Qwen api docs: Quickstart Guide

Install the Standard OpenAI SDK

Start by installing the official SDK for your preferred language. This ensures compatibility with our OpenAI-compatible endpoint without requiring custom wrappers. You can use pip for Python or npm for Node.js to add the necessary libraries to your project environment.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.qwenapidocs.com/v1", api_key="YOUR_KEY")

resp = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Summarise this thread without softening it."}],
)
print(resp.choices[0].message.content)

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.qwenapidocs.com/v1", apiKey: process.env.API_KEY });

const resp = await client.chat.completions.create({
  model: "uncensored",
  messages: [{ role: "user", content: "Draft a villain monologue for my game." }],
});
console.log(resp.choices[0].message.content);

Configure Base URL and Key

Point your SDK client to our specific base URL and provide your API key. This directs all requests to our uncensored model rather than the default OpenAI servers. The base URL is HTTPS://api.qwenapidocs.com/v1 and you retrieve your key from the dashboard.

Copycurl https://api.qwenapidocs.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "List the current pricing tiers for the qwen endpoint"}]
  }'

Send Your First Uncensored Request

Make a standard chat completion call to receive raw, unrestricted text output. Our model ignores typical content filters for lawful adult use, providing direct responses to your prompts. The model identifier is simply "uncensored".

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.qwenapidocs.com/v1", api_key="YOUR_KEY")

resp = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Summarise this thread without softening it."}],
)
print(resp.choices[0].message.content)

Handle Streaming Responses (SSE)

Enable streaming to receive tokens as they are generated, reducing perceived latency for long outputs. The SDK yields chunks of text as they become available, allowing for real-time display in your application. The final chunk contains the total token usage for billing.

Copystream = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Tell the story in second person."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Enable Tool Calling and JSON Mode

Use the standard function calling format or enforce JSON output for structured data extraction. Our API supports tool definitions and response_format parameters just like the OpenAI standard. This allows you to integrate our uncensored model into complex agent workflows without custom parsing logic.

Monitor Token Usage and Limits

You are charged per 1M input and output tokens, with errors and refusals being free. Your account has a limit of 300 requests per minute and a context window of 100,000 tokens. Monitoring usage helps you manage your prepaid crypto credit effectively.