agentops/docs/v1/integrations/swarmzero.mdx

---
title: SwarmZero
description: "Build powerful web search agents with SwarmZero and AgentOps monitoring"
---

import CodeTooltip from '/snippets/add-code-tooltip.mdx'
import EnvTooltip from '/snippets/add-env-tooltip.mdx'

AgentOps has first party support for [SwarmZero](https://swarmzero.ai) via its Python SDK. Explore development with SwarmZero by visiting their [docs](https://docs.swarmzero.ai).

## Steps to integrate SwarmZero with AgentOps

<Steps>
  <Step title="Install SwarmZero">
    <CodeGroup>
      ```bash pip 
      pip install swarmzero
      ```
      ```bash poetry
      poetry add swarmzero
      ```
    </CodeGroup>
  </Step>
  <Step title="Install the AgentOps SDK">
    <CodeGroup>
      ```bash pip 
      pip install agentops
      ```
      ```bash poetry
      poetry add agentops
      ```
    </CodeGroup>
  </Step>
  <Step title="Install additional dependencies">
    <CodeGroup>
      ```bash pip
      pip install python-dotenv tavily-python
      ```
      ```bash poetry
      poetry add python-dotenv tavily-python
      ```
    </CodeGroup>
  </Step>
  <Step title="Add AgentOps to your code">
    <CodeTooltip/>
      <CodeGroup>
        ```python python
        import os
        import agentops
        from dotenv import load_dotenv
        from swarmzero import Agent
        from tavily import TavilyClient

        # Load environment variables
        load_dotenv()

        # Initialize clients
        agentops.init(os.getenv("AGENTOPS_API_KEY"))
        tavily_client = TavilyClient(api_key=os.getenv("TAVILY_API_KEY"))

        # Your SwarmZero agent code here...
        ```
      </CodeGroup>
    <EnvTooltip />
      <CodeGroup>
        ```python .env
        AGENTOPS_API_KEY=<YOUR API KEY>
        TAVILY_API_KEY=<YOUR API KEY>
        OPENAI_API_KEY=<YOUR API KEY>
        ```
      </CodeGroup>
      Read more about environment variables in [Advanced Configuration](/v1/usage/advanced-configuration)
  </Step>
  <Step title="Run your Agent">
    Execute your program and visit [app.agentops.ai/drilldown](https://app.agentops.ai/drilldown) to observe your Agent! 🕵️
    <Tip>
      After your run, AgentOps prints a clickable url to console linking directly to your session in the Dashboard
    </Tip>
    <Frame type="glass" caption="Clickable link to session">
      <img height="200" src="https://github.com/AgentOps-AI/agentops/blob/main/docs/images/external/swarmzero/swarmzero_session.png?raw=true" />
    </Frame>
  </Step>
</Steps>

## Full Example

<CodeGroup>
  ```python web_search_agent.py
  import os
  import agentops
  from dotenv import load_dotenv
  from swarmzero import Agent
  from tavily import TavilyClient

  load_dotenv()
  agentops.init(os.getenv("AGENTOPS_API_KEY"))
  tavily_client = TavilyClient(api_key=os.getenv("TAVILY_API_KEY"))

  async def web_search(query: str) -> dict:
      response = tavily_client.search(query)
      results = []
      for result in response["results"][:3]:
          results.append({"title": result["title"], "url": result["url"], "content": result["content"]})
      return results

  async def extract_from_urls(urls: list[str]) -> dict:
      response = tavily_client.extract(urls=urls)

      if response["failed_results"]:
          print(f"Failed to extract from {response['failed_results']}")

      results = []
      for result in response["results"]:
          results.append({"url": result["url"], "raw_content": result["raw_content"]})

      return results

  my_agent = Agent(
      name="workflow-assistant",
      functions=[
          web_search,
          extract_from_urls,
      ],
      config_path="./swarmzero_config.toml", # see https://github.com/swarmzero/swarmzero/blob/main/swarmzero_config_example.toml
      instruction="You are a helpful assistant that can search the web and extract information from a given URL.",
      # chat_only_mode=True  # remove comment only if using `my_agent.chat()`
  )

  my_agent.run()  # see agent API at localhost:8000/docs

  """
  # chat directly without starting the agent's server
  import asyncio
  
  response = asyncio.run(my_agent.chat(prompt="what is Decentralized-AI about about?"))
  print(response)
  """

  ```
</CodeGroup>

### Using the Agent

Once your agent is running, you can interact with it using HTTP requests:

<CodeGroup>
  ```bash curl
  curl -X 'POST' \
    'http://localhost:8000/api/v1/chat' \
    -H 'accept: application/json' \
    -H 'Content-Type: multipart/form-data' \
    -F 'user_id=test_user' \
    -F 'session_id=test_web_search_agent' \
    -F 'chat_data={"messages":[{"role":"user","content":"what is Decentralized-AI about about?"}]}'
  ```
</CodeGroup>

This example can be found in this [notebook](https://github.com/AgentOps-AI/agentops/blob/main/examples/swarmzero_examples/web_search_agent.ipynb)
This full code for this example can be found in this [repository](https://github.com/swarmzero/examples/tree/main/agents/web_search_agent).

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