mirror of
https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-28 21:00:58 +03:00
Merge branch 'main' into feature/BabyAGI
This commit is contained in:
Henry
@@ -0,0 +1 @@
|
||||
PORT=3000
|
||||
Regular → Executable
Regular → Executable
Regular → Executable
Regular → Executable
@@ -3,11 +3,11 @@
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"type": "string",
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"rows": 5,
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"placeholder": "What is a good name for a company that makes {product}?"
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"rows": 4,
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"placeholder": "What is a good name for a company that makes {product}?",
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"label": "Format Prompt Values",
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"template": "Word: {word}\\nAntonym: {antonym}\\n"
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"template": "Word: {word}\\nAntonym: {antonym}\\n",
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@@ -39,22 +52,23 @@
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@@ -70,28 +84,32 @@
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|
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"rows": 4,
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"placeholder": "Give the antonym of every input",
|
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"id": "fewShotPromptTemplate_0-input-prefix-string"
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{
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"label": "Suffix",
|
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"name": "suffix",
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"type": "string",
|
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"rows": 3,
|
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"placeholder": "Word: {input}\nAntonym:"
|
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"rows": 4,
|
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"placeholder": "Word: {input}\nAntonym:",
|
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"id": "fewShotPromptTemplate_0-input-suffix-string"
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{
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"label": "Example Seperator",
|
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"name": "exampleSeparator",
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"placeholder": "\n\n"
|
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"placeholder": "\n\n",
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{
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"label": "Template Format",
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@@ -107,7 +125,8 @@
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"name": "jinja-2"
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"default": "f-string",
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@@ -134,12 +153,13 @@
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"type": "FewShotPromptTemplate | BaseStringPromptTemplate | BasePromptTemplate"
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@@ -148,8 +168,8 @@
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"height": 472,
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@@ -164,7 +184,8 @@
|
||||
{
|
||||
"label": "OpenAI Api Key",
|
||||
"name": "openAIApiKey",
|
||||
"type": "password"
|
||||
"type": "password",
|
||||
"id": "openAI_0-input-openAIApiKey-password"
|
||||
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|
||||
{
|
||||
"label": "Model Name",
|
||||
@@ -189,20 +210,22 @@
|
||||
}
|
||||
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||||
"default": "text-davinci-003",
|
||||
"optional": true
|
||||
"optional": true,
|
||||
"id": "openAI_0-input-modelName-options"
|
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||||
{
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||||
"label": "Temperature",
|
||||
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|
||||
"type": "number",
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||||
"default": 0.7,
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"optional": true,
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"id": "openAI_0-input-temperature-number"
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||||
"modelName": "text-davinci-003",
|
||||
"temperature": 0.7
|
||||
"temperature": "0"
|
||||
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||||
