[AI Readability Summary] TRAE v3.3.51 now supports custom models and full baseURL configuration, allowing developers to connect OpenAI, Anthropic, third-party gateways, and local LLMs. The main source of errors is that many users enter only the domain name. The correct approach is to provide the full API endpoint path.
Technical Specifications Snapshot
| Parameter | Details |
|---|---|
| Tool Name | TRAE |
| Version | v3.3.51 |
| Primary Capabilities | Custom models, full baseURL, multi-model switching |
| Compatible Protocols | OpenAI Chat Completions, Anthropic Messages |
| Runtime Form | AI coding IDE / model integration shell |
| Star Count | Not provided in the source |
| Core Dependencies | A model service compatible with OpenAI/Anthropic protocols, an API key, and an accessible gateway URL |
This Update Solves Real Model Integration Usability Issues
The key change in TRAE v3.3.51 is not just “one more input field.” It formally exposes backend routing for model integration. Previously, many IDEs could bind only to official APIs, which made it difficult for developers to connect enterprise gateways, relay services, or local models through a unified workflow.
Now, as long as the backend is compatible with the OpenAI or Anthropic protocol format, TRAE can serve as a unified front end. This means DeepSeek, Qwen, GPT, Claude, and even privately deployed models can all be connected through the same workflow.
You Need to Understand One Core Principle First
In TRAE, baseURL is no longer just a service domain. It is the full API endpoint that the final request must hit. If you omit part of the path hierarchy, the client cannot assemble the request correctly.
Incorrect: baseURL = https://api.xxx.com
Correct: baseURL = https://api.xxx.com/full/api/pathThis configuration tells TRAE exactly which protocol endpoint should receive the request.
The baseURL Must Include the Full Endpoint Path to Avoid Errors
The single most important pitfall in the original article is this: do not enter only the domain name. You must provide the endpoint-level path. This is the root cause of most configuration failures.
If you enter only https://api.openai.com or https://api.anthropic.com/v1, TRAE cannot infer which API it should call, so the request will fail.
The Correct OpenAI Protocol Format Must End at chat/completions
For OpenAI-compatible services, you must configure the URL all the way down to /openai/v1/chat/completions. If you use a proxy, relay platform, or local gateway, the domain can vary, but the trailing path must be correct.
https://your-domain/openai/v1/chat/completions
https://api.openai.com/openai/v1/chat/completions
https://xxx.com/openai/v1/chat/completionsThis address ensures that TRAE directly targets an OpenAI-style chat completions endpoint.
Common OpenAI Protocol Mistakes Are Worth Eliminating First
Do not use the following formats in v3.3.51, because they omit the final resource path.
https://api.openai.com ❌
https://api.openai.com/v1 ❌The validation rule is simple: if the path does not end at chat/completions, it is usually not a value you can submit directly to TRAE.
The Anthropic Protocol Must Point to the messages Endpoint
Anthropic organizes its API differently from OpenAI. It does not use chat/completions. Instead, conversational requests go to the messages endpoint, so the baseURL must point there precisely.
https://your-domain/anthropic/v1/messages
https://api.anthropic.com/anthropic/v1/messages
https://xxx.com/anthropic/v1/messagesThis configuration routes Claude-style model requests to the Anthropic Messages API.
Anthropic Protocol Errors Usually Come From Incomplete Paths
The most common issue is still not the API key. It is an incomplete URL path. You should rule out the following formats immediately.
https://api.anthropic.com ❌
https://api.anthropic.com/v1 ❌If the URL does not include /messages, TRAE cannot recognize it as an executable Anthropic request entry point.
The Correct Configuration Process Separates Protocol and Model
In TRAE, go to Settings -> Models -> Custom Model. Once there, you typically need only three core fields: model name, API key, and baseURL.
If you are connecting an OpenAI-compatible service, such as GPT, DeepSeek, or certain gateway-wrapped versions of Qwen, use the OpenAI protocol format. If you are connecting Claude, use the Anthropic protocol format.
The Minimal Working Configuration for Each Model Type Looks Like This
OpenAI Example
Model Name: gpt-4o
API Key: your-key
baseURL: https://xxx.com/openai/v1/chat/completions
Anthropic Example
Model Name: claude-3
API Key: your-key
baseURL: https://xxx.com/anthropic/v1/messagesThis example shows the minimum required fields for TRAE custom model integration.
The Same Integration Pattern Works for Third-Party Gateways and Local LLMs
The most valuable part of this update is that TRAE is no longer tightly coupled to a single model vendor. As long as your gateway exposes an OpenAI- or Anthropic-compatible interface, you can reuse the same configuration logic.
A common enterprise pattern is to keep TRAE as the front end while routing requests in the backend through One API, reverse proxies, API aggregation platforms, or local inference gateways to models such as Qwen, DeepSeek, and Llama. This approach helps solve cost, regional access, and permission control challenges at the same time.
A Request Validation Script You Can Use
# Check whether the OpenAI-style endpoint is reachable
curl https://xxx.com/openai/v1/chat/completions \
-H "Authorization: Bearer your-key" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o",
"messages": [
{"role": "user", "content": "Hello"}
]
}'Use this command to verify the gateway endpoint, authentication, and model name before integrating with TRAE.
Download and Installation Information Should Be Verified Carefully
The original content includes a beta download link and a sample installer URL, but it does not provide an official repository, release page, or checksum details. A safer approach is to verify the package through official channels before replacing an existing installation.
| Resource | URL |
|---|---|
| Beta Download | https://pan.quark.cn/s/04f13a16da02 |
| Sample Installer URL | https://example.com/TRAE-3.3.51 |
| Sample Project URL | https://example.com/TRAE |
If you plan to use this in production, add version provenance, hash verification, and release notes before deployment.
This Feature Expansion Makes TRAE Effectively Model-Neutral
For developers, the value of a tool is not just whether it can chat. It is whether it can reliably connect to your own model infrastructure. By exposing the full baseURL, TRAE v3.3.51 has effectively evolved from a fixed client into a general AI coding entry point that can connect enterprise gateways and local inference layers.
So the key takeaway is not a specific download link. It is this configuration rule: match the protocol correctly, and write the path all the way to the final endpoint.
OpenAI: /openai/v1/chat/completions
Anthropic: /anthropic/v1/messagesThese two paths should be your first troubleshooting checkpoints when diagnosing TRAE custom model issues.
FAQ
FAQ 1: Why does TRAE still return an error even after I entered the domain and API key?
The most common reason is not the API key. It is an incomplete baseURL. TRAE v3.3.51 requires the full API endpoint, not just the domain or /v1. For OpenAI, the path must end at /chat/completions. For Anthropic, it must end at /messages.
FAQ 2: Can I connect locally deployed DeepSeek or Qwen models to TRAE?
Yes. The prerequisite is that your local service or gateway exposes an API compatible with OpenAI or Anthropic. If your local gateway exposes an OpenAI-style endpoint, simply point baseURL to the corresponding /chat/completions path.
FAQ 3: What is the easiest thing to overlook when connecting a third-party relay platform?
The easiest thing to miss is that the path cannot be only the root domain. Many relay platforms require a specific prefix, such as /openai/v1/chat/completions. Before integration, it is best to send a real request with curl to confirm that the model name, authentication, and path all work correctly.
Core Summary: This article systematically explains the custom model capability in TRAE v3.3.51, with a focus on the requirement that baseURL must include the full API endpoint. It also provides the correct OpenAI and Anthropic formats, common mistakes, configuration steps, and methods for integrating local models and third-party gateways.