diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 03211d5..7c2222a 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -114,9 +114,42 @@ Flowise has 3 different modules in a single mono repository. 11. Commit code and submit Pull Request from forked branch pointing to [Flowise master](https://github.com/FlowiseAI/Flowise/tree/master). +## 🌱 Env Variables + +Flowise support different environment variables to configure your instance. You can specify the following variables in the `.env` file inside `packages/server` folder. Read [more](https://docs.flowiseai.com/environment-variables) + +| Variable | Description | Type | Default | +| -------------------------- | ---------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- | +| PORT | The HTTP port Flowise runs on | Number | 3000 | +| FLOWISE_USERNAME | Username to login | String | | +| FLOWISE_PASSWORD | Password to login | String | | +| DEBUG | Print logs from components | Boolean | | +| LOG_PATH | Location where log files are stored | String | `your-path/Flowise/logs` | +| LOG_LEVEL | Different levels of logs | Enum String: `error`, `info`, `verbose`, `debug` | `info` | +| APIKEY_PATH | Location where api keys are saved | String | `your-path/Flowise/packages/server` | +| EXECUTION_MODE | Whether predictions run in their own process or the main process | Enum String: `child`, `main` | `main` | +| TOOL_FUNCTION_BUILTIN_DEP | NodeJS built-in modules to be used for Tool Function | String | | +| TOOL_FUNCTION_EXTERNAL_DEP | External modules to be used for Tool Function | String | | +| OVERRIDE_DATABASE | Override current database with default | Enum String: `true`, `false` | `true` | +| DATABASE_TYPE | Type of database to store the flowise data | Enum String: `sqlite`, `mysql`, `postgres` | `sqlite` | +| DATABASE_PATH | Location where database is saved (When DATABASE_TYPE is sqlite) | String | `your-home-dir/.flowise` | +| DATABASE_HOST | Host URL or IP address (When DATABASE_TYPE is not sqlite) | String | | +| DATABASE_PORT | Database port (When DATABASE_TYPE is not sqlite) | String | | +| DATABASE_USERNAME | Database username (When DATABASE_TYPE is not sqlite) | String | | +| DATABASE_PASSWORD | Database password (When DATABASE_TYPE is not sqlite) | String | | +| DATABASE_NAME | Database name (When DATABASE_TYPE is not sqlite) | String | | +| PASSPHRASE | Passphrase used to create encryption key | String | `MYPASSPHRASE` | +| SECRETKEY_PATH | Location where encryption key (used to encrypt/decrypt credentials) is saved | String | `your-path/Flowise/packages/server` | + +You can also specify the env variables when using `npx`. For example: + +``` +npx flowise start --PORT=3000 --DEBUG=true +``` + ## πŸ“– Contribute to Docs -In-Progress +[Flowise Docs](https://github.com/FlowiseAI/FlowiseDocs) ## 🏷️ Pull Request process diff --git a/README.md b/README.md index 6a2289f..13da942 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,19 @@ -# Flowise + +# Flowise - Build LLM Apps Easily + +[![Release Notes](https://img.shields.io/github/release/FlowiseAI/Flowise)](https://github.com/FlowiseAI/Flowise/releases) +[![Discord](https://img.shields.io/discord/1087698854775881778?label=Discord&logo=discord)](https://discord.gg/jbaHfsRVBW) +[![Twitter Follow](https://img.shields.io/twitter/follow/FlowiseAI?style=social)](https://twitter.com/FlowiseAI) +[![GitHub star chart](https://img.shields.io/github/stars/FlowiseAI/Flowise?style=social)](https://star-history.com/#FlowiseAI/Flowise) +[![GitHub fork](https://img.shields.io/github/forks/FlowiseAI/Flowise?style=social)](https://github.com/FlowiseAI/Flowise/fork) + +

Drag & drop UI to build your customized LLM flow

-Drag & drop UI to build your customized LLM flow - ## ⚑Quick Start Download and Install [NodeJS](https://nodejs.org/en/download) >= 18.15.0 @@ -128,27 +135,7 @@ FLOWISE_PASSWORD=1234 ## 🌱 Env Variables -Flowise support different environment variables to configure your instance. You can specify the following variables in the `.env` file inside `packages/server` folder. - -| Variable | Description | Type | Default | -| ---------------- | ---------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- | -| PORT | The HTTP port Flowise runs on | Number | 3000 | -| PASSPHRASE | Passphrase used to create encryption key | String | `MYPASSPHRASE` | -| FLOWISE_USERNAME | Username to login | String | -| FLOWISE_PASSWORD | Password to login | String | -| DEBUG | Print logs from components | Boolean | -| LOG_PATH | Location where log files are stored | String | `your/path/Flowise/logs` | -| LOG_LEVEL | Different levels of logs | Enum String: `error`, `info`, `verbose`, `debug` | `info` | -| DATABASE_PATH | Location where database is saved | String | `your/home/dir/.flowise` | -| APIKEY_PATH | Location where api keys are saved | String | `your/path/Flowise/packages/server` | -| SECRETKEY_PATH | Location where encryption key (used to encrypt/decrypt credentials) is saved | String | `your/path/Flowise/packages/server` | -| EXECUTION_MODE | Whether predictions run in their own process or the main process | Enum String: `child`, `main` | `main` | - -You can also specify the env variables when using `npx`. For example: - -``` -npx flowise start --PORT=3000 --DEBUG=true -``` +Flowise support different environment variables to configure your instance. You can specify the following variables in the `.env` file inside `packages/server` folder. Read [more](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables) ## πŸ“– Documentation @@ -182,6 +169,12 @@ Feel free to ask any questions, raise problems, and request new features in [dis ## πŸ™Œ Contributing +Thanks go to these awesome contributors + + + + + See [contributing guide](CONTRIBUTING.md). Reach out to us at [Discord](https://discord.gg/jbaHfsRVBW) if you have any questions or issues. [![Star History Chart](https://api.star-history.com/svg?repos=FlowiseAI/Flowise&type=Timeline)](https://star-history.com/#FlowiseAI/Flowise&Date) diff --git a/artillery-load-test.yml b/artillery-load-test.yml new file mode 100644 index 0000000..6b1c814 --- /dev/null +++ b/artillery-load-test.yml @@ -0,0 +1,36 @@ +# npm install -g artillery@latest +# artillery run artillery-load-test.yml +# Refer https://www.artillery.io/docs + +config: + target: http://128.128.128.128:3000 # replace with your url + phases: + - duration: 1 + arrivalRate: 1 + rampTo: 2 + name: Warm up phase + - duration: 1 + arrivalRate: 2 + rampTo: 3 + name: Ramp up load + - duration: 1 + arrivalRate: 3 + name: Sustained peak load +scenarios: + - flow: + - loop: + - post: + url: '/api/v1/prediction/chatflow-id' # replace with your chatflowid + json: + question: 'hello' # replace with your question + count: 1 # how many request each user make + +# User __ +# 3 / +# 2 / +# 1 _/ +# 1 2 3 +# Seconds +# Total Users = 2 + 3 + 3 = 8 +# Each making 1 HTTP call +# Over a duration of 3 seconds diff --git a/docker/.env.example b/docker/.env.example index 29d592f..dd3b00f 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -1,11 +1,22 @@ PORT=3000 PASSPHRASE=MYPASSPHRASE # Passphrase used to create encryption key +DATABASE_PATH=/root/.flowise +APIKEY_PATH=/root/.flowise +SECRETKEY_PATH=/root/.flowise +LOG_PATH=/root/.flowise/logs + +# DATABASE_TYPE=postgres +# DATABASE_PORT="" +# DATABASE_HOST="" +# DATABASE_NAME="flowise" +# DATABASE_USER="" +# DATABASE_PASSWORD="" +# OVERRIDE_DATABASE=true + # FLOWISE_USERNAME=user # FLOWISE_PASSWORD=1234 # DEBUG=true -# DATABASE_PATH=/your/database/path/.flowise -# APIKEY_PATH=/your/api/key/path -# SECRETKEY_PATH=/your/secret/key/path -# LOG_PATH=/your/log/path # LOG_LEVEL=debug (error | warn | info | verbose | debug) # EXECUTION_MODE=main (child | main) +# TOOL_FUNCTION_BUILTIN_DEP=crypto,fs +# TOOL_FUNCTION_EXTERNAL_DEP=moment,lodash diff --git a/docker/README.md b/docker/README.md index 7f991a0..d3ad1c1 100644 --- a/docker/README.md +++ b/docker/README.md @@ -9,7 +9,7 @@ Starts Flowise from [DockerHub Image](https://hub.docker.com/repository/docker/f 3. Open [http://localhost:3000](http://localhost:3000) 4. You can bring the containers down by `docker-compose stop` -## With Authrorization +## πŸ”’ Authentication 1. Create `.env` file and specify the `PORT`, `FLOWISE_USERNAME`, and `FLOWISE_PASSWORD` (refer to `.env.example`) 2. Pass `FLOWISE_USERNAME` and `FLOWISE_PASSWORD` to the `docker-compose.yml` file: @@ -22,3 +22,14 @@ Starts Flowise from [DockerHub Image](https://hub.docker.com/repository/docker/f 3. `docker-compose up -d` 4. Open [http://localhost:3000](http://localhost:3000) 5. You can bring the containers down by `docker-compose stop` + +## 🌱 Env Variables + +If you like to persist your data (flows, logs, apikeys, credentials), set these variables in the `.env` file inside `docker` folder: + +- DATABASE_PATH=/root/.flowise +- APIKEY_PATH=/root/.flowise +- LOG_PATH=/root/.flowise/logs +- SECRETKEY_PATH=/root/.flowise + +Flowise also support different environment variables to configure your instance. Read [more](https://docs.flowiseai.com/environment-variables) diff --git a/docker/docker-compose.yml b/docker/docker-compose.yml index dca9696..e9b2824 100644 --- a/docker/docker-compose.yml +++ b/docker/docker-compose.yml @@ -9,13 +9,13 @@ services: - PASSPHRASE=${PASSPHRASE} - FLOWISE_USERNAME=${FLOWISE_USERNAME} - FLOWISE_PASSWORD=${FLOWISE_PASSWORD} + - DEBUG=${DEBUG} - DATABASE_PATH=${DATABASE_PATH} - APIKEY_PATH=${APIKEY_PATH} - SECRETKEY_PATH=${SECRETKEY_PATH} - LOG_LEVEL=${LOG_LEVEL} - LOG_PATH=${LOG_PATH} - EXECUTION_MODE=${EXECUTION_MODE} - - DEBUG=${DEBUG} ports: - '${PORT}:${PORT}' volumes: diff --git a/images/flowise.png b/images/flowise.png new file mode 100644 index 0000000..09c71fd Binary files /dev/null and b/images/flowise.png differ diff --git a/package.json b/package.json index 9d0d9d1..27c5358 100644 --- a/package.json +++ b/package.json @@ -1,6 +1,6 @@ { "name": "flowise", - "version": "1.2.15", + "version": "1.2.16", "private": true, "homepage": "https://flowiseai.com", "workspaces": [ @@ -28,7 +28,6 @@ "*.{js,jsx,ts,tsx,json,md}": "eslint --fix" }, "devDependencies": { - "turbo": "1.7.4", "@babel/preset-env": "^7.19.4", "@babel/preset-typescript": "7.18.6", "@types/express": "^4.17.13", @@ -48,6 +47,7 @@ "pretty-quick": "^3.1.3", "rimraf": "^3.0.2", "run-script-os": "^1.1.6", + "turbo": "1.7.4", "typescript": "^4.8.4" }, "engines": { diff --git a/packages/components/credentials/AirtableApi.credential.ts b/packages/components/credentials/AirtableApi.credential.ts new file mode 100644 index 0000000..7123c92 --- /dev/null +++ b/packages/components/credentials/AirtableApi.credential.ts @@ -0,0 +1,25 @@ +import { INodeParams, INodeCredential } from '../src/Interface' + +class AirtableApi implements INodeCredential { + label: string + name: string + description: string + inputs: INodeParams[] + + constructor() { + this.label = 'Airtable API' + this.name = 'airtableApi' + this.description = + 'Refer to official guide on how to get accessToken on Airtable' + this.inputs = [ + { + label: 'Access Token', + name: 'accessToken', + type: 'password', + placeholder: '' + } + ] + } +} + +module.exports = { credClass: AirtableApi } diff --git a/packages/components/credentials/BraveSearchApi.credential.ts b/packages/components/credentials/BraveSearchApi.credential.ts new file mode 100644 index 0000000..2f71354 --- /dev/null +++ b/packages/components/credentials/BraveSearchApi.credential.ts @@ -0,0 +1,22 @@ +import { INodeParams, INodeCredential } from '../src/Interface' + +class BraveSearchApi implements INodeCredential { + label: string + name: string + description: string + inputs: INodeParams[] + + constructor() { + this.label = 'Brave Search API' + this.name = 'braveSearchApi' + this.inputs = [ + { + label: 'BraveSearch Api Key', + name: 'braveApiKey', + type: 'password' + } + ] + } +} + +module.exports = { credClass: BraveSearchApi } diff --git a/packages/components/credentials/ReplicateApi.credential.ts b/packages/components/credentials/ReplicateApi.credential.ts new file mode 100644 index 0000000..bef3e9a --- /dev/null +++ b/packages/components/credentials/ReplicateApi.credential.ts @@ -0,0 +1,21 @@ +import { INodeParams, INodeCredential } from '../src/Interface' + +class ReplicateApi implements INodeCredential { + label: string + name: string + inputs: INodeParams[] + + constructor() { + this.label = 'Replicate API' + this.name = 'replicateApi' + this.inputs = [ + { + label: 'Replicate Api Key', + name: 'replicateApiKey', + type: 'password' + } + ] + } +} + +module.exports = { credClass: ReplicateApi } diff --git a/packages/components/credentials/SingleStoreApi.credential.ts b/packages/components/credentials/SingleStoreApi.credential.ts new file mode 100644 index 0000000..deb73b4 --- /dev/null +++ b/packages/components/credentials/SingleStoreApi.credential.ts @@ -0,0 +1,29 @@ +import { INodeParams, INodeCredential } from '../src/Interface' + +class SingleStoreApi implements INodeCredential { + label: string + name: string + description: string + inputs: INodeParams[] + + constructor() { + this.label = 'SingleStore API' + this.name = 'singleStoreApi' + this.inputs = [ + { + label: 'User', + name: 'user', + type: 'string', + placeholder: '' + }, + { + label: 'Password', + name: 'password', + type: 'password', + placeholder: '' + } + ] + } +} + +module.exports = { credClass: SingleStoreApi } diff --git a/packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts b/packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts new file mode 100644 index 0000000..3dc4847 --- /dev/null +++ b/packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts @@ -0,0 +1,231 @@ +import { ICommonObject, INode, INodeData, INodeParams, PromptTemplate } from '../../../src/Interface' +import { AgentExecutor } from 'langchain/agents' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { LoadPyodide, finalSystemPrompt, systemPrompt } from './core' +import { LLMChain } from 'langchain/chains' +import { BaseLanguageModel } from 'langchain/base_language' +import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler' +import axios from 'axios' + +class Airtable_Agents implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + credential: INodeParams + inputs: INodeParams[] + + constructor() { + this.label = 'Airtable Agent' + this.name = 'airtableAgent' + this.type = 'AgentExecutor' + this.category = 'Agents' + this.icon = 'airtable.svg' + this.description = 'Agent used to to answer queries on Airtable table' + this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['airtableApi'] + } + this.inputs = [ + { + label: 'Language Model', + name: 'model', + type: 'BaseLanguageModel' + }, + { + label: 'Base Id', + name: 'baseId', + type: 'string', + placeholder: 'app11RobdGoX0YNsC', + description: + 'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, app11RovdGoX0YNsC is the base id' + }, + { + label: 'Table Id', + name: 'tableId', + type: 'string', + placeholder: 'tblJdmvbrgizbYICO', + description: + 'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, tblJdmvbrgizbYICO is the table id' + }, + { + label: 'Return All', + name: 'returnAll', + type: 'boolean', + default: true, + additionalParams: true, + description: 'If all results should be returned or only up to a given limit' + }, + { + label: 'Limit', + name: 'limit', + type: 'number', + default: 100, + step: 1, + additionalParams: true, + description: 'Number of results to return' + } + ] + } + + async init(): Promise { + // Not used + return undefined + } + + async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { + const model = nodeData.inputs?.model as BaseLanguageModel + const baseId = nodeData.inputs?.baseId as string + const tableId = nodeData.inputs?.tableId as string + const returnAll = nodeData.inputs?.returnAll as boolean + const limit = nodeData.inputs?.limit as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const accessToken = getCredentialParam('accessToken', credentialData, nodeData) + + let airtableData: ICommonObject[] = [] + + if (returnAll) { + airtableData = await loadAll(baseId, tableId, accessToken) + } else { + airtableData = await loadLimit(limit ? parseInt(limit, 10) : 100, baseId, tableId, accessToken) + } + + let base64String = Buffer.from(JSON.stringify(airtableData)).toString('base64') + + const loggerHandler = new ConsoleCallbackHandler(options.logger) + const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId) + + const pyodide = await LoadPyodide() + + // First load the csv file and get the dataframe dictionary of column types + // For example using titanic.csv: {'PassengerId': 'int64', 'Survived': 'int64', 'Pclass': 'int64', 'Name': 'object', 'Sex': 'object', 'Age': 'float64', 'SibSp': 'int64', 'Parch': 'int64', 'Ticket': 'object', 'Fare': 'float64', 'Cabin': 'object', 'Embarked': 'object'} + let dataframeColDict = '' + try { + const code = `import pandas as pd +import base64 +import json + +base64_string = "${base64String}" + +decoded_data = base64.b64decode(base64_string) + +json_data = json.loads(decoded_data) + +df = pd.DataFrame(json_data) +my_dict = df.dtypes.astype(str).to_dict() +print(my_dict) +json.dumps(my_dict)` + dataframeColDict = await pyodide.runPythonAsync(code) + } catch (error) { + throw new Error(error) + } + + // Then tell GPT to come out with ONLY python code + // For example: len(df), df[df['SibSp'] > 3]['PassengerId'].count() + let pythonCode = '' + if (dataframeColDict) { + const chain = new LLMChain({ + llm: model, + prompt: PromptTemplate.fromTemplate(systemPrompt), + verbose: process.env.DEBUG === 'true' ? true : false + }) + const inputs = { + dict: dataframeColDict, + question: input + } + const res = await chain.call(inputs, [loggerHandler]) + pythonCode = res?.text + } + + // Then run the code using Pyodide + let finalResult = '' + if (pythonCode) { + try { + const code = `import pandas as pd\n${pythonCode}` + finalResult = await pyodide.runPythonAsync(code) + } catch (error) { + throw new Error(`Sorry, I'm unable to find answer for question: "${input}" using follwoing code: "${pythonCode}"`) + } + } + + // Finally, return a complete answer + if (finalResult) { + const chain = new LLMChain({ + llm: model, + prompt: PromptTemplate.fromTemplate(finalSystemPrompt), + verbose: process.env.DEBUG === 'true' ? true : false + }) + const inputs = { + question: input, + answer: finalResult + } + + if (options.socketIO && options.socketIOClientId) { + const result = await chain.call(inputs, [loggerHandler, handler]) + return result?.text + } else { + const result = await chain.call(inputs, [loggerHandler]) + return result?.text + } + } + + return pythonCode + } +} + +interface AirtableLoaderResponse { + records: AirtableLoaderPage[] + offset?: string +} + +interface AirtableLoaderPage { + id: string + createdTime: string + fields: ICommonObject +} + +const fetchAirtableData = async (url: string, params: ICommonObject, accessToken: string): Promise => { + try { + const headers = { + Authorization: `Bearer ${accessToken}`, + 'Content-Type': 'application/json', + Accept: 'application/json' + } + const response = await axios.get(url, { params, headers }) + return response.data + } catch (error) { + throw new Error(`Failed to fetch ${url} from Airtable: ${error}`) + } +} + +const loadAll = async (baseId: string, tableId: string, accessToken: string): Promise => { + const params: ICommonObject = { pageSize: 100 } + let data: AirtableLoaderResponse + let returnPages: AirtableLoaderPage[] = [] + + do { + data = await fetchAirtableData(`https://api.airtable.com/v0/${baseId}/${tableId}`, params, accessToken) + returnPages.push.apply(returnPages, data.records) + params.offset = data.offset + } while (data.offset !== undefined) + + return data.records.map((page) => page.fields) +} + +const loadLimit = async (limit: number, baseId: string, tableId: string, accessToken: string): Promise => { + const params = { maxRecords: limit } + const data = await fetchAirtableData(`https://api.airtable.com/v0/${baseId}/${tableId}`, params, accessToken) + if (data.records.length === 0) { + return [] + } + return data.records.map((page) => page.fields) +} + +module.exports = { nodeClass: Airtable_Agents } diff --git a/packages/components/nodes/agents/AirtableAgent/airtable.svg b/packages/components/nodes/agents/AirtableAgent/airtable.svg new file mode 100644 index 0000000..867c3b5 --- /dev/null +++ b/packages/components/nodes/agents/AirtableAgent/airtable.svg @@ -0,0 +1,9 @@ + + + + + + + + + diff --git a/packages/components/nodes/agents/AirtableAgent/core.ts b/packages/components/nodes/agents/AirtableAgent/core.ts new file mode 100644 index 0000000..450bf5e --- /dev/null +++ b/packages/components/nodes/agents/AirtableAgent/core.ts @@ -0,0 +1,29 @@ +import type { PyodideInterface } from 'pyodide' +import * as path from 'path' +import { getUserHome } from '../../../src/utils' + +let pyodideInstance: PyodideInterface | undefined + +export async function LoadPyodide(): Promise { + if (pyodideInstance === undefined) { + const { loadPyodide } = await import('pyodide') + const obj: any = { packageCacheDir: path.join(getUserHome(), '.flowise', 'pyodideCacheDir') } + pyodideInstance = await loadPyodide(obj) + await pyodideInstance.loadPackage(['pandas', 'numpy']) + } + + return pyodideInstance +} + +export const systemPrompt = `You are working with a pandas dataframe in Python. The name of the dataframe is df. + +The columns and data types of a dataframe are given below as a Python dictionary with keys showing column names and values showing the data types. +{dict} + +I will ask question, and you will output the Python code using pandas dataframe to answer my question. Do not provide any explanations. Do not respond with anything except the output of the code. + +Question: {question} +Output Code:` + +export const finalSystemPrompt = `You are given the question: {question}. You have an answer to the question: {answer}. Rephrase the answer into a standalone answer. +Standalone Answer:` diff --git a/packages/components/nodes/agents/CSVAgent/CSVAgent.ts b/packages/components/nodes/agents/CSVAgent/CSVAgent.ts new file mode 100644 index 0000000..0fe7195 --- /dev/null +++ b/packages/components/nodes/agents/CSVAgent/CSVAgent.ts @@ -0,0 +1,149 @@ +import { ICommonObject, INode, INodeData, INodeParams, PromptTemplate } from '../../../src/Interface' +import { AgentExecutor } from 'langchain/agents' +import { getBaseClasses } from '../../../src/utils' +import { LoadPyodide, finalSystemPrompt, systemPrompt } from './core' +import { LLMChain } from 'langchain/chains' +import { BaseLanguageModel } from 'langchain/base_language' +import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler' + +class CSV_Agents implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + inputs: INodeParams[] + + constructor() { + this.label = 'CSV Agent' + this.name = 'csvAgent' + this.type = 'AgentExecutor' + this.category = 'Agents' + this.icon = 'csvagent.png' + this.description = 'Agent used to to answer queries on CSV data' + this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)] + this.inputs = [ + { + label: 'Csv File', + name: 'csvFile', + type: 'file', + fileType: '.csv' + }, + { + label: 'Language Model', + name: 'model', + type: 'BaseLanguageModel' + } + ] + } + + async init(): Promise { + // Not used + return undefined + } + + async run(nodeData: INodeData, input: string, options: ICommonObject): Promise { + const csvFileBase64 = nodeData.inputs?.csvFile as string + const model = nodeData.inputs?.model as BaseLanguageModel + + const loggerHandler = new ConsoleCallbackHandler(options.logger) + const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId) + + let files: string[] = [] + + if (csvFileBase64.startsWith('[') && csvFileBase64.endsWith(']')) { + files = JSON.parse(csvFileBase64) + } else { + files = [csvFileBase64] + } + + let base64String = '' + + for (const file of files) { + const splitDataURI = file.split(',') + splitDataURI.pop() + base64String = splitDataURI.pop() ?? '' + } + + const pyodide = await LoadPyodide() + + // First load the csv file and get the dataframe dictionary of column types + // For example using titanic.csv: {'PassengerId': 'int64', 'Survived': 'int64', 'Pclass': 'int64', 'Name': 'object', 'Sex': 'object', 'Age': 'float64', 'SibSp': 'int64', 'Parch': 'int64', 'Ticket': 'object', 'Fare': 'float64', 'Cabin': 'object', 'Embarked': 'object'} + let dataframeColDict = '' + try { + const code = `import pandas as pd +import base64 +from io import StringIO +import json + +base64_string = "${base64String}" + +decoded_data = base64.b64decode(base64_string) + +csv_data = StringIO(decoded_data.decode('utf-8')) + +df = pd.read_csv(csv_data) +my_dict = df.dtypes.astype(str).to_dict() +print(my_dict) +json.dumps(my_dict)` + dataframeColDict = await pyodide.runPythonAsync(code) + } catch (error) { + throw