SmolAgents integration

AI Gateway

Route your LLM calls through the AI Gateway with a single base URL change. Zero vendor lock-in: always run on the best model at the lowest cost for your use case.

Observability

Instrument your code with OpenTelemetry to capture traces, logs, and metrics for every LLM call, agent step, and tool use.

AI Gateway

Overview

SmolAgents is a lightweight Python agent framework by Hugging Face. Using OpenAIServerModel with a custom api_base, you can route all LLM calls through Orq.ai’s AI Gateway for access to 300+ models, cost tracking, and reliability features.

Prerequisites

An Orq.ai account and API Key
Python 3.9 or higher

To setup your API key, see API keys & Endpoints.

Installation

pip install smolagents

Configuration

Python

import os
from smolagents import OpenAIServerModel

model = OpenAIServerModel(
    model_id="openai/gpt-4o",
    api_base="https://api.orq.ai/v3/router",
    api_key=os.environ["ORQ_API_KEY"],
)

api_base: https://api.orq.ai/v3/router

Basic Agent Example

Python

import os
from smolagents import CodeAgent, OpenAIServerModel

model = OpenAIServerModel(
    model_id="openai/gpt-4o-mini",
    api_base="https://api.orq.ai/v3/router",
    api_key=os.environ["ORQ_API_KEY"],
)

agent = CodeAgent(tools=[], model=model)
agent.run("What is the capital of France?")

Model Selection

With Orq.ai, you can use any supported model from 20+ providers:

Python

import os
from smolagents import OpenAIServerModel

# Use Claude
claude_model = OpenAIServerModel(
    model_id="anthropic/claude-sonnet-4-5-20250929",
    api_base="https://api.orq.ai/v3/router",
    api_key=os.environ["ORQ_API_KEY"],
)

# Use Gemini
gemini_model = OpenAIServerModel(
    model_id="google/gemini-2.5-flash",
    api_base="https://api.orq.ai/v3/router",
    api_key=os.environ["ORQ_API_KEY"],
)

# Use Groq
groq_model = OpenAIServerModel(
    model_id="groq/llama-3.3-70b-versatile",
    api_base="https://api.orq.ai/v3/router",
    api_key=os.environ["ORQ_API_KEY"],
)

Observability

Overview

SmolAgents uses the openinference-instrumentation-smolagents library to automatically instrument agent runs and export traces via OpenTelemetry.

Prerequisites

An Orq.ai account and API Key
Python 3.9 or higher

Installation

pip install smolagents \
    opentelemetry-api \
    opentelemetry-sdk \
    "opentelemetry-exporter-otlp-proto-http" \
    openinference-instrumentation-smolagents

Configuring Orq.ai Observability

Set up the tracer provider and instrument SmolAgents before creating any agents:

import os
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from openinference.instrumentation.smolagents import SmolagentsInstrumentor

exporter = OTLPSpanExporter(
    endpoint="https://api.orq.ai/v2/otel/v1/traces",
    headers={"Authorization": f"Bearer {os.environ['ORQ_API_KEY']}"},
)
tracer_provider = TracerProvider()
tracer_provider.add_span_processor(BatchSpanProcessor(exporter))

SmolagentsInstrumentor().instrument(tracer_provider=tracer_provider)

SmolagentsInstrumentor must be called before any agent is instantiated. Once instrumented, all CodeAgent and ToolCallingAgent runs are automatically traced.

Basic Example

import os
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from openinference.instrumentation.smolagents import SmolagentsInstrumentor

exporter = OTLPSpanExporter(
    endpoint="https://api.orq.ai/v2/otel/v1/traces",
    headers={"Authorization": f"Bearer {os.environ['ORQ_API_KEY']}"},
)
tracer_provider = TracerProvider()
tracer_provider.add_span_processor(BatchSpanProcessor(exporter))
SmolagentsInstrumentor().instrument(tracer_provider=tracer_provider)

from smolagents import CodeAgent, OpenAIServerModel

agent = CodeAgent(
    tools=[],
    model=OpenAIServerModel(
        model_id="openai/gpt-4o-mini",
        api_base="https://api.orq.ai/v3/router",
        api_key=os.environ["ORQ_API_KEY"],
    ),
)
agent.run("What is the capital of France?")

Evaluations & Experiments

Once your agents are running, use Evaluatorq to score outputs across a dataset and Experiments to compare configurations side-by-side.

Run Evaluations with Evaluatorq

Run parallel evaluations across your agents and compare results.

Run Experiments via the API

Compare agent configurations and view results in the AI Studio.

AI Providers

Coding Assistants

Frameworks

Automations

AI Gateway

Observability

AI Gateway

Overview

Prerequisites

Installation

Configuration

Basic Agent Example

Model Selection

Observability

Overview

Prerequisites

Installation

Configuring Orq.ai Observability

Basic Example

Evaluations & Experiments

Run Evaluations with Evaluatorq

Run Experiments via the API

AI Gateway

Observability

​AI Gateway

​Overview

​Prerequisites

​Installation

​Configuration

​Basic Agent Example

​Model Selection

​Observability

​Overview

​Prerequisites

​Installation

​Configuring Orq.ai Observability

​Basic Example

​Evaluations & Experiments

Run Evaluations with Evaluatorq

Run Experiments via the API

AI Gateway

Overview

Prerequisites

Installation

Configuration

Basic Agent Example

Model Selection

Observability

Overview

Prerequisites

Installation

Configuring Orq.ai Observability

Basic Example

Evaluations & Experiments