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{
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@@ -212,22 +235,23 @@
|
||||
"type": "OpenAI | BaseLLM | BaseLanguageModel"
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}
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@@ -240,12 +264,12 @@
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"description": "Chain to run queries against LLMs",
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{
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"label": "Format Prompt Values",
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"name": "promptValues",
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"label": "Chain Name",
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"name": "chainName",
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@@ -265,38 +289,44 @@
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"inputs": {
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"model": "{{openAI_0.data.instance}}",
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"prompt": "{{fewShotPromptTemplate_0.data.instance}}",
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{
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||||
"name": "llmChain",
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||||
"label": "LLM Chain",
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||||
"type": "LLMChain | BaseChain"
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||||
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{
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||||
"id": "llmChain_0-output-outputPrediction-string",
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"name": "outputPrediction",
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"label": "Output Prediction",
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||||
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@@ -318,6 +348,17 @@
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@@ -0,0 +1,307 @@
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||||
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"type": "AIPlugin | Tool"
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||||
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|
||||
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|
||||
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||||
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"name": "requestsPost",
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"label": "RequestsPost",
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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||||
"type": "RequestsGet | Tool"
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||||
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||||
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||||
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||||
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||||
"name": "mrklAgentChat",
|
||||
"type": "AgentExecutor",
|
||||
"baseClasses": ["AgentExecutor", "BaseChain"],
|
||||
"category": "Agents",
|
||||
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|
||||
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|
||||
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|
||||
{
|
||||
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|
||||
"name": "tools",
|
||||
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|
||||
"list": true,
|
||||
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|
||||
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|
||||
{
|
||||
"label": "Chat Model",
|
||||
"name": "model",
|
||||
"type": "BaseChatModel",
|
||||
"id": "mrklAgentChat_0-input-model-BaseChatModel"
|
||||
}
|
||||
],
|
||||
"inputs": {
|
||||
"tools": ["{{requestsGet_0.data.instance}}", "{{requestsPost_0.data.instance}}", "{{aiPlugin_0.data.instance}}"],
|
||||
"model": "{{chatOpenAI_0.data.instance}}"
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "mrklAgentChat_0-output-mrklAgentChat-AgentExecutor|BaseChain",
|
||||
"name": "mrklAgentChat",
|
||||
"label": "AgentExecutor",
|
||||
"type": "AgentExecutor | BaseChain"
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||||
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||||
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Load Diff
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{
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@@ -6,8 +6,8 @@
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"height": 472,
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@@ -22,7 +22,8 @@
