Passthrough

Forward provider-native requests through Bifrost with full core pipeline processing, including logs and observability.

Overview

Passthrough integrations let you call provider-native API paths and payloads through Bifrost without route-level request/response conversion.

When you use passthrough endpoints, the request still flows through Bifrost core logic. You keep Bifrost features such as logging and observability while sending provider-native paths and bodies.

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Endpoints

• /openai_passthrough Default provider: openai
• /anthropic_passthrough Default provider: anthropic
• /azure_passthrough Default provider: azure
• /genai_passthrough Default provider: gemini (with automatic Vertex detection for clients configured to use Vertex)

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How It Works

1. Send your request to a passthrough endpoint (OpenAI, Anthropic, Azure, or GenAI passthrough).
2. The integration strips the passthrough prefix and forwards the remaining provider-native path/body.
3. Bifrost handles provider execution through core inference and plugin pipelines.
4. Response status, headers, and body are returned as passthrough output (for both stream and non-stream requests).

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Provider Selection Rules

OpenAI Passthrough

• Uses openai as the default provider.

Anthropic Passthrough

• Uses anthropic as the default provider.

Azure Passthrough

• Uses azure as the default provider.
• Requires an Azure key with endpoint configured.
• api-version handling varies by route:
  • /openai/deployments/ routes: if the caller omits api-version, Bifrost injects a default (2025-04-01-preview). Pass your own api-version to override — for example, to pin to a GA version or use a specific preview version.

GenAI Passthrough

• Uses gemini by default.
• Automatically switches to vertex when Vertex patterns are detected, such as:
  • URL path containing /projects/{PROJECT_ID}/locations/{LOCATION}/
  • Request body model containing a Vertex resource path
  • OAuth token pattern typically used for Vertex (Bearer ya29...)

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Usage Examples

OpenAI Passthrough

Python SDK

import openai

client = openai.OpenAI(
    base_url="http://localhost:8080/openai_passthrough/v1",
    api_key="dummy-key"
)

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "hello from passthrough"}]
)

print(response.choices[0].message.content)

cURL

curl -X POST "http://localhost:8080/openai_passthrough/v1/chat/completions" \
  -H "content-type: application/json" \
  -H "authorization: Bearer sk-your-openai-key" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role":"user","content":"hello from passthrough"}]
  }'

Anthropic Passthrough

Python SDK

import anthropic

client = anthropic.Anthropic(
    base_url="http://localhost:8080/anthropic_passthrough",
    api_key="dummy-key"
)

response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "hello from passthrough"}]
)

print(response.content[0].text)

cURL

curl -X POST "http://localhost:8080/anthropic_passthrough/v1/messages" \
  -H "content-type: application/json" \
  -H "x-api-key: your-anthropic-key" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-sonnet-4-20250514",
    "max_tokens": 1024,
    "messages": [{"role":"user","content":"hello from passthrough"}]
  }'

Azure Passthrough

Azure OpenAI SDK

from openai import AzureOpenAI

client = AzureOpenAI(
    azure_endpoint="http://localhost:8080/azure_passthrough",
    api_key="dummy-key",
    api_version="2024-10-21",  # passed through as-is in the query string
)

response = client.chat.completions.create(
    model="gpt-4o",  # your Azure deployment name
    messages=[{"role": "user", "content": "hello from azure passthrough"}]
)

print(response.choices[0].message.content)

OpenAI SDK

from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:8080/azure_passthrough/openai/v1/",
    api_key="dummy-key",
)

response = client.responses.create(
    model="gpt-4.1",  # your Azure deployment name
    input="hello from azure passthrough",
)

print(response.output_text)

Anthropic SDK (Anthropic on Azure)

import anthropic

client = anthropic.Anthropic(
    base_url="http://localhost:8080/azure_passthrough",
    api_key="dummy-key",
)

response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "hello from azure passthrough"}]
)

print(response.content[0].text)

cURL

curl -X POST "http://localhost:8080/azure_passthrough/openai/deployments/gpt-4o/chat/completions?api-version=2025-04-01-preview" \
  -H "content-type: application/json" \
  -d '{
    "messages": [{"role": "user", "content": "hello from azure passthrough"}]
  }'

GenAI Passthrough (Gemini)

Python SDK

from google import genai
from google.genai.types import HttpOptions

client = genai.Client(
    api_key="dummy-key",
    http_options=HttpOptions(base_url="http://localhost:8080/genai_passthrough")
)

response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents="hello from passthrough"
)

print(response.text)

cURL

curl -X POST "http://localhost:8080/genai_passthrough/v1beta/models/gemini-2.5-flash:generateContent" \
  -H "content-type: application/json" \
  -H "x-goog-api-key: your-gemini-key" \
  -d '{
    "contents":[{"parts":[{"text":"hello from passthrough"}]}]
  }'

GenAI Passthrough (Vertex-style request)

Python SDK

from google import genai
from google.genai.types import HttpOptions

client = genai.Client(
    vertexai=True,
    api_key="dummy-key",
    http_options=HttpOptions(base_url="http://localhost:8080/genai_passthrough")
)

response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents="hello from vertex passthrough"
)

print(response.text)

cURL

curl -X POST "http://localhost:8080/genai_passthrough/v1/projects/my-project/locations/us-central1/publishers/google/models/gemini-2.5-flash:generateContent" \
  -H "content-type: application/json" \
  -H "authorization: Bearer ya29.your-vertex-token" \
  -d '{
    "contents":[{"parts":[{"text":"hello from vertex passthrough"}]}]
  }'

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Notes

• Use passthrough when you need a provider endpoint that is not directly supported by Bifrost integration routes yet.
• For Azure passthrough, auth headers (api-key, x-api-key, OAuth token) are always sourced from the Bifrost key config and never forwarded from the client request.
• For Azure /openai/deployments/ routes, Bifrost injects api-version=2025-04-01-preview when the caller does not supply one. Supply your own api-version query parameter to use a different version (e.g. 2024-10-21 for the latest GA, or a newer preview).