Direct model access

The LLM Gateway is in beta.

Direct model access exposes each provider API through a provider-specific gateway path. The gateway still handles authentication, provider secrets, policies, and tracing, but it does not translate the request and response into another provider’s API format. Prefer standard model access for model calls across providers. Use direct model access when you want to access a provider’s API directly, preserve its native request and response behavior, and avoid the gateway’s standardization layer.

Choose a provider path

Append a provider path to your regional gateway base URL:

Provider	Gateway path	Secret name
Anthropic	`/anthropic`	`ANTHROPIC_API_KEY`
AWS Bedrock	`/bedrock`	`AWS_BEARER_TOKEN_BEDROCK`
Azure Foundry	`/azure`	`AZURE_FOUNDRY_API_KEY`, `AZURE_FOUNDRY_RESOURCE_NAME`
Baseten	`/baseten`	`BASETEN_API_KEY`
Fireworks	`/fireworks`	`FIREWORKS_API_KEY`
Google Gemini	`/gemini`	`GOOGLE_API_KEY`
Gemini Enterprise Agent Platform	`/vertex`	`VERTEX_SERVICE_ACCOUNT_JSON`
OpenAI	`/openai`	`OPENAI_API_KEY`

Gateway Credits models use the standard endpoint rather than a provider-specific path. These hosted models require no provider secret of your own.

Configure provider SDKs

Set each provider SDK’s base URL to its direct gateway path and use your LangSmith API key as the provider API key:

export LANGSMITH_API_KEY="lsv2_..._....cbed3e"
export BASE_URL="https://gateway.smith.langchain.com"

export ANTHROPIC_BASE_URL="$BASE_URL/anthropic"
export OPENAI_BASE_URL="$BASE_URL/openai/v1"
export GOOGLE_GEMINI_BASE_URL="$BASE_URL/gemini"

export ANTHROPIC_API_KEY="$LANGSMITH_API_KEY"
export OPENAI_API_KEY="$LANGSMITH_API_KEY"
export GEMINI_API_KEY="$LANGSMITH_API_KEY"
export GOOGLE_API_KEY="$LANGSMITH_API_KEY"

The gateway resolves the actual provider key from your workspace’s Provider Secrets, so the provider key does not need to be stored locally.

import os

from openai import OpenAI

client = OpenAI(
    base_url=os.environ["OPENAI_BASE_URL"],
    api_key=os.environ["LANGSMITH_API_KEY"],
)
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "ping"}],
)
print(response.choices[0].message.content)

import os

import anthropic

client = anthropic.Anthropic(
    base_url=os.environ["ANTHROPIC_BASE_URL"],
    api_key=os.environ["LANGSMITH_API_KEY"],
)
message = client.messages.create(
    model="claude-opus-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "ping"}],
)
print(message.content[0].text)

Direct paths use the provider’s native model name without a provider prefix.

Configure LangChain and Deep Agents

LangChain chat models and Deep Agents, including Deep Agents Code, reach these provider paths through the LANGSMITH_GATEWAY environment variable:

export LANGSMITH_API_KEY="lsv2_..."
export LANGSMITH_GATEWAY="true"

Each supported integration appends its own provider path, so ChatAnthropic calls https://gateway.smith.langchain.com/anthropic and ChatOpenAI calls https://gateway.smith.langchain.com/openai/v1. To route requests through the standard endpoint instead, see the LLM Gateway quickstart.

Use a regional gateway

If your LangSmith account is on a regional instance, use the corresponding regional gateway and append the provider path. For example, use https://eu.gateway.smith.langchain.com/anthropic for direct Anthropic access in GCP EU.

Core capabilities

Administration and governance

Advanced

Choose a provider path

Configure provider SDKs

Configure LangChain and Deep Agents

Use a regional gateway

See also

​Choose a provider path

​Configure provider SDKs

​Configure LangChain and Deep Agents

​Use a regional gateway

​See also

Choose a provider path

Configure provider SDKs

Configure LangChain and Deep Agents

Use a regional gateway

See also