Default and Custom SiliconCloud Model Setup
The self-hosted FastGPT system includes a small set of pre-configured SiliconCloud models for quick initial testing. To add additional models beyond this default collection, users must follow the official manual custom model addition process, linked at ./intro.en.mdx#add-a-custom-model.
Example Target Model Configuration
This demonstration uses a standard set of SiliconCloud models to enable a complete AI workflow. The configured models cover core inference, embedding, reranking, text-to-speech (TTS), and speech-to-text (STT) functionality:
| Model Type | Model Identifier | Primary Use Case |
|---|---|---|
| Text & Vision Model | Qwen2.5 72b | Dual text generation and visual understanding |
| Embedding Model | bge-m3 | Vector embedding generation for semantic search |
| Rerank Model | bge-reranker-v2-m3 | Reorder search results to improve relevance |
| TTS Model | fish-speech-1.5 | Convert written text to natural speech audio |
| STT Model | SenseVoiceSmall | Convert spoken audio to written text transcript |
Configuration Validation
After completing the manual model addition steps outlined in the linked guide, users can cross-reference their setup with the included reference screenshot (image-104.png). This visual resource confirms the correct formatting and placement of all configured SiliconCloud model entries within the FastGPT administrative interface.
Source: FastGPT official source
Applicability and version scope
Use this page for the documented Deployment and upgrades scenario. Confirm the FastGPT, dependency, API, and deployment versions in the official source before applying a change.
Safety guardrails
Use [REDACTED_CREDENTIAL] for credentials and private data. Confirm the documented environment and version before review.
Rollback guidance
Restore the prior technical-content authority snapshot. Restore saved configuration and data snapshots, then repeat the smallest verification scenario.