TrueFoundry Integration ↗

Original Documentation

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 provides an enterprise-ready 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#

    pip install crewai
    ```
  <span class="step-end"></span>

  <span class="step-marker" data-step-title="Get TrueFoundry Access Token"></span>
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)
  <span class="step-end"></span>

  <span class="step-marker" data-step-title="Configure CrewAI with TrueFoundry"></span>
    <img src="https://mintcdn.com/crewai/qVjgZHKAyEOgSSUS/images/new-code-snippet.png?fit=max&auto=format&n=qVjgZHKAyEOgSSUS&q=85&s=746c0bd23a77535f35b0b2bcf3320bf5" alt="TrueFoundry Code Configuration" data-og-width="2940" width="2940" data-og-height="1664" height="1664" data-path="images/new-code-snippet.png" data-optimize="true" data-opv="3" srcset="https://mintcdn.com/crewai/qVjgZHKAyEOgSSUS/images/new-code-snippet.png?w=280&fit=max&auto=format&n=qVjgZHKAyEOgSSUS&q=85&s=1d7f4e8883760766aa1ae1274fba2ffe 280w, https://mintcdn.com/crewai/qVjgZHKAyEOgSSUS/images/new-code-snippet.png?w=560&fit=max&auto=format&n=qVjgZHKAyEOgSSUS&q=85&s=4604432c1e1121d24c3fa6ad93bc0bd9 560w, https://mintcdn.com/crewai/qVjgZHKAyEOgSSUS/images/new-code-snippet.png?w=840&fit=max&auto=format&n=qVjgZHKAyEOgSSUS&q=85&s=8dd95282de37aa70090ac61a00b6e1bb 840w, https://mintcdn.com/crewai/qVjgZHKAyEOgSSUS/images/new-code-snippet.png?w=1100&fit=max&auto=format&n=qVjgZHKAyEOgSSUS&q=85&s=920a67bee38e979c770d775195b60864 1100w, https://mintcdn.com/crewai/qVjgZHKAyEOgSSUS/images/new-code-snippet.png?w=1650&fit=max&auto=format&n=qVjgZHKAyEOgSSUS&q=85&s=4173b6e99ed12b00b54bf3f222589863 1650w, https://mintcdn.com/crewai/qVjgZHKAyEOgSSUS/images/new-code-snippet.png?w=2500&fit=max&auto=format&n=qVjgZHKAyEOgSSUS&q=85&s=176dd84222c8c1a6f40af3e0adb88e37 2500w" />

```python
    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
        )
    ```
  <span class="step-end"></span>
<span class="steps-end"></span>

### Complete CrewAI Example

```python
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: TrueFoundry metrics

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.For tracing, you can add the Traceloop SDK: For tracing, you can add the Traceloop SDK:

pip install traceloop-sdk

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. TrueFoundry CrewAI Tracing

Link last verified June 7, 2026. View original ↗

Source: CrewAI Docs

Link last verified: 2026-03-04