123 lines
3.6 KiB
Plaintext
123 lines
3.6 KiB
Plaintext
---
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title: 'Camel AI'
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description: 'Track and analyze CAMEL agents with AgentOps'
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---
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import CodeTooltip from '/snippets/add-code-tooltip.mdx'
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import EnvTooltip from '/snippets/add-env-tooltip.mdx'
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[CAMEL-AI](https://www.camel-ai.org/) is the first large language model (LLM) multi-agent framework and an open-source community dedicated to finding the scaling law of agents. Checkout their comprehensive documentation [here](https://docs.camel-ai.org/).
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## Adding AgentOps to CAMEL agents
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<Steps>
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<Step title="Install the AgentOps SDK">
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<CodeGroup>
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```bash pip
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pip install agentops
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```
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```bash poetry
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poetry add agentops
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```
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</CodeGroup>
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</Step>
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<Step title="Install CAMEL-AI with all dependencies">
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<CodeGroup>
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```bash pip
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pip install "camel-ai[all]==0.2.11"
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```
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```bash poetry
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poetry add "camel-ai[all]==0.2.11"
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```
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</CodeGroup>
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</Step>
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<Step title="Add AgentOps code to your code">
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<CodeTooltip/>
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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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# your code here
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agentops.end_session("Success") # Success|Fail|Indeterminate
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```
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</CodeGroup>
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<EnvTooltip />
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<CodeGroup>
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```python .env
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AGENTOPS_API_KEY=<YOUR API KEY>
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```
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</CodeGroup>
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Read more about environment variables in [Advanced Configuration](/v1/usage/advanced-configuration)
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</Step>
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<Step title="Run your agent">
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Execute your program and visit [app.agentops.ai/drilldown](https://app.agentops.ai/drilldown) to observe your CAMEL Agent! 🕵️
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<Tip>
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After your run, AgentOps prints a clickable url to console linking directly to your session in the Dashboard
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</Tip>
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<div/>{/* Intentionally blank div for newline */}
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<Frame type="glass" caption="Clickable link to session">
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<img height="200" src="https://github.com/AgentOps-AI/agentops/blob/main/docs/images/link-to-session.gif?raw=true" />
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</Frame>
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</Step>
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</Steps>
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## Full Examples
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### Single Agent Example with Tools
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Here's a simple example of tracking a single CAMEL agent with tools using AgentOps:
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```python
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import agentops
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import os
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from camel.agents import ChatAgent
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from camel.messages import BaseMessage
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from camel.models import ModelFactory
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from camel.types import ModelPlatformType, ModelType
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# Initialize AgentOps
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agentops.init(os.getenv("AGENTOPS_API_KEY"))
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# Import toolkits after AgentOps init for tracking
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from camel.toolkits import SearchToolkit
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# Set up the agent with search tools
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sys_msg = BaseMessage.make_assistant_message(
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role_name='Tools calling operator',
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content='You are a helpful assistant'
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)
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# Configure tools and model
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tools = [*SearchToolkit().get_tools()]
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model = ModelFactory.create(
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model_platform=ModelPlatformType.OPENAI,
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model_type=ModelType.GPT_4O_MINI,
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)
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# Create the agent
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camel_agent = ChatAgent(
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system_message=sys_msg,
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model=model,
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tools=tools,
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)
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# Run the agent
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user_msg = 'What is CAMEL-AI.org?'
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response = camel_agent.step(user_msg)
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print(response)
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# End the session
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agentops.end_session("Success")
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```
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### Multi-Agent Example
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Check out the example notebook [here](https://github.com/AgentOps-AI/agentops/tree/main/examples/camel_examples/camelai-multi-agent-example.ipynb) to see how to track multi-agent setups.
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<script type="module" src="/scripts/github_stars.js"></script>
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<script type="module" src="/scripts/scroll-img-fadein-animation.js"></script>
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<script type="module" src="/scripts/button_heartbeat_animation.js"></script>
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<script type="css" src="/styles/styles.css"></script>
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<script type="module" src="/scripts/adjust_api_dynamically.js"></script>
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