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Merge branch 'main' into feature/ChatHistory2

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chungyau97
2023-09-19 14:08:04 +08:00
parent f7178074ad 79545d0e9b
commit 922ba896ec
22 changed files with 415 additions and 305 deletions
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packages/server/.env.example
+1 -2
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@@ -1,5 +1,4 @@
PORT=3000
PASSPHRASE=MYPASSPHRASE # Passphrase used to create encryption key
# DATABASE_PATH=/your_database_path/.flowise
# APIKEY_PATH=/your_api_key_path/.flowise
# SECRETKEY_PATH=/your_api_key_path/.flowise
@@ -13,10 +12,10 @@ PASSPHRASE=MYPASSPHRASE # Passphrase used to create encryption key
# DATABASE_NAME="flowise"
# DATABASE_USER=""
# DATABASE_PASSWORD=""
# OVERRIDE_DATABASE=true
# FLOWISE_USERNAME=user
# FLOWISE_PASSWORD=1234
# FLOWISE_SECRETKEY_OVERWRITE=myencryptionkey
# DEBUG=true
# LOG_LEVEL=debug (error | warn | info | verbose | debug)
# TOOL_FUNCTION_BUILTIN_DEP=crypto,fs
packages/server/README-ZH.md
-20
View File
@@ -35,26 +35,6 @@ FLOWISE_PASSWORD=1234
Flowise 支持不同的环境变量来配置您的实例。您可以在`packages/server`文件夹中的`.env`文件中指定以下变量。阅读[更多](https://docs.flowiseai.com/environment-variables)
| 变量 | 描述 | 类型 | 默认值 |
| -------------------------- | ------------------------------------------------------ | ----------------------------------------------- | ----------------------------------- |
| PORT | Flowise 运行的 HTTP 端口 | 数字 | 3000 |
| FLOWISE_USERNAME | 登录的用户名 | 字符串 | |
| FLOWISE_PASSWORD | 登录的密码 | 字符串 | |
| DEBUG | 打印组件的日志 | 布尔值 | |
| LOG_PATH | 存储日志文件的位置 | 字符串 | `your-path/Flowise/logs` |
| LOG_LEVEL | 日志的不同级别 | 枚举字符串：`error`、`info`、`verbose`、`debug` | `info` |
| APIKEY_PATH | 存储 API 密钥的位置 | 字符串 | `your-path/Flowise/packages/server` |
| TOOL_FUNCTION_BUILTIN_DEP | 用于工具函数的 NodeJS 内置模块 | 字符串 | |
| TOOL_FUNCTION_EXTERNAL_DEP | 用于工具函数的外部模块 | 字符串 | |
| OVERRIDE_DATABASE | 使用默认值覆盖当前数据库 | 枚举字符串：`true`、`false` | `true` |
| DATABASE_TYPE | 存储 flowise 数据的数据库类型 | 枚举字符串：`sqlite`、`mysql`、`postgres` | `sqlite` |
| DATABASE_PATH | 数据库的保存位置（当 DATABASE_TYPE 为 sqlite 时） | 字符串 | `your-home-dir/.flowise` |
| DATABASE_HOST | 主机 URL 或 IP 地址（当 DATABASE_TYPE 不为 sqlite 时） | 字符串 | |
| DATABASE_PORT | 数据库端口（当 DATABASE_TYPE 不为 sqlite 时） | 字符串 | |
| DATABASE_USERNAME | 数据库用户名（当 DATABASE_TYPE 不为 sqlite 时） | 字符串 | |
| DATABASE_PASSWORD | 数据库密码（当 DATABASE_TYPE 不为 sqlite 时） | 字符串 | |
| DATABASE_NAME | 数据库名称（当 DATABASE_TYPE 不为 sqlite 时） | 字符串 | |
您还可以在使用`npx`时指定环境变量。例如：
```
packages/server/marketplaces/chatflows/Vectara LLM Chain Upload.json
+154 -217
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@@ -1,11 +1,125 @@
{
"description": "A simple LLM chain that uses Vectara to enable conversations with uploaded documents",
"description": "A simple LLM chain that uses Vectara to enable conversations with uploaded files",
"nodes": [
{
"width": 300,
"height": 524,
"id": "vectaraUpload_0",
"position": { "x": 219.0098475967174, "y": 189.74396248534583 },
"type": "customNode",
"data": {
"id": "vectaraUpload_0",
"label": "Vectara Upload File",
"version": 1,
"name": "vectaraUpload",
"type": "Vectara",
"baseClasses": ["Vectara", "VectorStoreRetriever", "BaseRetriever"],
"category": "Vector Stores",
"description": "Upload files to Vectara",
"inputParams": [
{
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"credentialNames": ["vectaraApi"],
"id": "vectaraUpload_0-input-credential-credential"
},
{
"label": "File",
"name": "file",
"description": "File to upload to Vectara. Supported file types: https://docs.vectara.com/docs/api-reference/indexing-apis/file-upload/file-upload-filetypes",
