Bug描述
当我使用LocalAI组件通过API调用部署在另一台服务器上的嵌入模型时,向量计算过程成功,但当数据传输到内存时,返回此错误。
重现步骤
- 转到'cd /root/app/Flowise/docker'
- 点击'docker-compose up'
- 滚动到底部...
- 转到'cd /root/app/Flowise/LocalAI'
- 点击'docker-compose up'
查看错误
预期行为
我希望当我通过localai调用我的嵌入模型时,界面可以成功地存储在我的本地内存中,这样我的LLM就可以根据我的文本回答问题了。
截图
流程
flowise_1 | 2023-10-31 11:26:31 [INFO]: POST /api/v1/chatmessage/628a845f-8876-48ab-a4a7-74cf8f660768
flowise_1 | 2023-10-31 11:26:31 [INFO]: POST /api/v1/internal-prediction/628a845f-8876-48ab-a4a7-74cf8f660768
flowise_1 | 2023-10-31 11:26:32 [ERROR]: Cannot read properties of undefined (reading 'embedding')
flowise_1 | TypeError: Cannot read properties of undefined (reading 'embedding')
flowise_1 | at OpenAIEmbeddings.embedDocuments (/usr/local/lib/node_modules/flowise/node_modules/langchain/dist/embeddings/openai.cjs:153:50)
flowise_1 | at process.processTicksAndRejections (node:internal/process/task_queues:95:5)
flowise_1 | at async MemoryVectorStore.addDocuments (/usr/local/lib/node_modules/flowise/node_modules/langchain/dist/vectorstores/memory.cjs:41:32)
flowise_1 | at async MemoryVectorStore.fromDocuments (/usr/local/lib/node_modules/flowise/node_modules/langchain/dist/vectorstores/memory.cjs:129:9)
flowise_1 | at async InMemoryVectorStore_VectorStores.init (/usr/local/lib/node_modules/flowise/node_modules/flowise-components/dist/nodes/vectorstores/InMemory/InMemoryVectorStore.js:62:29)
flowise_1 | at async buildLangchain (/usr/local/lib/node_modules/flowise/dist/utils/index.js:223:50)
flowise_1 | at async App.processPrediction (/usr/local/lib/node_modules/flowise/dist/index.js:816:40)
flowise_1 | at async /usr/local/lib/node_modules/flowise
1条答案
按热度按时间mfpqipee1#
出于某种原因,它调用了
OpenAIEmbeddings
而不是LocalAI Embeddings
。我的建议是尝试创建一个新的聊天流程,并在空白画布上进行测试,看看问题是否仍然存在。