new Error(error) + } + + // Then tell GPT to come out with ONLY python code + // For example: len(df), df[df['SibSp'] > 3]['PassengerId'].count() + let pythonCode = '' + if (dataframeColDict) { + const chain = new LLMChain({ + llm: model, + prompt: PromptTemplate.fromTemplate(systemPrompt), + verbose: process.env.DEBUG === 'true' ? true : false + }) + const inputs = { + dict: dataframeColDict, + question: input + } + const res = await chain.call(inputs, [loggerHandler]) + pythonCode = res?.text + } + + // Then run the code using Pyodide + let finalResult = '' + if (pythonCode) { + try { + const code = `import pandas as pd\n${pythonCode}` + finalResult = await pyodide.runPythonAsync(code) + } catch (error) { + throw new Error(`Sorry, I'm unable to find answer for question: "${input}" using follwoing code: "${pythonCode}"`) + } + } + + // Finally, return a complete answer + if (finalResult) { + const chain = new LLMChain({ + llm: model, + prompt: PromptTemplate.fromTemplate(finalSystemPrompt), + verbose: process.env.DEBUG === 'true' ? true : false + }) + const inputs = { + question: input, + answer: finalResult + } + + if (options.socketIO && options.socketIOClientId) { + const result = await chain.call(inputs, [loggerHandler, handler]) + return result?.text + } else { + const result = await chain.call(inputs, [loggerHandler]) + return result?.text + } + } + + return pythonCode + } +} + +module.exports = { nodeClass: CSV_Agents } diff --git a/packages/components/nodes/agents/CSVAgent/core.ts b/packages/components/nodes/agents/CSVAgent/core.ts new file mode 100644 index 0000000..450bf5e --- /dev/null +++ b/packages/components/nodes/agents/CSVAgent/core.ts @@ -0,0 +1,29 @@ +import type { PyodideInterface } from 'pyodide' +import * as path from 'path' +import { getUserHome } from '../../../src/utils' + +let pyodideInstance: PyodideInterface | undefined + +export async function LoadPyodide(): Promise { + if (pyodideInstance === undefined) { + const { loadPyodide } = await import('pyodide') + const obj: any = { packageCacheDir: path.join(getUserHome(), '.flowise', 'pyodideCacheDir') } + pyodideInstance = await loadPyodide(obj) + await pyodideInstance.loadPackage(['pandas', 'numpy']) + } + + return pyodideInstance +} + +export const systemPrompt = `You are working with a pandas dataframe in Python. The name of the dataframe is df. + +The columns and data types of a dataframe are given below as a Python dictionary with keys showing column names and values showing the data types. +{dict} + +I will ask question, and you will output the Python code using pandas dataframe to answer my question. Do not provide any explanations. Do not respond with anything except the output of the code. + +Question: {question} +Output Code:` + +export const finalSystemPrompt = `You are given the question: {question}. You have an answer to the question: {answer}. Rephrase the answer into a standalone answer. +Standalone Answer:` diff --git a/packages/components/nodes/agents/CSVAgent/csvagent.png b/packages/components/nodes/agents/CSVAgent/csvagent.png new file mode 100644 index 0000000..3ed16bb Binary files /dev/null and b/packages/components/nodes/agents/CSVAgent/csvagent.png differ diff --git a/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts b/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts index 9faf83d..f4d065d 100644 --- a/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts +++ b/packages/components/nodes/agents/OpenAIFunctionAgent/OpenAIFunctionAgent.ts @@ -22,7 +22,7 @@ class OpenAIFunctionAgent_Agents implements INode { this.name = 'openAIFunctionAgent' this.type = 'AgentExecutor' this.category = 'Agents' - this.icon = 'openai.svg' + this.icon = 'openai.png' this.description = `An agent that uses OpenAI's Function Calling functionality to pick the tool and args to call` this.baseClasses = [this.type, ...getBaseClasses(AgentExecutor)] this.inputs = [ diff --git a/packages/components/nodes/agents/OpenAIFunctionAgent/openai.png b/packages/components/nodes/agents/OpenAIFunctionAgent/openai.png new file mode 100644 index 0000000..de08a05 Binary files /dev/null and b/packages/components/nodes/agents/OpenAIFunctionAgent/openai.png differ diff --git a/packages/components/nodes/agents/OpenAIFunctionAgent/openai.svg b/packages/components/nodes/agents/OpenAIFunctionAgent/openai.svg deleted file mode 100644 index 9d3261d..0000000 --- a/packages/components/nodes/agents/OpenAIFunctionAgent/openai.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts b/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts index 24b40d4..2c86530 100644 --- a/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts +++ b/packages/components/nodes/chains/ConversationalRetrievalQAChain/ConversationalRetrievalQAChain.ts @@ -1,32 +1,21 @@ import { BaseLanguageModel } from 'langchain/base_language' import { ICommonObject, IMessage, INode, INodeData, INodeParams } from '../../../src/Interface' import { getBaseClasses } from '../../../src/utils' -import { ConversationalRetrievalQAChain } from 'langchain/chains' -import { AIMessage, BaseRetriever, HumanMessage } from 'langchain/schema' -import { BaseChatMemory, BufferMemory, ChatMessageHistory } from 'langchain/memory' +import { ConversationalRetrievalQAChain, QAChainParams } from 'langchain/chains' +import { AIMessage, HumanMessage } from 'langchain/schema' +import { BaseRetriever } from 'langchain/schema/retriever' +import { BaseChatMemory, BufferMemory, ChatMessageHistory, BufferMemoryInput } from 'langchain/memory' import { PromptTemplate } from 'langchain/prompts' import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler' - -const default_qa_template = `Use the following pieces of context to answer the question at the end, in its original language. If you don't know the answer, just say that you don't know in its original language, don't try to make up an answer. - -{context} - -Question: {question} -Helpful Answer:` - -const qa_template = `Use the following pieces of context to answer the question at the end, in its original language. - -{context} - -Question: {question} -Helpful Answer:` - -const CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT = `Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question, in its original language. include it in the standalone question. - -Chat History: -{chat_history} -Follow Up Input: {question} -Standalone question:` +import { + default_map_reduce_template, + default_qa_template, + qa_template, + map_reduce_template, + CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT, + refine_question_template, + refine_template +} from './prompts' class ConversationalRetrievalQAChain_Chains implements INode { label: string @@ -60,9 +49,9 @@ class ConversationalRetrievalQAChain_Chains implements INode { { label: 'Memory', name: 'memory', - type: 'DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory', + type: 'BaseMemory', optional: true, - description: 'If no memory connected, default BufferMemory will be used' + description: 'If left empty, a default BufferMemory will be used' }, { label: 'Return Source Documents', @@ -118,28 +107,54 @@ class ConversationalRetrievalQAChain_Chains implements INode { const obj: any = { verbose: process.env.DEBUG === 'true' ? true : false, - qaChainOptions: { - type: 'stuff', - prompt: PromptTemplate.fromTemplate(systemMessagePrompt ? `${systemMessagePrompt}\n${qa_template}` : default_qa_template) - }, questionGeneratorChainOptions: { template: CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT } } if (returnSourceDocuments) obj.returnSourceDocuments = returnSourceDocuments - if (chainOption) obj.qaChainOptions = { ...obj.qaChainOptions, type: chainOption } + if (chainOption === 'map_reduce') { + obj.qaChainOptions = { + type: 'map_reduce', + combinePrompt: PromptTemplate.fromTemplate( + systemMessagePrompt ? `${systemMessagePrompt}\n${map_reduce_template}` : default_map_reduce_template + ) + } as QAChainParams + } else if (chainOption === 'refine') { + const qprompt = new PromptTemplate({ + inputVariables: ['context', 'question'], + template: refine_question_template(systemMessagePrompt) + }) + const rprompt = new PromptTemplate({ + inputVariables: ['context', 'question', 'existing_answer'], + template: refine_template + }) + obj.qaChainOptions = { + type: 'refine', + questionPrompt: qprompt, + refinePrompt: rprompt + } as QAChainParams + } else { + obj.qaChainOptions = { + type: 'stuff', + prompt: PromptTemplate.fromTemplate(systemMessagePrompt ? `${systemMessagePrompt}\n${qa_template}` : default_qa_template) + } as QAChainParams + } + if (memory) { memory.inputKey = 'question' - memory.outputKey = 'text' memory.memoryKey = 'chat_history' + if (chainOption === 'refine') memory.outputKey = 'output_text' + else memory.outputKey = 'text' obj.memory = memory } else { - obj.memory = new BufferMemory({ + const fields: BufferMemoryInput = { memoryKey: 'chat_history', inputKey: 'question', - outputKey: 'text', returnMessages: true - }) + } + if (chainOption === 'refine') fields.outputKey = 'output_text' + else fields.outputKey = 'text' + obj.memory = new BufferMemory(fields) } const chain = ConversationalRetrievalQAChain.fromLLM(model, vectorStoreRetriever, obj) @@ -150,6 +165,7 @@ class ConversationalRetrievalQAChain_Chains implements INode { const chain = nodeData.instance as ConversationalRetrievalQAChain const returnSourceDocuments = nodeData.inputs?.returnSourceDocuments as boolean const memory = nodeData.inputs?.memory + const chainOption = nodeData.inputs?.chainOption as string let model = nodeData.inputs?.model @@ -179,8 +195,22 @@ class ConversationalRetrievalQAChain_Chains implements INode { const loggerHandler = new ConsoleCallbackHandler(options.logger) if (options.socketIO && options.socketIOClientId) { - const handler = new CustomChainHandler(options.socketIO, options.socketIOClientId, undefined, returnSourceDocuments) + const handler = new CustomChainHandler( + options.socketIO, + options.socketIOClientId, + chainOption === 'refine' ? 4 : undefined, + returnSourceDocuments + ) const res = await chain.call(obj, [loggerHandler, handler]) + if (chainOption === 'refine') { + if (res.output_text && res.sourceDocuments) { + return { + text: res.output_text, + sourceDocuments: res.sourceDocuments + } + } + return res?.output_text + } if (res.text && res.sourceDocuments) return res return res?.text } else { diff --git a/packages/components/nodes/chains/ConversationalRetrievalQAChain/prompts.ts b/packages/components/nodes/chains/ConversationalRetrievalQAChain/prompts.ts new file mode 100644 index 0000000..132e3a9 --- /dev/null +++ b/packages/components/nodes/chains/ConversationalRetrievalQAChain/prompts.ts @@ -0,0 +1,64 @@ +export const default_qa_template = `Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer. + +{context} + +Question: {question} +Helpful Answer:` + +export const qa_template = `Use the following pieces of context to answer the question at the end. + +{context} + +Question: {question} +Helpful Answer:` + +export const default_map_reduce_template = `Given the following extracted parts of a long document and a question, create a final answer. +If you don't know the answer, just say that you don't know. Don't try to make up an answer. + +{summaries} + +Question: {question} +Helpful Answer:` + +export const map_reduce_template = `Given the following extracted parts of a long document and a question, create a final answer. + +{summaries} + +Question: {question} +Helpful Answer:` + +export const refine_question_template = (sysPrompt?: string) => { + let returnPrompt = '' + if (sysPrompt) + returnPrompt = `Context information is below. +--------------------- +{context} +--------------------- +Given the context information and not prior knowledge, ${sysPrompt} +Answer the question: {question}. +Answer:` + if (!sysPrompt) + returnPrompt = `Context information is below. +--------------------- +{context} +--------------------- +Given the context information and not prior knowledge, answer the question: {question}. +Answer:` + return returnPrompt +} + +export const refine_template = `The original question is as follows: {question} +We have provided an existing answer: {existing_answer} +We have the opportunity to refine the existing answer (only if needed) with some more context below. +------------ +{context} +------------ +Given the new context, refine the original answer to better answer the question. +If you can't find answer from the context, return the original answer.` + +export const CUSTOM_QUESTION_GENERATOR_CHAIN_PROMPT = `Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question, answer in the same language as the follow up question. include it in the standalone question. + +Chat History: +{chat_history} +Follow Up Input: {question} +Standalone question:` diff --git a/packages/components/nodes/chains/LLMChain/LLMChain.ts b/packages/components/nodes/chains/LLMChain/LLMChain.ts index 1d0ccb9..eca56d3 100644 --- a/packages/components/nodes/chains/LLMChain/LLMChain.ts +++ b/packages/components/nodes/chains/LLMChain/LLMChain.ts @@ -1,5 +1,5 @@ import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' -import { getBaseClasses } from '../../../src/utils' +import { getBaseClasses, handleEscapeCharacters } from '../../../src/utils' import { LLMChain } from 'langchain/chains' import { BaseLanguageModel } from 'langchain/base_language' import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler' @@ -73,7 +73,12 @@ class LLMChain_Chains implements INode { console.log('\x1b[92m\x1b[1m\n*****OUTPUT PREDICTION*****\n\x1b[0m\x1b[0m') // eslint-disable-next-line no-console console.log(res) - return res + /** + * Apply string transformation to convert special chars: + * FROM: hello i am ben\n\n\thow are you? + * TO: hello i am benFLOWISE_NEWLINEFLOWISE_NEWLINEFLOWISE_TABhow are you? + */ + return handleEscapeCharacters(res, false) } } @@ -81,7 +86,6 @@ class LLMChain_Chains implements INode { const inputVariables = nodeData.instance.prompt.inputVariables as string[] // ["product"] const chain = nodeData.instance as LLMChain const promptValues = nodeData.inputs?.prompt.promptValues as ICommonObject - const res = await runPrediction(inputVariables, chain, input, promptValues, options) // eslint-disable-next-line no-console console.log('\x1b[93m\x1b[1m\n*****FINAL RESULT*****\n\x1b[0m\x1b[0m') @@ -95,7 +99,7 @@ const runPrediction = async ( inputVariables: string[], chain: LLMChain, input: string, - promptValues: ICommonObject, + promptValuesRaw: ICommonObject, options: ICommonObject ) => { const loggerHandler = new ConsoleCallbackHandler(options.logger) @@ -103,6 +107,13 @@ const runPrediction = async ( const socketIO = isStreaming ? options.socketIO : undefined const socketIOClientId = isStreaming ? options.socketIOClientId : '' + /** + * Apply string transformation to reverse converted special chars: + * FROM: { "value": "hello i am benFLOWISE_NEWLINEFLOWISE_NEWLINEFLOWISE_TABhow are you?" } + * TO: { "value": "hello i am ben\n\n\thow are you?" } + */ + const promptValues = handleEscapeCharacters(promptValuesRaw, true) + if (inputVariables.length === 1) { if (isStreaming) { const handler = new CustomChainHandler(socketIO, socketIOClientId) diff --git a/packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts b/packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts index eaf5a0a..1571e72 100644 --- a/packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts +++ b/packages/components/nodes/chains/RetrievalQAChain/RetrievalQAChain.ts @@ -1,6 +1,6 @@ import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' import { RetrievalQAChain } from 'langchain/chains' -import { BaseRetriever } from 'langchain/schema' +import { BaseRetriever } from 'langchain/schema/retriever' import { getBaseClasses } from '../../../src/utils' import { BaseLanguageModel } from 'langchain/base_language' import { ConsoleCallbackHandler, CustomChainHandler } from '../../../src/handler' diff --git a/packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts b/packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts index 13262b5..1339d1f 100644 --- a/packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts +++ b/packages/components/nodes/chatmodels/ChatOpenAI/ChatOpenAI.ts @@ -17,7 +17,7 @@ class ChatOpenAI_ChatModels implements INode { this.label = 'ChatOpenAI' this.name = 'chatOpenAI' this.type = 'ChatOpenAI' - this.icon = 'openai.svg' + this.icon = 'openai.png' this.category = 'Chat Models' this.description = 'Wrapper around OpenAI large language models that use the Chat endpoint' this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)] diff --git a/packages/components/nodes/chatmodels/ChatOpenAI/openai.png b/packages/components/nodes/chatmodels/ChatOpenAI/openai.png new file mode 100644 index 0000000..de08a05 Binary files /dev/null and b/packages/components/nodes/chatmodels/ChatOpenAI/openai.png differ diff --git a/packages/components/nodes/chatmodels/ChatOpenAI/openai.svg b/packages/components/nodes/chatmodels/ChatOpenAI/openai.svg deleted file mode 100644 index 9d3261d..0000000 --- a/packages/components/nodes/chatmodels/ChatOpenAI/openai.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/packages/components/nodes/documentloaders/API/APILoader.ts b/packages/components/nodes/documentloaders/API/APILoader.ts new file mode 100644 index 0000000..30fa31d --- /dev/null +++ b/packages/components/nodes/documentloaders/API/APILoader.ts @@ -0,0 +1,198 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { TextSplitter } from 'langchain/text_splitter' +import { BaseDocumentLoader } from 'langchain/document_loaders/base' +import { Document } from 'langchain/document' +import axios, { AxiosRequestConfig } from 'axios' + +class API_DocumentLoaders implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + inputs?: INodeParams[] + + constructor() { + this.label = 'API Loader' + this.name = 'apiLoader' + this.type = 'Document' + this.icon = 'api-loader.png' + this.category = 'Document Loaders' + this.description = `Load data from an API` + this.baseClasses = [this.type] + this.inputs = [ + { + label: 'Text Splitter', + name: 'textSplitter', + type: 'TextSplitter', + optional: true + }, + { + label: 'Method', + name: 'method', + type: 'options', + options: [ + { + label: 'GET', + name: 'GET' + }, + { + label: 'POST', + name: 'POST' + } + ] + }, + { + label: 'URL', + name: 'url', + type: 'string' + }, + { + label: 'Headers', + name: 'headers', + type: 'json', + additionalParams: true, + optional: true + }, + { + label: 'Body', + name: 'body', + type: 'json', + description: + 'JSON body for the POST request. If not specified, agent will try to figure out itself from AIPlugin if provided', + additionalParams: true, + optional: true + } + ] + } + async init(nodeData: INodeData): Promise { + const headers = nodeData.inputs?.headers as string + const url = nodeData.inputs?.url as string + const body = nodeData.inputs?.body as string + const method = nodeData.inputs?.method as string + const textSplitter = nodeData.inputs?.textSplitter as TextSplitter + const metadata = nodeData.inputs?.metadata + + const options: ApiLoaderParams = { + url, + method + } + + if (headers) { + const parsedHeaders = typeof headers === 'object' ? headers : JSON.parse(headers) + options.headers = parsedHeaders + } + + if (body) { + const parsedBody = typeof body === 'object' ? body : JSON.parse(body) + options.body = parsedBody + } + + const loader = new ApiLoader(options) + + let docs = [] + + if (textSplitter) { + docs = await loader.loadAndSplit(textSplitter) + } else { + docs = await loader.load() + } + + if (metadata) { + const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata) + let finaldocs = [] + for (const doc of docs) { + const newdoc = { + ...doc, + metadata: { + ...doc.metadata, + ...parsedMetadata + } + } + finaldocs.push(newdoc) + } + return finaldocs + } + + return docs + } +} + +interface ApiLoaderParams { + url: string + method: string + headers?: ICommonObject + body?: ICommonObject +} + +class ApiLoader extends BaseDocumentLoader { + public readonly url: string + + public readonly headers?: ICommonObject + + public readonly body?: ICommonObject + + public readonly method: string + + constructor({ url, headers, body, method }: ApiLoaderParams) { + super() + this.url = url + this.headers = headers + this.body = body + this.method = method + } + + public async load(): Promise { + if (this.method === 'POST') { + return this.executePostRequest(this.url, this.headers, this.body) + } else { + return this.executeGetRequest(this.url, this.headers) + } + } + + protected async executeGetRequest(url: string, headers?: ICommonObject): Promise { + try { + const config: AxiosRequestConfig = {} + if (headers) { + config.headers = headers + } + const response = await axios.get(url, config) + const responseJsonString = JSON.stringify(response.data, null, 2) + const doc = new Document({ + pageContent: responseJsonString, + metadata: { + url + } + }) + return [doc] + } catch (error) { + throw new Error(`Failed to fetch ${url}: ${error}`) + } + } + + protected async executePostRequest(url: string, headers?: ICommonObject, body?: ICommonObject): Promise { + try { + const config: AxiosRequestConfig = {} + if (headers) { + config.headers = headers + } + const response = await axios.post(url, body ?? {}, config) + const responseJsonString = JSON.stringify(response.data, null, 2) + const doc = new Document({ + pageContent: responseJsonString, + metadata: { + url + } + }) + return [doc] + } catch (error) { + throw new Error(`Failed to post ${url}: ${error}`) + } + } +} + +module.exports = { + nodeClass: API_DocumentLoaders +} diff --git a/packages/components/nodes/documentloaders/API/api-loader.png b/packages/components/nodes/documentloaders/API/api-loader.png new file mode 100644 index 0000000..93668c4 Binary files /dev/null and b/packages/components/nodes/documentloaders/API/api-loader.png differ diff --git a/packages/components/nodes/documentloaders/Airtable/Airtable.ts b/packages/components/nodes/documentloaders/Airtable/Airtable.ts new file mode 100644 index 0000000..a9b47a8 --- /dev/null +++ b/packages/components/nodes/documentloaders/Airtable/Airtable.ts @@ -0,0 +1,229 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { TextSplitter } from 'langchain/text_splitter' +import { BaseDocumentLoader } from 'langchain/document_loaders/base' +import { Document } from 'langchain/document' +import axios from 'axios' +import { getCredentialData, getCredentialParam } from '../../../src/utils' + +class Airtable_DocumentLoaders implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + credential: INodeParams + inputs?: INodeParams[] + + constructor() { + this.label = 'Airtable' + this.name = 'airtable' + this.type = 'Document' + this.icon = 'airtable.svg' + this.category = 'Document Loaders' + this.description = `Load data from Airtable table` + this.baseClasses = [this.type] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['airtableApi'] + } + this.inputs = [ + { + label: 'Text Splitter', + name: 'textSplitter', + type: 'TextSplitter', + optional: true + }, + { + label: 'Base Id', + name: 'baseId', + type: 'string', + placeholder: 'app11RobdGoX0YNsC', + description: + 'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, app11RovdGoX0YNsC is the base id' + }, + { + label: 'Table Id', + name: 'tableId', + type: 'string', + placeholder: 'tblJdmvbrgizbYICO', + description: + 'If your table URL looks like: https://airtable.com/app11RobdGoX0YNsC/tblJdmvbrgizbYICO/viw9UrP77Id0CE4ee, tblJdmvbrgizbYICO is the table id' + }, + { + label: 'Return All', + name: 'returnAll', + type: 'boolean', + default: true, + additionalParams: true, + description: 'If all results should be returned or only up to a given limit' + }, + { + label: 'Limit', + name: 'limit', + type: 'number', + default: 100, + step: 1, + additionalParams: true, + description: 'Number of results to return' + }, + { + label: 'Metadata', + name: 'metadata', + type: 'json', + optional: true, + additionalParams: true + } + ] + } + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const baseId = nodeData.inputs?.baseId as string + const tableId = nodeData.inputs?.tableId as string + const returnAll = nodeData.inputs?.returnAll as boolean + const limit = nodeData.inputs?.limit as string + const textSplitter = nodeData.inputs?.textSplitter as TextSplitter + const metadata = nodeData.inputs?.metadata + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const accessToken = getCredentialParam('accessToken', credentialData, nodeData) + + const airtableOptions: AirtableLoaderParams = { + baseId, + tableId, + returnAll, + accessToken, + limit: limit ? parseInt(limit, 10) : 100 + } + + const loader = new AirtableLoader(airtableOptions) + + let docs = [] + + if (textSplitter) { + docs = await loader.loadAndSplit(textSplitter) + } else { + docs = await loader.load() + } + + if (metadata) { + const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata) + let finaldocs = [] + for (const doc of docs) { + const newdoc = { + ...doc, + metadata: { + ...doc.metadata, + ...parsedMetadata + } + } + finaldocs.push(newdoc) + } + return finaldocs + } + + return docs + } +} + +interface AirtableLoaderParams { + baseId: string + tableId: string + accessToken: string + limit?: number + returnAll?: boolean +} + +interface AirtableLoaderResponse { + records: AirtableLoaderPage[] + offset?: string +} + +interface AirtableLoaderPage { + id: string + createdTime: string + fields: ICommonObject +} + +class AirtableLoader extends BaseDocumentLoader { + public readonly baseId: string + + public readonly tableId: string + + public readonly accessToken: string + + public readonly limit: number + + public readonly returnAll: boolean + + constructor({ baseId, tableId, accessToken, limit = 100, returnAll = false }: AirtableLoaderParams) { + super() + this.baseId = baseId + this.tableId = tableId + this.accessToken = accessToken + this.limit = limit + this.returnAll = returnAll + } + + public async load(): Promise { + if (this.returnAll) { + return this.loadAll() + } + return this.loadLimit() + } + + protected async fetchAirtableData(url: string, params: ICommonObject): Promise { + try { + const headers = { + Authorization: `Bearer ${this.accessToken}`, + 'Content-Type': 'application/json', + Accept: 'application/json' + } + const response = await axios.get(url, { params, headers }) + return response.data + } catch (error) { + throw new Error(`Failed to fetch ${url} from Airtable: ${error}`) + } + } + + private createDocumentFromPage(page: AirtableLoaderPage): Document { + // Generate the URL + const pageUrl = `https://api.airtable.com/v0/${this.baseId}/${this.tableId}/${page.id}` + + // Return a langchain document + return new Document({ + pageContent: JSON.stringify(page.fields, null, 2), + metadata: { + url: pageUrl + } + }) + } + + private async loadLimit(): Promise { + const params = { maxRecords: this.limit } + const data = await this.fetchAirtableData(`https://api.airtable.com/v0/${this.baseId}/${this.tableId}`, params) + if (data.records.length === 0) { + return [] + } + return data.records.map((page) => this.createDocumentFromPage(page)) + } + + private async loadAll(): Promise { + const params: ICommonObject = { pageSize: 100 } + let data: AirtableLoaderResponse + let returnPages: AirtableLoaderPage[] = [] + + do { + data = await this.fetchAirtableData(`https://api.airtable.com/v0/${this.baseId}/${this.tableId}`, params) + returnPages.push.apply(returnPages, data.records) + params.offset = data.offset + } while (data.offset !