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{
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"label": "OpenAI Api Key",
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"name": "openAIApiKey",
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},
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{
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"label": "Model Name",
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@@ -47,14 +48,16 @@
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}
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"default": "text-davinci-003",
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@@ -70,69 +73,23 @@
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"type": "OpenAI | BaseLLM | BaseLanguageModel"
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"baseClasses": ["PromptTemplate", "BaseStringPromptTemplate", "BasePromptTemplate"],
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{
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{
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"name": "promptTemplate",
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"label": "PromptTemplate",
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{
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"inputs": {
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@@ -3,66 +3,91 @@
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|
||||
"chainName": "Language Translation"
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate",
|
||||
"name": "chatPromptTemplate",
|
||||
"label": "ChatPromptTemplate",
|
||||
"type": "ChatPromptTemplate | BaseChatPromptTemplate | BasePromptTemplate"
|
||||
"name": "output",
|
||||
"label": "Output",
|
||||
"type": "options",
|
||||
"options": [
|
||||
{
|
||||
"id": "llmChain_0-output-llmChain-LLMChain|BaseChain",
|
||||
"name": "llmChain",
|
||||
"label": "LLM Chain",
|
||||
"type": "LLMChain | BaseChain"
|
||||
},
|
||||
{
|
||||
"id": "llmChain_0-output-outputPrediction-string",
|
||||
"name": "outputPrediction",
|
||||
"label": "Output Prediction",
|
||||
"type": "string"
|
||||
}
|
||||
],
|
||||
"default": "llmChain"
|
||||
}
|
||||
],
|
||||
"outputs": {
|
||||
"output": "llmChain"
|
||||
},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
|
||||
"dragging": false,
|
||||
"positionAbsolute": {
|
||||
"x": 524,
|
||||
"y": 237
|
||||
}
|
||||
"x": 1136.5578350285277,
|
||||
"y": 619.2492937692573
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"width": 300,
|
||||
"height": 472,
|
||||
"id": "chatOpenAI_0",
|
||||
"position": {
|
||||
"x": 855.1997276913991,
|
||||
"y": 24.090553068402556
|
||||
"x": 776.3729862229602,
|
||||
"y": 290.4580650723551
|
||||
},
|
||||
"type": "customNode",
|
||||
"data": {
|
||||
@@ -77,7 +102,8 @@
|
||||
{
|
||||
"label": "OpenAI Api Key",
|
||||
"name": "openAIApiKey",
|
||||
"type": "password"
|
||||
"type": "password",
|
||||
"id": "chatOpenAI_0-input-openAIApiKey-password"
|
||||
},
|
||||
{
|
||||
"label": "Model Name",
|
||||
@@ -106,20 +132,22 @@
|
||||
}
|
||||
],
|
||||
"default": "gpt-3.5-turbo",
|
||||
"optional": true
|
||||
"optional": true,
|
||||
"id": "chatOpenAI_0-input-modelName-options"
|
||||
},
|
||||
{
|
||||
"label": "Temperature",
|
||||
"name": "temperature",
|
||||
"type": "number",
|
||||
"default": 0.9,
|
||||
"optional": true
|
||||
"optional": true,
|
||||
"id": "chatOpenAI_0-input-temperature-number"
|
||||
}
|
||||
],
|
||||
"inputAnchors": [],
|
||||
"inputs": {
|
||||
"modelName": "gpt-3.5-turbo",
|
||||
"temperature": 0.9
|
||||
"temperature": "0"
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
@@ -129,75 +157,83 @@
|
||||
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
|
||||
"positionAbsolute": {
|
||||
"x": 855.1997276913991,
|
||||
"y": 24.090553068402556
|
||||
"x": 776.3729862229602,
|
||||
"y": 290.4580650723551
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"width": 300,
|
||||
"height": 461,
|
||||
"id": "llmChain_0",
|
||||
"height": 710,
|
||||
"id": "chatPromptTemplate_0",
|
||||
"position": {
|
||||
"x": 1192.2235692202612,
|
||||
"y": 361.71736677076257
|
||||
"x": 428.40848918154023,
|
||||
"y": 291.77611240963313
|
||||
},
|
||||
"type": "customNode",
|
||||
"data": {
|
||||
"id": "llmChain_0",
|
||||
"label": "LLM Chain",
|
||||
"name": "llmChain",
|
||||
"type": "LLMChain",
|
||||
"baseClasses": ["LLMChain", "BaseChain"],
|
||||
"category": "Chains",
|
||||
"description": "Chain to run queries against LLMs",
|
||||
"id": "chatPromptTemplate_0",
