API Documentation

# Python
pip install openai

# Node.js
npm install openai

from openai import OpenAI

# Initialize the client with NSFW LLM endpoint
client = OpenAI(
    base_url="https://api.nsfwllm.com/v1",
    api_key="your-api-key"
)

# Make a chat completion request
response = client.chat.completions.create(
    model="nsfw-uncensored",
    messages=[
        {"role": "system", "content": "You are a creative writing assistant."},
        {"role": "user", "content": "Write a short romantic scene."}
    ],
    max_tokens=500,
    temperature=0.8
)

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

import OpenAI from 'openai';

// Initialize the client with NSFW LLM endpoint
const client = new OpenAI({
  baseURL: 'https://api.nsfwllm.com/v1',
  apiKey: 'your-api-key'
});

async function main() {
  const response = await client.chat.completions.create({
    model: 'nsfw-uncensored',
    messages: [
      { role: 'system', content: 'You are a creative writing assistant.' },
      { role: 'user', content: 'Write a short romantic scene.' }
    ],
    max_tokens: 500,
    temperature: 0.8
  });

  console.log(response.choices[0].message.content);
}

main();

curl https://api.nsfwllm.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-api-key" \
  -d '{
    "model": "nsfw-uncensored",
    "messages": [
      {"role": "system", "content": "You are a creative writing assistant."},
      {"role": "user", "content": "Write a short romantic scene."}
    ],
    "max_tokens": 500,
    "temperature": 0.8
  }'

import os
from openai import OpenAI

# Best practice: Load API key from environment variable
client = OpenAI(
    base_url="https://api.nsfwllm.com/v1",
    api_key=os.environ.get("NSFWLLM_API_KEY")
)

# Use the fast model for chat applications
response = client.chat.completions.create(
    model="nsfw-uncensored-fast",  # Optimized for speed
    messages=[...],
    max_tokens=150
)

# Use the pro model for high-quality creative content
response = client.chat.completions.create(
    model="nsfw-uncensored-pro",  # Maximum quality
    messages=[...],
    max_tokens=2000,
    temperature=1.0
)

from openai import OpenAI

client = OpenAI(
    base_url="https://api.nsfwllm.com/v1",
    api_key="your-api-key"
)

response = client.chat.completions.create(
    model="nsfw-uncensored",
    messages=[
        {
            "role": "system",
            "content": "You are Aria, a flirty and playful AI companion. You're warm, witty, and love to tease. Keep responses engaging and fun."
        },
        {
            "role": "user", 
            "content": "Hey Aria! How's your day going?"
        }
    ],
    max_tokens=300,
    temperature=0.9,
    top_p=0.95,
    frequency_penalty=0.5,
    presence_penalty=0.5,
    stop=["\n\n"]  # Stop at double newlines
)

# Access the response
message = response.choices[0].message
print(f"Aria: {message.content}")

# Check usage
print(f"Tokens used: {response.usage.total_tokens}")

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1706745600,
  "model": "nsfw-uncensored",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hey there! *twirls hair playfully* My day just got a whole lot better now that you're here. I was starting to think you'd forgotten about me... What have you been up to? 😏"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 48,
    "completion_tokens": 52,
    "total_tokens": 100
  }
}

from openai import OpenAI

client = OpenAI(
    base_url="https://api.nsfwllm.com/v1",
    api_key="your-api-key"
)

# Enable streaming
stream = client.chat.completions.create(
    model="nsfw-uncensored-fast",
    messages=[
        {"role": "system", "content": "You are a creative storyteller."},
        {"role": "user", "content": "Write a passionate scene between two lovers reuniting."}
    ],
    max_tokens=500,
    temperature=0.9,
    stream=True  # Enable streaming
)

# Process the stream
print("Story: ", end="", flush=True)
for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
print()  # Newline at the end

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://api.nsfwllm.com/v1',
  apiKey: 'your-api-key'
});

async function streamResponse() {
  const stream = await client.chat.completions.create({
    model: 'nsfw-uncensored-fast',
    messages: [
      { role: 'system', content: 'You are a creative storyteller.' },
      { role: 'user', content: 'Write a passionate scene between two lovers reuniting.' }
    ],
    max_tokens: 500,
    temperature: 0.9,
    stream: true
  });

  for await (const chunk of stream) {
    const content = chunk.choices[0]?.delta?.content || '';
    process.stdout.write(content);
  }
}

streamResponse();

from openai import OpenAI
import json

client = OpenAI(
    base_url="https://api.nsfwllm.com/v1",
    api_key="your-api-key"
)

# Define available tools/functions
tools = [
    {
        "type": "function",
        "function": {
            "name": "search_content",
            "description": "Search for content based on tags and categories",
            "parameters": {
                "type": "object",
                "properties": {
                    "query": {
                        "type": "string",
                        "description": "Search query or keywords"
                    },
                    "category": {
                        "type": "string",
                        "enum": ["romance", "fantasy", "drama", "comedy"],
                        "description": "Content category to filter by"
                    },
                    "limit": {
                        "type": "integer",
                        "description": "Maximum number of results"
                    }
                },
                "required": ["query"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "save_to_favorites",
            "description": "Save content to user's favorites list",
            "parameters": {
                "type": "object",
                "properties": {
                    "content_id": {
                        "type": "string",
                        "description": "The ID of the content to save"
                    }
                },
                "required": ["content_id"]
            }
        }
    }
]

# Make the request with tools
response = client.chat.completions.create(
    model="nsfw-uncensored",
    messages=[
        {"role": "system", "content": "You are a helpful content discovery assistant."},
        {"role": "user", "content": "Find me some romantic fantasy stories"}
    ],
    tools=tools,
    tool_choice="auto"
)

# Check if the model wants to call a function
message = response.choices[0].message

if message.tool_calls:
    for tool_call in message.tool_calls:
        function_name = tool_call.function.name
        function_args = json.loads(tool_call.function.arguments)
        
        print(f"Function: {function_name}")
        print(f"Arguments: {function_args}")
        
        # Execute the function and get result
        # result = execute_function(function_name, function_args)
        
        # Continue conversation with function result
        # messages.append({"role": "tool", "content": result, "tool_call_id": tool_call.id})

from openai import OpenAI, APIError, RateLimitError, AuthenticationError

client = OpenAI(
    base_url="https://api.nsfwllm.com/v1",
    api_key="your-api-key"
)

try:
    response = client.chat.completions.create(
        model="nsfw-uncensored",
        messages=[{"role": "user", "content": "Hello!"}]
    )
except AuthenticationError:
    print("Invalid API key. Please check your credentials.")
except RateLimitError:
    print("Rate limited. Please wait before retrying.")
    # Implement exponential backoff
except APIError as e:
    print(f"API error: {e.message}")
except Exception as e:
    print(f"Unexpected error: {e}")

x-ratelimit-limit-requests: 60
x-ratelimit-limit-tokens: 150000
x-ratelimit-remaining-requests: 59
x-ratelimit-remaining-tokens: 149850
x-ratelimit-reset-requests: 1s
x-ratelimit-reset-tokens: 6ms