== undefined) + return returnPages.map((page) => this.createDocumentFromPage(page)) + } +} + +module.exports = { + nodeClass: Airtable_DocumentLoaders +} diff --git a/packages/components/nodes/documentloaders/Airtable/airtable.svg b/packages/components/nodes/documentloaders/Airtable/airtable.svg new file mode 100644 index 0000000..867c3b5 --- /dev/null +++ b/packages/components/nodes/documentloaders/Airtable/airtable.svg @@ -0,0 +1,9 @@ + + + + + + + + + diff --git a/packages/components/nodes/documentloaders/NotionDB/NotionDB.ts b/packages/components/nodes/documentloaders/Notion/NotionDB.ts similarity index 94% rename from packages/components/nodes/documentloaders/NotionDB/NotionDB.ts rename to packages/components/nodes/documentloaders/Notion/NotionDB.ts index 5fec608..3f0730e 100644 --- a/packages/components/nodes/documentloaders/NotionDB/NotionDB.ts +++ b/packages/components/nodes/documentloaders/Notion/NotionDB.ts @@ -39,8 +39,7 @@ class NotionDB_DocumentLoaders implements INode { label: 'Notion Database Id', name: 'databaseId', type: 'string', - description: - 'If your URL looks like - https://www.notion.so/?v=, then is the database ID' + description: 'If your URL looks like - https://www.notion.so/abcdefh?v=long_hash_2, then abcdefh is the database ID' }, { label: 'Metadata', diff --git a/packages/components/nodes/documentloaders/NotionFolder/NotionFolder.ts b/packages/components/nodes/documentloaders/Notion/NotionFolder.ts similarity index 100% rename from packages/components/nodes/documentloaders/NotionFolder/NotionFolder.ts rename to packages/components/nodes/documentloaders/Notion/NotionFolder.ts diff --git a/packages/components/nodes/documentloaders/NotionPage/NotionPage.ts b/packages/components/nodes/documentloaders/Notion/NotionPage.ts similarity index 100% rename from packages/components/nodes/documentloaders/NotionPage/NotionPage.ts rename to packages/components/nodes/documentloaders/Notion/NotionPage.ts diff --git a/packages/components/nodes/documentloaders/NotionDB/notion.png b/packages/components/nodes/documentloaders/Notion/notion.png similarity index 100% rename from packages/components/nodes/documentloaders/NotionDB/notion.png rename to packages/components/nodes/documentloaders/Notion/notion.png diff --git a/packages/components/nodes/documentloaders/NotionFolder/notion.png b/packages/components/nodes/documentloaders/NotionFolder/notion.png deleted file mode 100644 index 3910516..0000000 Binary files a/packages/components/nodes/documentloaders/NotionFolder/notion.png and /dev/null differ diff --git a/packages/components/nodes/documentloaders/NotionPage/notion.png b/packages/components/nodes/documentloaders/NotionPage/notion.png deleted file mode 100644 index 3910516..0000000 Binary files a/packages/components/nodes/documentloaders/NotionPage/notion.png and /dev/null differ diff --git a/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/HuggingFaceInferenceEmbedding.ts b/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/HuggingFaceInferenceEmbedding.ts index bfbb93e..aaf13ef 100644 --- a/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/HuggingFaceInferenceEmbedding.ts +++ b/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/HuggingFaceInferenceEmbedding.ts @@ -32,6 +32,8 @@ class HuggingFaceInferenceEmbedding_Embeddings implements INode { label: 'Model', name: 'modelName', type: 'string', + description: 'If using own inference endpoint, leave this blank', + placeholder: 'sentence-transformers/distilbert-base-nli-mean-tokens', optional: true }, { diff --git a/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/core.ts b/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/core.ts index 41e63aa..c75658d 100644 --- a/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/core.ts +++ b/packages/components/nodes/embeddings/HuggingFaceInferenceEmbedding/core.ts @@ -30,18 +30,26 @@ export class HuggingFaceInferenceEmbeddings extends Embeddings implements Huggin async _embed(texts: string[]): Promise { // replace newlines, which can negatively affect performance. const clean = texts.map((text) => text.replace(/\n/g, ' ')) + const hf = new HfInference(this.apiKey) const obj: any = { inputs: clean } - if (!this.endpoint) obj.model = this.model - return this.caller.call(() => this.client.featureExtraction(obj)) as Promise + if (this.endpoint) { + hf.endpoint(this.endpoint) + } else { + obj.model = this.model + } + + const res = await this.caller.callWithOptions({}, hf.featureExtraction.bind(hf), obj) + return res as number[][] } - embedQuery(document: string): Promise { - return this._embed([document]).then((embeddings) => embeddings[0]) + async embedQuery(document: string): Promise { + const res = await this._embed([document]) + return res[0] } - embedDocuments(documents: string[]): Promise { + async embedDocuments(documents: string[]): Promise { return this._embed(documents) } } diff --git a/packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding.ts b/packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding.ts index f2f5eb4..6f79dc3 100644 --- a/packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding.ts +++ b/packages/components/nodes/embeddings/OpenAIEmbedding/OpenAIEmbedding.ts @@ -17,7 +17,7 @@ class OpenAIEmbedding_Embeddings implements INode { this.label = 'OpenAI Embeddings' this.name = 'openAIEmbeddings' this.type = 'OpenAIEmbeddings' - this.icon = 'openai.svg' + this.icon = 'openai.png' this.category = 'Embeddings' this.description = 'OpenAI API to generate embeddings for a given text' this.baseClasses = [this.type, ...getBaseClasses(OpenAIEmbeddings)] diff --git a/packages/components/nodes/embeddings/OpenAIEmbedding/openai.png b/packages/components/nodes/embeddings/OpenAIEmbedding/openai.png new file mode 100644 index 0000000..de08a05 Binary files /dev/null and b/packages/components/nodes/embeddings/OpenAIEmbedding/openai.png differ diff --git a/packages/components/nodes/embeddings/OpenAIEmbedding/openai.svg b/packages/components/nodes/embeddings/OpenAIEmbedding/openai.svg deleted file mode 100644 index 9d3261d..0000000 --- a/packages/components/nodes/embeddings/OpenAIEmbedding/openai.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/packages/components/nodes/llms/OpenAI/OpenAI.ts b/packages/components/nodes/llms/OpenAI/OpenAI.ts index 884cf63..50aa1c6 100644 --- a/packages/components/nodes/llms/OpenAI/OpenAI.ts +++ b/packages/components/nodes/llms/OpenAI/OpenAI.ts @@ -17,7 +17,7 @@ class OpenAI_LLMs implements INode { this.label = 'OpenAI' this.name = 'openAI' this.type = 'OpenAI' - this.icon = 'openai.svg' + this.icon = 'openai.png' this.category = 'LLMs' this.description = 'Wrapper around OpenAI large language models' this.baseClasses = [this.type, ...getBaseClasses(OpenAI)] diff --git a/packages/components/nodes/llms/OpenAI/openai.png b/packages/components/nodes/llms/OpenAI/openai.png new file mode 100644 index 0000000..de08a05 Binary files /dev/null and b/packages/components/nodes/llms/OpenAI/openai.png differ diff --git a/packages/components/nodes/llms/OpenAI/openai.svg b/packages/components/nodes/llms/OpenAI/openai.svg deleted file mode 100644 index 9d3261d..0000000 --- a/packages/components/nodes/llms/OpenAI/openai.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/packages/components/nodes/llms/Replicate/Replicate.ts b/packages/components/nodes/llms/Replicate/Replicate.ts new file mode 100644 index 0000000..144874d --- /dev/null +++ b/packages/components/nodes/llms/Replicate/Replicate.ts @@ -0,0 +1,122 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { Replicate, ReplicateInput } from 'langchain/llms/replicate' + +class Replicate_LLMs implements INode { + label: string + name: string + type: string + icon: string + category: string + description: string + baseClasses: string[] + credential: INodeParams + inputs: INodeParams[] + + constructor() { + this.label = 'Replicate' + this.name = 'replicate' + this.type = 'Replicate' + this.icon = 'replicate.svg' + this.category = 'LLMs' + this.description = 'Use Replicate to run open source models on cloud' + this.baseClasses = [this.type, 'BaseChatModel', ...getBaseClasses(Replicate)] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['replicateApi'] + } + this.inputs = [ + { + label: 'Model', + name: 'model', + type: 'string', + placeholder: 'a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5', + optional: true + }, + { + label: 'Temperature', + name: 'temperature', + type: 'number', + description: + 'Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.', + default: 0.7, + optional: true + }, + { + label: 'Max Tokens', + name: 'maxTokens', + type: 'number', + description: 'Maximum number of tokens to generate. A word is generally 2-3 tokens', + optional: true, + additionalParams: true + }, + { + label: 'Top Probability', + name: 'topP', + type: 'number', + description: + 'When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens', + optional: true, + additionalParams: true + }, + { + label: 'Repetition Penalty', + name: 'repetitionPenalty', + type: 'number', + description: + 'Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it. (minimum: 0.01; maximum: 5)', + optional: true, + additionalParams: true + }, + { + label: 'Additional Inputs', + name: 'additionalInputs', + type: 'json', + description: + 'Each model has different parameters, refer to the specific model accepted inputs. For example: llama13b-v2', + additionalParams: true, + optional: true + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const modelName = nodeData.inputs?.model as string + const temperature = nodeData.inputs?.temperature as string + const maxTokens = nodeData.inputs?.maxTokens as string + const topP = nodeData.inputs?.topP as string + const repetitionPenalty = nodeData.inputs?.repetitionPenalty as string + const additionalInputs = nodeData.inputs?.additionalInputs as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const apiKey = getCredentialParam('apiKey', credentialData, nodeData) + + const version = modelName.split(':').pop() + const name = modelName.split(':')[0].split('/').pop() + const org = modelName.split(':')[0].split('/')[0] + + const obj: ReplicateInput = { + model: `${org}/${name}:${version}`, + apiKey + } + + let inputs: any = {} + if (maxTokens) inputs.max_length = parseInt(maxTokens, 10) + if (temperature) inputs.temperature = parseFloat(temperature) + if (topP) inputs.top_p = parseFloat(topP) + if (repetitionPenalty) inputs.repetition_penalty = parseFloat(repetitionPenalty) + if (additionalInputs) { + const parsedInputs = + typeof additionalInputs === 'object' ? additionalInputs : additionalInputs ? JSON.parse(additionalInputs) : {} + inputs = { ...inputs, ...parsedInputs } + } + if (Object.keys(inputs).length) obj.input = inputs + + const model = new Replicate(obj) + return model + } +} + +module.exports = { nodeClass: Replicate_LLMs } diff --git a/packages/components/nodes/llms/Replicate/replicate.svg b/packages/components/nodes/llms/Replicate/replicate.svg new file mode 100644 index 0000000..2e46453 --- /dev/null +++ b/packages/components/nodes/llms/Replicate/replicate.svg @@ -0,0 +1,7 @@ + \ No newline at end of file diff --git a/packages/components/nodes/memory/DynamoDb/DynamoDb.ts b/packages/components/nodes/memory/DynamoDb/DynamoDb.ts index d9fc75d..71f8166 100644 --- a/packages/components/nodes/memory/DynamoDb/DynamoDb.ts +++ b/packages/components/nodes/memory/DynamoDb/DynamoDb.ts @@ -63,39 +63,49 @@ class DynamoDb_Memory implements INode { } ] } + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { - const tableName = nodeData.inputs?.tableName as string - const partitionKey = nodeData.inputs?.partitionKey as string - const sessionId = nodeData.inputs?.sessionId as string - const region = nodeData.inputs?.region as string - const memoryKey = nodeData.inputs?.memoryKey as string + return initalizeDynamoDB(nodeData, options) + } + + async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { + const dynamodbMemory = await initalizeDynamoDB(nodeData, options) + await dynamodbMemory.clear() + } +} + +const initalizeDynamoDB = async (nodeData: INodeData, options: ICommonObject): Promise => { + const tableName = nodeData.inputs?.tableName as string + const partitionKey = nodeData.inputs?.partitionKey as string + const sessionId = nodeData.inputs?.sessionId as string + const region = nodeData.inputs?.region as string + const memoryKey = nodeData.inputs?.memoryKey as string - const chatId = options.chatId + const chatId = options.chatId - const credentialData = await getCredentialData(nodeData.credential ?? '', options) - const accessKey = getCredentialParam('accessKey', credentialData, nodeData) - const secretAccessKey = getCredentialParam('secretAccessKey', credentialData, nodeData) + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const accessKeyId = getCredentialParam('accessKey', credentialData, nodeData) + const secretAccessKey = getCredentialParam('secretAccessKey', credentialData, nodeData) - const dynamoDb = new DynamoDBChatMessageHistory({ - tableName, - partitionKey, - sessionId: sessionId ? sessionId : chatId, - config: { - region, - credentials: { - accessKeyId: accessKey, - secretAccessKey - } + const dynamoDb = new DynamoDBChatMessageHistory({ + tableName, + partitionKey, + sessionId: sessionId ? sessionId : chatId, + config: { + region, + credentials: { + accessKeyId, + secretAccessKey } - }) + } + }) - const memory = new BufferMemory({ - memoryKey, - chatHistory: dynamoDb, - returnMessages: true - }) - return memory - } + const memory = new BufferMemory({ + memoryKey, + chatHistory: dynamoDb, + returnMessages: true + }) + return memory } module.exports = { nodeClass: DynamoDb_Memory } diff --git a/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts b/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts index 904bd67..a66045d 100644 --- a/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts +++ b/packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts @@ -58,37 +58,46 @@ class MotorMemory_Memory implements INode { } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { - const memoryKey = nodeData.inputs?.memoryKey as string - const baseURL = nodeData.inputs?.baseURL as string - const sessionId = nodeData.inputs?.sessionId as string + return initalizeMotorhead(nodeData, options) + } - const chatId = options?.chatId as string + async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { + const motorhead = await initalizeMotorhead(nodeData, options) + await motorhead.clear() + } +} - const credentialData = await getCredentialData(nodeData.credential ?? '', options) - const apiKey = getCredentialParam('apiKey', credentialData, nodeData) - const clientId = getCredentialParam('clientId', credentialData, nodeData) +const initalizeMotorhead = async (nodeData: INodeData, options: ICommonObject): Promise => { + const memoryKey = nodeData.inputs?.memoryKey as string + const baseURL = nodeData.inputs?.baseURL as string + const sessionId = nodeData.inputs?.sessionId as string - let obj: MotorheadMemoryInput = { - returnMessages: true, - sessionId: sessionId ? sessionId : chatId, - memoryKey - } + const chatId = options?.chatId as string - if (baseURL) { - obj = { - ...obj, - url: baseURL - } - } else { - obj = { - ...obj, - apiKey, - clientId - } - } + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const apiKey = getCredentialParam('apiKey', credentialData, nodeData) + const clientId = getCredentialParam('clientId', credentialData, nodeData) + + let obj: MotorheadMemoryInput = { + returnMessages: true, + sessionId: sessionId ? sessionId : chatId, + memoryKey + } - return new MotorheadMemory(obj) + if (baseURL) { + obj = { + ...obj, + url: baseURL + } + } else { + obj = { + ...obj, + apiKey, + clientId + } } + + return new MotorheadMemory(obj) } module.exports = { nodeClass: MotorMemory_Memory } diff --git a/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts b/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts index 37f1cbe..a1cf3ed 100644 --- a/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts +++ b/packages/components/nodes/memory/RedisBackedChatMemory/RedisBackedChatMemory.ts @@ -58,31 +58,40 @@ class RedisBackedChatMemory_Memory implements INode { } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { - const baseURL = nodeData.inputs?.baseURL as string - const sessionId = nodeData.inputs?.sessionId as string - const sessionTTL = nodeData.inputs?.sessionTTL as number - const memoryKey = nodeData.inputs?.memoryKey as string + return initalizeRedis(nodeData, options) + } - const chatId = options?.chatId as string + async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { + const redis = initalizeRedis(nodeData, options) + redis.clear() + } +} - const redisClient = createClient({ url: baseURL }) - let obj: RedisChatMessageHistoryInput = { - sessionId: sessionId ? sessionId : chatId, - client: redisClient - } +const initalizeRedis = (nodeData: INodeData, options: ICommonObject): BufferMemory => { + const baseURL = nodeData.inputs?.baseURL as string + const sessionId = nodeData.inputs?.sessionId as string + const sessionTTL = nodeData.inputs?.sessionTTL as number + const memoryKey = nodeData.inputs?.memoryKey as string - if (sessionTTL) { - obj = { - ...obj, - sessionTTL - } - } + const chatId = options?.chatId as string - let redisChatMessageHistory = new RedisChatMessageHistory(obj) - let redis = new BufferMemory({ memoryKey, chatHistory: redisChatMessageHistory, returnMessages: true }) + const redisClient = createClient({ url: baseURL }) + let obj: RedisChatMessageHistoryInput = { + sessionId: sessionId ? sessionId : chatId, + client: redisClient + } - return redis + if (sessionTTL) { + obj = { + ...obj, + sessionTTL + } } + + let redisChatMessageHistory = new RedisChatMessageHistory(obj) + let redis = new BufferMemory({ memoryKey, chatHistory: redisChatMessageHistory, returnMessages: true }) + + return redis } module.exports = { nodeClass: RedisBackedChatMemory_Memory } diff --git a/packages/components/nodes/memory/ZepMemory/ZepMemory.ts b/packages/components/nodes/memory/ZepMemory/ZepMemory.ts index 211f60b..497f460 100644 --- a/packages/components/nodes/memory/ZepMemory/ZepMemory.ts +++ b/packages/components/nodes/memory/ZepMemory/ZepMemory.ts @@ -107,33 +107,12 @@ class ZepMemory_Memory implements INode { } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { - const baseURL = nodeData.inputs?.baseURL as string - const aiPrefix = nodeData.inputs?.aiPrefix as string - const humanPrefix = nodeData.inputs?.humanPrefix as string - const memoryKey = nodeData.inputs?.memoryKey as string - const inputKey = nodeData.inputs?.inputKey as string const autoSummaryTemplate = nodeData.inputs?.autoSummaryTemplate as string const autoSummary = nodeData.inputs?.autoSummary as boolean - const sessionId = nodeData.inputs?.sessionId as string - const k = nodeData.inputs?.k as string - - const chatId = options?.chatId as string - const credentialData = await getCredentialData(nodeData.credential ?? '', options) - const apiKey = getCredentialParam('apiKey', credentialData, nodeData) - - const obj: ZepMemoryInput = { - baseURL, - sessionId: sessionId ? sessionId : chatId, - aiPrefix, - humanPrefix, - returnMessages: true, - memoryKey, - inputKey - } - if (apiKey) obj.apiKey = apiKey + const k = nodeData.inputs?.k as string - let zep = new ZepMemory(obj) + let zep = await initalizeZep(nodeData, options) // hack to support summary let tmpFunc = zep.loadMemoryVariables @@ -158,6 +137,38 @@ class ZepMemory_Memory implements INode { } return zep } + + async clearSessionMemory(nodeData: INodeData, options: ICommonObject): Promise { + const zep = await initalizeZep(nodeData, options) + await zep.clear() + } +} + +const initalizeZep = async (nodeData: INodeData, options: ICommonObject): Promise => { + const baseURL = nodeData.inputs?.baseURL as string + const aiPrefix = nodeData.inputs?.aiPrefix as string + const humanPrefix = nodeData.inputs?.humanPrefix as string + const memoryKey = nodeData.inputs?.memoryKey as string + const inputKey = nodeData.inputs?.inputKey as string + const sessionId = nodeData.inputs?.sessionId as string + + const chatId = options?.chatId as string + + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const apiKey = getCredentialParam('apiKey', credentialData, nodeData) + + const obj: ZepMemoryInput = { + baseURL, + sessionId: sessionId ? sessionId : chatId, + aiPrefix, + humanPrefix, + returnMessages: true, + memoryKey, + inputKey + } + if (apiKey) obj.apiKey = apiKey + + return new ZepMemory(obj) } module.exports = { nodeClass: ZepMemory_Memory } diff --git a/packages/components/nodes/prompts/ChatPromptTemplate/ChatPromptTemplate.ts b/packages/components/nodes/prompts/ChatPromptTemplate/ChatPromptTemplate.ts index 4eeb1dd..8880334 100644 --- a/packages/components/nodes/prompts/ChatPromptTemplate/ChatPromptTemplate.ts +++ b/packages/components/nodes/prompts/ChatPromptTemplate/ChatPromptTemplate.ts @@ -58,7 +58,7 @@ class ChatPromptTemplate_Prompts implements INode { let promptValues: ICommonObject = {} if (promptValuesStr) { - promptValues = JSON.parse(promptValuesStr.replace(/\s/g, '')) + promptValues = JSON.parse(promptValuesStr) } // @ts-ignore prompt.promptValues = promptValues diff --git a/packages/components/nodes/prompts/FewShotPromptTemplate/FewShotPromptTemplate.ts b/packages/components/nodes/prompts/FewShotPromptTemplate/FewShotPromptTemplate.ts index a42a1d0..3bf305a 100644 --- a/packages/components/nodes/prompts/FewShotPromptTemplate/FewShotPromptTemplate.ts +++ b/packages/components/nodes/prompts/FewShotPromptTemplate/FewShotPromptTemplate.ts @@ -86,7 +86,7 @@ class FewShotPromptTemplate_Prompts implements INode { const examplePrompt = nodeData.inputs?.examplePrompt as PromptTemplate const inputVariables = getInputVariables(suffix) - const examples: Example[] = JSON.parse(examplesStr.replace(/\s/g, '')) + const examples: Example[] = JSON.parse(examplesStr) try { const obj: FewShotPromptTemplateInput = { diff --git a/packages/components/nodes/prompts/PromptTemplate/PromptTemplate.ts