Lambda AI | liteLLM (original) (raw)

Overview​

https://docs.lambda.ai/api

We support ALL Lambda AI models, just set lambda_ai/ as a prefix when sending completion requests

Available Models​

Lambda AI offers a diverse selection of state-of-the-art open-source models:

Large Language Models​

DeepSeek Models​

Hermes Models​

Coding Models​

Vision Models​

Specialized Models​

Required Variables​

Environment Variables

os.environ["LAMBDA_API_KEY"] = ""  # your Lambda AI API key

Usage - LiteLLM Python SDK​

Non-streaming​

Lambda AI Non-streaming Completion

import os
import litellm
from litellm import completion

os.environ["LAMBDA_API_KEY"] = ""  # your Lambda AI API key

messages = [{"content": "Hello, how are you?", "role": "user"}]

# Lambda AI call
response = completion(
    model="lambda_ai/llama3.1-8b-instruct", 
    messages=messages
)

print(response)

Streaming​

Lambda AI Streaming Completion

import os
import litellm
from litellm import completion

os.environ["LAMBDA_API_KEY"] = ""  # your Lambda AI API key

messages = [{"content": "Write a short story about AI", "role": "user"}]

# Lambda AI call with streaming
response = completion(
    model="lambda_ai/llama3.1-70b-instruct-fp8", 
    messages=messages,
    stream=True
)

for chunk in response:
    print(chunk)

Vision/Multimodal Support​

The Llama 3.2 Vision model supports image inputs:

Lambda AI Vision/Multimodal

import os
import litellm
from litellm import completion

os.environ["LAMBDA_API_KEY"] = ""  # your Lambda AI API key

messages = [{
    "role": "user",
    "content": [
        {
            "type": "text",
            "text": "What's in this image?"
        },
        {
            "type": "image_url",
            "image_url": {
                "url": "https://example.com/image.jpg"
            }
        }
    ]
}]

# Lambda AI vision model call
response = completion(
    model="lambda_ai/llama3.2-11b-vision-instruct",
    messages=messages
)

print(response)

Function Calling​

Lambda AI models support function calling:

Lambda AI Function Calling

import os
import litellm
from litellm import completion

os.environ["LAMBDA_API_KEY"] = ""  # your Lambda AI API key

# Define tools
tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Get the current weather in a location",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {
                    "type": "string",
                    "description": "The city and state, e.g. San Francisco, CA"
                }
            },
            "required": ["location"]
        }
    }
}]

messages = [{"role": "user", "content": "What's the weather in Boston?"}]

# Lambda AI call with function calling
response = completion(
    model="lambda_ai/hermes3-70b",
    messages=messages,
    tools=tools,
    tool_choice="auto"
)

print(response)

Usage - LiteLLM Proxy Server​

config.yaml

model_list:
  - model_name: llama-8b
    litellm_params:
      model: lambda_ai/llama3.1-8b-instruct
      api_key: os.environ/LAMBDA_API_KEY
  - model_name: deepseek-70b
    litellm_params:
      model: lambda_ai/deepseek-llama3.3-70b
      api_key: os.environ/LAMBDA_API_KEY
  - model_name: hermes-405b
    litellm_params:
      model: lambda_ai/hermes3-405b
      api_key: os.environ/LAMBDA_API_KEY
  - model_name: qwen-coder
    litellm_params:
      model: lambda_ai/qwen25-coder-32b-instruct
      api_key: os.environ/LAMBDA_API_KEY

Custom API Base​

If you need to use a custom API base URL:

Custom API Base

import os
import litellm
from litellm import completion

# Using environment variable
os.environ["LAMBDA_API_BASE"] = "https://custom.lambda-api.com/v1"
os.environ["LAMBDA_API_KEY"] = ""  # your API key

# Or pass directly
response = completion(
    model="lambda_ai/llama3.1-8b-instruct",
    messages=[{"content": "Hello!", "role": "user"}],
    api_base="https://custom.lambda-api.com/v1",
    api_key="your-api-key"
)

Supported OpenAI Parameters​

Lambda AI supports all standard OpenAI parameters since it's fully OpenAI-compatible:

• temperature
• max_tokens
• top_p
• frequency_penalty
• presence_penalty
• stop
• n
• stream
• tools
• tool_choice
• response_format
• seed
• user
• logit_bias

Example with parameters:

Lambda AI with Parameters

response = completion(
    model="lambda_ai/hermes3-405b",
    messages=[{"content": "Explain quantum computing", "role": "user"}],
    temperature=0.7,
    max_tokens=500,
    top_p=0.9,
    frequency_penalty=0.2,
    presence_penalty=0.1
)