Gen3 Gt Api Runbooks Librechat - GT-Edge-AI/GT-AI-OS GitHub Wiki
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Point LibreChat custom OpenAI endpoints at GT API via librechat.yaml and environment secrets; bind custom model entries to published agent aliases. Recommended preset: OpenAI-compatible chat client.
Why this matters
This runbook maps LibreChat to GT API routes operators actually publish.
Details
Compatibility: Guided OpenAI-compatible setup ยท Category: Workflow and builders
Official documentation
- https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints
- https://www.librechat.ai/docs/configuration/dotenv
- https://www.librechat.ai/docs/configuration/librechat_yaml/object_structure/custom_endpoint
Configuration fields
- OPENAI_REVERSE_PROXY:
https://<tenant-host>/api/tenant - OPENAI_API_KEY:
gtak_... - librechat.yaml โ endpoints.custom[].baseURL:
https://<tenant-host>/api/tenant
GT route mapping
| GT route | Verdict | Client integration |
|---|---|---|
GET /v1/models |
native | LibreChat custom endpoint model list or fetch against /v1/models |
POST /v1/chat/completions |
native | LibreChat OpenAI client โ /v1/chat/completions |
POST /v1/embeddings |
native | When embed scope enabled and LibreChat routes embed calls to same proxy |
POST /v1/audio/transcriptions |
not_supported | Not default LibreChat custom OpenAI endpoint path |
POST /v1/audio/speech |
not_supported | Not default LibreChat custom OpenAI endpoint path |
POST /v1/images/generations |
not_supported | Not default unless image endpoint configured with GT image scope |
POST /v1/conversations/files |
not_supported | Custom middleware HTTP multipart โ not default LibreChat files |
POST /v1/datasets/{id}/files |
not_supported | Custom middleware to GT dataset upload route |
GET /v1/files/{id} |
not_supported | Custom middleware GET poll |
Not supported in this product
- LibreChat native file upload UX does not map to GT dataset or conversation multipart routes without custom middleware.
Prerequisites
- Decide which deployment personas need GT access.
- Create one inference key per environment for hard isolation if needed.
Setup steps
- Configure OpenAI-compatible endpoint URL to tenant GT API base in
librechat.yamlor env. - Store GT API key in LibreChat secrets/env as documented.
- Map selectable model names to published aliases.
- Validate first chat completion end-to-end.
GT extensions and caveats
- GT conversation bootstrap as custom middleware if persisted GT threads are required.
- Use chat-plus-embeddings preset when embedding calls route through GT.
Validation checklist
- Chat works with published alias.
- Internal endpoints not exposed in model lists.
- Credential rotation does not break unrelated LibreChat providers.
Plain-text export
LibreChat runbook
Guided OpenAI-compatible setup ยท Workflow and builders
Recommended key preset: OpenAI-compatible chat client
Evidence: documented compatibility (vendor docs cross-check)
Point LibreChat custom OpenAI endpoints at GT API via `librechat.yaml` and environment secrets; bind custom model entries to published agent aliases.
Official documentation:
- https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints
- https://www.librechat.ai/docs/configuration/dotenv
- https://www.librechat.ai/docs/configuration/librechat_yaml/object_structure/custom_endpoint
Configuration fields:
- OPENAI_REVERSE_PROXY: https://<tenant-host>/api/tenant
- OPENAI_API_KEY: gtak_...
- librechat.yaml โ endpoints.custom[].baseURL: https://<tenant-host>/api/tenant
GT route mapping:
- GET /v1/models (native): LibreChat custom endpoint model list or fetch against `/v1/models`
- POST /v1/chat/completions (native): LibreChat OpenAI client โ `/v1/chat/completions`
- POST /v1/embeddings (native): When embed scope enabled and LibreChat routes embed calls to same proxy
- POST /v1/audio/transcriptions (not_supported): Not default LibreChat custom OpenAI endpoint path
- POST /v1/audio/speech (not_supported): Not default LibreChat custom OpenAI endpoint path
- POST /v1/images/generations (not_supported): Not default unless image endpoint configured with GT image scope
- POST /v1/conversations/files (not_supported): Custom middleware HTTP multipart โ not default LibreChat files
- POST /v1/datasets/{id}/files (not_supported): Custom middleware to GT dataset upload route
- GET /v1/files/{id} (not_supported): Custom middleware GET poll
Not supported in this product:
- LibreChat native file upload UX does not map to GT dataset or conversation multipart routes without custom middleware.
Prerequisites:
- Decide which deployment personas need GT access.
- Create one inference key per environment for hard isolation if needed.
Setup steps:
1. Configure OpenAI-compatible endpoint URL to tenant GT API base in `librechat.yaml` or env.
2. Store GT API key in LibreChat secrets/env as documented.
3. Map selectable model names to published aliases.
4. Validate first chat completion end-to-end.
GT extensions and caveats:
- GT conversation bootstrap as custom middleware if persisted GT threads are required.
- Use chat-plus-embeddings preset when embedding calls route through GT.
Validation checklist:
- Chat works with published alias.
- Internal endpoints not exposed in model lists.
- Credential rotation does not break unrelated LibreChat providers.