"type": "file",
"id": "vectaraUpload_0-input-file-file"
},
{
"label": "Vectara Metadata Filter",
"name": "filter",
"description": "Filter to apply to Vectara metadata. Refer to the <a target=\"_blank\" href=\"https://docs.flowiseai.com/vector-stores/vectara\">documentation</a> on how to use Vectara filters with Flowise.",
"type": "string",
"additionalParams": true,
"optional": true,
"id": "vectaraUpload_0-input-filter-string"
},
{
"label": "Sentences Before",
"name": "sentencesBefore",
"description": "Number of sentences to fetch before the matched sentence. Defaults to 2.",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpload_0-input-sentencesBefore-number"
},
{
"label": "Sentences After",
"name": "sentencesAfter",
"description": "Number of sentences to fetch after the matched sentence. Defaults to 2.",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpload_0-input-sentencesAfter-number"
},
{
"label": "Lambda",
"name": "lambda",
"description": "Improves retrieval accuracy by adjusting the balance (from 0 to 1) between neural search and keyword-based search factors.",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpload_0-input-lambda-number"
},
{
"label": "Top K",
"name": "topK",
"description": "Number of top results to fetch. Defaults to 4",
"placeholder": "4",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpload_0-input-topK-number"
}
],
"inputAnchors": [],
"inputs": {
"filter": "",
"sentencesBefore": "",
"sentencesAfter": "",
"lambda": "",
"topK": ""
},
"outputAnchors": [
{
"name": "output",
"label": "Output",
"type": "options",
"options": [
{
"id": "vectaraUpload_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",
"name": "retriever",
"label": "Vectara Retriever",
"type": "Vectara | VectorStoreRetriever | BaseRetriever"
},
{
"id": "vectaraUpload_0-output-vectorStore-Vectara|VectorStore",
"name": "vectorStore",
"label": "Vectara Vector Store",
"type": "Vectara | VectorStore"
}
],
"default": "retriever"
}
],
"outputs": { "output": "retriever" },
"selected": false
},
"selected": false,
"positionAbsolute": { "x": 219.0098475967174, "y": 189.74396248534583 },
"dragging": false
},
{
"width": 300,
"height": 525,
"id": "chatOpenAI_0",
"position": { "x": 514.1088940275924, "y": 199.574479681537 },
"position": { "x": 669.6533996522251, "y": 177.86181519287192 },
"type": "customNode",
"data": {
"id": "chatOpenAI_0",
@@ -13,7 +127,7 @@
"version": 1,
"name": "chatOpenAI",
"type": "ChatOpenAI",
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"],
"baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel", "Runnable"],
"category": "Chat Models",
"description": "Wrapper around OpenAI large language models that use the Chat endpoint",
"inputParams": [
@@ -36,7 +150,10 @@
{ "label": "gpt-3.5-turbo", "name": "gpt-3.5-turbo" },
{ "label": "gpt-3.5-turbo-0613", "name": "gpt-3.5-turbo-0613" },
{ "label": "gpt-3.5-turbo-16k", "name": "gpt-3.5-turbo-16k" },
{ "label": "gpt-3.5-turbo-16k-0613", "name": "gpt-3.5-turbo-16k-0613" }
{
"label": "gpt-3.5-turbo-16k-0613",
"name": "gpt-3.5-turbo-16k-0613"
}
],
"default": "gpt-3.5-turbo",
"optional": true,
@@ -103,6 +220,14 @@
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-basepath-string"
},
{
"label": "BaseOptions",
"name": "baseOptions",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-baseOptions-json"
}
],
"inputAnchors": [],
@@ -114,28 +239,29 @@
"frequencyPenalty": "",
"presencePenalty": "",
"timeout": "",
"basepath": ""
"basepath": "",
"baseOptions": ""
},
"outputAnchors": [
{
"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"name": "chatOpenAI",
"label": "ChatOpenAI",
