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Documentation Index

Fetch the complete documentation index at: https://langchain.idochub.dev/llms.txt

Use this file to discover all available pages before exploring further.

This will help you get started with ChatAbso chat models. For detailed documentation of all ChatAbso features and configurations, head to the API reference.
  • You can find the full documentation for the Abso router [here] (abso.ai)

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Overview

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Integration details

ClassPackageLocalSerializableJS supportDownloadsVersion
ChatAbsolangchain-abso❌❌❌PyPI - DownloadsPyPI - Version

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Setup

To access ChatAbso models, you’ll need to create an OpenAI account, get an API key, and install the langchain-abso integration package.

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Credentials

  • TODO: Update with relevant info.
Head to (TODO: link) to sign up for ChatAbso and generate an API key. Once you’ve done this, set the ABSO_API_KEY environment variable: 
import getpass
import os

if not os.getenv("OPENAI_API_KEY"):
    os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter your OpenAI API key: ")

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Installation

The LangChain ChatAbso integration lives in the langchain-abso package: 
%pip install -qU langchain-abso

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Instantiation

Now we can instantiate our model object and generate chat completions: 
from langchain_abso import ChatAbso

llm = ChatAbso(fast_model="gpt-4o", slow_model="o3-mini")

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Invocation

messages = [
    (
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ),
    ("human", "I love programming."),
]
ai_msg = llm.invoke(messages)
ai_msg

print(ai_msg.content)

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Chaining

We can chain our model with a prompt template like so: 
from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate(
    [
        (
            "system",
            "You are a helpful assistant that translates {input_language} to {output_language}.",
        ),
        ("human", "{input}"),
    ]
)

chain = prompt | llm
chain.invoke(
    {
        "input_language": "English",
        "output_language": "German",
        "input": "I love programming.",
    }
)

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API reference

For detailed documentation of all ChatAbso features and configurations head to the API reference: python.langchain.com/api_reference/en/latest/chat_models/langchain_abso.chat_models.ChatAbso.html