b/packages/components/nodes/prompts/PromptTemplate/PromptTemplate.ts index f9c6c53..bd5740d 100644 --- a/packages/components/nodes/prompts/PromptTemplate/PromptTemplate.ts +++ b/packages/components/nodes/prompts/PromptTemplate/PromptTemplate.ts @@ -45,7 +45,7 @@ class PromptTemplate_Prompts implements INode { let promptValues: ICommonObject = {} if (promptValuesStr) { - promptValues = JSON.parse(promptValuesStr.replace(/\s/g, '')) + promptValues = JSON.parse(promptValuesStr) } const inputVariables = getInputVariables(template) diff --git a/packages/components/nodes/retrievers/HydeRetriever/HydeRetriever.ts b/packages/components/nodes/retrievers/HydeRetriever/HydeRetriever.ts new file mode 100644 index 0000000..a90f987 --- /dev/null +++ b/packages/components/nodes/retrievers/HydeRetriever/HydeRetriever.ts @@ -0,0 +1,121 @@ +import { VectorStore } from 'langchain/vectorstores/base' +import { INode, INodeData, INodeParams } from '../../../src/Interface' +import { HydeRetriever, HydeRetrieverOptions, PromptKey } from 'langchain/retrievers/hyde' +import { BaseLanguageModel } from 'langchain/base_language' +import { PromptTemplate } from 'langchain/prompts' + +class HydeRetriever_Retrievers implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + inputs: INodeParams[] + + constructor() { + this.label = 'Hyde Retriever' + this.name = 'HydeRetriever' + this.type = 'HydeRetriever' + this.icon = 'hyderetriever.svg' + this.category = 'Retrievers' + this.description = 'Use HyDE retriever to retrieve from a vector store' + this.baseClasses = [this.type, 'BaseRetriever'] + this.inputs = [ + { + label: 'Language Model', + name: 'model', + type: 'BaseLanguageModel' + }, + { + label: 'Vector Store', + name: 'vectorStore', + type: 'VectorStore' + }, + { + label: 'Prompt Key', + name: 'promptKey', + type: 'options', + options: [ + { + label: 'websearch', + name: 'websearch' + }, + { + label: 'scifact', + name: 'scifact' + }, + { + label: 'arguana', + name: 'arguana' + }, + { + label: 'trec-covid', + name: 'trec-covid' + }, + { + label: 'fiqa', + name: 'fiqa' + }, + { + label: 'dbpedia-entity', + name: 'dbpedia-entity' + }, + { + label: 'trec-news', + name: 'trec-news' + }, + { + label: 'mr-tydi', + name: 'mr-tydi' + } + ], + default: 'websearch' + }, + { + label: 'Custom Prompt', + name: 'customPrompt', + description: 'If custom prompt is used, this will override Prompt Key', + placeholder: 'Please write a passage to answer the question\nQuestion: {question}\nPassage:', + type: 'string', + rows: 4, + additionalParams: true, + optional: true + }, + { + label: 'Top K', + name: 'topK', + description: 'Number of top results to fetch. Default to 4', + placeholder: '4', + type: 'number', + default: 4, + additionalParams: true, + optional: true + } + ] + } + + async init(nodeData: INodeData): Promise { + const llm = nodeData.inputs?.model as BaseLanguageModel + const vectorStore = nodeData.inputs?.vectorStore as VectorStore + const promptKey = nodeData.inputs?.promptKey as PromptKey + const customPrompt = nodeData.inputs?.customPrompt as string + const topK = nodeData.inputs?.topK as string + const k = topK ? parseInt(topK, 10) : 4 + + const obj: HydeRetrieverOptions = { + llm, + vectorStore, + k + } + + if (customPrompt) obj.promptTemplate = PromptTemplate.fromTemplate(customPrompt) + else if (promptKey) obj.promptTemplate = promptKey + + const retriever = new HydeRetriever(obj) + return retriever + } +} + +module.exports = { nodeClass: HydeRetriever_Retrievers } diff --git a/packages/components/nodes/retrievers/HydeRetriever/hyderetriever.svg b/packages/components/nodes/retrievers/HydeRetriever/hyderetriever.svg new file mode 100644 index 0000000..da3a9f2 --- /dev/null +++ b/packages/components/nodes/retrievers/HydeRetriever/hyderetriever.svg @@ -0,0 +1,9 @@ + + + + + + + + + \ No newline at end of file diff --git a/packages/components/nodes/textsplitters/HtmlToMarkdownTextSplitter/HtmlToMarkdownTextSplitter.ts b/packages/components/nodes/textsplitters/HtmlToMarkdownTextSplitter/HtmlToMarkdownTextSplitter.ts new file mode 100644 index 0000000..161cb89 --- /dev/null +++ b/packages/components/nodes/textsplitters/HtmlToMarkdownTextSplitter/HtmlToMarkdownTextSplitter.ts @@ -0,0 +1,70 @@ +import { INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses } from '../../../src/utils' +import { MarkdownTextSplitter, MarkdownTextSplitterParams } from 'langchain/text_splitter' +import { NodeHtmlMarkdown } from 'node-html-markdown' + +class HtmlToMarkdownTextSplitter_TextSplitters implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + inputs: INodeParams[] + + constructor() { + this.label = 'HtmlToMarkdown Text Splitter' + this.name = 'htmlToMarkdownTextSplitter' + this.type = 'HtmlToMarkdownTextSplitter' + this.icon = 'htmlToMarkdownTextSplitter.svg' + this.category = 'Text Splitters' + this.description = `Converts Html to Markdown and then split your content into documents based on the Markdown headers` + this.baseClasses = [this.type, ...getBaseClasses(HtmlToMarkdownTextSplitter)] + this.inputs = [ + { + label: 'Chunk Size', + name: 'chunkSize', + type: 'number', + default: 1000, + optional: true + }, + { + label: 'Chunk Overlap', + name: 'chunkOverlap', + type: 'number', + optional: true + } + ] + } + + async init(nodeData: INodeData): Promise { + const chunkSize = nodeData.inputs?.chunkSize as string + const chunkOverlap = nodeData.inputs?.chunkOverlap as string + + const obj = {} as MarkdownTextSplitterParams + + if (chunkSize) obj.chunkSize = parseInt(chunkSize, 10) + if (chunkOverlap) obj.chunkOverlap = parseInt(chunkOverlap, 10) + + const splitter = new HtmlToMarkdownTextSplitter(obj) + + return splitter + } +} +class HtmlToMarkdownTextSplitter extends MarkdownTextSplitter implements MarkdownTextSplitterParams { + constructor(fields?: Partial) { + { + super(fields) + } + } + splitText(text: string): Promise { + return new Promise((resolve) => { + const markdown = NodeHtmlMarkdown.translate(text) + super.splitText(markdown).then((result) => { + resolve(result) + }) + }) + } +} +module.exports = { nodeClass: HtmlToMarkdownTextSplitter_TextSplitters } diff --git a/packages/components/nodes/textsplitters/HtmlToMarkdownTextSplitter/htmlToMarkdownTextSplitter.svg b/packages/components/nodes/textsplitters/HtmlToMarkdownTextSplitter/htmlToMarkdownTextSplitter.svg new file mode 100644 index 0000000..f7d45d6 --- /dev/null +++ b/packages/components/nodes/textsplitters/HtmlToMarkdownTextSplitter/htmlToMarkdownTextSplitter.svg @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/packages/components/nodes/tools/BraveSearchAPI/BraveSearchAPI.ts b/packages/components/nodes/tools/BraveSearchAPI/BraveSearchAPI.ts new file mode 100644 index 0000000..037fd13 --- /dev/null +++ b/packages/components/nodes/tools/BraveSearchAPI/BraveSearchAPI.ts @@ -0,0 +1,40 @@ +import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { BraveSearch } from 'langchain/tools' + +class BraveSearchAPI_Tools implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + credential: INodeParams + inputs: INodeParams[] + + constructor() { + this.label = 'BraveSearch API' + this.name = 'braveSearchAPI' + this.type = 'BraveSearchAPI' + this.icon = 'brave.svg' + this.category = 'Tools' + this.description = 'Wrapper around BraveSearch API - a real-time API to access Brave search results' + this.inputs = [] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + credentialNames: ['braveSearchApi'] + } + this.baseClasses = [this.type, ...getBaseClasses(BraveSearch)] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const braveApiKey = getCredentialParam('braveApiKey', credentialData, nodeData) + return new BraveSearch({ apiKey: braveApiKey }) + } +} + +module.exports = { nodeClass: BraveSearchAPI_Tools } diff --git a/packages/components/nodes/tools/BraveSearchAPI/brave.svg b/packages/components/nodes/tools/BraveSearchAPI/brave.svg new file mode 100644 index 0000000..0c0c0e8 --- /dev/null +++ b/packages/components/nodes/tools/BraveSearchAPI/brave.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/packages/components/nodes/tools/CustomTool/core.ts b/packages/components/nodes/tools/CustomTool/core.ts index 0d3d7bc..12dd72f 100644 --- a/packages/components/nodes/tools/CustomTool/core.ts +++ b/packages/components/nodes/tools/CustomTool/core.ts @@ -2,7 +2,37 @@ import { z } from 'zod' import { CallbackManagerForToolRun } from 'langchain/callbacks' import { StructuredTool, ToolParams } from 'langchain/tools' import { NodeVM } from 'vm2' -import { availableDependencies } from '../../../src/utils' + +/* + * List of dependencies allowed to be import in vm2 + */ +const availableDependencies = [ + '@dqbd/tiktoken', + '@getzep/zep-js', + '@huggingface/inference', + '@pinecone-database/pinecone', + '@supabase/supabase-js', + 'axios', + 'cheerio', + 'chromadb', + 'cohere-ai', + 'd3-dsv', + 'form-data', + 'graphql', + 'html-to-text', + 'langchain', + 'linkifyjs', + 'mammoth', + 'moment', + 'node-fetch', + 'pdf-parse', + 'pdfjs-dist', + 'playwright', + 'puppeteer', + 'srt-parser-2', + 'typeorm', + 'weaviate-ts-client' +] export interface BaseDynamicToolInput extends ToolParams { name: string @@ -51,25 +81,37 @@ export class DynamicStructuredTool< } } + const defaultAllowBuiltInDep = [ + 'assert', + 'buffer', + 'crypto', + 'events', + 'http', + 'https', + 'net', + 'path', + 'querystring', + 'timers', + 'tls', + 'url', + 'zlib' + ] + + const builtinDeps = process.env.TOOL_FUNCTION_BUILTIN_DEP + ? defaultAllowBuiltInDep.concat(process.env.TOOL_FUNCTION_BUILTIN_DEP.split(',')) + : defaultAllowBuiltInDep + const externalDeps = process.env.TOOL_FUNCTION_EXTERNAL_DEP ? process.env.TOOL_FUNCTION_EXTERNAL_DEP.split(',') : [] + const deps = availableDependencies.concat(externalDeps) + const options = { console: 'inherit', sandbox, require: { - external: false as boolean | { modules: string[] }, - builtin: ['*'] + external: { modules: deps }, + builtin: builtinDeps } } as any - const external = JSON.stringify(availableDependencies) - if (external) { - const deps = JSON.parse(external) - if (deps && deps.length) { - options.require.external = { - modules: deps - } - } - } - const vm = new NodeVM(options) const response = await vm.run(`module.exports = async function() {${this.code}}()`, __dirname) diff --git a/packages/components/nodes/vectorstores/Singlestore_Existing/Singlestore_Existing.ts b/packages/components/nodes/vectorstores/Singlestore_Existing/Singlestore_Existing.ts new file mode 100644 index 0000000..15bc9ac --- /dev/null +++ b/packages/components/nodes/vectorstores/Singlestore_Existing/Singlestore_Existing.ts @@ -0,0 +1,144 @@ +import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { Embeddings } from 'langchain/embeddings/base' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { SingleStoreVectorStore, SingleStoreVectorStoreConfig } from 'langchain/vectorstores/singlestore' + +class SingleStoreExisting_VectorStores implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + inputs: INodeParams[] + credential: INodeParams + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'SingleStore Load Existing Table' + this.name = 'singlestoreExisting' + this.type = 'SingleStore' + this.icon = 'singlestore.svg' + this.category = 'Vector Stores' + this.description = 'Load existing document from SingleStore' + this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + description: 'Needed when using SingleStore cloud hosted', + optional: true, + credentialNames: ['singleStoreApi'] + } + this.inputs = [ + { + label: 'Embeddings', + name: 'embeddings', + type: 'Embeddings' + }, + { + label: 'Host', + name: 'host', + type: 'string' + }, + { + label: 'Database', + name: 'database', + type: 'string' + }, + { + label: 'Table Name', + name: 'tableName', + type: 'string', + placeholder: 'embeddings', + additionalParams: true, + optional: true + }, + { + label: 'Content Column Name', + name: 'contentColumnName', + type: 'string', + placeholder: 'content', + additionalParams: true, + optional: true + }, + { + label: 'Vector Column Name', + name: 'vectorColumnName', + type: 'string', + placeholder: 'vector', + additionalParams: true, + optional: true + }, + { + label: 'Metadata Column Name', + name: 'metadataColumnName', + type: 'string', + placeholder: 'metadata', + additionalParams: true, + optional: true + }, + { + label: 'Top K', + name: 'topK', + placeholder: '4', + type: 'number', + additionalParams: true, + optional: true + } + ] + this.outputs = [ + { + label: 'SingleStore Retriever', + name: 'retriever', + baseClasses: this.baseClasses + }, + { + label: 'SingleStore Vector Store', + name: 'vectorStore', + baseClasses: [this.type, ...getBaseClasses(SingleStoreVectorStore)] + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const user = getCredentialParam('user', credentialData, nodeData) + const password = getCredentialParam('password', credentialData, nodeData) + + const singleStoreConnectionConfig = { + connectionOptions: { + host: nodeData.inputs?.host as string, + port: 3306, + user, + password, + database: nodeData.inputs?.database as string + }, + ...(nodeData.inputs?.tableName ? { tableName: nodeData.inputs.tableName as string } : {}), + ...(nodeData.inputs?.contentColumnName ? { contentColumnName: nodeData.inputs.contentColumnName as string } : {}), + ...(nodeData.inputs?.vectorColumnName ? { vectorColumnName: nodeData.inputs.vectorColumnName as string } : {}), + ...(nodeData.inputs?.metadataColumnName ? { metadataColumnName: nodeData.inputs.metadataColumnName as string } : {}) + } as SingleStoreVectorStoreConfig + + const embeddings = nodeData.inputs?.embeddings as Embeddings + const output = nodeData.outputs?.output as string + const topK = nodeData.inputs?.topK as string + const k = topK ? parseInt(topK, 10) : 4 + + let vectorStore: SingleStoreVectorStore + + vectorStore = new SingleStoreVectorStore(embeddings, singleStoreConnectionConfig) + + if (output === 'retriever') { + const retriever = vectorStore.asRetriever(k) + return retriever + } else if (output === 'vectorStore') { + ;(vectorStore as any).k = k + return vectorStore + } + return vectorStore + } +} + +module.exports = { nodeClass: SingleStoreExisting_VectorStores } diff --git a/packages/components/nodes/vectorstores/Singlestore_Existing/singlestore.svg b/packages/components/nodes/vectorstores/Singlestore_Existing/singlestore.svg new file mode 100644 index 0000000..bd8dc81 --- /dev/null +++ b/packages/components/nodes/vectorstores/Singlestore_Existing/singlestore.svg @@ -0,0 +1,20 @@ + + + SingleStore + + + + + + + + + + + + + + + + + diff --git a/packages/components/nodes/vectorstores/Singlestore_Upsert/Singlestore_Upsert.ts b/packages/components/nodes/vectorstores/Singlestore_Upsert/Singlestore_Upsert.ts new file mode 100644 index 0000000..bbff67c --- /dev/null +++ b/packages/components/nodes/vectorstores/Singlestore_Upsert/Singlestore_Upsert.ts @@ -0,0 +1,160 @@ +import { ICommonObject, INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface' +import { Embeddings } from 'langchain/embeddings/base' +import { Document } from 'langchain/document' +import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils' +import { SingleStoreVectorStore, SingleStoreVectorStoreConfig } from 'langchain/vectorstores/singlestore' +import { flatten } from 'lodash' + +class SingleStoreUpsert_VectorStores implements INode { + label: string + name: string + description: string + type: string + icon: string + category: string + baseClasses: string[] + inputs: INodeParams[] + credential: INodeParams + outputs: INodeOutputsValue[] + + constructor() { + this.label = 'SingleStore Upsert Document' + this.name = 'singlestoreUpsert' + this.type = 'SingleStore' + this.icon = 'singlestore.svg' + this.category = 'Vector Stores' + this.description = 'Upsert documents to SingleStore' + this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever'] + this.credential = { + label: 'Connect Credential', + name: 'credential', + type: 'credential', + description: 'Needed when using SingleStore cloud hosted', + optional: true, + credentialNames: ['singleStoreApi'] + } + this.inputs = [ + { + label: 'Document', + name: 'document', + type: 'Document', + list: true + }, + { + label: 'Embeddings', + name: 'embeddings', + type: 'Embeddings' + }, + { + label: 'Host', + name: 'host', + type: 'string' + }, + { + label: 'Database', + name: 'database', + type: 'string' + }, + { + label: 'Table Name', + name: 'tableName', + type: 'string', + placeholder: 'embeddings', + additionalParams: true, + optional: true + }, + { + label: 'Content Column Name', + name: 'contentColumnName', + type: 'string', + placeholder: 'content', + additionalParams: true, + optional: true + }, + { + label: 'Vector Column Name', + name: 'vectorColumnName', + type: 'string', + placeholder: 'vector', + additionalParams: true, + optional: true + }, + { + label: 'Metadata Column Name', + name: 'metadataColumnName', + type: 'string', + placeholder: 'metadata', + additionalParams: true, + optional: true + }, + { + label: 'Top K', + name: 'topK', + placeholder: '4', + type: 'number', + additionalParams: true, + optional: true + } + ] + this.outputs = [ + { + label: 'SingleStore Retriever', + name: 'retriever', + baseClasses: this.baseClasses + }, + { + label: 'SingleStore Vector Store', + name: 'vectorStore', + baseClasses: [this.type, ...getBaseClasses(SingleStoreVectorStore)] + } + ] + } + + async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { + const credentialData = await getCredentialData(nodeData.credential ?? '', options) + const user = getCredentialParam('user', credentialData, nodeData) + const password = getCredentialParam('password', credentialData, nodeData) + + const singleStoreConnectionConfig = { + connectionOptions: { + host: nodeData.inputs?.host as string, + port: 3306, + user, + password, + database: nodeData.inputs?.database as string + }, + ...(nodeData.inputs?.tableName ? { tableName: nodeData.inputs.tableName as string } : {}), + ...(nodeData.inputs?.contentColumnName ? { contentColumnName: nodeData.inputs.contentColumnName as string } : {}), + ...(nodeData.inputs?.vectorColumnName ? { vectorColumnName: nodeData.inputs.vectorColumnName as string } : {}), + ...(nodeData.inputs?.metadataColumnName ? { metadataColumnName: nodeData.inputs.metadataColumnName as string } : {}) + } as SingleStoreVectorStoreConfig + + const docs = nodeData.inputs?.document as Document[] + const embeddings = nodeData.inputs?.embeddings as Embeddings + const output = nodeData.outputs?.output as string + const topK = nodeData.inputs?.topK as string + const k = topK ? parseInt(topK, 10) : 4 + + const flattenDocs = docs && docs.length ? flatten(docs) : [] + const finalDocs = [] + for (let i = 0; i < flattenDocs.length; i += 1) { + finalDocs.push(new Document(flattenDocs[i])) + } + + let vectorStore: SingleStoreVectorStore + + vectorStore = new SingleStoreVectorStore(embeddings, singleStoreConnectionConfig) + vectorStore.addDocuments.bind(vectorStore)(finalDocs) + + if (output === 'retriever') { + const retriever = vectorStore.asRetriever(k) + return retriever + } else if (output === 'vectorStore') { + ;(vectorStore as any).k = k + return vectorStore + } + return vectorStore + } +} + +module.exports = { nodeClass: SingleStoreUpsert_VectorStores } diff --git a/packages/components/nodes/vectorstores/Singlestore_Upsert/singlestore.svg b/packages/components/nodes/vectorstores/Singlestore_Upsert/singlestore.svg new file mode 100644 index 0000000..bd8dc81 --- /dev/null +++ b/packages/components/nodes/vectorstores/Singlestore_Upsert/singlestore.svg @@ -0,0 +1,20 @@ + + + SingleStore + + + + + + + + + + + + + + + + + diff --git a/packages/components/package.json b/packages/components/package.json index 8da1253..01738a7 100644 --- a/packages/components/package.json +++ b/packages/components/package.json @@ -1,6 +1,6 @@ { "name": "flowise-components", - "version": "1.2.16", + "version": "1.2.17", "description": "Flowiseai Components", "main": "dist/src/index", "types": "dist/src/index.d.ts", @@ -18,13 +18,13 @@ "dependencies": { "@aws-sdk/client-dynamodb": "^3.360.0", "@dqbd/tiktoken": "^1.0.7", - "@getzep/zep-js": "^0.3.1", + "@getzep/zep-js": "^0.4.1", "@huggingface/inference": "^2.6.1", - "@notionhq/client": "^2.2.7", + "@notionhq/client": "^2.2.8", "@opensearch-project/opensearch": "^1.2.0", - "@pinecone-database/pinecone": "^0.0.12", + "@pinecone-database/pinecone": "^0.0.14", "@qdrant/js-client-rest": "^1.2.2", - "@supabase/supabase-js": "^2.21.0", + "@supabase/supabase-js": "^2.29.0", "@types/js-yaml": "^4.0.5", "@types/jsdom": "^21.1.1", "axios": "^0.27.2", @@ -38,17 +38,21 @@ "form-data": "^4.0.0", "graphql": "^16.6.0", "html-to-text": "^9.0.5", - "langchain": "^0.0.110", + "langchain": "^0.0.117", "linkifyjs": "^4.1.1", "mammoth": "^1.5.1", "moment": "^2.29.3", + "mysql2": "^3.5.1", "node-fetch": "^2.6.11", + "node-html-markdown": "^1.3.0", "notion-to-md": "^3.1.1", "pdf-parse": "^1.1.1", "pdfjs-dist": "^3.7.107", "playwright": "^1.35.0", "puppeteer": "^20.7.1", + "pyodide": ">=0.21.0-alpha.2", "redis": "^4.6.7", + "replicate": "^0.12.3", "srt-parser-2": "^1.2.3", "vm2": "^3.9.19", "weaviate-ts-client": "^1.1.0", diff --git a/packages/components/src/Interface.ts b/packages/components/src/Interface.ts index 4a69a9a..d88ac46 100644 --- a/packages/components/src/Interface.ts +++ b/packages/components/src/Interface.ts @@ -98,6 +98,7 @@ export interface INode extends INodeProperties { } init?(nodeData: INodeData, input: string, options?: ICommonObject): Promise run?(nodeData: INodeData, input: string, options?: ICommonObject): Promise + clearSessionMemory?(nodeData: INodeData, options?: ICommonObject): Promise } export interface INodeData extends INodeProperties { diff --git a/packages/components/src/utils.ts b/packages/components/src/utils.ts index f6bf87f..8167a35 100644 --- a/packages/components/src/utils.ts +++ b/packages/components/src/utils.ts @@ -323,7 +323,7 @@ export async function xmlScrape(currentURL: string, limit: number): Promise { @@ -418,7 +417,7 @@ export const getCredentialData = async (selectedCredentialId: string, options: I id: selectedCredentialId }) - if (!credential) throw new Error(`Credential ${selectedCredentialId} not found`) + if (!credential) return {} // Decrpyt credentialData const decryptedCredentialData = await decryptCredentialData(credential.encryptedData) @@ -430,36 +429,52 @@ export const getCredentialData = async (selectedCredentialId: string, options: I } export const getCredentialParam = (paramName: string, credentialData: ICommonObject, nodeData: INodeData): any => { - return (nodeData.inputs as ICommonObject)[paramName] ?? credentialData[paramName] + return (nodeData.inputs as ICommonObject)[paramName] ?? credentialData[paramName] ?? undefined } -/* - * List of dependencies allowed to be import in vm2 - */ -export const availableDependencies = [ - '@dqbd/tiktoken', - '@getzep/zep-js', - '@huggingface/inference', - '@pinecone-database/pinecone', - '@supabase/supabase-js', - 'axios', - 'cheerio', - 'chromadb', - 'cohere-ai', - 'd3-dsv', - 'form-data', - 'graphql', - 'html-to-text', - 'langchain', - 'linkifyjs', - 'mammoth', - 'moment', - 'node-fetch', - 'pdf-parse', - 'pdfjs-dist', - 'playwright', - 'puppeteer', - 'srt-parser-2', - 'typeorm', - 'weaviate-ts-client' +// reference https://www.freeformatter.com/json-escape.html +const jsonEscapeCharacters = [ + { escape: '"', value: 'FLOWISE_DOUBLE_QUOTE' }, + { escape: '\n', value: 'FLOWISE_NEWLINE' }, + { escape: '\b', value: 'FLOWISE_BACKSPACE' }, + { escape: '\f', value: 'FLOWISE_FORM_FEED' }, + { escape: '\r', value: 'FLOWISE_CARRIAGE_RETURN' }, + { escape: '\t', value: 'FLOWISE_TAB' }, + { escape: '\\', value: 'FLOWISE_BACKSLASH' } ] + +function handleEscapesJSONParse(input: string, reverse: Boolean): string { + for (const element of jsonEscapeCharacters) { + input = reverse ? input.replaceAll(element.value, element.escape) : input.replaceAll(element.escape, element.value) + } + return input +} + +function iterateEscapesJSONParse(input: any, reverse: Boolean): any { + for (const element in input) { + const type = typeof input[element] + if (type === 'string') input[element] = handleEscapesJSONParse(input[element], reverse) + else if (type === 'object') input[element] = iterateEscapesJSONParse(input[element], reverse) + } + return input +} + +export function handleEscapeCharacters(input: any, reverse: Boolean): any { + const type = typeof input + if (type === 'string') return handleEscapesJSONParse(input, reverse) + else if (type === 'object') return iterateEscapesJSONParse(input, reverse) + return input +} + +export const getUserHome = (): string => { + let variableName = 'HOME' + if (process.platform === 'win32') { + variableName = 'USERPROFILE' + } + + if (process.env[variableName] === undefined) { + // If for some reason the variable does not exist, fall back to current folder + return process.cwd() + } + return process.env[variableName] as string +} diff --git a/packages/components/tsconfig.json b/packages/components/tsconfig.json index 5ace3d9..d213dab 100644 --- a/packages/components/tsconfig.json +++ b/packages/components/tsconfig.json @@ -1,6 +1,6 @@ { "compilerOptions": { - "lib": ["ES2020"], + "lib": ["ES2020", "ES2021.String"], "experimentalDecorators": true /* Enable experimental support for TC39 stage 2 draft decorators. */, "emitDecoratorMetadata": true /* Emit design-type metadata for decorated declarations in source files. */, "target": "ES2020", // or higher diff --git a/packages/server/.env.example b/packages/server/.env.example index 29d592f..1e10452 100644 --- a/packages/server/.env.example +++ b/packages/server/.env.example @@ -1,11 +1,22 @@ 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 +# LOG_PATH=/your_log_path/.flowise/logs + +# DATABASE_TYPE=postgres +# DATABASE_PORT="" +# DATABASE_HOST="" +# DATABASE_NAME="flowise" +# DATABASE_USER="" +# DATABASE_PASSWORD="" +# OVERRIDE_DATABASE=true + # FLOWISE_USERNAME=user # FLOWISE_PASSWORD=1234 # DEBUG=true -# DATABASE_PATH=/your/database/path/.flowise -# APIKEY_PATH=/your/api/key/path -# SECRETKEY_PATH=/your/secret/key/path -# LOG_PATH=/your/log/path # LOG_LEVEL=debug (error | warn | info | verbose | debug) # EXECUTION_MODE=main (child | main) +# TOOL_FUNCTION_BUILTIN_DEP=crypto,fs +# TOOL_FUNCTION_EXTERNAL_DEP=moment,lodash diff --git a/packages/server/README.md b/packages/server/README.md index 377cc31..6c3bc7f 100644 --- a/packages/server/README.md +++ b/packages/server/README.md @@ -31,21 +31,7 @@ FLOWISE_PASSWORD=1234 ## 🌱 Env Variables -Flowise support different environment variables to configure your instance. You can specify the following variables in the `.env` file inside `packages/server` folder. - -| Variable | Description | Type | Default | -| ---------------- | ---------------------------------------------------------------------------- | ------------------------------------------------ | ----------------------------------- | -| PORT | The HTTP port Flowise runs on | Number | 3000 | -| PASSPHRASE | Passphrase used to create encryption key | String | `MYPASSPHRASE` | -| FLOWISE_USERNAME | Username to login | String | -| FLOWISE_PASSWORD | Password to login | String | -| DEBUG | Print logs from components | Boolean | -| LOG_PATH | Location where log files are stored | String | `your/path/Flowise/logs` | -| LOG_LEVEL | Different levels of logs | Enum String: `error`, `info`, `verbose`, `debug` | `info` | -| DATABASE_PATH | Location where database is saved | String | `your/home/dir/.flowise` | -| APIKEY_PATH | Location where api keys are saved | String | `your/path/Flowise/packages/server` | -| SECRETKEY_PATH | Location where encryption key (used to encrypt/decrypt credentials) is saved | String | `your/path/Flowise/packages/server` | -| EXECUTION_MODE | Whether predictions run in their own process or the main process | Enum String: `child`, `main` | `main` | +Flowise support different environment variables to configure your instance. You can specify the following variables in the `.env` file inside `packages/server` folder. Read [more](https://github.com/FlowiseAI/Flowise/blob/main/CONTRIBUTING.md#-env-variables) You can also specify the env variables when using `npx`. For example: diff --git a/packages/server/marketplaces/chatflows/API Agent 2.json b/packages/server/marketplaces/chatflows/API Agent OpenAI.json similarity index 99% rename from packages/server/marketplaces/chatflows/API Agent 2.json rename to packages/server/marketplaces/chatflows/API Agent OpenAI.json index cb5b3d1..c51cdaf 100644 --- a/packages/server/marketplaces/chatflows/API Agent 2.json +++ b/packages/server/marketplaces/chatflows/API Agent OpenAI.json @@ -1,5 +1,5 @@ { - "description": "Use OpenAI Function Agent to automatically decide which API to call, generating url and body request from conversation", + "description": "Use OpenAI Function Agent and Chain to automatically decide which API to call, generating url and body request from conversation", "nodes": [ { "width": 300, diff --git a/packages/server/marketplaces/chatflows/API Agent 1.json b/packages/server/marketplaces/chatflows/API Agent.json similarity index 100% rename from packages/server/marketplaces/chatflows/API Agent 1.json rename to packages/server/marketplaces/chatflows/API Agent.json diff --git a/packages/server/marketplaces/chatflows/CSV Agent.json b/packages/server/marketplaces/chatflows/CSV Agent.json new file mode 100644 index 0000000..eaaacf3 --- /dev/null +++ b/packages/server/marketplaces/chatflows/CSV Agent.json @@ -0,0 +1,226 @@ +{ + "description": "Analyse and summarize CSV data", + "nodes": [ + { + "width": 300, + "height": 377, + "id": "csvAgent_0", + "position": { + "x": 1064.0780498701288, + "y": 284.44352695304724 + }, + "type": "customNode", + "data": { + "id": "csvAgent_0", + "label": "CSV Agent", + "name": "csvAgent", + "type": "AgentExecutor", + "baseClasses": ["AgentExecutor", "BaseChain"], + "category": "Agents", + "description": "Agent used to to answer queries on CSV data", + "inputParams": [ + { + "label": "Csv File", + "name": "csvFile", + "type": "file", + "fileType": ".csv", + "id": "csvAgent_0-input-csvFile-file" + } + ], + "inputAnchors": [ + { + "label": "Language Model", + "name": "model", + "type": "BaseLanguageModel", + "id": "csvAgent_0-input-model-BaseLanguageModel" + } + ], + "inputs": { + "model": "{{chatOpenAI_0.data.instance}}" + }, + "outputAnchors": [ + { + "id": "csvAgent_0-output-csvAgent-AgentExecutor|BaseChain", + "name": "csvAgent", + "label": "AgentExecutor", + "type": "AgentExecutor | BaseChain" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1064.0780498701288, + "y": 284.44352695304724 + }, + "dragging": false + }, + { + "width": 300, + "height": 522, + "id": "chatOpenAI_0", + "position": { + "x": 657.3762197414501, + "y": 220.2950766042332 + }, + "type": "customNode", + "data": { + "id": "chatOpenAI_0", + "label": "ChatOpenAI", + "name": "chatOpenAI", + "type": "ChatOpenAI", + "baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"], + "category": "Chat Models", + "description": "Wrapper around OpenAI large language models that use the Chat endpoint", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["openAIApi"], + "id": "chatOpenAI_0-input-credential-credential" + }, + { + "label": "Model Name", + "name": "modelName", + "type": "options", + "options": [ + { + "label": "gpt-4", + "name": "gpt-4" + }, + { + "label": "gpt-4-0613", + "name": "gpt-4-0613" + }, + { + "label": "gpt-4-32k", + "name": "gpt-4-32k" + }, + { + "label": "gpt-4-32k-0613", + "name": "gpt-4-32k-0613" + }, + { + "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" + } + ], + "default": "gpt-3.5-turbo", + "optional": true, + "id": "chatOpenAI_0-input-modelName-options" + }, + { + "label": "Temperature", + "name": "temperature", + "type": "number", + "default": 0.9, + "optional": true, + "id": "chatOpenAI_0-input-temperature-number" + }, + { + "label": "Max Tokens", + "name": "maxTokens", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-maxTokens-number" + }, + { + "label": "Top Probability", + "name": "topP", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-topP-number" + }, + { + "label": "Frequency Penalty", + "name": "frequencyPenalty", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-frequencyPenalty-number" + }, + { + "label": "Presence Penalty", + "name": "presencePenalty", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-presencePenalty-number" + }, + { + "label": "Timeout", + "name": "timeout", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-timeout-number" + }, + { + "label": "BasePath", + "name": "basepath", + "type": "string", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-basepath-string" + } + ], + "inputAnchors": [], + "inputs": { + "modelName": "gpt-3.5-turbo", + "temperature": 0.9, + "maxTokens": "", + "topP": "", + "frequencyPenalty": "", + "presencePenalty": "", + "timeout": "", + "basepath": "" + }, + "outputAnchors": [ + { + "id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel", + "name": "chatOpenAI", + "label": "ChatOpenAI", + "type": "ChatOpenAI | BaseChatModel | BaseLanguageModel" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 657.3762197414501, + "y": 220.2950766042332 + }, + "dragging": false + } + ], + "edges": [ + { + "source": "chatOpenAI_0", + "sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel", + "target": "csvAgent_0", + "targetHandle": "csvAgent_0-input-model-BaseLanguageModel", + "type": "buttonedge", + "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel-csvAgent_0-csvAgent_0-input-model-BaseLanguageModel", + "data": { + "label": "" + } + } + ] +} diff --git a/packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json b/packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json index c05e56b..c6c9187 100644 --- a/packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json +++ b/packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json @@ -3,132 +3,11 @@ "nodes": [ { "width": 300, - "height": 376, - "id": "recursiveCharacterTextSplitter_1", - "position": { - "x": 422.81091375202413, - "y": 122.99825010325736 - }, - "type": "customNode", - "data": { - "id": "recursiveCharacterTextSplitter_1", - "label": "Recursive Character Text Splitter", - "name": "recursiveCharacterTextSplitter", - "type": "RecursiveCharacterTextSplitter", - "baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter"], - "category": "Text Splitters", - "description": "Split documents recursively by different characters - starting with \"\n\n\", then \"\n\", then \" \"", - "inputParams": [ - { - "label": "Chunk Size", - "name": "chunkSize", - "type": "number", - "default": 1000, - "optional": true, - "id": "recursiveCharacterTextSplitter_1-input-chunkSize-number" - }, - { - "label": "Chunk Overlap", - "name": "chunkOverlap", - "type": "number", - "optional": true, - "id": "recursiveCharacterTextSplitter_1-input-chunkOverlap-number" - } - ], - "inputAnchors": [], - "inputs": { - "chunkSize": 1000, - "chunkOverlap": "" - }, - "outputAnchors": [ - { - "id": "recursiveCharacterTextSplitter_1-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter", - "name": "recursiveCharacterTextSplitter", - "label": "RecursiveCharacterTextSplitter", - "type": "RecursiveCharacterTextSplitter | TextSplitter" - } - ], - "outputs": {}, - "selected": false - }, - "selected": false, - "positionAbsolute": { - "x": 422.81091375202413, - "y": 122.99825010325736 - }, - "dragging": false - }, - { - "width": 300, - "height": 392, - "id": "textFile_1", - "position": { - "x": 788.5395420616719, - "y": 126.30459801017741 - }, - "type": "customNode", - "data": { - "id": "textFile_1", - "label": "Text File", - "name": "textFile", - "type": "Document", - "baseClasses": ["Document"], - "category": "Document Loaders", - "description": "Load data from text files", - "inputParams": [ - { - "label": "Txt File", - "name": "txtFile", - "type": "file", - "fileType": ".txt", - "id": "textFile_1-input-txtFile-file" - }, - { - "label": "Metadata", - "name": "metadata", - "type": "json", - "optional": true, - "additionalParams": true, - "id": "textFile_1-input-metadata-json" - } - ], - "inputAnchors": [ - { - "label": "Text Splitter", - "name": "textSplitter", - "type": "TextSplitter", - "optional": true, - "id": "textFile_1-input-textSplitter-TextSplitter" - } - ], - "inputs": { - "textSplitter": "{{recursiveCharacterTextSplitter_1.data.instance}}" - }, - "outputAnchors": [ - { - "id": "textFile_1-output-textFile-Document", - "name": "textFile", - "label": "Document", - "type": "Document" - } - ], - "outputs": {}, - "selected": false - }, - "selected": false, - "positionAbsolute": { - "x": 788.5395420616719, - "y": 126.30459801017741 - }, - "dragging": false - }, - { - "width": 300, - "height": 523, + "height": 522, "id": "chatOpenAI_0", "position": { - "x": 1200.8283780918746, - "y": 12.591428916196605 + "x": 1184.1176114500388, + "y": -44.15535835370571 }, "type": "customNode", "data": { @@ -249,7 +128,7 @@ "inputAnchors": [], "inputs": { "modelName": "gpt-3.5-turbo", - "temperature": 0.9, + "temperature": "0", "maxTokens": "", "topP": "", "frequencyPenalty": "", @@ -268,129 +147,20 @@ "outputs": {}, "selected": false }, - "selected": false, "positionAbsolute": { - "x": 1200.8283780918746, - "y": 12.591428916196605 - }, - "dragging": false - }, - { - "width": 300, - "height": 480, - "id": "conversationalRetrievalQAChain_0", - "position": { - "x": 1626.7402076624098, - "y": 394.29095783927113 - }, - "type": "customNode", - "data": { - "id": "conversationalRetrievalQAChain_0", - "label": "Conversational Retrieval QA Chain", - "name": "conversationalRetrievalQAChain", - "type": "ConversationalRetrievalQAChain", - "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"], - "category": "Chains", - "description": "Document QA - built on RetrievalQAChain to provide a chat history component", - "inputParams": [ - { - "label": "Return Source Documents", - "name": "returnSourceDocuments", - "type": "boolean", - "optional": true, - "id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean" - }, - { - "label": "System Message", - "name": "systemMessagePrompt", - "type": "string", - "rows": 4, - "additionalParams": true, - "optional": true, - "placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.", - "id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string" - }, - { - "label": "Chain Option", - "name": "chainOption", - "type": "options", - "options": [ - { - "label": "MapReduceDocumentsChain", - "name": "map_reduce", - "description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time" - }, - { - "label": "RefineDocumentsChain", - "name": "refine", - "description": "Suitable for QA tasks over a large number of documents." - }, - { - "label": "StuffDocumentsChain", - "name": "stuff", - "description": "Suitable for QA tasks over a small number of documents." - } - ], - "additionalParams": true, - "optional": true, - "id": "conversationalRetrievalQAChain_0-input-chainOption-options" - } - ], - "inputAnchors": [ - { - "label": "Language Model", - "name": "model", - "type": "BaseLanguageModel", - "id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel" - }, - { - "label": "Vector Store Retriever", - "name": "vectorStoreRetriever", - "type": "BaseRetriever", - "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever" - }, - { - "label": "Memory", - "name": "memory", - "type": "DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", - "optional": true, - "description": "If no memory connected, default BufferMemory will be used", - "id": "conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory" - } - ], - "inputs": { - "model": "{{chatOpenAI_0.data.instance}}", - "vectorStoreRetriever": "{{pineconeUpsert_0.data.instance}}", - "memory": "", - "returnSourceDocuments": "", - "systemMessagePrompt": "", - "chainOption": "" - }, - "outputAnchors": [ - { - "id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain", - "name": "conversationalRetrievalQAChain", - "label": "ConversationalRetrievalQAChain", - "type": "ConversationalRetrievalQAChain | BaseChain" - } - ], - "outputs": {}, - "selected": false + "x": 1184.1176114500388, + "y": -44.15535835370571 }, "selected": false, - "positionAbsolute": { - "x": 1626.7402076624098, - "y": 394.29095783927113 - }, "dragging": false }, { "width": 300, - "height": 329, + "height": 328, "id": "openAIEmbeddings_0", "position": { - "x": 788.1802387155774, - "y": 579.9826205586049 + "x": 795.6162477805387, + "y": 603.260214150876 }, "type": "customNode", "data": { @@ -462,18 +232,18 @@ }, "selected": false, "positionAbsolute": { - "x": 788.1802387155774, - "y": 579.9826205586049 + "x": 795.6162477805387, + "y": 603.260214150876 }, "dragging": false }, { "width": 300, - "height": 555, + "height": 554, "id": "pineconeUpsert_0", "position": { - "x": 1200.8283780918746, - "y": 588.825080688097 + "x": 1191.1792786926865, + "y": 514.2126330994578 }, "type": "customNode", "data": { @@ -534,7 +304,7 @@ } ], "inputs": { - "document": ["{{textFile_1.data.instance}}"], + "document": ["{{textFile_0.data.instance}}"], "embeddings": "{{openAIEmbeddings_0.data.instance}}", "pineconeIndex": "", "pineconeNamespace": "", @@ -569,53 +339,283 @@ }, "selected": false, "positionAbsolute": { - "x": 1200.8283780918746, - "y": 588.825080688097 + "x": 1191.1792786926865, + "y": 514.2126330994578 + }, + "dragging": false + }, + { + "width": 300, + "height": 376, + "id": "recursiveCharacterTextSplitter_0", + "position": { + "x": 406.08456707531263, + "y": 197.66460328693972 + }, + "type": "customNode", + "data": { + "id": "recursiveCharacterTextSplitter_0", + "label": "Recursive Character Text Splitter", + "name": "recursiveCharacterTextSplitter", + "type": "RecursiveCharacterTextSplitter", + "baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter"], + "category": "Text Splitters", + "description": "Split documents recursively by different characters - starting with \"\\n\\n\", then \"\\n\", then \" \"", + "inputParams": [ + { + "label": "Chunk Size", + "name": "chunkSize", + "type": "number", + "default": 1000, + "optional": true, + "id": "recursiveCharacterTextSplitter_0-input-chunkSize-number" + }, + { + "label": "Chunk Overlap", + "name": "chunkOverlap", + "type": "number", + "optional": true, + "id": "recursiveCharacterTextSplitter_0-input-chunkOverlap-number" + } + ], + "inputAnchors": [], + "inputs": { + "chunkSize": 1000, + "chunkOverlap": "" + }, + "outputAnchors": [ + { + "id": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter", + "name": "recursiveCharacterTextSplitter", + "label": "RecursiveCharacterTextSplitter", + "type": "RecursiveCharacterTextSplitter | TextSplitter" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 406.08456707531263, + "y": 197.66460328693972 }, "dragging": false + }, + { + "width": 300, + "height": 410, + "id": "textFile_0", + "position": { + "x": 786.5497697231324, + "y": 140.09563157584407 + }, + "type": "customNode", + "data": { + "id": "textFile_0", + "label": "Text File", + "name": "textFile", + "type": "Document", + "baseClasses": ["Document"], + "category": "Document Loaders", + "description": "Load data from text files", + "inputParams": [ + { + "label": "Txt File", + "name": "txtFile", + "type": "file", + "fileType": ".txt", + "id": "textFile_0-input-txtFile-file" + }, + { + "label": "Metadata", + "name": "metadata", + "type": "json", + "optional": true, + "additionalParams": true, + "id": "textFile_0-input-metadata-json" + } + ], + "inputAnchors": [ + { + "label": "Text Splitter", + "name": "textSplitter", + "type": "TextSplitter", + "optional": true, + "id": "textFile_0-input-textSplitter-TextSplitter" + } + ], + "inputs": { + "textSplitter": "{{recursiveCharacterTextSplitter_0.data.instance}}", + "metadata": "" + }, + "outputAnchors": [ + { + "id": "textFile_0-output-textFile-Document", + "name": "textFile", + "label": "Document", + "type": "Document" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 786.5497697231324, + "y": 140.09563157584407 + }, + "dragging": false + }, + { + "width": 300, + "height": 479, + "id": "conversationalRetrievalQAChain_0", + "position": { + "x": 1558.6564094656787, + "y": 386.60217819991124 + }, + "type": "customNode", + "data": { + "id": "conversationalRetrievalQAChain_0", + "label": "Conversational Retrieval QA Chain", + "name": "conversationalRetrievalQAChain", + "type": "ConversationalRetrievalQAChain", + "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"], + "category": "Chains", + "description": "Document QA - built on RetrievalQAChain to provide a chat history component", + "inputParams": [ + { + "label": "Return Source Documents", + "name": "returnSourceDocuments", + "type": "boolean", + "optional": true, + "id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean" + }, + { + "label": "System Message", + "name": "systemMessagePrompt", + "type": "string", + "rows": 4, + "additionalParams": true, + "optional": true, + "placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.", + "id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string" + }, + { + "label": "Chain Option", + "name": "chainOption", + "type": "options", + "options": [ + { + "label": "MapReduceDocumentsChain", + "name": "map_reduce", + "description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time" + }, + { + "label": "RefineDocumentsChain", + "name": "refine", + "description": "Suitable for QA tasks over a large number of documents." + }, + { + "label": "StuffDocumentsChain", + "name": "stuff", + "description": "Suitable for QA tasks over a small number of documents." + } + ], + "additionalParams": true, + "optional": true, + "id": "conversationalRetrievalQAChain_0-input-chainOption-options" + } + ], + "inputAnchors": [ + { + "label": "Language Model", + "name": "model", + "type": "BaseLanguageModel", + "id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel" + }, + { + "label": "Vector Store Retriever", + "name": "vectorStoreRetriever", + "type": "BaseRetriever", + "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever" + }, + { + "label": "Memory", + "name": "memory", + "type": "BaseMemory", + "optional": true, + "description": "If left empty, a default BufferMemory will be used", + "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" + } + ], + "inputs": { + "model": "{{chatOpenAI_0.data.instance}}", + "vectorStoreRetriever": "{{pineconeUpsert_0.data.instance}}", + "memory": "", + "returnSourceDocuments": "", + "systemMessagePrompt": "", + "chainOption": "" + }, + "outputAnchors": [ + { + "id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain", + "name": "conversationalRetrievalQAChain", + "label": "ConversationalRetrievalQAChain", + "type": "ConversationalRetrievalQAChain | BaseChain" + } + ], + "outputs": {}, + "selected": false + }, + "positionAbsolute": { + "x": 1558.6564094656787, + "y": 386.60217819991124 + }, + "selected": false } ], "edges": [ { - "source": "recursiveCharacterTextSplitter_1", - "sourceHandle": "recursiveCharacterTextSplitter_1-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter", - "target": "textFile_1", - "targetHandle": "textFile_1-input-textSplitter-TextSplitter", + "source": "openAIEmbeddings_0", + "sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings", + "target": "pineconeUpsert_0", + "targetHandle": "pineconeUpsert_0-input-embeddings-Embeddings", "type": "buttonedge", - "id": "recursiveCharacterTextSplitter_1-recursiveCharacterTextSplitter_1-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter-textFile_1-textFile_1-input-textSplitter-TextSplitter", + "id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-pineconeUpsert_0-pineconeUpsert_0-input-embeddings-Embeddings", "data": { "label": "" } }, { - "source": "chatOpenAI_0", - "sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel", - "target": "conversationalRetrievalQAChain_0", - "targetHandle": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel", + "source": "recursiveCharacterTextSplitter_0", + "sourceHandle": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter", + "target": "textFile_0", + "targetHandle": "textFile_0-input-textSplitter-TextSplitter", "type": "buttonedge", - "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-model-BaseLanguageModel", + "id": "recursiveCharacterTextSplitter_0-recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter-textFile_0-textFile_0-input-textSplitter-TextSplitter", "data": { "label": "" } }, { - "source": "textFile_1", - "sourceHandle": "textFile_1-output-textFile-Document", + "source": "textFile_0", + "sourceHandle": "textFile_0-output-textFile-Document", "target": "pineconeUpsert_0", "targetHandle": "pineconeUpsert_0-input-document-Document", "type": "buttonedge", - "id": "textFile_1-textFile_1-output-textFile-Document-pineconeUpsert_0-pineconeUpsert_0-input-document-Document", + "id": "textFile_0-textFile_0-output-textFile-Document-pineconeUpsert_0-pineconeUpsert_0-input-document-Document", "data": { "label": "" } }, { - "source": "openAIEmbeddings_0", - "sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings", - "target": "pineconeUpsert_0", - "targetHandle": "pineconeUpsert_0-input-embeddings-Embeddings", + "source": "chatOpenAI_0", + "sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel", + "target": "conversationalRetrievalQAChain_0", + "targetHandle": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel", "type": "buttonedge", - "id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-pineconeUpsert_0-pineconeUpsert_0-input-embeddings-Embeddings", + "id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-model-BaseLanguageModel", "data": { "label": "" } diff --git