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel"
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | Runnable"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": { "x": 514.1088940275924, "y": 199.574479681537 },
"positionAbsolute": { "x": 669.6533996522251, "y": 177.86181519287192 },
"dragging": false
},
{
"width": 300,
"height": 481,
"id": "conversationalRetrievalQAChain_0",
"position": { "x": 900.4793407261002, "y": 205.9476004518217 },
"position": { "x": 1135.5490908971935, "y": 201.62146241822506 },
"type": "customNode",
"data": {
"id": "conversationalRetrievalQAChain_0",
@@ -143,7 +269,7 @@
"version": 1,
"name": "conversationalRetrievalQAChain",
"type": "ConversationalRetrievalQAChain",
"baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"],
"baseClasses": ["ConversationalRetrievalQAChain", "BaseChain", "Runnable"],
"category": "Chains",
"description": "Document QA - built on RetrievalQAChain to provide a chat history component",
"inputParams": [
@@ -214,234 +340,45 @@
],
"inputs": {
"model": "{{chatOpenAI_0.data.instance}}",
"vectorStoreRetriever": "{{vectaraUpsert_0.data.instance}}",
"vectorStoreRetriever": "{{vectaraUpload_0.data.instance}}",
"memory": "",
"returnSourceDocuments": "",
"returnSourceDocuments": true,
"systemMessagePrompt": "",
"chainOption": ""
},
"outputAnchors": [
{
"id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain",
"id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain|Runnable",
"name": "conversationalRetrievalQAChain",
"label": "ConversationalRetrievalQAChain",
"type": "ConversationalRetrievalQAChain | BaseChain"
"type": "ConversationalRetrievalQAChain | BaseChain | Runnable"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": { "x": 900.4793407261002, "y": 205.9476004518217 },
"dragging": false
},
{
"width": 300,
"height": 509,
"id": "pdfFile_0",
"position": { "x": -210.44158723479913, "y": 236.6627524951051 },
"type": "customNode",
"data": {
"id": "pdfFile_0",
"label": "Pdf File",
"version": 1,
"name": "pdfFile",
"type": "Document",
"baseClasses": ["Document"],
"category": "Document Loaders",
"description": "Load data from PDF files",
"inputParams": [
{ "label": "Pdf File", "name": "pdfFile", "type": "file", "fileType": ".pdf", "id": "pdfFile_0-input-pdfFile-file" },
{
"label": "Usage",
"name": "usage",
"type": "options",
"options": [
{ "label": "One document per page", "name": "perPage" },
{ "label": "One document per file", "name": "perFile" }
],
"default": "perPage",
"id": "pdfFile_0-input-usage-options"
},
{
"label": "Use Legacy Build",
"name": "legacyBuild",
"type": "boolean",
"optional": true,
"additionalParams": true,
"id": "pdfFile_0-input-legacyBuild-boolean"
},
{
"label": "Metadata",
"name": "metadata",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "pdfFile_0-input-metadata-json"
}
],
"inputAnchors": [
{
"label": "Text Splitter",
"name": "textSplitter",
"type": "TextSplitter",
"optional": true,
"id": "pdfFile_0-input-textSplitter-TextSplitter"
}
],
"inputs": { "textSplitter": "", "usage": "perPage", "legacyBuild": "", "metadata": "" },
"outputAnchors": [
{ "id": "pdfFile_0-output-pdfFile-Document", "name": "pdfFile", "label": "Document", "type": "Document" }
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": { "x": -210.44158723479913, "y": 236.6627524951051 },
"dragging": false
},
{
"width": 300,
"height": 408,
"id": "vectaraUpsert_0",
"position": { "x": 172.06946164914868, "y": 373.11406233089934 },
"type": "customNode",
"data": {
"id": "vectaraUpsert_0",
"label": "Vectara Upsert Document",
"version": 1,
"name": "vectaraUpsert",
"type": "Vectara",
"baseClasses": ["Vectara", "VectorStoreRetriever", "BaseRetriever"],
