Service eligibility and regional restrictions
PuppyIP serves only compliant overseas businesses and their authorized personnel. Proxy services are not available in mainland China. The service may only be used for lawful business activities outside mainland China. Use of this service within mainland China is prohibited.
Hosting a proxy IP or server overseas does not change these restrictions. The service must not be provided to end users in mainland China through relaying, forwarding, sharing or resale. Before use, read the Terms of Service.
Key Takeaways
- Longer context generally increases cost and latency.
- Streaming lets you see results sooner, but connection stability becomes more important.
- Consider request length, model choice, retries and the proxy network together when controlling costs.
Step 1: Understand that context is not unlimited
Context is the input the model can see for the current request. Sending large amounts of logs, code and documentation at once increases cost, latency and the chance of failure.
A more reliable approach is to clarify the task, remove irrelevant material and process it in sections. For code projects in particular, do not include real keys, production settings or customer data.
Step 2: Choose the right output mode
Streaming suits chat, long-form generation and situations where results need to appear in real time. Non-streamed output suits background batches and saving a result all at once.
Streaming connections are more sensitive to network stability. Frequent proxy disconnections may interrupt the visible output without any fault in the model itself.
Step 3: Control costs in four places
Start with model choice, input length, output length and retry policy. Do not let the program retry without limit after network failures.
For stable AI API or documentation access, visit the PuppyIP website to prepare a fixed proxy exit, then check the setup using the usage tutorials.
Frequently Asked Questions
Is longer context always better?
Not necessarily. Longer context generally costs more, takes longer and can introduce more irrelevant information.
Does a streaming failure mean the model is at fault?
Not necessarily. Connection interruptions, unstable proxies, service rate limits and client-side processing errors can all cause streaming to fail.