a/packages/server/marketplaces/chatflows/Flowise Docs QnA.json b/packages/server/marketplaces/chatflows/Flowise Docs QnA.json new file mode 100644 index 0000000..4c4d085 --- /dev/null +++ b/packages/server/marketplaces/chatflows/Flowise Docs QnA.json @@ -0,0 +1,637 @@ +{ + "description": "Flowise Docs Github QnA using conversational retrieval QA chain", + "nodes": [ + { + "width": 300, + "height": 376, + "id": "markdownTextSplitter_0", + "position": { + "x": 1081.1540334344143, + "y": -113.73571627207801 + }, + "type": "customNode", + "data": { + "id": "markdownTextSplitter_0", + "label": "Markdown Text Splitter", + "name": "markdownTextSplitter", + "type": "MarkdownTextSplitter", + "baseClasses": ["MarkdownTextSplitter", "RecursiveCharacterTextSplitter", "TextSplitter", "BaseDocumentTransformer"], + "category": "Text Splitters", + "description": "Split your content into documents based on the Markdown headers", + "inputParams": [ + { + "label": "Chunk Size", + "name": "chunkSize", + "type": "number", + "default": 1000, + "optional": true, + "id": "markdownTextSplitter_0-input-chunkSize-number" + }, + { + "label": "Chunk Overlap", + "name": "chunkOverlap", + "type": "number", + "optional": true, + "id": "markdownTextSplitter_0-input-chunkOverlap-number" + } + ], + "inputAnchors": [], + "inputs": { + "chunkSize": "4000", + "chunkOverlap": "" + }, + "outputAnchors": [ + { + "id": "markdownTextSplitter_0-output-markdownTextSplitter-MarkdownTextSplitter|RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer", + "name": "markdownTextSplitter", + "label": "MarkdownTextSplitter", + "type": "MarkdownTextSplitter | RecursiveCharacterTextSplitter | TextSplitter | BaseDocumentTransformer" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1081.1540334344143, + "y": -113.73571627207801 + }, + "dragging": false + }, + { + "width": 300, + "height": 405, + "id": "memoryVectorStore_0", + "position": { + "x": 1844.88052464165, + "y": 484.60473328470243 + }, + "type": "customNode", + "data": { + "id": "memoryVectorStore_0", + "label": "In-Memory Vector Store", + "name": "memoryVectorStore", + "type": "Memory", + "baseClasses": ["Memory", "VectorStoreRetriever", "BaseRetriever"], + "category": "Vector Stores", + "description": "In-memory vectorstore that stores embeddings and does an exact, linear search for the most similar embeddings.", + "inputParams": [ + { + "label": "Top K", + "name": "topK", + "description": "Number of top results to fetch. Default to 4", + "placeholder": "4", + "type": "number", + "optional": true, + "id": "memoryVectorStore_0-input-topK-number" + } + ], + "inputAnchors": [ + { + "label": "Document", + "name": "document", + "type": "Document", + "list": true, + "id": "memoryVectorStore_0-input-document-Document" + }, + { + "label": "Embeddings", + "name": "embeddings", + "type": "Embeddings", + "id": "memoryVectorStore_0-input-embeddings-Embeddings" + } + ], + "inputs": { + "document": ["{{github_0.data.instance}}"], + "embeddings": "{{openAIEmbeddings_0.data.instance}}", + "topK": "" + }, + "outputAnchors": [ + { + "name": "output", + "label": "Output", + "type": "options", + "options": [ + { + "id": "memoryVectorStore_0-output-retriever-Memory|VectorStoreRetriever|BaseRetriever", + "name": "retriever", + "label": "Memory Retriever", + "type": "Memory | VectorStoreRetriever | BaseRetriever" + }, + { + "id": "memoryVectorStore_0-output-vectorStore-Memory|VectorStore", + "name": "vectorStore", + "label": "Memory Vector Store", + "type": "Memory | VectorStore" + } + ], + "default": "retriever" + } + ], + "outputs": { + "output": "retriever" + }, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1844.88052464165, + "y": 484.60473328470243 + }, + "dragging": false + }, + { + "width": 300, + "height": 479, + "id": "conversationalRetrievalQAChain_0", + "position": { + "x": 2311.697827287373, + "y": 228.14841720207832 + }, + "type": "customNode", + "data": { + "id": "conversationalRetrievalQAChain_0", + "label": "Conversational Retrieval QA Chain", + "name": "conversationalRetrievalQAChain", + "type": "ConversationalRetrievalQAChain", + "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"], + "category": "Chains", + "description": "Document QA - built on RetrievalQAChain to provide a chat history component", + "inputParams": [ + { + "label": "Return Source Documents", + "name": "returnSourceDocuments", + "type": "boolean", + "optional": true, + "id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean" + }, + { + "label": "System Message", + "name": "systemMessagePrompt", + "type": "string", + "rows": 4, + "additionalParams": true, + "optional": true, + "placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.", + "id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string" + }, + { + "label": "Chain Option", + "name": "chainOption", + "type": "options", + "options": [ + { + "label": "MapReduceDocumentsChain", + "name": "map_reduce", + "description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time" + }, + { + "label": "RefineDocumentsChain", + "name": "refine", + "description": "Suitable for QA tasks over a large number of documents." + }, + { + "label": "StuffDocumentsChain", + "name": "stuff", + "description": "Suitable for QA tasks over a small number of documents." + } + ], + "additionalParams": true, + "optional": true, + "id": "conversationalRetrievalQAChain_0-input-chainOption-options" + } + ], + "inputAnchors": [ + { + "label": "Language Model", + "name": "model", + "type": "BaseLanguageModel", + "id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel" + }, + { + "label": "Vector Store Retriever", + "name": "vectorStoreRetriever", + "type": "BaseRetriever", + "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever" + }, + { + "label": "Memory", + "name": "memory", + "type": "BaseMemory", + "optional": true, + "description": "If left empty, a default BufferMemory will be used", + "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" + } + ], + "inputs": { + "model": "{{chatOpenAI_0.data.instance}}", + "vectorStoreRetriever": "{{memoryVectorStore_0.data.instance}}", + "memory": "", + "returnSourceDocuments": true, + "systemMessagePrompt": "", + "chainOption": "" + }, + "outputAnchors": [ + { + "id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain", + "name": "conversationalRetrievalQAChain", + "label": "ConversationalRetrievalQAChain", + "type": "ConversationalRetrievalQAChain | BaseChain" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "dragging": false, + "positionAbsolute": { + "x": 2311.697827287373, + "y": 228.14841720207832 + } + }, + { + "width": 300, + "height": 673, + "id": "github_0", + "position": { + "x": 1460.1858988997, + "y": -137.83585695472374 + }, + "type": "customNode", + "data": { + "id": "github_0", + "label": "Github", + "name": "github", + "type": "Document", + "baseClasses": ["Document"], + "category": "Document Loaders", + "description": "Load data from a GitHub repository", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "description": "Only needed when accessing private repo", + "optional": true, + "credentialNames": ["githubApi"], + "id": "github_0-input-credential-credential" + }, + { + "label": "Repo Link", + "name": "repoLink", + "type": "string", + "placeholder": "https://github.com/FlowiseAI/Flowise", + "id": "github_0-input-repoLink-string" + }, + { + "label": "Branch", + "name": "branch", + "type": "string", + "default": "main", + "id": "github_0-input-branch-string" + }, + { + "label": "Recursive", + "name": "recursive", + "type": "boolean", + "optional": true, + "id": "github_0-input-recursive-boolean" + }, + { + "label": "Metadata", + "name": "metadata", + "type": "json", + "optional": true, + "additionalParams": true, + "id": "github_0-input-metadata-json" + } + ], + "inputAnchors": [ + { + "label": "Text Splitter", + "name": "textSplitter", + "type": "TextSplitter", + "optional": true, + "id": "github_0-input-textSplitter-TextSplitter" + } + ], + "inputs": { + "repoLink": "https://github.com/FlowiseAI/FlowiseDocs", + "branch": "main", + "recursive": true, + "textSplitter": "{{markdownTextSplitter_0.data.instance}}", + "metadata": "" + }, + "outputAnchors": [ + { + "id": "github_0-output-github-Document", + "name": "github", + "label": "Document", + "type": "Document" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1460.1858988997, + "y": -137.83585695472374 + }, + "dragging": false + }, + { + "width": 300, + "height": 522, + "id": "chatOpenAI_0", + "position": { + "x": 1857.367353502965, + "y": -104.25095383414119 + }, + "type": "customNode", + "data": { + "id": "chatOpenAI_0", + "label": "ChatOpenAI", + "name": "chatOpenAI", + "type": "ChatOpenAI", + "baseClasses": ["ChatOpenAI", "BaseChatModel", "BaseLanguageModel"], + "category": "Chat Models", + "description": "Wrapper around OpenAI large language models that use the Chat endpoint", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["openAIApi"], + "id": "chatOpenAI_0-input-credential-credential" + }, + { + "label": "Model Name", + "name": "modelName", + "type": "options", + "options": [ + { + "label": "gpt-4", + "name": "gpt-4" + }, + { + "label": "gpt-4-0613", + "name": "gpt-4-0613" + }, + { + "label": "gpt-4-32k", + "name": "gpt-4-32k" + }, + { + "label": "gpt-4-32k-0613", + "name": "gpt-4-32k-0613" + }, + { + "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" + } + ], + "default": "gpt-3.5-turbo", + "optional": true, + "id": "chatOpenAI_0-input-modelName-options" + }, + { + "label": "Temperature", + "name": "temperature", + "type": "number", + "default": 0.9, + "optional": true, + "id": "chatOpenAI_0-input-temperature-number" + }, + { + "label": "Max Tokens", + "name": "maxTokens", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-maxTokens-number" + }, + { + "label": "Top Probability", + "name": "topP", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-topP-number" + }, + { + "label": "Frequency Penalty", + "name": "frequencyPenalty", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-frequencyPenalty-number" + }, + { + "label": "Presence Penalty", + "name": "presencePenalty", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-presencePenalty-number" + }, + { + "label": "Timeout", + "name": "timeout", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-timeout-number" + }, + { + "label": "BasePath", + "name": "basepath", + "type": "string", + "optional": true, + "additionalParams": true, + "id": "chatOpenAI_0-input-basepath-string" + } + ], + "inputAnchors": [], + "inputs": { + "modelName": "gpt-3.5-turbo", + "temperature": 0.9, + "maxTokens": "", + "topP": "", + "frequencyPenalty": "", + "presencePenalty": "", + "timeout": "", + "basepath": "" + }, + "outputAnchors": [ + { + "id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel", + "name": "chatOpenAI", + "label": "ChatOpenAI", + "type": "ChatOpenAI | BaseChatModel | BaseLanguageModel" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1857.367353502965, + "y": -104.25095383414119 + }, + "dragging": false + }, + { + "width": 300, + "height": 328, + "id": "openAIEmbeddings_0", + "position": { + "x": 1299.9983863833309, + "y": 581.8406384863323 + }, + "type": "customNode", + "data": { + "id": "openAIEmbeddings_0", + "label": "OpenAI Embeddings", + "name": "openAIEmbeddings", + "type": "OpenAIEmbeddings", + "baseClasses": ["OpenAIEmbeddings", "Embeddings"], + "category": "Embeddings", + "description": "OpenAI API to generate embeddings for a given text", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "credentialNames": ["openAIApi"], + "id": "openAIEmbeddings_0-input-credential-credential" + }, + { + "label": "Strip New Lines", + "name": "stripNewLines", + "type": "boolean", + "optional": true, + "additionalParams": true, + "id": "openAIEmbeddings_0-input-stripNewLines-boolean" + }, + { + "label": "Batch Size", + "name": "batchSize", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "openAIEmbeddings_0-input-batchSize-number" + }, + { + "label": "Timeout", + "name": "timeout", + "type": "number", + "optional": true, + "additionalParams": true, + "id": "openAIEmbeddings_0-input-timeout-number" + }, + { + "label": "BasePath", + "name": "basepath", + "type": "string", + "optional": true, + "additionalParams": true, + "id": "openAIEmbeddings_0-input-basepath-string" + } + ], + "inputAnchors": [], + "inputs": { + "stripNewLines": "", + "batchSize": "", + "timeout": "", + "basepath": "" + }, + "outputAnchors": [ + { + "id": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings", + "name": "openAIEmbeddings", + "label": "OpenAIEmbeddings", + "type": "OpenAIEmbeddings | Embeddings" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "dragging": false, + "positionAbsolute": { + "x": 1299.9983863833309, + "y": 581.8406384863323 + } + } + ], + "edges": [ + { + "source": "memoryVectorStore_0", + "sourceHandle": "memoryVectorStore_0-output-retriever-Memory|VectorStoreRetriever|BaseRetriever", + "target": "conversationalRetrievalQAChain_0", + "targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever", + "type": "buttonedge", + "id": "memoryVectorStore_0-memoryVectorStore_0-output-retriever-Memory|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever", + "data": { + "label": "" + } + }, + { + "source": "markdownTextSplitter_0", + "sourceHandle": "markdownTextSplitter_0-output-markdownTextSplitter-MarkdownTextSplitter|RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer", + "target": "github_0", + "targetHandle": "github_0-input-textSplitter-TextSplitter", + "type": "buttonedge", + "id": "markdownTextSplitter_0-markdownTextSplitter_0-output-markdownTextSplitter-MarkdownTextSplitter|RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer-github_0-github_0-input-textSplitter-TextSplitter", + "data": { + "label": "" + } + }, + { + "source": "github_0", + "sourceHandle": "github_0-output-github-Document", + "target": "memoryVectorStore_0", + "targetHandle": "memoryVectorStore_0-input-document-Document", + "type": "buttonedge", + "id": "github_0-github_0-output-github-Document-memoryVectorStore_0-memoryVectorStore_0-input-document-Document", + "data": { + "label": "" + } + }, + { + "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": "openAIEmbeddings_0", + "sourceHandle": "openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings", + "target": "memoryVectorStore_0", + "targetHandle": "memoryVectorStore_0-input-embeddings-Embeddings", + "type": "buttonedge", + "id": "openAIEmbeddings_0-openAIEmbeddings_0-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-memoryVectorStore_0-memoryVectorStore_0-input-embeddings-Embeddings", + "data": { + "label": "" + } + } + ] +} diff --git a/packages/server/marketplaces/chatflows/Local QnA.json b/packages/server/marketplaces/chatflows/Local QnA.json index 5265c42..ea9453b 100644 --- a/packages/server/marketplaces/chatflows/Local QnA.json +++ b/packages/server/marketplaces/chatflows/Local QnA.json @@ -135,15 +135,16 @@ { "label": "Memory", "name": "memory", - "type": "DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", + "type": "BaseMemory", "optional": true, - "description": "If no memory connected, default BufferMemory will be used", - "id": "conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory" + "description": "If left empty, a default BufferMemory will be used", + "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" } ], "inputs": { "model": "{{chatLocalAI_0.data.instance}}", - "vectorStoreRetriever": "{{faissUpsert_0.data.instance}}" + "vectorStoreRetriever": "{{faissUpsert_0.data.instance}}", + "memory": "" }, "outputAnchors": [ { diff --git a/packages/server/marketplaces/chatflows/Long Term Memory.json b/packages/server/marketplaces/chatflows/Long Term Memory.json index 3857cff..db7ab6c 100644 --- a/packages/server/marketplaces/chatflows/Long Term Memory.json +++ b/packages/server/marketplaces/chatflows/Long Term Memory.json @@ -78,10 +78,10 @@ { "label": "Memory", "name": "memory", - "type": "DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", + "type": "BaseMemory", "optional": true, - "description": "If no memory connected, default BufferMemory will be used", - "id": "conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory" + "description": "If left empty, a default BufferMemory will be used", + "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" } ], "inputs": { @@ -631,9 +631,9 @@ "source": "ZepMemory_0", "sourceHandle": "ZepMemory_0-output-ZepMemory-ZepMemory|BaseChatMemory|BaseMemory", "target": "conversationalRetrievalQAChain_0", - "targetHandle": "conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", + "targetHandle": "conversationalRetrievalQAChain_0-input-memory-BaseMemory", "type": "buttonedge", - "id": "ZepMemory_0-ZepMemory_0-output-ZepMemory-ZepMemory|BaseChatMemory|BaseMemory-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", + "id": "ZepMemory_0-ZepMemory_0-output-ZepMemory-ZepMemory|BaseChatMemory|BaseMemory-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-memory-BaseMemory", "data": { "label": "" } diff --git a/packages/server/marketplaces/chatflows/Metadata Filter Load.json b/packages/server/marketplaces/chatflows/Metadata Filter Load.json index 59516a4..2076c15 100644 --- a/packages/server/marketplaces/chatflows/Metadata Filter Load.json +++ b/packages/server/marketplaces/chatflows/Metadata Filter Load.json @@ -78,10 +78,10 @@ { "label": "Memory", "name": "memory", - "type": "DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", + "type": "BaseMemory", "optional": true, - "description": "If no memory connected, default BufferMemory will be used", - "id": "conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory" + "description": "If left empty, a default BufferMemory will be used", + "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" } ], "inputs": { diff --git a/packages/server/marketplaces/chatflows/Metadata Filter Upsert.json b/packages/server/marketplaces/chatflows/Metadata Filter Upsert.json index a715f23..a085298 100644 --- a/packages/server/marketplaces/chatflows/Metadata Filter Upsert.json +++ b/packages/server/marketplaces/chatflows/Metadata Filter Upsert.json @@ -283,10 +283,10 @@ { "label": "Memory", "name": "memory", - "type": "DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", + "type": "BaseMemory", "optional": true, - "description": "If no memory connected, default BufferMemory will be used", - "id": "conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory" + "description": "If left empty, a default BufferMemory will be used", + "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" } ], "inputs": { diff --git a/packages/server/marketplaces/chatflows/Replicate LLM.json b/packages/server/marketplaces/chatflows/Replicate LLM.json new file mode 100644 index 0000000..6637766 --- /dev/null +++ b/packages/server/marketplaces/chatflows/Replicate LLM.json @@ -0,0 +1,273 @@ +{ + "description": "Use Replicate API that runs Llama 13b v2 model with LLMChain", + "nodes": [ + { + "width": 300, + "height": 405, + "id": "llmChain_1", + "position": { + "x": 967.581544453458, + "y": 320.56761595884564 + }, + "type": "customNode", + "data": { + "id": "llmChain_1", + "label": "LLM Chain", + "name": "llmChain", + "type": "LLMChain", + "baseClasses": ["LLMChain", "BaseChain", "BaseLangChain"], + "category": "Chains", + "description": "Chain to run queries against LLMs", + "inputParams": [ + { + "label": "Chain Name", + "name": "chainName", + "type": "string", + "placeholder": "Name Your Chain", + "optional": true, + "id": "llmChain_1-input-chainName-string" + } + ], + "inputAnchors": [ + { + "label": "Language Model", + "name": "model", + "type": "BaseLanguageModel", + "id": "llmChain_1-input-model-BaseLanguageModel" + }, + { + "label": "Prompt", + "name": "prompt", + "type": "BasePromptTemplate", + "id": "llmChain_1-input-prompt-BasePromptTemplate" + } + ], + "inputs": { + "model": "{{replicate_0.data.instance}}", + "prompt": "{{promptTemplate_0.data.instance}}", + "chainName": "" + }, + "outputAnchors": [ + { + "name": "output", + "label": "Output", + "type": "options", + "options": [ + { + "id": "llmChain_1-output-llmChain-LLMChain|BaseChain|BaseLangChain", + "name": "llmChain", + "label": "LLM Chain", + "type": "LLMChain | BaseChain | BaseLangChain" + }, + { + "id": "llmChain_1-output-outputPrediction-string|json", + "name": "outputPrediction", + "label": "Output Prediction", + "type": "string | json" + } + ], + "default": "llmChain" + } + ], + "outputs": { + "output": "llmChain" + }, + "selected": false + }, + "positionAbsolute": { + "x": 967.581544453458, + "y": 320.56761595884564 + }, + "selected": false, + "dragging": false + }, + { + "width": 300, + "height": 475, + "id": "promptTemplate_0", + "position": { + "x": 269.2203229225663, + "y": 129.02909641085535 + }, + "type": "customNode", + "data": { + "id": "promptTemplate_0", + "label": "Prompt Template", + "name": "promptTemplate", + "type": "PromptTemplate", + "baseClasses": ["PromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate"], + "category": "Prompts", + "description": "Schema to represent a basic prompt for an LLM", + "inputParams": [ + { + "label": "Template", + "name": "template", + "type": "string", + "rows": 4, + "placeholder": "What is a good name for a company that makes {product}?", + "id": "promptTemplate_0-input-template-string" + }, + { + "label": "Format Prompt Values", + "name": "promptValues", + "type": "json", + "optional": true, + "acceptVariable": true, + "list": true, + "id": "promptTemplate_0-input-promptValues-json" + } + ], + "inputAnchors": [], + "inputs": { + "template": "Assistant: You are a helpful assistant. You do not respond as 'User' or pretend to be 'User'. You only respond once as Assistant.