Overview
| Property | Details |
|---|---|
| Description | AI/ML API provides access to state-of-the-art AI models including flux-pro/v1.1 for high-quality image generation. |
| Provider Route on LiteLLM | aiml/ |
| Link to Provider Doc | AI/ML API ↗ |
| Supported Operations | [/chat/completions], /images/generations |
LiteLLM supports AI/ML API Image Generation calls.
API Base, Key
# env variable
os.environ['AIML_API_KEY']="your-api-key"
os.environ['AIML_API_BASE']="https://api.aimlapi.com"# [optional]
Getting started with the AI/ML API is simple. Follow these steps to set up your integration:
1. Get Your API Key
To begin, you need an API key. You can obtain yours here:
🔑 Get Your API Key
2. Explore Available Models
Looking for a different model? Browse the full list of supported models:
📚 Full List of Models
3. Read the Documentation
For detailed setup instructions and usage guidelines, check out the official documentation:
📖 AI/ML API Docs
4. Need Help?
If you have any questions, feel free to reach out. We’re happy to assist! 🚀 Discord
Usage
You can choose from LLama, Qwen, Flux, and 200+ other open and closed-source models on aimlapi.com/models. For example:
import litellm
response = litellm.completion(
model="aiml/meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",# The model name must include prefix "openai" + the model name from ai/ml api
api_key="",# your aiml api-key
api_base="https://api.aimlapi.com/v2",
messages=[
{
"role":"user",
"content":"Hey, how's it going?",
}
],
)
Streaming
import litellm
response = litellm.completion(
model="aiml/Qwen/Qwen2-72B-Instruct",# The model name must include prefix "openai" + the model name from ai/ml api
api_key="",# your aiml api-key
api_base="https://api.aimlapi.com/v2",
messages=[
{
"role":"user",
"content":"Hey, how's it going?",
}
],
stream=True,
)
for chunk in response:
print(chunk)
Async Completion
import asyncio
import litellm
asyncdefmain():
response =await litellm.acompletion(
model="aiml/anthropic/claude-3-5-haiku",# The model name must include prefix "openai" + the model name from ai/ml api
api_key="",# your aiml api-key
api_base="https://api.aimlapi.com/v2",
messages=[
{
"role":"user",
"content":"Hey, how's it going?",
}
],
)
print(response)
if __name__ =="__main__":
asyncio.run(main())
Async Streaming
import asyncio
import traceback
import litellm
asyncdefmain():
try:
print("test acompletion + streaming")
response =await litellm.acompletion(
model="aiml/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",# The model name must include prefix "openai" + the model name from ai/ml api
api_key="",# your aiml api-key
api_base="https://api.aimlapi.com/v2",
messages=[{"content":"Hey, how's it going?","role":"user"}],
stream=True,
)
print(f"response: {response}")
asyncfor chunk in response:
print(chunk)
except:
print(f"error occurred: {traceback.format_exc()}")
pass
if __name__ =="__main__":
asyncio.run(main())
Async Embedding
import asyncio
import litellm
asyncdefmain():
response =await litellm.aembedding(
model="aiml/text-embedding-3-small",# The model name must include prefix "openai" + the model name from ai/ml api
api_key="",# your aiml api-key
api_base="https://api.aimlapi.com/v1",# 👈 the URL has changed from v2 to v1
input="Your text string",
)
print(response)
if __name__ =="__main__":
asyncio.run(main())
Async Image Generation
import asyncio
import litellm
asyncdefmain():
response =await litellm.aimage_generation(
model="aiml/dall-e-3",# The model name must include prefix "openai" + the model name from ai/ml api
api_key="",# your aiml api-key
api_base="https://api.aimlapi.com/v1",# 👈 the URL has changed from v2 to v1
prompt="A cute baby sea otter",
)
print(response)
if __name__ =="__main__":
asyncio.run(main())