This article is translated from the official documentation of FastGPT, introducing how to use SiliconFlow models in FastGPT. Original Source
1. Register for a SiliconFlow Account
- Register for SiliconFlow Account
- Go to the console to get the API key: https://cloud.siliconflow.cn/account/ak
2. Modify FastGPT Environment Variables
3. Modify FastGPT Configuration File
We will use SiliconFlow models for the FastGPT configuration. Here, we configure the pure language and vision modelwen2.5 72b; choosebge-m3 as the vector model; choose bge-reranker-v2-m3 the reordering model. Choose fish-speech-1.5 as the speech model; choose SenseVoiceSmall as input model.
Note: The ReRank model still be configured with an API key once.
4. Restart FastGPT
5. Test Experience
Test Chat and Image Recognition
Create a simple application and select the corresponding models, then enable image upload for testing:
You can see 72B very fast. If you don a few 4090 GPUs locally, not only would setting up the environment be challenging, but the output might take 30 seconds or more.
测试知识库导入和知识库问答
新建一个知识库(由于只配置了一个向量模型,页面上不会展示向量模型选择)
导入本地文件,直接选择文件,然后一路下一步即可。79 个索引,大概花了 20s 的时间就完成了。现在我们去测试一下知识库问答。
首先回到我们刚创建的应用,选择知识库,调整一下参数后即可开始对话:
对话完成后,点击底部的引用,可以查看引用详情,同时可以看到具体的检索和重排得分:
测试语音播放
继续在刚刚的应用中,左侧配置中找到语音播放,点击后可以从弹窗中选择语音模型,并进行试听:
测试语言输入
继续在刚刚的应用中,左侧配置中找到语音输入,点击后可以从弹窗中开启语言输入
开启后,对话输入框中,会增加一个话筒的图标,点击可进行语音输入:










