---
title: "Passthrough"
description: "Forward provider-native requests through Bifrost with full core pipeline processing, including logs and observability."
icon: "route"
---

## 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.

---

## 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)

---

## 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).

---

## 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` is injected automatically:
  - **Key config `api_version`** takes priority (consistent with how auth is handled).
  - Falls back to any `api-version` the client supplied in the query string.

### 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...`)

---

## Usage Examples

### OpenAI Passthrough

<Tabs group="openai-passthrough">
<Tab title="Python SDK">

```python
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)
```

</Tab>
<Tab title="cURL">

```bash
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"}]
  }'
```

</Tab>
</Tabs>

### Anthropic Passthrough

<Tabs group="anthropic-passthrough">
<Tab title="Python SDK">

```python
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)
```

</Tab>
<Tab title="cURL">

```bash
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"}]
  }'
```

</Tab>
</Tabs>

### Azure Passthrough

<Tabs group="azure-passthrough">
<Tab title="Azure OpenAI SDK">

```python
from openai import AzureOpenAI

client = AzureOpenAI(
    azure_endpoint="http://localhost:8080/azure_passthrough",
    api_key="dummy-key",
    api_version="2024-10-21",  # overridden by key config api_version if set
)

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)
```

</Tab>
<Tab title="OpenAI SDK">

```python
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)
```

</Tab>
<Tab title="Anthropic SDK (Anthropic on Azure)">

```python
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)
```

</Tab>
<Tab title="cURL">

```bash
curl -X POST "http://localhost:8080/azure_passthrough/openai/deployments/gpt-4o/chat/completions" \
  -H "content-type: application/json" \
  -d '{
    "messages": [{"role": "user", "content": "hello from azure passthrough"}]
  }'
```

</Tab>
</Tabs>

### GenAI Passthrough (Gemini)

<Tabs group="genai-passthrough">
<Tab title="Python SDK">

```python
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)
```

</Tab>
<Tab title="cURL">

```bash
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"}]}]
  }'
```

</Tab>
</Tabs>

### GenAI Passthrough (Vertex-style request)

<Tabs group="vertex-passthrough">
<Tab title="Python SDK">

```python
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)
```

</Tab>
<Tab title="cURL">

```bash
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"}]}]
  }'
```

</Tab>
</Tabs>

---

## 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.
