ChatAimlapi

This page will help you get started with AI/ML API chat models. For detailed documentation of all ChatAimlapi features and configurations, head to the API reference.

AI/ML API provides access to 300+ models (Deepseek, Gemini, ChatGPT, etc.) via high-uptime and high-rate API.

Overview

Integration details

Class	Package	Local	Serializable	JS support	Package downloads	Package latest
ChatAimlapi	langchain-aimlapi	✅	beta	❌

Model features

Tool calling	Structured output	JSON mode	Image input	Audio input	Video input	Token-level streaming	Native async	Token usage	Logprobs
✅	✅	✅	✅	✅	✅	✅	✅	✅	✅

Setup

To access AI/ML API models, sign up at aimlapi.com, generate an API key, and set the AIMLAPI_API_KEY environment variable:

import getpass
import os

if "AIMLAPI_API_KEY" not in os.environ:
    os.environ["AIMLAPI_API_KEY"] = getpass.getpass("Enter your AI/ML API key: ")

Installation

Install the langchain-aimlapi package:

%pip install -qU langchain-aimlapi

Note: you may need to restart the kernel to use updated packages.

Instantiation

Now we can instantiate the ChatAimlapi model and generate chat completions:

from langchain_aimlapi import ChatAimlapi

llm = ChatAimlapi(
    model="meta-llama/Llama-3-70b-chat-hf",
    temperature=0.7,
    max_tokens=512,
    timeout=30,
    max_retries=3,
)

Invocation

You can invoke the model with a list of messages:

messages = [
    ("system", "You are a helpful assistant that translates English to French."),
    ("human", "I love programming."),
]

ai_msg = llm.invoke(messages)
print(ai_msg.content)

J'adore la programmation.

Chaining

We can chain the model with a prompt template as follows:

from langchain_core.prompts import ChatPromptTemplate

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

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

API Reference:ChatPromptTemplate

Ich liebe das Programmieren.

API reference

For detailed documentation of all ChatAimlapi features and configurations, visit the API Reference.

Related

• Chat model conceptual guide
• Chat model how-to guides