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Author SHA1 Message Date
Lucas Gomide
b9f852880e Merge branch 'main' into lg-upgrade-litellm 2025-06-09 09:33:21 -03:00
Akshit Madan
b0d89698fd docs: added Maxim support for Agent Observability (#2861)
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* docs: added Maxim support for Agent Observability

* enhanced the maxim integration doc page as per the github PR reviewer bot suggestions

* Update maxim-observability.mdx

* Update maxim-observability.mdx

- Fixed Python version, >=3.10
- added expected_output field in Task
- Removed marketing links and added github link

* added maxim in observability

---------

Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
2025-06-08 13:39:01 -04:00
Tony Kipkemboi
6a66f3de7f Merge branch 'main' into lg-upgrade-litellm 2025-06-06 13:07:18 -04:00
Lucas Gomide
482d9d084d Merge branch 'main' into lg-upgrade-litellm 2025-06-06 11:04:20 -03:00
Lucas Gomide
785f87adf5 Merge branch 'main' into lg-upgrade-litellm 2025-06-05 12:50:46 -03:00
Lucas Gomide
9da26bc341 Merge branch 'main' into lg-upgrade-litellm 2025-06-05 10:54:42 -03:00
Lucas Gomide
788768a6b2 build: upgrade LiteLLM to support latest Openai version 2025-06-05 09:27:09 -03:00
4 changed files with 161 additions and 8 deletions

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@@ -201,6 +201,7 @@
"observability/arize-phoenix",
"observability/langfuse",
"observability/langtrace",
"observability/maxim",
"observability/mlflow",
"observability/openlit",
"observability/opik",

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@@ -0,0 +1,152 @@
---
title: Maxim Integration
description: Start Agent monitoring, evaluation, and observability
icon: bars-staggered
---
# Maxim Integration
Maxim AI provides comprehensive agent monitoring, evaluation, and observability for your CrewAI applications. With Maxim's one-line integration, you can easily trace and analyse agent interactions, performance metrics, and more.
## Features: One Line Integration
- **End-to-End Agent Tracing**: Monitor the complete lifecycle of your agents
- **Performance Analytics**: Track latency, tokens consumed, and costs
- **Hyperparameter Monitoring**: View the configuration details of your agent runs
- **Tool Call Tracking**: Observe when and how agents use their tools
- **Advanced Visualisation**: Understand agent trajectories through intuitive dashboards
## Getting Started
### Prerequisites
- Python version >=3.10
- A Maxim account ([sign up here](https://getmaxim.ai/))
- A CrewAI project
### Installation
Install the Maxim SDK via pip:
```python
pip install maxim-py>=3.6.2
```
Or add it to your `requirements.txt`:
```
maxim-py>=3.6.2
```
### Basic Setup
### 1. Set up environment variables
```python
### 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
```
### 2. Import the required packages
```python
from crewai import Agent, Task, Crew, Process
from maxim import Maxim
from maxim.logger.crewai import instrument_crewai
```
### 3. Initialise Maxim with your API key
```python
# Initialize Maxim logger
logger = Maxim().logger()
# Instrument CrewAI with just one line
instrument_crewai(logger)
```
### 4. Create and run your CrewAI application as usual
```python
# Create your agent
researcher = Agent(
role='Senior Research Analyst',
goal='Uncover cutting-edge developments in AI',
backstory="You are an expert researcher at a tech think tank...",
verbose=True,
llm=llm
)
# Define the task
research_task = Task(
description="Research the latest AI advancements...",
expected_output="",
agent=researcher
)
# Configure and run the crew
crew = Crew(
agents=[researcher],
tasks=[research_task],
verbose=True
)
try:
result = crew.kickoff()
finally:
maxim.cleanup() # Ensure cleanup happens even if errors occur
```
That's it! All your CrewAI agent interactions will now be logged and available in your Maxim dashboard.
Check this Google Colab Notebook for a quick reference - [Notebook](https://colab.research.google.com/drive/1ZKIZWsmgQQ46n8TH9zLsT1negKkJA6K8?usp=sharing)
## Viewing Your Traces
After running your CrewAI application:
![Example trace in Maxim showing agent interactions](https://raw.githubusercontent.com/maximhq/maxim-docs/master/images/Screenshot2025-05-14at12.10.58PM.png)
1. Log in to your [Maxim Dashboard](https://getmaxim.ai/dashboard)
2. Navigate to your repository
3. View detailed agent traces, including:
- Agent conversations
- Tool usage patterns
- Performance metrics
- Cost analytics
## Troubleshooting
### Common Issues
- **No traces appearing**: Ensure your API key and repository ID are correc
- Ensure you've **called `instrument_crewai()`** ***before*** running your crew. This initializes logging hooks correctly.
- Set `debug=True` in your `instrument_crewai()` call to surface any internal errors:
```python
instrument_crewai(logger, debug=True)
```
- Configure your agents with `verbose=True` to capture detailed logs:
```python
agent = CrewAgent(..., verbose=True)
```
- Double-check that `instrument_crewai()` is called **before** creating or executing agents. This might be obvious, but it's a common oversight.
### Support
If you encounter any issues:
- Check the [Maxim Documentation](https://getmaxim.ai/docs)
- Maxim Github [Link](https://github.com/maximhq)

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@@ -11,7 +11,7 @@ dependencies = [
# Core Dependencies
"pydantic>=2.4.2",
"openai>=1.13.3",
"litellm==1.68.0",
"litellm==1.72.0",
"instructor>=1.3.3",
# Text Processing
"pdfplumber>=0.11.4",

14
uv.lock generated
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@@ -820,7 +820,7 @@ requires-dist = [
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