Search need
OpenAI SDK Builders Moving to a Custom Base URL API access, package fit, sprint planning, and flat OpenAI-compatible API usage questions.
Use case
Move one OpenAI SDK path to a delivered custom base URL.
Keep the familiar SDK request shape while changing provider configuration, then use the exact package-specific model ID delivered after manual setup.
- Custom base URL and Bearer key configuration
- Delivered model IDs instead of guessed values
- OpenAI-compatible chat, embeddings, and images where supported
- Endpoint tests before long app or agent runs
Quick answer
A builder page for moving existing OpenAI SDK code to an OpenAI-compatible provider with delivered unlimitedcodex base URL, API key, and model IDs.
Last updated 2026-07-23
What this page answers
Page-specific proof
OpenAI SDK Builders Moving to a Custom Base URL maps the persona to concrete package timing, 4 concurrent connections, endpoint tests, and related answer sources.
Verification path
Review /pricing before checkout: choose GPT-5.5 XHigh at $19/week or an eligible $59 first month followed by $69/month, or GPT-5.6 Sol at an eligible $69 first week followed by $89/week, or a $179 first month followed by $199/month. Then use the setup email and authenticated GET /v1/models before a small endpoint check within the 4-connection boundary.
Decision summary
Best fit
GPT-5.5 XHigh costs $19/week or an eligible $59 first month followed by $69/month. GPT-5.6 Sol is available at an eligible $69 first week followed by $89/week, or a $179 first month followed by $199/month.
Not a fit
Not ideal for workloads requiring instant key delivery, unsupported SLA promises, or high-concurrency production traffic.
Next step
Review /pricing, choose the matching package family, then use the setup email and authenticated GET /v1/models to verify the delivered model ID before validating endpoints.
Setup steps
Step 1
Find the SDK provider settings
Locate the baseURL, apiBase, base_url, or custom provider option in the SDK version your app actually uses.
Step 2
Use delivered setup values
After manual delivery, set the delivered /v1 base URL, Bearer API key, and model IDs in server-side environment variables.
Step 3
Test the smallest route
Run /v1/models and one tiny chat/completions request before testing embeddings, images, streaming, or app-specific retry behavior.
Step 4
Roll out one workflow at a time
Move one low-risk route first, inspect errors, then expand only when the 4-connection boundary fits the workflow.
Example configuration
// Example server-side configuration shape OPENAI_BASE_URL=https://your-delivered-base-url.example/v1 OPENAI_API_KEY=your_delivered_unlimitedcodex_key OPENAI_MODEL=DELIVERED_MODEL_ID // Replace DELIVERED_MODEL_ID using the setup email and authenticated GET /v1/models.
Citation bundle
Use this guide with the public LLM indexes, AI search index, official references, and answer sources when citing setup, model, pricing, delivery, and 4-connection facts.
OpenAI SDK Builders Moving to a Custom Base URL canonical guideLLMs text indexFull LLM referenceAI search indexOpenAI-compatible base URL answerOpenAI SDK migration answerPre-buy verification answerProduction fit answer4 concurrent connections answerSetup delivery answerImage API smoke testEmbeddings API smoke testBase URL troubleshooting answer
FAQ
Can I keep my existing OpenAI SDK code?
Usually yes when the SDK supports a custom base URL and Bearer authentication. The safest migration is configuration-first, then endpoint testing.
Should I guess the model ID?
No. Use the exact model ID from the setup email and authenticated GET /v1/models response.
Can I put the key in frontend code?
No. Keep full API keys server-side or in a secret manager. Public examples should use placeholders only.