Python Integration
MakeHub offers full compatibility with the OpenAI API, allowing you to easily use our services with your existing Python applications.
Installation
pip install openaiConfiguration
from openai import OpenAI
# Initialize the client with the MakeHub endpoint
client = OpenAI(
api_key="YOUR_MAKEHUB_API_KEY", # Replace with your MakeHub API key
base_url="https://api.makehub.ai/v1" # MakeHub endpoint
)
# Example completion request
response = client.chat.completions.create(
model="meta/llama-3-70b-instruct", # Model available on MakeHub
messages=[
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "Explain how machine learning works in simple terms."}
]
)
# Display the response
print(response.choices[0].message.content)Streaming
from openai import OpenAI
# Initialize the client with the MakeHub endpoint
client = OpenAI(
api_key="YOUR_MAKEHUB_API_KEY",
base_url="https://api.makehub.ai/v1"
)
# Example streaming request
stream = client.chat.completions.create(
model="meta/llama-3-70b-instruct",
messages=[
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "Write a short poem about artificial intelligence."}
],
stream=True
)
# Display the response as it arrives
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="", flush=True)
print()Function Calling
from openai import OpenAI
# Initialize the client with the MakeHub endpoint
client = OpenAI(
api_key="YOUR_MAKEHUB_API_KEY",
base_url="https://api.makehub.ai/v1"
)
# Define available tools
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather for a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and country, e.g. 'Paris, France'"
}
},
"required": ["location"]
}
}
}
]
# Example request with function calling
response = client.chat.completions.create(
model="openai/gpt-4o", # A model supporting function calling
messages=[
{"role": "user", "content": "What's the weather like in Paris today?"}
],
tools=tools
)
# Display the response
print(response.choices[0].message.content)
print(response.choices[0].message.tool_calls)