"category": "Vector Stores",
"description": "Upsert documents to Vectara",
"inputParams": [
{
"label": "Connect Credential",
"name": "credential",
"type": "credential",
"credentialNames": ["vectaraApi"],
"id": "vectaraUpsert_0-input-credential-credential"
},
{
"label": "Vectara Metadata Filter",
"name": "filter",
"description": "Filter to apply to Vectara metadata. Refer to the <a target=\"_blank\" href=\"https://docs.flowiseai.com/vector-stores/vectara\">documentation</a> on how to use Vectara filters with Flowise.",
"type": "string",
"additionalParams": true,
"optional": true,
"id": "vectaraUpsert_0-input-filter-string"
},
{
"label": "Sentences Before",
"name": "sentencesBefore",
"description": "Number of sentences to fetch before the matched sentence. Defaults to 2.",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpsert_0-input-sentencesBefore-number"
},
{
"label": "Sentences After",
"name": "sentencesAfter",
"description": "Number of sentences to fetch after the matched sentence. Defaults to 2.",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpsert_0-input-sentencesAfter-number"
},
{
"label": "Lambda",
"name": "lambda",
"description": "Improves retrieval accuracy by adjusting the balance (from 0 to 1) between neural search and keyword-based search factors.",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpsert_0-input-lambda-number"
},
{
"label": "Top K",
"name": "topK",
"description": "Number of top results to fetch. Defaults to 4",
"placeholder": "4",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "vectaraUpsert_0-input-topK-number"
}
],
"inputAnchors": [
{
"label": "Document",
"name": "document",
"type": "Document",
"list": true,
"id": "vectaraUpsert_0-input-document-Document"
}
],
"inputs": {
"document": ["{{pdfFile_0.data.instance}}"],
"filter": "",
"sentencesBefore": "",
"sentencesAfter": "",
"lambda": "",
"topK": ""
},
"outputAnchors": [
{
"name": "output",
"label": "Output",
"type": "options",
"options": [
{
"id": "vectaraUpsert_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",
"name": "retriever",
"label": "Vectara Retriever",
"type": "Vectara | VectorStoreRetriever | BaseRetriever"
},
{
"id": "vectaraUpsert_0-output-vectorStore-Vectara|VectorStore",
"name": "vectorStore",
"label": "Vectara Vector Store",
"type": "Vectara | VectorStore"
}
],
"default": "retriever"
}
],
"outputs": { "output": "retriever" },
"selected": false
},
"positionAbsolute": { "x": 172.06946164914868, "y": 373.11406233089934 },
"selected": false
"dragging": false,
"positionAbsolute": { "x": 1135.5490908971935, "y": 201.62146241822506 }
}
],
"edges": [
{
"source": "chatOpenAI_0",
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel",
"target": "conversationalRetrievalQAChain_0",
"targetHandle": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"data": { "label": "" }
},
{
"source": "pdfFile_0",
"sourceHandle": "pdfFile_0-output-pdfFile-Document",
"target": "vectaraUpsert_0",
"targetHandle": "vectaraUpsert_0-input-document-Document",
"type": "buttonedge",
"id": "pdfFile_0-pdfFile_0-output-pdfFile-Document-vectaraUpsert_0-vectaraUpsert_0-input-document-Document",
"data": { "label": "" }
},
{
"source": "vectaraUpsert_0",
"sourceHandle": "vectaraUpsert_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",
"source": "vectaraUpload_0",
"sourceHandle": "vectaraUpload_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever",
"target": "conversationalRetrievalQAChain_0",
"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
"type": "buttonedge",
"id": "vectaraUpsert_0-vectaraUpsert_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