|
||||
"label": "Chat Prompt Template",
|
||||
"name": "chatPromptTemplate",
|
||||
"type": "ChatPromptTemplate",
|
||||
"baseClasses": ["ChatPromptTemplate", "BaseChatPromptTemplate", "BasePromptTemplate"],
|
||||
"category": "Prompts",
|
||||
"description": "Schema to represent a chat prompt",
|
||||
"inputParams": [
|
||||
{
|
||||
"label": "System Message",
|
||||
"name": "systemMessagePrompt",
|
||||
"type": "string",
|
||||
"rows": 4,
|
||||
"placeholder": "You are a helpful assistant that translates {input_language} to {output_language}.",
|
||||
"id": "chatPromptTemplate_0-input-systemMessagePrompt-string"
|
||||
},
|
||||
{
|
||||
"label": "Human Message",
|
||||
"name": "humanMessagePrompt",
|
||||
"type": "string",
|
||||
"rows": 4,
|
||||
"placeholder": "{text}",
|
||||
"id": "chatPromptTemplate_0-input-humanMessagePrompt-string"
|
||||
},
|
||||
{
|
||||
"label": "Format Prompt Values",
|
||||
"name": "promptValues",
|
||||
"type": "string",
|
||||
"rows": 5,
|
||||
"rows": 4,
|
||||
"placeholder": "{\n \"input_language\": \"English\",\n \"output_language\": \"French\"\n}",
|
||||
"optional": true
|
||||
}
|
||||
],
|
||||
"inputAnchors": [
|
||||
{
|
||||
"label": "Language Model",
|
||||
"name": "model",
|
||||
"type": "BaseLanguageModel",
|
||||
"id": "llmChain_0-input-model-BaseLanguageModel"
|
||||
},
|
||||
{
|
||||
"label": "Prompt",
|
||||
"name": "prompt",
|
||||
"type": "BasePromptTemplate",
|
||||
"id": "llmChain_0-input-prompt-BasePromptTemplate"
|
||||
"optional": true,
|
||||
"acceptVariable": true,
|
||||
"list": true,
|
||||
"id": "chatPromptTemplate_0-input-promptValues-string"
|
||||
}
|
||||
],
|
||||
"inputAnchors": [],
|
||||
"inputs": {
|
||||
"model": "{{chatOpenAI_0.data.instance}}",
|
||||
"prompt": "{{chatPromptTemplate_0.data.instance}}",
|
||||
"systemMessagePrompt": "You are a helpful assistant that translates {input_language} to {output_language}.",
|
||||
"humanMessagePrompt": "{input}",
|
||||
"promptValues": "{\n \"input_language\": \"English\",\n \"output_language\": \"French\"\n}"
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "llmChain_0-output-llmChain-LLMChain|BaseChain",
|
||||
"name": "llmChain",
|
||||
"label": "LLMChain",
|
||||
"type": "LLMChain | BaseChain"
|
||||
"id": "chatPromptTemplate_0-output-chatPromptTemplate-ChatPromptTemplate|BaseChatPromptTemplate|BasePromptTemplate",
|
||||
"name": "chatPromptTemplate",
|
||||
"label": "ChatPromptTemplate",
|
||||
"type": "ChatPromptTemplate | BaseChatPromptTemplate | BasePromptTemplate"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"selected": false,
|
||||
"positionAbsolute": {
|
||||
"x": 1192.2235692202612,
|
||||
"y": 361.71736677076257
|
||||
"x": 428.40848918154023,
|
||||
"y": 291.77611240963313
|
||||
},
|
||||
"dragging": false
|
||||
}
|
||||
|
||||
@@ -1,9 +1,8 @@
|
||||
import { INodeData } from 'flowise-components'
|
||||
import { IActiveChatflows } from './Interface'
|
||||
import { IActiveChatflows, INodeData, IReactFlowNode } from './Interface'
|
||||
|
||||
/**
|
||||
* This pool is to keep track of active test triggers (event listeners),
|
||||
* so we can clear the event listeners whenever user refresh or exit page
|
||||
* This pool is to keep track of active chatflow pools
|
||||
* so we can prevent building langchain flow all over again
|
||||
*/
|
||||
export class ChatflowPool {
|
||||
activeChatflows: IActiveChatflows = {}
|
||||
@@ -12,9 +11,11 @@ export class ChatflowPool {
|
||||
* Add to the pool
|
||||
* @param {string} chatflowid
|
||||
* @param {INodeData} endingNodeData
|
||||
* @param {IReactFlowNode[]} startingNodes
|
||||
*/
|
||||
add(chatflowid: string, endingNodeData: INodeData) {
|
||||
add(chatflowid: string, endingNodeData: INodeData, startingNodes: IReactFlowNode[]) {
|
||||
this.activeChatflows[chatflowid] = {
|
||||
startingNodes,
|
||||
endingNodeData,
|
||||
inSync: true
|
||||
}
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
import { INode, INodeData } from 'flowise-components'
|
||||
import { INode, INodeData as INodeDataFromComponent, INodeParams } from 'flowise-components'
|
||||
|
||||
export type MessageType = 'apiMessage' | 'userMessage'
|
||||
|
||||
@@ -38,6 +38,12 @@ export interface INodeDirectedGraph {
|
||||
[key: string]: string[]
|
||||
}
|
||||
|
||||
export interface INodeData extends INodeDataFromComponent {
|
||||
inputAnchors: INodeParams[]
|
||||
inputParams: INodeParams[]
|
||||
outputAnchors: INodeParams[]
|
||||
}
|
||||
|
||||
export interface IReactFlowNode {
|
||||
id: string
|
||||
position: {
|
||||
