mirror of
https://github.com/deepset-ai/haystack.git
synced 2026-02-06 15:02:30 +00:00
158 lines
6.1 KiB
Plaintext
158 lines
6.1 KiB
Plaintext
---
|
||
title: "OpenRouterChatGenerator"
|
||
id: openrouterchatgenerator
|
||
slug: "/openrouterchatgenerator"
|
||
description: "This component enables chat completion with any model hosted on [OpenRouter](https://openrouter.ai/)."
|
||
---
|
||
|
||
# OpenRouterChatGenerator
|
||
|
||
This component enables chat completion with any model hosted on [OpenRouter](https://openrouter.ai/).
|
||
|
||
<div className="key-value-table">
|
||
|
||
| | |
|
||
| --- | --- |
|
||
| **Most common position in a pipeline** | After a [ChatPromptBuilder](../builders/chatpromptbuilder.mdx) |
|
||
| **Mandatory init variables** | `api_key`: An OpenRouter API key. Can be set with `OPENROUTER_API_KEY` env variable or passed to `init()` method. |
|
||
| **Mandatory run variables** | `messages`: A list of [ChatMessage](../../concepts/data-classes/chatmessage.mdx) objects |
|
||
| **Output variables** | `replies`: A list of [ChatMessage](../../concepts/data-classes/chatmessage.mdx) objects |
|
||
| **API reference** | [OpenRouter](/reference/integrations-openrouter) |
|
||
| **GitHub link** | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/openrouter |
|
||
|
||
</div>
|
||
|
||
## Overview
|
||
|
||
The `OpenRouterChatGenerator` enables you to use models from multiple providers (such as `openai/gpt-4o`, `anthropic/claude-3.5-sonnet`, and others) by making chat completion calls to the [OpenRouter API](https://openrouter.ai/docs/quickstart).
|
||
|
||
This generator also supports OpenRouter-specific features such as:
|
||
|
||
- Provider routing and model fallback that are configurable with the `generation_kwargs` parameter during initialization or runtime.
|
||
- Custom HTTP headers that can be supplied using the `extra_headers` parameter.
|
||
|
||
This component uses the same `ChatMessage` format as other Haystack Chat Generators for structured input and output. For more information, see the [ChatMessage documentation](../../concepts/data-classes/chatmessage.mdx).
|
||
|
||
### Tool Support
|
||
|
||
`OpenRouterChatGenerator` supports function calling through the `tools` parameter, which accepts flexible tool configurations:
|
||
|
||
- **A list of Tool objects**: Pass individual tools as a list
|
||
- **A single Toolset**: Pass an entire Toolset directly
|
||
- **Mixed Tools and Toolsets**: Combine multiple Toolsets with standalone tools in a single list
|
||
|
||
This allows you to organize related tools into logical groups while also including standalone tools as needed.
|
||
|
||
```python
|
||
from haystack.tools import Tool, Toolset
|
||
from haystack_integrations.components.generators.openrouter import OpenRouterChatGenerator
|
||
|
||
# Create individual tools
|
||
weather_tool = Tool(name="weather", description="Get weather info", ...)
|
||
news_tool = Tool(name="news", description="Get latest news", ...)
|
||
|
||
# Group related tools into a toolset
|
||
math_toolset = Toolset([add_tool, subtract_tool, multiply_tool])
|
||
|
||
# Pass mixed tools and toolsets to the generator
|
||
generator = OpenRouterChatGenerator(
|
||
tools=[math_toolset, weather_tool, news_tool] # Mix of Toolset and Tool objects
|
||
)
|
||
```
|
||
|
||
For more details on working with tools, see the [Tool](../../tools/tool.mdx) and [Toolset](../../tools/toolset.mdx) documentation.
|
||
|
||
### Initialization
|
||
|
||
To use this integration, you must have an active OpenRouter subscription with sufficient credits and an API key. You can provide it with the `OPENROUTER_API_KEY` environment variable or by using a [Secret](../../concepts/secret-management.mdx).
|
||
|
||
Then, install the `openrouter-haystack` integration:
|
||
|
||
```shell
|
||
pip install openrouter-haystack
|
||
```
|
||
|
||
### Streaming
|
||
|
||
`OpenRouterChatGenerator` supports [streaming](guides-to-generators/choosing-the-right-generator.mdx#streaming-support) responses from the LLM, allowing tokens to be emitted as they are generated. To enable streaming, pass a callable to the `streaming_callback` parameter during initialization.
|
||
|
||
## Usage
|
||
|
||
### On its own
|
||
|
||
```python
|
||
from haystack.dataclasses import ChatMessage
|
||
from haystack_integrations.components.generators.openrouter import OpenRouterChatGenerator
|
||
|
||
client = OpenRouterChatGenerator()
|
||
response = client.run(
|
||
[ChatMessage.from_user("What are Agentic Pipelines? Be brief.")]
|
||
)
|
||
print(response["replies"][0].text)
|
||
```
|
||
|
||
With streaming and model routing:
|
||
|
||
```python
|
||
from haystack.dataclasses import ChatMessage
|
||
from haystack_integrations.components.generators.openrouter import OpenRouterChatGenerator
|
||
|
||
client = OpenRouterChatGenerator(model="openrouter/auto",
|
||
streaming_callback=lambda chunk: print(chunk.content, end="", flush=True))
|
||
|
||
response = client.run(
|
||
[ChatMessage.from_user("What are Agentic Pipelines? Be brief.")]
|
||
)
|
||
|
||
## check the model used for the response
|
||
print("\n\n Model used: ", response["replies"][0].meta["model"])
|
||
```
|
||
|
||
With multimodal inputs:
|
||
|
||
```python
|
||
from haystack.dataclasses import ChatMessage, ImageContent
|
||
from haystack_integrations.components.generators.openrouter import OpenRouterChatGenerator
|
||
|
||
llm = OpenRouterChatGenerator(model="anthropic/claude-3-5-sonnet")
|
||
|
||
image = ImageContent.from_file_path("apple.jpg")
|
||
user_message = ChatMessage.from_user(content_parts=[
|
||
"What does the image show? Max 5 words.",
|
||
image
|
||
])
|
||
|
||
response = llm.run([user_message])["replies"][0].text
|
||
print(response)
|
||
|
||
# Red apple on straw.
|
||
```
|
||
|
||
### In a pipeline
|
||
|
||
```python
|
||
from haystack import Pipeline
|
||
from haystack.components.builders import ChatPromptBuilder
|
||
from haystack.dataclasses import ChatMessage
|
||
from haystack_integrations.components.generators.openrouter import OpenRouterChatGenerator
|
||
|
||
prompt_builder = ChatPromptBuilder()
|
||
llm = OpenRouterChatGenerator(model="openai/gpt-4o-mini")
|
||
|
||
pipe = Pipeline()
|
||
pipe.add_component("builder", prompt_builder)
|
||
pipe.add_component("llm", llm)
|
||
pipe.connect("builder.prompt", "llm.messages")
|
||
|
||
messages = [
|
||
ChatMessage.from_system("Give brief answers."),
|
||
ChatMessage.from_user("Tell me about {{city}}")
|
||
]
|
||
|
||
response = pipe.run(
|
||
data={"builder": {"template": messages,
|
||
"template_variables": {"city": "Berlin"}}}
|
||
)
|
||
print(response)
|
||
```
|