> ## Documentation Index
> Fetch the complete documentation index at: https://docs.crewai.com/llms.txt
> Use this file to discover all available pages before exploring further.
# TrueFoundry Integration
TrueFoundry provides an enterprise-ready [AI Gateway](https://www.truefoundry.com/ai-gateway) which can integrate with agentic frameworks like CrewAI and provides governance and observability for your AI Applications. TrueFoundry AI Gateway serves as a unified interface for LLM access, providing:
* **Unified API Access**: Connect to 250+ LLMs (OpenAI, Claude, Gemini, Groq, Mistral) through one API
* **Low Latency**: Sub-3ms internal latency with intelligent routing and load balancing
* **Enterprise Security**: SOC 2, HIPAA, GDPR compliance with RBAC and audit logging
* **Quota and cost management**: Token-based quotas, rate limiting, and comprehensive usage tracking
* **Observability**: Full request/response logging, metrics, and traces with customizable retention
## How TrueFoundry Integrates with CrewAI
### Installation & Setup
```bash theme={null}
pip install crewai
```
1. Sign up for a [TrueFoundry account](https://www.truefoundry.com/register)
2. Follow the steps here in [Quick start](https://docs.truefoundry.com/gateway/quick-start)
```python theme={null}
from crewai import LLM
# Create an LLM instance with TrueFoundry AI Gateway
truefoundry_llm = LLM(
model="openai-main/gpt-4o", # Similarly, you can call any model from any provider
base_url="your_truefoundry_gateway_base_url",
api_key="your_truefoundry_api_key"
)
# Use in your CrewAI agents
from crewai import Agent
@agent
def researcher(self) -> Agent:
return Agent(
config=self.agents_config['researcher'],
llm=truefoundry_llm,
verbose=True
)
```
### Complete CrewAI Example
```python theme={null}
from crewai import Agent, Task, Crew, LLM
# Configure LLM with TrueFoundry
llm = LLM(
model="openai-main/gpt-4o",
base_url="your_truefoundry_gateway_base_url",
api_key="your_truefoundry_api_key"
)
# Create agents
researcher = Agent(
role='Research Analyst',
goal='Conduct detailed market research',
backstory='Expert market analyst with attention to detail',
llm=llm,
verbose=True
)
writer = Agent(
role='Content Writer',
goal='Create comprehensive reports',
backstory='Experienced technical writer',
llm=llm,
verbose=True
)
# Create tasks
research_task = Task(
description='Research AI market trends for 2024',
agent=researcher,
expected_output='Comprehensive research summary'
)
writing_task = Task(
description='Create a market research report',
agent=writer,
expected_output='Well-structured report with insights',
context=[research_task]
)
# Create and execute crew
crew = Crew(
agents=[researcher, writer],
tasks=[research_task, writing_task],
verbose=True
)
result = crew.kickoff()
```
### Observability and Governance
Monitor your CrewAI agents through TrueFoundry's metrics tab:
With Truefoundry's AI gateway, you can monitor and analyze:
* **Performance Metrics**: Track key latency metrics like Request Latency, Time to First Token (TTFS), and Inter-Token Latency (ITL) with P99, P90, and P50 percentiles
* **Cost and Token Usage**: Gain visibility into your application's costs with detailed breakdowns of input/output tokens and the associated expenses for each model
* **Usage Patterns**: Understand how your application is being used with detailed analytics on user activity, model distribution, and team-based usage
* **Rate limit and Load balancing**: You can set up rate limiting, load balancing and fallback for your models
## Tracing
For a more detailed understanding on tracing, please see [getting-started-tracing](https://docs.truefoundry.com/docs/tracing/tracing-getting-started).For tracing, you can add the Traceloop SDK:
For tracing, you can add the Traceloop SDK:
```bash theme={null}
pip install traceloop-sdk
```
```python theme={null}
from traceloop.sdk import Traceloop
# Initialize enhanced tracing
Traceloop.init(
api_endpoint="https://your-truefoundry-endpoint/api/tracing",
headers={
"Authorization": f"Bearer {your_truefoundry_pat_token}",
"TFY-Tracing-Project": "your_project_name",
},
)
```
This provides additional trace correlation across your entire CrewAI workflow.