\nUser: {query}\nAssistant:", + "promptValues": "{\"query\":\"{{question}}\"}" + }, + "outputAnchors": [ + { + "id": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate", + "name": "promptTemplate", + "label": "PromptTemplate", + "type": "PromptTemplate | BaseStringPromptTemplate | BasePromptTemplate" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 269.2203229225663, + "y": 129.02909641085535 + }, + "dragging": false + }, + { + "width": 300, + "height": 527, + "id": "replicate_0", + "position": { + "x": 607.4915400488668, + "y": -60.643337207007804 + }, + "type": "customNode", + "data": { + "id": "replicate_0", + "label": "Replicate", + "name": "replicate", + "type": "Replicate", + "baseClasses": ["Replicate", "LLM", "BaseLLM", "BaseLanguageModel"], + "category": "LLMs", + "description": "Use Replicate to run open source models on cloud", + "inputParams": [ + { + "label": "Replicate Api Key", + "name": "replicateApiKey", + "type": "password", + "id": "replicate_0-input-replicateApiKey-password" + }, + { + "label": "Model", + "name": "model", + "type": "string", + "placeholder": "a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5", + "optional": true, + "id": "replicate_0-input-model-string" + }, + { + "label": "Temperature", + "name": "temperature", + "type": "number", + "description": "Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.", + "default": 0.7, + "optional": true, + "id": "replicate_0-input-temperature-number" + }, + { + "label": "Max Tokens", + "name": "maxTokens", + "type": "number", + "description": "Maximum number of tokens to generate. A word is generally 2-3 tokens", + "optional": true, + "additionalParams": true, + "id": "replicate_0-input-maxTokens-number" + }, + { + "label": "Top Probability", + "name": "topP", + "type": "number", + "description": "When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens", + "optional": true, + "additionalParams": true, + "id": "replicate_0-input-topP-number" + }, + { + "label": "Repetition Penalty", + "name": "repetitionPenalty", + "type": "number", + "description": "Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it. (minimum: 0.01; maximum: 5)", + "optional": true, + "additionalParams": true, + "id": "replicate_0-input-repetitionPenalty-number" + }, + { + "label": "Additional Inputs", + "name": "additionalInputs", + "type": "json", + "description": "Each model has different parameters, refer to the specific model accepted inputs. For example: llama13b-v2", + "additionalParams": true, + "optional": true, + "id": "replicate_0-input-additionalInputs-json" + } + ], + "inputAnchors": [], + "inputs": { + "model": "a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5", + "temperature": 0.7, + "maxTokens": "", + "topP": "", + "repetitionPenalty": "", + "additionalInputs": "" + }, + "outputAnchors": [ + { + "id": "replicate_0-output-replicate-Replicate|LLM|BaseLLM|BaseLanguageModel", + "name": "replicate", + "label": "Replicate", + "type": "Replicate | LLM | BaseLLM | BaseLanguageModel" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 607.4915400488668, + "y": -60.643337207007804 + }, + "dragging": false + } + ], + "edges": [ + { + "source": "promptTemplate_0", + "sourceHandle": "promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate", + "target": "llmChain_1", + "targetHandle": "llmChain_1-input-prompt-BasePromptTemplate", + "type": "buttonedge", + "id": "promptTemplate_0-promptTemplate_0-output-promptTemplate-PromptTemplate|BaseStringPromptTemplate|BasePromptTemplate-llmChain_1-llmChain_1-input-prompt-BasePromptTemplate", + "data": { + "label": "" + } + }, + { + "source": "replicate_0", + "sourceHandle": "replicate_0-output-replicate-Replicate|LLM|BaseLLM|BaseLanguageModel", + "target": "llmChain_1", + "targetHandle": "llmChain_1-input-model-BaseLanguageModel", + "type": "buttonedge", + "id": "replicate_0-replicate_0-output-replicate-Replicate|LLM|BaseLLM|BaseLanguageModel-llmChain_1-llmChain_1-input-model-BaseLanguageModel", + "data": { + "label": "" + } + } + ] +} diff --git a/packages/server/marketplaces/chatflows/WebPage QnA.json b/packages/server/marketplaces/chatflows/WebPage QnA.json index ec287ec..817bd78 100644 --- a/packages/server/marketplaces/chatflows/WebPage QnA.json +++ b/packages/server/marketplaces/chatflows/WebPage QnA.json @@ -1,122 +1,13 @@ { - "description": "Scrape web pages for QnA using conversational retrieval QA chain", + "description": "Scrape web pages for QnA with long term memory Motorhead and return source documents", "nodes": [ { "width": 300, - "height": 480, - "id": "conversationalRetrievalQAChain_0", - "position": { - "x": 1574.2192193338556, - "y": 334.4358233039927 - }, - "type": "customNode", - "data": { - "id": "conversationalRetrievalQAChain_0", - "label": "Conversational Retrieval QA Chain", - "name": "conversationalRetrievalQAChain", - "type": "ConversationalRetrievalQAChain", - "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"], - "category": "Chains", - "description": "Document QA - built on RetrievalQAChain to provide a chat history component", - "inputParams": [ - { - "label": "Return Source Documents", - "name": "returnSourceDocuments", - "type": "boolean", - "optional": true, - "id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean" - }, - { - "label": "System Message", - "name": "systemMessagePrompt", - "type": "string", - "rows": 4, - "additionalParams": true, - "optional": true, - "placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.", - "id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string" - }, - { - "label": "Chain Option", - "name": "chainOption", - "type": "options", - "options": [ - { - "label": "MapReduceDocumentsChain", - "name": "map_reduce", - "description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time" - }, - { - "label": "RefineDocumentsChain", - "name": "refine", - "description": "Suitable for QA tasks over a large number of documents." - }, - { - "label": "StuffDocumentsChain", - "name": "stuff", - "description": "Suitable for QA tasks over a small number of documents." - } - ], - "additionalParams": true, - "optional": true, - "id": "conversationalRetrievalQAChain_0-input-chainOption-options" - } - ], - "inputAnchors": [ - { - "label": "Language Model", - "name": "model", - "type": "BaseLanguageModel", - "id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel" - }, - { - "label": "Vector Store Retriever", - "name": "vectorStoreRetriever", - "type": "BaseRetriever", - "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever" - }, - { - "label": "Memory", - "name": "memory", - "type": "DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory", - "optional": true, - "description": "If no memory connected, default BufferMemory will be used", - "id": "conversationalRetrievalQAChain_0-input-memory-DynamoDBChatMemory | RedisBackedChatMemory | ZepMemory" - } - ], - "inputs": { - "model": "{{chatOpenAI_0.data.instance}}", - "vectorStoreRetriever": "{{pineconeUpsert_0.data.instance}}", - "memory": "", - "returnSourceDocuments": "", - "systemMessagePrompt": "", - "chainOption": "" - }, - "outputAnchors": [ - { - "id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain", - "name": "conversationalRetrievalQAChain", - "label": "ConversationalRetrievalQAChain", - "type": "ConversationalRetrievalQAChain | BaseChain" - } - ], - "outputs": {}, - "selected": false - }, - "positionAbsolute": { - "x": 1574.2192193338556, - "y": 334.4358233039927 - }, - "selected": false, - "dragging": false - }, - { - "width": 300, - "height": 523, + "height": 522, "id": "chatOpenAI_0", "position": { - "x": 1184.1176114500388, - "y": -44.15535835370571 + "x": 1509.7110310286191, + "y": -171.0099374102956 }, "type": "customNode", "data": { @@ -257,19 +148,19 @@ "selected": false }, "positionAbsolute": { - "x": 1184.1176114500388, - "y": -44.15535835370571 + "x": 1509.7110310286191, + "y": -171.0099374102956 }, "selected": false, "dragging": false }, { "width": 300, - "height": 329, + "height": 328, "id": "openAIEmbeddings_0", "position": { - "x": 795.6162477805387, - "y": 603.260214150876 + "x": 827.6835380475393, + "y": 253.8955254525015 }, "type": "customNode", "data": { @@ -341,18 +232,18 @@ }, "selected": false, "positionAbsolute": { - "x": 795.6162477805387, - "y": 603.260214150876 + "x": 827.6835380475393, + "y": 253.8955254525015 }, "dragging": false }, { "width": 300, - "height": 555, + "height": 554, "id": "pineconeUpsert_0", "position": { - "x": 1191.1792786926865, - "y": 514.2126330994578 + "x": 1178.0855412625938, + "y": -1.6626550640073674 }, "type": "customNode", "data": { @@ -448,18 +339,18 @@ }, "selected": false, "positionAbsolute": { - "x": 1191.1792786926865, - "y": 514.2126330994578 + "x": 1178.0855412625938, + "y": -1.6626550640073674 }, "dragging": false }, { "width": 300, - "height": 380, + "height": 379, "id": "cheerioWebScraper_0", "position": { - "x": 788.9349009610441, - "y": 180.57790622561026 + "x": 829.4409518246235, + "y": -168.78678247276423 }, "type": "customNode", "data": { @@ -528,9 +419,9 @@ ], "inputs": { "url": "https://www.itsjane.com", - "textSplitter": "{{recursiveCharacterTextSplitter_0.data.instance}}", - "relativeLinksMethod": "webCrawl", - "limit": "0", + "textSplitter": "{{htmlToMarkdownTextSplitter_0.data.instance}}", + "relativeLinksMethod": "", + "limit": "", "metadata": "" }, "outputAnchors": [ @@ -546,28 +437,34 @@ }, "selected": false, "positionAbsolute": { - "x": 788.9349009610441, - "y": 180.57790622561026 + "x": 829.4409518246235, + "y": -168.78678247276423 }, "dragging": false }, { "width": 300, "height": 376, - "id": "recursiveCharacterTextSplitter_0", + "id": "htmlToMarkdownTextSplitter_0", "position": { - "x": 406.08456707531263, - "y": 197.66460328693972 + "x": 443.00626484042334, + "y": 1.2942107707648631 }, "type": "customNode", "data": { - "id": "recursiveCharacterTextSplitter_0", - "label": "Recursive Character Text Splitter", - "name": "recursiveCharacterTextSplitter", - "type": "RecursiveCharacterTextSplitter", - "baseClasses": ["RecursiveCharacterTextSplitter", "TextSplitter"], + "id": "htmlToMarkdownTextSplitter_0", + "label": "HtmlToMarkdown Text Splitter", + "name": "htmlToMarkdownTextSplitter", + "type": "HtmlToMarkdownTextSplitter", + "baseClasses": [ + "HtmlToMarkdownTextSplitter", + "MarkdownTextSplitter", + "RecursiveCharacterTextSplitter", + "TextSplitter", + "BaseDocumentTransformer" + ], "category": "Text Splitters", - "description": "Split documents recursively by different characters - starting with \"\\n\\n\", then \"\\n\", then \" \"", + "description": "Converts Html to Markdown and then split your content into documents based on the Markdown headers", "inputParams": [ { "label": "Chunk Size", @@ -575,14 +472,14 @@ "type": "number", "default": 1000, "optional": true, - "id": "recursiveCharacterTextSplitter_0-input-chunkSize-number" + "id": "htmlToMarkdownTextSplitter_0-input-chunkSize-number" }, { "label": "Chunk Overlap", "name": "chunkOverlap", "type": "number", "optional": true, - "id": "recursiveCharacterTextSplitter_0-input-chunkOverlap-number" + "id": "htmlToMarkdownTextSplitter_0-input-chunkOverlap-number" } ], "inputAnchors": [], @@ -592,10 +489,197 @@ }, "outputAnchors": [ { - "id": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter", - "name": "recursiveCharacterTextSplitter", - "label": "RecursiveCharacterTextSplitter", - "type": "RecursiveCharacterTextSplitter | TextSplitter" + "id": "htmlToMarkdownTextSplitter_0-output-htmlToMarkdownTextSplitter-HtmlToMarkdownTextSplitter|MarkdownTextSplitter|RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer", + "name": "htmlToMarkdownTextSplitter", + "label": "HtmlToMarkdownTextSplitter", + "type": "HtmlToMarkdownTextSplitter | MarkdownTextSplitter | RecursiveCharacterTextSplitter | TextSplitter | BaseDocumentTransformer" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 443.00626484042334, + "y": 1.2942107707648631 + }, + "dragging": false + }, + { + "width": 300, + "height": 479, + "id": "conversationalRetrievalQAChain_0", + "position": { + "x": 1882.5543981868987, + "y": 305.08959224761225 + }, + "type": "customNode", + "data": { + "id": "conversationalRetrievalQAChain_0", + "label": "Conversational Retrieval QA Chain", + "name": "conversationalRetrievalQAChain", + "type": "ConversationalRetrievalQAChain", + "baseClasses": ["ConversationalRetrievalQAChain", "BaseChain"], + "category": "Chains", + "description": "Document QA - built on RetrievalQAChain to provide a chat history component", + "inputParams": [ + { + "label": "Return Source Documents", + "name": "returnSourceDocuments", + "type": "boolean", + "optional": true, + "id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean" + }, + { + "label": "System Message", + "name": "systemMessagePrompt", + "type": "string", + "rows": 4, + "additionalParams": true, + "optional": true, + "placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.", + "id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string" + }, + { + "label": "Chain Option", + "name": "chainOption", + "type": "options", + "options": [ + { + "label": "MapReduceDocumentsChain", + "name": "map_reduce", + "description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time" + }, + { + "label": "RefineDocumentsChain", + "name": "refine", + "description": "Suitable for QA tasks over a large number of documents." + }, + { + "label": "StuffDocumentsChain", + "name": "stuff", + "description": "Suitable for QA tasks over a small number of documents." + } + ], + "additionalParams": true, + "optional": true, + "id": "conversationalRetrievalQAChain_0-input-chainOption-options" + } + ], + "inputAnchors": [ + { + "label": "Language Model", + "name": "model", + "type": "BaseLanguageModel", + "id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel" + }, + { + "label": "Vector Store Retriever", + "name": "vectorStoreRetriever", + "type": "BaseRetriever", + "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever" + }, + { + "label": "Memory", + "name": "memory", + "type": "BaseMemory", + "optional": true, + "description": "If left empty, a default BufferMemory will be used", + "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" + } + ], + "inputs": { + "model": "{{chatOpenAI_0.data.instance}}", + "vectorStoreRetriever": "{{pineconeUpsert_0.data.instance}}", + "memory": "{{motorheadMemory_0.data.instance}}", + "returnSourceDocuments": true, + "systemMessagePrompt": "", + "chainOption": "" + }, + "outputAnchors": [ + { + "id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain", + "name": "conversationalRetrievalQAChain", + "label": "ConversationalRetrievalQAChain", + "type": "ConversationalRetrievalQAChain | BaseChain" + } + ], + "outputs": {}, + "selected": false + }, + "selected": false, + "positionAbsolute": { + "x": 1882.5543981868987, + "y": 305.08959224761225 + }, + "dragging": false + }, + { + "width": 300, + "height": 426, + "id": "motorheadMemory_0", + "position": { + "x": 1515.4202055109095, + "y": 539.7912360964175 + }, + "type": "customNode", + "data": { + "id": "motorheadMemory_0", + "label": "Motorhead Memory", + "name": "motorheadMemory", + "type": "MotorheadMemory", + "baseClasses": ["MotorheadMemory", "BaseChatMemory", "BaseMemory"], + "category": "Memory", + "description": "Use Motorhead Memory to store chat conversations", + "inputParams": [ + { + "label": "Connect Credential", + "name": "credential", + "type": "credential", + "optional": true, + "description": "Only needed when using hosted solution - https://getmetal.io", + "credentialNames": ["motorheadMemoryApi"], + "id": "motorheadMemory_0-input-credential-credential" + }, + { + "label": "Base URL", + "name": "baseURL", + "type": "string", + "optional": true, + "description": "To use the online version, leave the URL blank. More details at https://getmetal.io.", + "id": "motorheadMemory_0-input-baseURL-string" + }, + { + "label": "Session Id", + "name": "sessionId", + "type": "string", + "description": "if empty, chatId will be used automatically", + "default": "", + "additionalParams": true, + "optional": true, + "id": "motorheadMemory_0-input-sessionId-string" + }, + { + "label": "Memory Key", + "name": "memoryKey", + "type": "string", + "default": "chat_history", + "additionalParams": true, + "id": "motorheadMemory_0-input-memoryKey-string" + } + ], + "inputAnchors": [], + "inputs": { + "baseURL": "", + "sessionId": "", + "memoryKey": "chat_history" + }, + "outputAnchors": [ + { + "id": "motorheadMemory_0-output-motorheadMemory-MotorheadMemory|BaseChatMemory|BaseMemory", + "name": "motorheadMemory", + "label": "MotorheadMemory", + "type": "MotorheadMemory | BaseChatMemory | BaseMemory" } ], "outputs": {}, @@ -603,8 +687,8 @@ }, "selected": false, "positionAbsolute": { - "x": 406.08456707531263, - "y": 197.66460328693972 + "x": 1515.4202055109095, + "y": 539.7912360964175 }, "dragging": false } @@ -622,12 +706,23 @@ } }, { - "source": "pineconeUpsert_0", - "sourceHandle": "pineconeUpsert_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever", - "target": "conversationalRetrievalQAChain_0", - "targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever", + "source": "cheerioWebScraper_0", + "sourceHandle": "cheerioWebScraper_0-output-cheerioWebScraper-Document", + "target": "pineconeUpsert_0", + "targetHandle": "pineconeUpsert_0-input-document-Document", "type": "buttonedge", - "id": "pineconeUpsert_0-pineconeUpsert_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever", + "id": "cheerioWebScraper_0-cheerioWebScraper_0-output-cheerioWebScraper-Document-pineconeUpsert_0-pineconeUpsert_0-input-document-Document", + "data": { + "label": "" + } + }, + { + "source": "htmlToMarkdownTextSplitter_0", + "sourceHandle": "htmlToMarkdownTextSplitter_0-output-htmlToMarkdownTextSplitter-HtmlToMarkdownTextSplitter|MarkdownTextSplitter|RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer", + "target": "cheerioWebScraper_0", + "targetHandle": "cheerioWebScraper_0-input-textSplitter-TextSplitter", + "type": "buttonedge", + "id": "htmlToMarkdownTextSplitter_0-htmlToMarkdownTextSplitter_0-output-htmlToMarkdownTextSplitter-HtmlToMarkdownTextSplitter|MarkdownTextSplitter|RecursiveCharacterTextSplitter|TextSplitter|BaseDocumentTransformer-cheerioWebScraper_0-cheerioWebScraper_0-input-textSplitter-TextSplitter", "data": { "label": "" } @@ -644,23 +739,23 @@ } }, { - "source": "recursiveCharacterTextSplitter_0", - "sourceHandle": "recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter", - "target": "cheerioWebScraper_0", - "targetHandle": "cheerioWebScraper_0-input-textSplitter-TextSplitter", + "source": "pineconeUpsert_0", + "sourceHandle": "pineconeUpsert_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever", + "target": "conversationalRetrievalQAChain_0", + "targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever", "type": "buttonedge", - "id": "recursiveCharacterTextSplitter_0-recursiveCharacterTextSplitter_0-output-recursiveCharacterTextSplitter-RecursiveCharacterTextSplitter|TextSplitter-cheerioWebScraper_0-cheerioWebScraper_0-input-textSplitter-TextSplitter", + "id": "pineconeUpsert_0-pineconeUpsert_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever", "data": { "label": "" } }, { - "source": "cheerioWebScraper_0", - "sourceHandle": "cheerioWebScraper_0-output-cheerioWebScraper-Document", - "target": "pineconeUpsert_0", - "targetHandle": "pineconeUpsert_0-input-document-Document", + "source": "motorheadMemory_0", + "sourceHandle": "motorheadMemory_0-output-motorheadMemory-MotorheadMemory|BaseChatMemory|BaseMemory", + "target": "conversationalRetrievalQAChain_0", + "targetHandle": "conversationalRetrievalQAChain_0-input-memory-BaseMemory", "type": "buttonedge", - "id": "cheerioWebScraper_0-cheerioWebScraper_0-output-cheerioWebScraper-Document-pineconeUpsert_0-pineconeUpsert_0-input-document-Document", + "id": "motorheadMemory_0-motorheadMemory_0-output-motorheadMemory-MotorheadMemory|BaseChatMemory|BaseMemory-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-memory-BaseMemory", "data": { "label": "" } diff --git a/packages/server/nodemon.json b/packages/server/nodemon.json index d896b48..bf25eb0 100644 --- a/packages/server/nodemon.json +++ b/packages/server/nodemon.json @@ -1,6 +1,6 @@ { "ignore": ["**/*.spec.ts", ".git", "node_modules"], - "watch": ["commands", "index.ts", "src"], + "watch": ["commands", "index.ts", "src", "../components/nodes", "../components/src"], "exec": "yarn oclif-dev", "ext": "ts" } diff --git a/packages/server/package.json b/packages/server/package.json index 689c0c8..b8b5fe3 100644 --- a/packages/server/package.json +++ b/packages/server/package.json @@ -1,6 +1,6 @@ { "name": "flowise", - "version": "1.2.15", + "version": "1.2.16", "description": "Flowiseai Server", "main": "dist/index", "types": "dist/index.d.ts", @@ -56,6 +56,8 @@ "flowise-ui": "*", "moment-timezone": "^0.5.34", "multer": "^1.4.5-lts.1", + "mysql": "^2.18.1", + "pg": "^8.11.1", "reflect-metadata": "^0.1.13", "socket.io": "^4.6.1", "sqlite3": "^5.1.6", diff --git a/packages/server/src/ChildProcess.ts b/packages/server/src/ChildProcess.ts index 85e16cf..c055e20 100644 --- a/packages/server/src/ChildProcess.ts +++ b/packages/server/src/ChildProcess.ts @@ -1,6 +1,14 @@ import path from 'path' import { IChildProcessMessage, IReactFlowNode, IReactFlowObject, IRunChatflowMessageValue, INodeData } from './Interface' -import { buildLangchain, constructGraphs, getEndingNode, getStartingNodes, getUserHome, resolveVariables } from './utils' +import { + buildLangchain, + constructGraphs, + getEndingNode, + getStartingNodes, + getUserHome, + replaceInputsWithConfig, + resolveVariables +} from './utils' import { DataSource } from 'typeorm' import { ChatFlow } from './entity/ChatFlow' import { ChatMessage } from './entity/ChatMessage' @@ -110,6 +118,8 @@ export class ChildProcess { return } + if (incomingInput.overrideConfig) + nodeToExecute.data = replaceInputsWithConfig(nodeToExecute.data, incomingInput.overrideConfig) const reactFlowNodeData: INodeData = resolveVariables(nodeToExecute.data, reactFlowNodes, incomingInput.question) nodeToExecuteData = reactFlowNodeData @@ -143,14 +153,59 @@ export class ChildProcess { * @returns {DataSource} */ async function initDB() { - const homePath = process.env.DATABASE_PATH ?? path.join(getUserHome(), '.flowise') - const childAppDataSource = new DataSource({ - type: 'sqlite', - database: path.resolve(homePath, 'database.sqlite'), - synchronize: true, - entities: [ChatFlow, ChatMessage, Tool, Credential], - migrations: [] - }) + let childAppDataSource + let homePath + const synchronize = process.env.OVERRIDE_DATABASE === 'false' ? false : true + switch (process.env.DATABASE_TYPE) { + case 'sqlite': + homePath = process.env.DATABASE_PATH ?? path.join(getUserHome(), '.flowise') + childAppDataSource = new DataSource({ + type: 'sqlite', + database: path.resolve(homePath, 'database.sqlite'), + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + case 'mysql': + childAppDataSource = new DataSource({ + type: 'mysql', + host: process.env.DATABASE_HOST, + port: parseInt(process.env.DATABASE_PORT || '3306'), + username: process.env.DATABASE_USER, + password: process.env.DATABASE_PASSWORD, + database: process.env.DATABASE_NAME, + charset: 'utf8mb4', + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + case 'postgres': + childAppDataSource = new DataSource({ + type: 'postgres', + host: process.env.DATABASE_HOST, + port: parseInt(process.env.DATABASE_PORT || '5432'), + username: process.env.DATABASE_USER, + password: process.env.DATABASE_PASSWORD, + database: process.env.DATABASE_NAME, + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + default: + homePath = process.env.DATABASE_PATH ?? path.join(getUserHome(), '.flowise') + childAppDataSource = new DataSource({ + type: 'sqlite', + database: path.resolve(homePath, 'database.sqlite'), + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + } + return await childAppDataSource.initialize() } diff --git a/packages/server/src/DataSource.ts b/packages/server/src/DataSource.ts index fdf0c92..b0d5647 100644 --- a/packages/server/src/DataSource.ts +++ b/packages/server/src/DataSource.ts @@ -10,15 +10,57 @@ import { getUserHome } from './utils' let appDataSource: DataSource export const init = async (): Promise => { - const homePath = process.env.DATABASE_PATH ?? path.join(getUserHome(), '.flowise') - - appDataSource = new DataSource({ - type: 'sqlite', - database: path.resolve(homePath, 'database.sqlite'), - synchronize: true, - entities: [ChatFlow, ChatMessage, Tool, Credential], - migrations: [] - }) + let homePath + const synchronize = process.env.OVERRIDE_DATABASE === 'false' ? false : true + switch (process.env.DATABASE_TYPE) { + case 'sqlite': + homePath = process.env.DATABASE_PATH ?? path.join(getUserHome(), '.flowise') + appDataSource = new DataSource({ + type: 'sqlite', + database: path.resolve(homePath, 'database.sqlite'), + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + case 'mysql': + appDataSource = new DataSource({ + type: 'mysql', + host: process.env.DATABASE_HOST, + port: parseInt(process.env.DATABASE_PORT || '3306'), + username: process.env.DATABASE_USER, + password: process.env.DATABASE_PASSWORD, + database: process.env.DATABASE_NAME, + charset: 'utf8mb4', + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + case 'postgres': + appDataSource = new DataSource({ + type: 'postgres', + host: process.env.DATABASE_HOST, + port: parseInt(process.env.DATABASE_PORT || '5432'), + username: process.env.DATABASE_USER, + password: process.env.DATABASE_PASSWORD, + database: process.env.DATABASE_NAME, + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + default: + homePath = process.env.DATABASE_PATH ?? path.join(getUserHome(), '.flowise') + appDataSource = new DataSource({ + type: 'sqlite', + database: path.resolve(homePath, 'database.sqlite'), + synchronize, + entities: [ChatFlow, ChatMessage, Tool, Credential], + migrations: [] + }) + break + } } export function getDataSource(): DataSource { diff --git a/packages/server/src/commands/start.ts b/packages/server/src/commands/start.ts index 49d665b..6c6260b 100644 --- a/packages/server/src/commands/start.ts +++ b/packages/server/src/commands/start.ts @@ -21,12 +21,21 @@ export default class Start extends Command { PORT: Flags.string(), PASSPHRASE: Flags.string(), DEBUG: Flags.string(), - DATABASE_PATH: Flags.string(), APIKEY_PATH: Flags.string(), SECRETKEY_PATH: Flags.string(), LOG_PATH: Flags.string(), LOG_LEVEL: Flags.string(), - EXECUTION_MODE: Flags.string() + EXECUTION_MODE: 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(), + DATABASE_HOST: Flags.string(), + DATABASE_NAME: Flags.string(), + DATABASE_USER: Flags.string(), + DATABASE_PASSWORD: Flags.string() } async stopProcess() { @@ -58,17 +67,37 @@ export default class Start extends Command { }) const { flags } = await this.parse(Start) + + if (flags.PORT) process.env.PORT = flags.PORT + if (flags.EXECUTION_MODE) process.env.EXECUTION_MODE = flags.EXECUTION_MODE + if (flags.DEBUG) process.env.DEBUG = flags.DEBUG + + // Authorization if (flags.FLOWISE_USERNAME) process.env.FLOWISE_USERNAME = flags.FLOWISE_USERNAME if (flags.FLOWISE_PASSWORD) process.env.FLOWISE_PASSWORD = flags.FLOWISE_PASSWORD - if (flags.PORT) process.env.PORT = flags.PORT - if (flags.PASSPHRASE) process.env.PASSPHRASE = flags.PASSPHRASE - if (flags.DATABASE_PATH) process.env.DATABASE_PATH = flags.DATABASE_PATH 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 + + // Logs if (flags.LOG_PATH) process.env.LOG_PATH = flags.LOG_PATH if (flags.LOG_LEVEL) process.env.LOG_LEVEL = flags.LOG_LEVEL - if (flags.EXECUTION_MODE) process.env.EXECUTION_MODE = flags.EXECUTION_MODE - if (flags.DEBUG) process.env.DEBUG = flags.DEBUG + + // Tool functions + if (flags.TOOL_FUNCTION_BUILTIN_DEP) process.env.TOOL_FUNCTION_BUILTIN_DEP = flags.TOOL_FUNCTION_BUILTIN_DEP + 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 + if (flags.DATABASE_HOST) process.env.DATABASE_HOST = flags.DATABASE_HOST + if (flags.DATABASE_NAME) process.env.DATABASE_NAME = flags.DATABASE_NAME + if (flags.DATABASE_USER) process.env.DATABASE_USER = flags.DATABASE_USER + if (flags.DATABASE_PASSWORD) process.env.DATABASE_PASSWORD = flags.DATABASE_PASSWORD await (async () => { try { diff --git a/packages/server/src/entity/ChatFlow.ts b/packages/server/src/entity/ChatFlow.ts index e1d212c..4c37e08 100644 --- a/packages/server/src/entity/ChatFlow.ts +++ b/packages/server/src/entity/ChatFlow.ts @@ -10,7 +10,7 @@ export class ChatFlow implements IChatFlow { @Column() name: string - @Column() + @Column({ type: 'text' }) flowData: string @Column({ nullable: true }) diff --git a/packages/server/src/entity/ChatMessage.ts b/packages/server/src/entity/ChatMessage.ts index 3e4e41d..8123020 100644 --- a/packages/server/src/entity/ChatMessage.ts +++ b/packages/server/src/entity/ChatMessage.ts @@ -14,7 +14,7 @@ export class ChatMessage implements IChatMessage { @Column() chatflowid: string - @Column() + @Column({ type: 'text' }) content: string @Column({ nullable: true }) diff --git a/packages/server/src/entity/Tool.ts b/packages/server/src/entity/Tool.ts index 222fd76..011bf95 100644 --- a/packages/server/src/entity/Tool.ts +++ b/packages/server/src/entity/Tool.ts @@ -10,7 +10,7 @@ export class Tool implements ITool { @Column() name: string - @Column() + @Column({ type: 'text' }) description: string @Column() diff --git a/packages/server/src/index.ts b/packages/server/src/index.ts index f5a4399..befafd6 100644 --- a/packages/server/src/index.ts +++ b/packages/server/src/index.ts @@ -42,7 +42,9 @@ import { databaseEntities, getApiKey, transformToCredentialEntity, - decryptCredentialData + decryptCredentialData, + clearSessionMemory, + replaceInputsWithConfig } from './utils' import { cloneDeep, omit } from 'lodash' import { getDataSource } from './DataSource' @@ -63,9 +65,6 @@ export class App { constructor() { this.app = express() - - // Add the expressRequestLogger middleware to log all requests - this.app.use(expressRequestLogger) } async initDatabase() { @@ -97,6 +96,9 @@ export class App { // Allow access from * this.app.use(cors()) + // Add the expressRequestLogger middleware to log all requests + this.app.use(expressRequestLogger) + if (process.env.FLOWISE_USERNAME && process.env.FLOWISE_PASSWORD) { const username = process.env.FLOWISE_USERNAME const password = process.env.FLOWISE_PASSWORD @@ -362,8 +364,13 @@ export class App { // Get all chatmessages from chatflowid this.app.get('/api/v1/chatmessage/:id', async (req: Request, res: Response) => { - const chatmessages = await this.AppDataSource.getRepository(ChatMessage).findBy({ - chatflowid: req.params.id + const chatmessages = await this.AppDataSource.getRepository(ChatMessage).find({ + where: { + chatflowid: req.params.id + }, + order: { + createdDate: 'ASC' + } }) return res.json(chatmessages) }) @@ -382,6 +389,19 @@ export class App { // Delete all chatmessages from chatflowid this.app.delete('/api/v1/chatmessage/:id', async (req: Request, res: Response) => { + const chatflow = await this.AppDataSource.getRepository(ChatFlow).findOneBy({ + id: req.params.id + }) + if (!chatflow) { + res.status(404).send(`Chatflow ${req.params.id} not found`) + return + } + const flowData = chatflow.flowData + const parsedFlowData: IReactFlowObject = JSON.parse(flowData) + const nodes = parsedFlowData.nodes + let chatId = await getChatId(chatflow.id) + if (!chatId) chatId = chatflow.id + clearSessionMemory(nodes, this.nodesPool.componentNodes, chatId, req.query.sessionId as string) const results = await this.AppDataSource.getRepository(ChatMessage).delete({ chatflowid: req.params.id }) return res.json(results) }) @@ -630,6 +650,8 @@ export class App { } templates.push(template) }) + const FlowiseDocsQnA = templates.find((tmp) => tmp.name === 'Flowise Docs QnA') + if (FlowiseDocsQnA) templates.unshift(FlowiseDocsQnA) return res.json(templates) }) @@ -809,7 +831,7 @@ export class App { if (!chatflow) return res.status(404).send(`Chatflow ${chatflowid} not found`) let chatId = await getChatId(chatflow.id) - if (!chatId) chatId = Date.now().toString() + if (!chatId) chatId = chatflowid if (!isInternal) { await this.validateKey(req, res, chatflow) @@ -941,6 +963,8 @@ export class App { const nodeToExecute = reactFlowNodes.find((node: IReactFlowNode) => node.id === endingNodeId) if (!nodeToExecute) return res.status(404).send(`Node ${endingNodeId} not found`) + if (incomingInput.overrideConfig) + nodeToExecute.data = replaceInputsWithConfig(nodeToExecute.data, incomingInput.overrideConfig) const reactFlowNodeData: INodeData = resolveVariables(nodeToExecute.data, reactFlowNodes, incomingInput.question) nodeToExecuteData = reactFlowNodeData diff --git a/packages/server/src/utils/config.ts b/packages/server/src/utils/config.ts index 8540b3b..b5f5884 100644 --- a/packages/server/src/utils/config.ts +++ b/packages/server/src/utils/config.ts @@ -7,7 +7,7 @@ dotenv.config({ path: path.join(__dirname, '..', '..', '.env'), override: true } // default config const loggingConfig = { - dir: process.env.LOG_PATH ?? path.join(__dirname, '..', '..', '..', '..', 'logs'), + dir: process.env.LOG_PATH ?? path.join(__dirname, '..', '..', 'logs'), server: { level: process.env.LOG_LEVEL ?? 'info', filename: 'server.log', diff --git a/packages/server/src/utils/index.ts b/packages/server/src/utils/index.ts index abb0904..f92cc6d 100644 --- a/packages/server/src/utils/index.ts +++ b/packages/server/src/utils/index.ts @@ -19,7 +19,7 @@ import { ICredentialReqBody } from '../Interface' import { cloneDeep, get, omit, merge } from 'lodash' -import { ICommonObject, getInputVariables, IDatabaseEntity } from 'flowise-components' +import { ICommonObject, getInputVariables, IDatabaseEntity, handleEscapeCharacters } from 'flowise-components' import { scryptSync, randomBytes, timingSafeEqual } from 'crypto' import { lib, PBKDF2, AES, enc } from 'crypto-js' @@ -281,6 +281,29 @@ export const buildLangchain = async ( return flowNodes } +/** + * Clear memory + * @param {IReactFlowNode[]} reactFlowNodes + * @param {IComponentNodes} componentNodes + * @param {string} chatId + * @param {string} sessionId + */ +export const clearSessionMemory = async ( + reactFlowNodes: IReactFlowNode[], + componentNodes: IComponentNodes, + chatId: string, + sessionId?: string +) => { + for (const node of reactFlowNodes) { + if (node.data.category !== 'Memory') continue + const nodeInstanceFilePath = componentNodes[node.data.name].filePath as string + const nodeModule = await import(nodeInstanceFilePath) + const newNodeInstance = new nodeModule.nodeClass() + if (sessionId && node.data.inputs) node.data.inputs.sessionId = sessionId + if (newNodeInstance.clearSessionMemory) await newNodeInstance?.clearSessionMemory(node.data, { chatId }) + } +} + /** * Get variable value from outputResponses.output * @param {string} paramValue @@ -310,8 +333,13 @@ export const getVariableValue = (paramValue: string, reactFlowNodes: IReactFlowN const variableEndIdx = startIdx const variableFullPath = returnVal.substring(variableStartIdx, variableEndIdx) + /** + * Apply string transformation to convert special chars: + * FROM: hello i am ben\n\n\thow are you? + * TO: hello i am benFLOWISE_NEWLINEFLOWISE_NEWLINEFLOWISE_TABhow are you? + */ if (isAcceptVariable && variableFullPath === QUESTION_VAR_PREFIX) { - variableDict[`{{${variableFullPath}}}`] = question + variableDict[`{{${variableFullPath}}}`] = handleEscapeCharacters(question, false) } // Split by first occurrence of '.' to get just nodeId @@ -414,7 +442,11 @@ export const replaceInputsWithConfig = (flowNodeData: INodeData, overrideConfig: const getParamValues = (paramsObj: ICommonObject) => { for (const config in overrideConfig) { - paramsObj[config] = overrideConfig[config] + let paramValue = overrideConfig[config] ?? paramsObj[config] + // Check if boolean + if (paramValue === 'true') paramValue = true + else if (paramValue === 'false') paramValue = false + paramsObj[config] = paramValue } } @@ -730,7 +762,7 @@ export const isFlowValidForStream = (reactFlowNodes: IReactFlowNode[], endingNod isValidChainOrAgent = !blacklistChains.includes(endingNodeData.name) } else if (endingNodeData.category === 'Agents') { // Agent that are available to stream - const whitelistAgents = ['openAIFunctionAgent'] + const whitelistAgents = ['openAIFunctionAgent', 'csvAgent', 'airtableAgent'] isValidChainOrAgent = whitelistAgents.includes(endingNodeData.name) } diff --git a/packages/server/src/utils/logger.ts b/packages/server/src/utils/logger.ts index 72a326a..839f1ad 100644 --- a/packages/server/src/utils/logger.ts +++ b/packages/server/src/utils/logger.ts @@ -57,44 +57,47 @@ const logger = createLogger({ * this.app.use(expressRequestLogger) */ export function expressRequestLogger(req: Request, res: Response, next: NextFunction): void { - const fileLogger = createLogger({ - format: combine(timestamp({ format: 'YYYY-MM-DD HH:mm:ss' }), format.json(), errors({ stack: true })), - defaultMeta: { - package: 'server', - request: { - method: req.method, - url: req.url, - body: req.body, - query: req.query, - params: req.params, - headers: req.headers + const unwantedLogURLs = ['/api/v1/node-icon/'] + if (req.url.includes('/api/v1/') && !unwantedLogURLs.some((url) => req.url.includes(url))) { + const fileLogger = createLogger({ + format: combine(timestamp({ format: 'YYYY-MM-DD HH:mm:ss' }), format.json(), errors({ stack: true })), + defaultMeta: { + package: 'server', + request: { + method: req.method, + url: req.url, + body: req.body, + query: req.query, + params: req.params, + headers: req.headers + } + }, + transports: [ + new transports.File({ + filename: path.join(logDir, config.logging.express.filename ?? 'server-requests.log.jsonl'), + level: config.logging.express.level ?? 'debug' + }) + ] + }) + + const getRequestEmoji = (method: string) => { + const requetsEmojis: Record = { + GET: '⬇️', + POST: '⬆️', + PUT: 'πŸ–Š', + DELETE: '❌', + OPTION: 'πŸ”—' } - }, - transports: [ - new transports.File({ - filename: path.join(logDir, config.logging.express.filename ?? 'server-requests.log.jsonl'), - level: config.logging.express.level ?? 'debug' - }) - ] - }) - const getRequestEmoji = (method: string) => { - const requetsEmojis: Record = { - GET: '⬇️', - POST: '⬆️', - PUT: 'πŸ–Š', - DELETE: '❌', - OPTION: 'πŸ”—' + return requetsEmojis[method] || '?' } - return requetsEmojis[method] || '?' - } - - if (req.method !== 'GET') { - fileLogger.info(`${getRequestEmoji(req.method)} ${req.method} ${req.url}`) - logger.info(`${getRequestEmoji(req.method)} ${req.method} ${req.url}`) - } else { - fileLogger.http(`${getRequestEmoji(req.method)} ${req.method} ${req.url}`) + if (req.method !== 'GET') { + fileLogger.info(`${getRequestEmoji(req.method)} ${req.method} ${req.url}`) + logger.info(`${getRequestEmoji(req.method)} ${req.method} ${req.url}`) + } else { + fileLogger.http(`${getRequestEmoji(req.method)} ${req.method} ${req.url}`) + } } next() diff --git a/packages/ui/package.json b/packages/ui/package.json index 0df2756..bdb4984 100644 --- a/packages/ui/package.json +++ b/packages/ui/package.json @@ -1,6 +1,6 @@ { "name": "flowise-ui", - "version": "1.2.14", + "version": "1.2.15", "license": "SEE LICENSE IN LICENSE.md", "homepage": "https://flowiseai.com", "author": { diff --git a/packages/ui/src/store/actions.js b/packages/ui/src/store/actions.js index 306c5cb..64be491 100644 --- a/packages/ui/src/store/actions.js +++ b/packages/ui/src/store/actions.js @@ -11,6 +11,8 @@ export const SET_DARKMODE = '@customization/SET_DARKMODE' export const SET_DIRTY = '@canvas/SET_DIRTY' export const REMOVE_DIRTY = '@canvas/REMOVE_DIRTY' export const SET_CHATFLOW = '@canvas/SET_CHATFLOW' +export const SHOW_CANVAS_DIALOG = '@canvas/SHOW_CANVAS_DIALOG' +export const HIDE_CANVAS_DIALOG = '@canvas/HIDE_CANVAS_DIALOG' // action - notifier reducer export const ENQUEUE_SNACKBAR = 'ENQUEUE_SNACKBAR' diff --git a/packages/ui/src/store/reducers/canvasReducer.js b/packages/ui/src/store/reducers/canvasReducer.js index e98805b..8dfae52 100644 --- a/packages/ui/src/store/reducers/canvasReducer.js +++ b/packages/ui/src/store/reducers/canvasReducer.js @@ -3,7 +3,8 @@ import * as actionTypes from '../actions' export const initialState = { isDirty: false, - chatflow: null + chatflow: null, + canvasDialogShow: false } // ==============================|| CANVAS REDUCER ||============================== // @@ -25,6 +26,16 @@ const canvasReducer = (state = initialState, action) => { ...state, chatflow: action.chatflow } + case actionTypes.SHOW_CANVAS_DIALOG: + return { + ...state, + canvasDialogShow: true + } + case actionTypes.HIDE_CANVAS_DIALOG: + return { + ...state, + canvasDialogShow: false + } default: return state } diff --git a/packages/ui/src/ui-component/dialog/AdditionalParamsDialog.js b/packages/ui/src/ui-component/dialog/AdditionalParamsDialog.js index 66a1eaf..364706f 100644 --- a/packages/ui/src/ui-component/dialog/AdditionalParamsDialog.js +++ b/packages/ui/src/ui-component/dialog/AdditionalParamsDialog.js @@ -1,12 +1,15 @@ import { createPortal } from 'react-dom' +import { useDispatch } from 'react-redux' import { useState, useEffect } from 'react' import PropTypes from 'prop-types' import { Dialog, DialogContent } from '@mui/material' import PerfectScrollbar from 'react-perfect-scrollbar' import NodeInputHandler from 'views/canvas/NodeInputHandler' +import { HIDE_CANVAS_DIALOG, SHOW_CANVAS_DIALOG } from 'store/actions' const AdditionalParamsDialog = ({ show, dialogProps, onCancel }) => { const portalElement = document.getElementById('portal') + const dispatch = useDispatch() const [inputParams, setInputParams] = useState([]) const [data, setData] = useState({}) @@ -21,6 +24,11 @@ const AdditionalParamsDialog = ({ show, dialogProps, onCancel }) => { } }, [dialogProps]) + useEffect(() => { + if (show) dispatch({ type: SHOW_CANVAS_DIALOG }) + else dispatch({ type: HIDE_CANVAS_DIALOG }) + }, [show, dispatch]) + const component = show ? ( { const portalElement = document.getElementById('portal') const theme = useTheme() + const dispatch = useDispatch() const customization = useSelector((state) => state.customization) const languageType = 'json' @@ -31,6 +33,11 @@ const ExpandTextDialog = ({ show, dialogProps, onCancel, onConfirm }) => { } }, [dialogProps]) + useEffect(() => { + if (show) dispatch({ type: SHOW_CANVAS_DIALOG }) + else dispatch({ type: HIDE_CANVAS_DIALOG }) + }, [show, dispatch]) + const component = show ? ( diff --git a/packages/ui/src/ui-component/dialog/FormatPromptValuesDialog.js b/packages/ui/src/ui-component/dialog/FormatPromptValuesDialog.js index df1d357..95f833c 100644 --- a/packages/ui/src/ui-component/dialog/FormatPromptValuesDialog.js +++ b/packages/ui/src/ui-component/dialog/FormatPromptValuesDialog.js @@ -1,13 +1,21 @@ +import { useEffect } from 'react' import { createPortal } from 'react-dom' -import { useSelector } from 'react-redux' +import { useSelector, useDispatch } from 'react-redux' import PropTypes from 'prop-types' import { Dialog, DialogContent, DialogTitle } from '@mui/material' import PerfectScrollbar from 'react-perfect-scrollbar' import { JsonEditorInput } from 'ui-component/json/JsonEditor' +import { HIDE_CANVAS_DIALOG, SHOW_CANVAS_DIALOG } from 'store/actions' const FormatPromptValuesDialog = ({ show, dialogProps, onChange, onCancel }) => { const portalElement = document.getElementById('portal') const customization = useSelector((state) => state.customization) + const dispatch = useDispatch() + + useEffect(() => { + if (show) dispatch({ type: SHOW_CANVAS_DIALOG }) + else dispatch({ type: HIDE_CANVAS_DIALOG }) + }, [show, dispatch]) const component = show ? ( { + // If file type is file, isFormDataRequired = true let isFormDataRequired = false - try { const flowData = JSON.parse(chatflow.flowData) const nodes = flowData.nodes @@ -105,11 +105,27 @@ const CanvasHeader = ({ chatflow, handleSaveFlow, handleDeleteFlow, handleLoadFl console.error(e) } + // If sessionId memory, isSessionMemory = true + let isSessionMemory = false + try { + const flowData = JSON.parse(chatflow.flowData) + const nodes = flowData.nodes + for (const node of nodes) { + if (node.data.inputParams.find((param) => param.name === 'sessionId')) { + isSessionMemory = true + break + } + } + } catch (e) { + console.error(e) + } + setAPIDialogProps({ title: 'Embed in website or use as API', chatflowid: chatflow.id, chatflowApiKeyId: chatflow.apikeyid, - isFormDataRequired + isFormDataRequired, + isSessionMemory }) setAPIDialogOpen(true) } diff --git a/packages/ui/src/views/canvas/index.js b/packages/ui/src/views/canvas/index.js index 60cc147..c0206a9 100644 --- a/packages/ui/src/views/canvas/index.js +++ b/packages/ui/src/views/canvas/index.js @@ -511,6 +511,7 @@ const Canvas = () => { onConnect={onConnect} onInit={setReactFlowInstance} fitView + deleteKeyCode={canvas.canvasDialogShow ? null : ['Backspace', 'Delete']} minZoom={0.1} > { const [loginDialogOpen, setLoginDialogOpen] = useState(false) const [loginDialogProps, setLoginDialogProps] = useState({}) const [isLoading, setLoading] = useState(true) + const [chatbotOverrideConfig, setChatbotOverrideConfig] = useState({}) const getSpecificChatflowFromPublicApi = useApi(chatflowsApi.getSpecificChatflowFromPublicEndpoint) const getSpecificChatflowApi = useApi(chatflowsApi.getSpecificChatflow) @@ -77,10 +78,19 @@ const ChatbotFull = () => { setChatflow(chatflowData) if (chatflowData.chatbotConfig) { try { - setChatbotTheme(JSON.parse(chatflowData.chatbotConfig)) + const parsedConfig = JSON.parse(chatflowData.chatbotConfig) + setChatbotTheme(parsedConfig) + if (parsedConfig.overrideConfig) { + // Generate new sessionId + if (parsedConfig.overrideConfig.generateNewSession) { + parsedConfig.overrideConfig.sessionId = Date.now().toString() + } + setChatbotOverrideConfig(parsedConfig.overrideConfig) + } } catch (e) { console.error(e) setChatbotTheme({}) + setChatbotOverrideConfig({}) } } } @@ -97,7 +107,12 @@ const ChatbotFull = () => { {!chatflow || chatflow.apikeyid ? (

Invalid Chatbot

) : ( - + )} diff --git a/packages/ui/src/views/chatflows/APICodeDialog.js b/packages/ui/src/views/chatflows/APICodeDialog.js index 5e32c1d..994f755 100644 --- a/packages/ui/src/views/chatflows/APICodeDialog.js +++ b/packages/ui/src/views/chatflows/APICodeDialog.js @@ -190,7 +190,10 @@ output = query({ "${baseURL}/api/v1/prediction/${dialogProps.chatflowid}", { method: "POST", - body: data + headers: { + "Content-Type": "application/json" + }, + body: JSON.stringify(data) } ); const result = await response.json(); @@ -204,7 +207,8 @@ query({"question": "Hey, how are you?"}).then((response) => { } else if (codeLang === 'cURL') { return `curl ${baseURL}/api/v1/prediction/${dialogProps.chatflowid} \\ -X POST \\ - -d '{"question": "Hey, how are you?"}'` + -d '{"question": "Hey, how are you?"}' \\ + -H "Content-Type: application/json"` } return '' } @@ -229,9 +233,12 @@ output = query({ const response = await fetch( "${baseURL}/api/v1/prediction/${dialogProps.chatflowid}", { - headers: { Authorization: "Bearer ${selectedApiKey?.apiKey}" }, + headers: { + Authorization: "Bearer ${selectedApiKey?.apiKey}", + "Content-Type": "application/json" + }, method: "POST", - body: data + body: JSON.stringify(data) } ); const result = await response.json(); @@ -246,6 +253,7 @@ query({"question": "Hey, how are you?"}).then((response) => { return `curl ${baseURL}/api/v1/prediction/${dialogProps.chatflowid} \\ -X POST \\ -d '{"question": "Hey, how are you?"}' \\ + -H "Content-Type: application/json" \\ -H "Authorization: Bearer ${selectedApiKey?.apiKey}"` } return '' @@ -316,7 +324,8 @@ query(formData).then((response) => { ` } else if (codeLang === 'cURL') { return `curl ${baseURL}/api/v1/prediction/${dialogProps.chatflowid} \\ - -X POST \\${getConfigExamplesForCurl(configData, 'formData')}` + -X POST \\${getConfigExamplesForCurl(configData, 'formData')} \\ + -H "Content-Type: multipart/form-data"` } return '' } @@ -363,6 +372,7 @@ query(formData).then((response) => { } else if (codeLang === 'cURL') { return `curl ${baseURL}/api/v1/prediction/${dialogProps.chatflowid} \\ -X POST \\${getConfigExamplesForCurl(configData, 'formData')} \\ + -H "Content-Type: multipart/form-data" \\ -H "Authorization: Bearer ${selectedApiKey?.apiKey}"` } return '' @@ -392,7 +402,10 @@ output = query({ "${baseURL}/api/v1/prediction/${dialogProps.chatflowid}", { method: "POST", - body: data + headers: { + "Content-Type": "application/json" + }, + body: JSON.stringify(data) } ); const result = await response.json(); @@ -410,7 +423,8 @@ query({ } else if (codeLang === 'cURL') { return `curl ${baseURL}/api/v1/prediction/${dialogProps.chatflowid} \\ -X POST \\ - -d '{"question": "Hey, how are you?", "overrideConfig": {${getConfigExamplesForCurl(configData, 'json')}}'` + -d '{"question": "Hey, how are you?", "overrideConfig": {${getConfigExamplesForCurl(configData, 'json')}}' \\ + -H "Content-Type: application/json"` } return '' } @@ -439,9 +453,12 @@ output = query({ const response = await fetch( "${baseURL}/api/v1/prediction/${dialogProps.chatflowid}", { - headers: { Authorization: "Bearer ${selectedApiKey?.apiKey}" }, + headers: { + Authorization: "Bearer ${selectedApiKey?.apiKey}", + "Content-Type": "application/json" + }, method: "POST", - body: data + body: JSON.stringify(data) } ); const result = await response.json(); @@ -460,6 +477,7 @@ query({ return `curl ${baseURL}/api/v1/prediction/${dialogProps.chatflowid} \\ -X POST \\ -d '{"question": "Hey, how are you?", "overrideConfig": {${getConfigExamplesForCurl(configData, 'json')}}' \\ + -H "Content-Type: application/json" \\ -H "Authorization: Bearer ${selectedApiKey?.apiKey}"` } return '' @@ -594,7 +612,9 @@ query({ )} )} - {codeLang === 'Share Chatbot' && !chatflowApiKeyId && } + {codeLang === 'Share Chatbot' && !chatflowApiKeyId && ( + + )} ))} diff --git a/packages/ui/src/views/chatflows/ShareChatbot.js b/packages/ui/src/views/chatflows/ShareChatbot.js index 51e12e5..0f05c28 100644 --- a/packages/ui/src/views/chatflows/ShareChatbot.js +++ b/packages/ui/src/views/chatflows/ShareChatbot.js @@ -2,6 +2,7 @@ import { useState } from 'react' import { useDispatch, useSelector } from 'react-redux' import { enqueueSnackbar as enqueueSnackbarAction, closeSnackbar as closeSnackbarAction, SET_CHATFLOW } from 'store/actions' import { SketchPicker } from 'react-color' +import PropTypes from 'prop-types' import { Box, Typography, Button, Switch, OutlinedInput, Popover, Stack, IconButton } from '@mui/material' import { useTheme } from '@mui/material/styles' @@ -41,7 +42,7 @@ const defaultConfig = { } } -const ShareChatbot = () => { +const ShareChatbot = ({ isSessionMemory }) => { const dispatch = useDispatch() const theme = useTheme() const chatflow = useSelector((state) => state.canvas.chatflow) @@ -54,6 +55,7 @@ const ShareChatbot = () => { const closeSnackbar = (...args) => dispatch(closeSnackbarAction(...args)) const [isPublicChatflow, setChatflowIsPublic] = useState(chatflow.isPublic ?? false) + const [generateNewSession, setGenerateNewSession] = useState(chatbotConfig?.generateNewSession ?? false) const [welcomeMessage, setWelcomeMessage] = useState(chatbotConfig?.welcomeMessage ?? '') const [backgroundColor, setBackgroundColor] = useState(chatbotConfig?.backgroundColor ?? defaultConfig.backgroundColor) @@ -103,7 +105,8 @@ const ShareChatbot = () => { userMessage: { showAvatar: false }, - textInput: {} + textInput: {}, + overrideConfig: {} } if (welcomeMessage) obj.welcomeMessage = welcomeMessage if (backgroundColor) obj.backgroundColor = backgroundColor @@ -125,6 +128,8 @@ const ShareChatbot = () => { if (textInputPlaceholder) obj.textInput.placeholder = textInputPlaceholder if (textInputSendButtonColor) obj.textInput.sendButtonColor = textInputSendButtonColor + if (isSessionMemory) obj.overrideConfig.generateNewSession = generateNewSession + return obj } @@ -273,6 +278,9 @@ const ShareChatbot = () => { case 'userMessageShowAvatar': setUserMessageShowAvatar(value) break + case 'generateNewSession': + setGenerateNewSession(value) + break } } @@ -431,6 +439,16 @@ const ShareChatbot = () => { {textField(textInputPlaceholder, 'textInputPlaceholder', 'TextInput Placeholder', 'string', `Type question..`)} {colorField(textInputSendButtonColor, 'textInputSendButtonColor', 'TextIntput Send Button Color')} + {/*Session Memory Input*/} + {isSessionMemory && ( + <> + + Session Memory + + {booleanField(generateNewSession, 'generateNewSession', 'Start new session when chatbot link is opened or refreshed')} + + )} + onSave()}> Save Changes @@ -470,4 +488,8 @@ const ShareChatbot = () => { ) } +ShareChatbot.propTypes = { + isSessionMemory: PropTypes.bool +} + export default ShareChatbot