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Merge branch 'main' into feature/Credential

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# Conflicts:
#	README.md
#	docker/.env.example
#	packages/components/nodes/documentloaders/Notion/NotionDB.ts
#	packages/components/nodes/memory/DynamoDb/DynamoDb.ts
#	packages/components/nodes/memory/MotorheadMemory/MotorheadMemory.ts
#	packages/components/nodes/memory/ZepMemory/ZepMemory.ts
#	packages/components/package.json
#	packages/components/src/utils.ts
#	packages/server/.env.example
#	packages/server/README.md
#	packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json
#	packages/server/src/ChildProcess.ts
#	packages/server/src/DataSource.ts
#	packages/server/src/commands/start.ts
#	packages/server/src/index.ts
#	packages/server/src/utils/index.ts
#	packages/server/src/utils/logger.ts
This commit is contained in:
Henry
2023-07-27 11:26:34 +01:00
parent 0665dcef55 e2d3f27842
commit 61dabbb7da
107 changed files with 4347 additions and 826 deletions
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packages/server/.env.example
+15 -4
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@@ -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
packages/server/README.md
+1 -15
View File
@@ -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:
packages/server/marketplaces/chatflows/API Agent 2.json → packages/server/marketplaces/chatflows/API Agent OpenAI.json
+1 -1
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@@ -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,
packages/server/marketplaces/chatflows/API Agent 1.json → packages/server/marketplaces/chatflows/API Agent.json
View File
packages/server/marketplaces/chatflows/CSV Agent.json
+226
View File
@@ -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": ""
}
}
]
}
packages/server/marketplaces/chatflows/Conversational Retrieval QA Chain.json
+275 -275
View File
@@ -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
"x": 1184.1176114500388,
"y": -44.15535835370571
},
"selected": false,
"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
},
"selected": false,
"positionAbsolute": {
"x": 1626.7402076624098,
"y": 394.29095783927113
},
"dragging": false
},
{
"width": 300,
"height": 329,
"height": 328,
"id": "openAIEmbeddings_0",
"position": {
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"y": 579.9826205586049
"x": 795.6162477805387,
"y": 603.260214150876
},
"type": "customNode",
"data": {
@@ -462,18 +232,18 @@
},
"selected": false,
"positionAbsolute": {
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"y": 579.9826205586049
"x": 795.6162477805387,
"y": 603.260214150876
},
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},
{
"width": 300,
"height": 555,
"height": 554,
"id": "pineconeUpsert_0",
"position": {
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"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": "",
@@ -569,20 +339,272 @@
},
"selected": false,
"positionAbsolute": {
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"y": 588.825080688097
"x": 1191.1792786926865,
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},
"dragging": false
},
{
"width": 300,
"height": 376,
"id": "recursiveCharacterTextSplitter_0",
"position": {
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"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
},
{
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"height": 410,
"id": "textFile_0",
"position": {
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"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
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"positionAbsolute": {
"x": 786.5497697231324,
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},
{
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"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": [
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"label": "MapReduceDocumentsChain",
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packages/server/marketplaces/chatflows/Flowise Docs QnA.json
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View File
@@ -0,0 +1,637 @@
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packages/server/marketplaces/chatflows/Local QnA.json
+5 -4
View File
@@ -135,15 +135,16 @@
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],
"inputs": {
"model": "{{chatLocalAI_0.data.instance}}",
"vectorStoreRetriever": "{{faissUpsert_0.data.instance}}"
"vectorStoreRetriever": "{{faissUpsert_0.data.instance}}",
"memory": ""
},
"outputAnchors": [
{
packages/server/marketplaces/chatflows/Long Term Memory.json
+5 -5
View File
@@ -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": ""
}
packages/server/marketplaces/chatflows/Metadata Filter Load.json
+3 -3
View File
@@ -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": {
packages/server/marketplaces/chatflows/Metadata Filter Upsert.json
+3 -3
View File
@@ -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": {
packages/server/marketplaces/chatflows/Replicate LLM.json
+273
View File
@@ -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
},
{
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"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: <a target=\"_blank\" href=\"https://replicate.com/a16z-infra/llama13b-v2-chat/api#inputs\">llama13b-v2</a>",
"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": ""
}
}
]
}
packages/server/marketplaces/chatflows/WebPage QnA.json
+260 -165
View File
@@ -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
},
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"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": {
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"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": {
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"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 +489,10 @@
},
"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": {},
@@ -603,8 +500,195 @@
},
"selected": false,
"positionAbsolute": {
"x": 406.08456707531263,
"y": 197.66460328693972
"x": 443.00626484042334,
"y": 1.2942107707648631
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},
{
"width": 300,
"height": 479,
"id": "conversationalRetrievalQAChain_0",
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"y": 305.08959224761225
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"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": [
{
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"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": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"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": ""
}
packages/server/nodemon.json
+1 -1
View File
@@ -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"
}
packages/server/package.json
+3 -1
View File
@@ -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",
packages/server/src/ChildProcess.ts
+64 -9
View File
@@ -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()
}
packages/server/src/DataSource.ts
+51 -9
View File
@@ -10,15 +10,57 @@ import { getUserHome } from './utils'
let appDataSource: DataSource
export const init = async (): Promise<void> => {
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 {
packages/server/src/commands/start.ts
+39 -10
View File
@@ -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() {
@@ -58,18 +67,38 @@ export default class Start extends Command {
})
const { flags } = await this.parse(Start)
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
if (flags.SECRETKEY_PATH) process.env.SECRETKEY_PATH = flags.SECRETKEY_PATH
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
// 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.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
// 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 {
logger.info('Starting Flowise...')
packages/server/src/entity/ChatFlow.ts
+1 -1
View File
@@ -10,7 +10,7 @@ export class ChatFlow implements IChatFlow {
@Column()
name: string
@Column()
@Column({ type: 'text' })
flowData: string
@Column({ nullable: true })
packages/server/src/entity/ChatMessage.ts
+1 -1
View File
@@ -14,7 +14,7 @@ export class ChatMessage implements IChatMessage {
@Column()
chatflowid: string
@Column()
@Column({ type: 'text' })
content: string
@Column({ nullable: true })
packages/server/src/entity/Tool.ts
+1 -1
View File
@@ -10,7 +10,7 @@ export class Tool implements ITool {
@Column()
name: string
@Column()
@Column({ type: 'text' })
description: string
@Column()
packages/server/src/index.ts
+31 -7
View File
@@ -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
packages/server/src/utils/config.ts
+1 -1
View File
@@ -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',
packages/server/src/utils/index.ts
+36 -4
View File
@@ -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)
}
packages/server/src/utils/logger.ts
+38 -35
View File
@@ -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
}
},
transports: [
new transports.File({
filename: path.join(logDir, config.logging.express.filename ?? 'server-requests.log.jsonl'),
level: config.logging.express.level ?? 'debug'
})
]
})
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<string, string> = {
GET: '⬇️',
POST: '⬆️',
PUT: '🖊',
DELETE: '❌',
OPTION: '🔗'
const getRequestEmoji = (method: string) => {
const requetsEmojis: Record<string, string> = {
GET: '⬇️',
POST: '⬆️',
PUT: '🖊',
DELETE: '❌',
OPTION: '🔗'
}
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()