Card title="Groq" icon="bolt" href="https://docs.agentops.ai/v1/integrations/groq" />
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</CardGroup>
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Observability and monitoring for your AI agents and LLM apps. And we do it all in just two lines of code...
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<CodeGroup>
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```python python
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import agentops
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agentops.init(<INSERT YOUR API KEY HERE>)
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```
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</CodeGroup>
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... that logs everything back to your AgentOps Dashboard.
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<Note>
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AgentOps is also available for TypeScript/JavaScript applications. Check out our [TypeScript SDK guide](/v2/usage/typescript-sdk) for Node.js projects.
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</Note>
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## The AgentOps Dashboard
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<Check>[Give us a star](https://github.com/AgentOps-AI/agentops) to bookmark on GitHub, save for later 🖇️)</Check>
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With just two lines of code, you can free yourself from the chains of the terminal and, instead, visualize your agents' behavior
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in your AgentOps Dashboard. After setting up AgentOps, each execution of your program is recorded as a session and the above
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data is automatically recorded for you.
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The examples below were captured with two lines of code.
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### Session Drilldown
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Here you will find a list of all of your previously recorded sessions and useful data about each such as total execution time.
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You also get helpful debugging info such as any SDK versions you were on if you're building on a supported agent framework like Crew or AutoGen.
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LLM calls are presented as a familiar chat history view, and charts give you a breakdown of the types of events that were called and how long they took.
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<Frame type="glass" caption="Session Summary">
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<img height="200" src="https://github.com/AgentOps-AI/agentops/blob/main/docs/images/session-summary.gif?raw=true" />
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</Frame>
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Find any past sessions from your Session Drawer.
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<Frame type="glass" caption="Session Drawer">
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<img height="250" src="https://github.com/AgentOps-AI/agentops/blob/main/docs/images/session-drawer.gif?raw=true" />
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</Frame>
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Most powerful of all is the Session Waterfall. On the left, a time visualization of all your LLM calls, Action events, Tool calls, and Errors.
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On the right, specific details about the event you've selected on the waterfall. For instance the exact prompt and completion for a given LLM call.
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Most of which has been automatically recorded for you.
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<Frame type="glass" caption="Session Waterfall">
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<img height="200" src="https://github.com/AgentOps-AI/agentops/blob/main/docs/images/session-waterfall.gif?raw=true" />
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</Frame>
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### Session Overview
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View a meta-analysis of all of your sessions in a single view.
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<Frame type="glass" caption="Session Overview">
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<img height="200" src="https://github.com/AgentOps-AI/agentops/blob/main/docs/images/overview.png?raw=true" />
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</Frame>
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<script type="module" src="/scripts/github_stars.js"></script>
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<script type="module" src="/scripts/adjust_api_dynamically.js"></script>
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