DeepSeek api Production Checklist

Verify Model Identity and Uncensorship

The model responding to your requests is not DeepSeek, Qwen, or any other major vendor. It is a dedicated uncensored large language model hosted on our servers. When you send a request, the response uses the model id "uncensored". This distinction matters because proxy services often route traffic through multiple providers. You need to know exactly which model generates your content. Check the response headers to confirm the identity. Our model is tuned to answer without content refusals for lawful adult use. It does not apply standard corporate filters. However, a hard limit always applies: requests involving minors are refused. Verify this behavior by sending a test prompt that would typically trigger a refusal in standard models. Ensure the response is direct and unfiltered. This confirms you are using a true uncensored API for your NSFW chatbot needs.

• Check the model id in the API response.
• Test a prompt known to trigger refusals in standard models.
• Confirm the response is direct and unfiltered.

Check Streaming and Token Usage Headers

Streaming must update token usage in real time. Our API supports server-sent events for streaming responses. Each chunk contains usage data. This allows your application to track token consumption accurately. Without this, you might lose track of your prepaid credit. The last chunk always contains the final token count. Verify this by sending a streaming request. Watch the console output. Ensure the numbers match your expectations. This is crucial for managing your uncensored AI usage. If the token count is missing, your billing might be inaccurate. Test with a simple prompt. Confirm the headers update correctly. This ensures transparent billing for your uncensored LLM.

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 streaming in your client.
• Log the usage data in each chunk.
• Verify the final token count matches the summary.

Test Function Calling and JSON Mode

Function calling and JSON mode are essential for robust applications. Our API supports both features. You can define tools and specify tool_choice. This allows your model to generate structured data. Use the response_format parameter to enforce JSON output. This is useful for building NSFW API integrations that require strict data formats. Test with a simple function definition. Verify the model follows the schema. If the output is malformed, your application might break. Ensure the JSON mode works correctly. This ensures your uncensored API integrates smoothly with your code. Test with various tool definitions. Confirm the model respects the constraints. This improves reliability for your deepseek uncensored projects.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.deepseektokenplan.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)

• Define a simple tool schema.
• Send a request with tool_choice set.
• Verify the output matches the schema.

Validate Rate Limits and Concurrency

Rate limits and concurrency affect your application performance. Our API allows 300 requests per minute per key. You can have 8 requests at the same time. The request body size is limited to 8 MB. If you exceed these limits, you will receive an error. Ensure your application handles these limits gracefully. Use retry logic with exponential backoff. This prevents overwhelming the server. Test with multiple concurrent requests. Monitor the response times. If you hit the limit, your requests will fail. This is important for high-traffic NSFW API use cases. Ensure your client respects the rate limits. This ensures a stable connection for your uncensored LLM.

• Send 300 requests in one minute.
• Check for rate limit errors.
• Implement retry logic in your code.

Confirm Crypto Payment and Bonus Structure

Crypto payments are the only method for topping up credit. We accept USDT on TRC20 and USDC on Base. The minimum top-up amount is $20. The maximum is $500. Bonus credit is added based on the amount. You get +5% for $50, +10% for $100, and +15% for $200. This bonus credit never expires. It is charged by real token usage. Errors and refusals are free. Ensure you understand the bonus structure. This helps you maximize your credit. Check the top-up page for current crypto addresses. Verify the bonus is applied correctly. This ensures transparent billing for your uncensored API. This simplifies the payment process.

• Top up with USDT or USDC.
• Verify the bonus credit is applied.
• Check that credit never expires.

Ensure No Subscription Lock-In

There are no monthly subscriptions or hidden fees. You pay for what you use. Your prepaid credit covers your usage. If you do not use your credit, it remains available. This is different from subscription-based services. You own your credit. It is not tied to a monthly plan. This flexibility is crucial for developers who need an uncensored API. Ensure you understand the prepaid model. This avoids unexpected charges. Verify that your credit balance is accurate. This ensures you are not locked into a subscription. This is ideal for variable workloads. Use your credit as needed. This provides financial control.

• Check that no monthly fee is charged.
• Verify the prepaid credit balance.
• Ensure credit does not expire.

Review Privacy and Data Usage Terms

Privacy is a key concern for many users. We do not use your prompts for training. Your data remains private. This is important for NSFW content creators. Ensure you review the privacy policy. Confirm that your data is not shared. This ensures your content remains confidential. Verify the data retention policy. This protects your intellectual property. This is crucial for professional uncensored AI usage. Ensure you are comfortable with the terms. This provides peace of mind. Use the API with confidence. This ensures your data is secure.

• Check the privacy policy.
• Verify data is not used for training.
• Confirm data retention policies.

Test Error Handling and Retry Logic

Error handling is critical for reliable applications. Our API returns standard HTTP status codes. Use these codes to handle errors. Implement retry logic for transient failures. This ensures your application does not crash. Test with various error scenarios. Verify the error messages are clear. This helps you debug issues quickly. Ensure your client handles rate limits correctly. This prevents request failures. Test with a malformed request. Confirm the error response. This ensures robust integration for your deepseek uncensored API. Use the error details to improve your code. This improves user experience.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.deepseektokenplan.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);

• Send a malformed request.
• Check the error response.
• Implement retry logic for transient errors.