"id": "vectaraUpload_0-vectaraUpload_0-output-retriever-Vectara|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
"data": { "label": "" }
},
{
"source": "chatOpenAI_0",
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable",
"target": "conversationalRetrievalQAChain_0",
"targetHandle": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|Runnable-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"data": { "label": "" }
}
]
packages/server/package.json
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "flowise",
"version": "1.3.4",
"version": "1.3.5",
"description": "Flowiseai Server",
"main": "dist/index",
"types": "dist/index.d.ts",
packages/server/src/commands/start.ts
+2 -4
View File
@@ -19,15 +19,14 @@ export default class Start extends Command {
FLOWISE_USERNAME: Flags.string(),
FLOWISE_PASSWORD: Flags.string(),
PORT: Flags.string(),
PASSPHRASE: Flags.string(),
DEBUG: Flags.string(),
APIKEY_PATH: Flags.string(),
SECRETKEY_PATH: Flags.string(),
FLOWISE_SECRETKEY_OVERWRITE: Flags.string(),
LOG_PATH: Flags.string(),
LOG_LEVEL: Flags.string(),
TOOL_FUNCTION_BUILTIN_DEP: Flags.string(),
TOOL_FUNCTION_EXTERNAL_DEP: Flags.string(),
OVERRIDE_DATABASE: Flags.string(),
DATABASE_TYPE: Flags.string(),
DATABASE_PATH: Flags.string(),
DATABASE_PORT: Flags.string(),
@@ -80,8 +79,8 @@ export default class Start extends Command {
if (flags.APIKEY_PATH) process.env.APIKEY_PATH = flags.APIKEY_PATH
// Credentials
if (flags.PASSPHRASE) process.env.PASSPHRASE = flags.PASSPHRASE
if (flags.SECRETKEY_PATH) process.env.SECRETKEY_PATH = flags.SECRETKEY_PATH
if (flags.FLOWISE_SECRETKEY_OVERWRITE) process.env.FLOWISE_SECRETKEY_OVERWRITE = flags.FLOWISE_SECRETKEY_OVERWRITE
// Logs
if (flags.LOG_PATH) process.env.LOG_PATH = flags.LOG_PATH
@@ -92,7 +91,6 @@ export default class Start extends Command {
if (flags.TOOL_FUNCTION_EXTERNAL_DEP) process.env.TOOL_FUNCTION_EXTERNAL_DEP = flags.TOOL_FUNCTION_EXTERNAL_DEP
// Database config
if (flags.OVERRIDE_DATABASE) process.env.OVERRIDE_DATABASE = flags.OVERRIDE_DATABASE
if (flags.DATABASE_TYPE) process.env.DATABASE_TYPE = flags.DATABASE_TYPE
if (flags.DATABASE_PATH) process.env.DATABASE_PATH = flags.DATABASE_PATH
if (flags.DATABASE_PORT) process.env.DATABASE_PORT = flags.DATABASE_PORT
packages/server/src/utils/index.ts
+6 -8
View File
@@ -28,7 +28,7 @@ import {
convertChatHistoryToText
} from 'flowise-components'
import { scryptSync, randomBytes, timingSafeEqual } from 'crypto'
import { lib, PBKDF2, AES, enc } from 'crypto-js'
import { AES, enc } from 'crypto-js'
import { ChatFlow } from '../database/entities/ChatFlow'
import { ChatMessage } from '../database/entities/ChatMessage'
@@ -814,12 +814,7 @@ export const getEncryptionKeyPath = (): string => {
* @returns {string}
*/
export const generateEncryptKey = (): string => {
const salt = lib.WordArray.random(128 / 8)
const key256Bits = PBKDF2(process.env.PASSPHRASE || 'MYPASSPHRASE', salt, {
keySize: 256 / 32,
iterations: 1000
})
return key256Bits.toString()
return randomBytes(24).toString('base64')
}
/**
@@ -827,6 +822,9 @@ export const generateEncryptKey = (): string => {
* @returns {Promise<string>}
*/
export const getEncryptionKey = async (): Promise<string> => {
if (process.env.FLOWISE_SECRETKEY_OVERWRITE !== undefined && process.env.FLOWISE_SECRETKEY_OVERWRITE !== '') {
return process.env.FLOWISE_SECRETKEY_OVERWRITE
}
try {
return await fs.promises.readFile(getEncryptionKeyPath(), 'utf8')
} catch (error) {
@@ -868,7 +866,7 @@ export const decryptCredentialData = async (
return JSON.parse(decryptedData.toString(enc.Utf8))
} catch (e) {
console.error(e)
throw new Error('Credentials could not be decrypted.')
return {}
}
}