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Our API is compatible with the OpenAI Python SDK for specific endpoints, allowing you to integrate our service with minimal code changes for your tests.

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Installation

Install the OpenAI Python SDK: 
pip install openai

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Configuration

Configure the client to point to our API: 
from openai import OpenAI
client = OpenAI(
    api_key="your-paradigm-api-key",
    base_url="https://paradigm.lighton.ai/api/v2"
)

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Compatible Endpoints

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Chat Completions

Create chat completions using the same interface as OpenAI’s API.
response = client.chat.completions.create(
    model="your-model-name",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"}
    ],
    temperature=0.7,
    max_tokens=150
)

print(response.choices[0].message.content)

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Streaming response

Stream responses for real-time output:
stream = client.chat.completions.create(
    model="your-model-name",
    messages=[{"role": "user", "content": "Tell me a story"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

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Completions

Generate text completions using the legacy completions endpoint.
response = client.completions.create(
    model="your-model-name",
    prompt="Once upon a time",
    max_tokens=100,
    temperature=0.7
)

print(response.choices[0].text)

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Streaming response

stream = client.completions.create(
    model="your-model-name",
    prompt="Write a poem about",
    stream=True
)

for chunk in stream:
    if chunk.choices[0].text:
        print(chunk.choices[0].text, end="")

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Embeddings

Generate embeddings for text:
response = client.embeddings.create(
    model="your-embedding-model",
    input="Text to embed"
)

embedding = response.data[0].embedding
print(embedding)

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List Models

Retrieve a list of all available models.
# List all models
models = client.models.list()

for model in models.data:
    print(f"{model.name}: {model.technical_name=} / {model.model_type}")

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Upload Files

Upload files for use with assistants or other endpoints.
# Upload a file
with open("document.pdf", "rb") as file:
    response = client.files.create(
        file=file,
        purpose="assistants"
    )

file_id = response.id
print(f"File uploaded: {file_id}")
Supported Parameters:
  • file (required) - File object to upload

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List Files

Retrieve a list of all uploaded files.
# List all files
files = client.files.list()

for file in files.data:
    print(f"{file.id}: {file.filename} ({file.bytes} bytes)")

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Retrieve File

Get information about a specific file.
# Get file details
file = client.files.retrieve(file_id="file-abc123")

print(f"Filename: {file.filename}")
print(f"Size: {file.bytes} bytes")
print(f"Created: {file.created_at}")

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Delete File

Delete a file from your account.
# Delete a file
response = client.files.delete("file-abc123")

if response.deleted:
    print("File deleted successfully")

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Differences from OpenAI

While our API maintains compatibility with the OpenAI SDK, note the following differences:
Important Differences:
  • Model names are specific to our platform
  • Some advanced parameters may not be supported
  • Rate limits differ from OpenAI’s limits

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Error Handling

Handle errors using standard try-except blocks: 
from openai import OpenAIError
try:
    response = client.chat.completions.create(
        model="your-model-name",
        messages=[{"role": "user", "content": "Hello"}]
    )
except OpenAIError as e:
    print(f"Error: {e}")

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Migration Guide

To migrate from OpenAI to our API:
  1. Update the base_url parameter in your client configuration
  2. Replace OpenAI model names with our model identifiers
  3. Update your API key to use our platform’s key
  4. Test your implementation with our endpoints
# Before (OpenAI)
client = OpenAI(api_key="sk-...")
# After (LightOn API)
client = OpenAI(
    api_key="your-paradigm-api-key",
    base_url="https://paradigm.lighton.ai/api/v2"
)