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Documentation Index

Fetch the complete documentation index at: https://www.getmaxim.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

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Getting Started

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Prerequisites

  • Python version >=3.10
  • A Maxim account (sign up here)
  • Generate Maxim API Key
  • An Agno project

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Installation

Install the Maxim SDK via pip: 
pip install maxim-py
Or add it to your requirements.txt:

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Basic Setup

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1. Set up environment variables

### Environment Variables Setup

# Create a `.env` file in your project root:

# Maxim API Configuration
MAXIM_API_KEY=your_api_key_here
MAXIM_LOG_REPO_ID=your_repo_id_here
OPENAI_API_KEY=your_openai_api_key
# You can also choose another LLM Provider (Gemini, Groq, Anthropic etc.)

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2. Import the required packages

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.googlesearch import GoogleSearchTools
from agno.tools.yfinance import YFinanceTools
from maxim import Maxim
from maxim.logger.agno import instrument_agno

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3. Initialise Maxim with your API key

# Instrument Agno with just one line
instrument_agno(Maxim().logger())

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4. Create and run your Agno application as usual

# Create your agent
researcher = Agent(
    name="Research Agent",
    role="Senior Research Analyst",
    model=OpenAIChat(id="gpt-4o"),
    tools=[GoogleSearchTools()],
    instructions="You are an expert researcher at a tech think tank...",
    show_tool_calls=True,
    markdown=True
)

# Run your agent
response = researcher.run("Research the latest AI advancements...")
print(response.content)
That’s it! All your Agno agent interactions will now be logged and available in your Maxim dashboard. Check this Cookbook for a quick reference - Notebook

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Multi-Agent Example

Here’s how to set up a multi-agent system with Maxim integration: 
# Create individual agents
web_search_agent = Agent(
    name="Web Agent",
    role="Search the web for information",
    model=OpenAIChat(id="gpt-4o"),
    tools=[GoogleSearchTools()],
    instructions="Always include sources",
    show_tool_calls=True,
    markdown=True,
)

finance_agent = Agent(
    name="Finance Agent",
    role="Get financial data",
    model=OpenAIChat(id="gpt-4o"),
    tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)],
    instructions="Use tables to display data",
    markdown=True,
)

# Create multi-agent system
multi_ai_agent = Agent(
    team=[web_search_agent, finance_agent],
    model=OpenAIChat(id="gpt-4o"),
    instructions="You are a helpful financial assistant. Answer user questions about stocks, companies, and financial data.",
    show_tool_calls=True,
    markdown=True
)

# Run the multi-agent system
response = multi_ai_agent.run("What's the current stock price of Apple?")
print(response.content)

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Viewing Your Traces

After running your Agno application:
  1. Log in to your Maxim Dashboard
  2. Navigate to your repository
  3. View detailed agent traces, including:
    • Agent conversations
    • Tool usage patterns
    • Performance metrics
    • Cost analytics
    • Token usage
    • Model information
agno.gif

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Troubleshooting

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Common Issues

  • No traces appearing: Ensure your API key and repository ID are correct
  • Ensure you’ve called instrument_agno() before running your agents. This initializes logging hooks correctly.
  • Set debug=True in your instrument_agno() call to surface any internal errors: 
    instrument_agno(logger, {"debug" : True})
  • Double-check that instrument_agno() is called before creating or executing agents. This might be obvious, but it’s a common oversight.

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Debug Mode

Enable debug mode to see detailed logging information: 
from maxim import Maxim
from maxim.logger.agno import instrument_agno

# Enable debug mode
maxim = Maxim()
instrument_agno(maxim.logger(), {"debug":True})

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Resources

Agno Docs

Official Agno documentation

Maxim Docs

Official Maxim documentation

Maxim Github

Official Maxim GitHub repository