@@ -111,6 +117,7 @@ export interface IncomingInput {
|
||||
|
||||
export interface IActiveChatflows {
|
||||
[key: string]: {
|
||||
startingNodes: IReactFlowNode[]
|
||||
endingNodeData: INodeData
|
||||
inSync: boolean
|
||||
}
|
||||
|
||||
@@ -4,15 +4,22 @@ import cors from 'cors'
|
||||
import http from 'http'
|
||||
import * as fs from 'fs'
|
||||
|
||||
import { IChatFlow, IncomingInput, IReactFlowNode, IReactFlowObject } from './Interface'
|
||||
import { getNodeModulesPackagePath, getStartingNodes, buildLangchain, getEndingNode, constructGraphs } from './utils'
|
||||
import { IChatFlow, IncomingInput, IReactFlowNode, IReactFlowObject, INodeData } from './Interface'
|
||||
import {
|
||||
getNodeModulesPackagePath,
|
||||
getStartingNodes,
|
||||
buildLangchain,
|
||||
getEndingNode,
|
||||
constructGraphs,
|
||||
resolveVariables,
|
||||
isStartNodeDependOnInput
|
||||
} from './utils'
|
||||
import { cloneDeep } from 'lodash'
|
||||
import { getDataSource } from './DataSource'
|
||||
import { NodesPool } from './NodesPool'
|
||||
import { ChatFlow } from './entity/ChatFlow'
|
||||
import { ChatMessage } from './entity/ChatMessage'
|
||||
import { ChatflowPool } from './ChatflowPool'
|
||||
import { INodeData } from 'flowise-components'
|
||||
|
||||
export class App {
|
||||
app: express.Application
|
||||
@@ -196,12 +203,19 @@ export class App {
|
||||
|
||||
let nodeToExecuteData: INodeData
|
||||
|
||||
/* Check if:
|
||||
* - Node Data already exists in pool
|
||||
* - Still in sync (i.e the flow has not been modified since)
|
||||
* - Flow doesn't start with nodes that depend on incomingInput.question
|
||||
***/
|
||||
if (
|
||||
Object.prototype.hasOwnProperty.call(this.chatflowPool.activeChatflows, chatflowid) &&
|
||||
this.chatflowPool.activeChatflows[chatflowid].inSync
|
||||
this.chatflowPool.activeChatflows[chatflowid].inSync &&
|
||||
!isStartNodeDependOnInput(this.chatflowPool.activeChatflows[chatflowid].startingNodes)
|
||||
) {
|
||||
nodeToExecuteData = this.chatflowPool.activeChatflows[chatflowid].endingNodeData
|
||||
} else {
|
||||
/*** Get chatflows and prepare data ***/
|
||||
const chatflow = await this.AppDataSource.getRepository(ChatFlow).findOneBy({
|
||||
id: chatflowid
|
||||
})
|
||||
@@ -209,33 +223,53 @@ export class App {
|
||||
|
||||
const flowData = chatflow.flowData
|
||||
const parsedFlowData: IReactFlowObject = JSON.parse(flowData)
|
||||
const nodes = parsedFlowData.nodes
|
||||
const edges = parsedFlowData.edges
|
||||
|
||||
/*** Get Ending Node with Directed Graph ***/
|
||||
const { graph, nodeDependencies } = constructGraphs(parsedFlowData.nodes, parsedFlowData.edges)
|
||||
const { graph, nodeDependencies } = constructGraphs(nodes, edges)
|
||||
const directedGraph = graph
|
||||
const endingNodeId = getEndingNode(nodeDependencies, directedGraph)
|
||||
if (!endingNodeId) return res.status(500).send(`Ending node must be either a Chain or Agent`)
|
||||
|
||||
const endingNodeData = nodes.find((nd) => nd.id === endingNodeId)?.data
|
||||
if (!endingNodeData) return res.status(500).send(`Ending node must be either a Chain or Agent`)
|
||||
|
||||
if (
|
||||
endingNodeData.outputs &&
|
||||
Object.keys(endingNodeData.outputs).length &&
|
||||
!Object.values(endingNodeData.outputs).includes(endingNodeData.name)
|
||||
) {
|
||||
return res
|
||||
.status(500)
|
||||
.send(
|
||||
`Output of ${endingNodeData.label} (${endingNodeData.id}) must be ${endingNodeData.label}, can't be an Output Prediction`
|
||||
)
|
||||
}
|
||||
|
||||
/*** Get Starting Nodes with Non-Directed Graph ***/
|
||||
const constructedObj = constructGraphs(parsedFlowData.nodes, parsedFlowData.edges, true)
|
||||
const constructedObj = constructGraphs(nodes, edges, true)
|
||||
const nonDirectedGraph = constructedObj.graph
|
||||
const { startingNodeIds, depthQueue } = getStartingNodes(nonDirectedGraph, endingNodeId)
|
||||
|
||||
/*** BFS to traverse from Starting Nodes to Ending Node ***/
|
||||
const reactFlowNodes = await buildLangchain(
|
||||
startingNodeIds,
|
||||
parsedFlowData.nodes,
|
||||
nodes,
|
||||
graph,
|
||||
depthQueue,
|
||||
this.nodesPool.componentNodes
|
||||
this.nodesPool.componentNodes,
|
||||
incomingInput.question
|
||||
)
|
||||
|
||||
const nodeToExecute = reactFlowNodes.find((node: IReactFlowNode) => node.id === endingNodeId)
|
||||
if (!nodeToExecute) return res.status(404).send(`Node ${endingNodeId} not found`)
|
||||
|
||||
nodeToExecuteData = nodeToExecute.data
|
||||
const reactFlowNodeData: INodeData = resolveVariables(nodeToExecute.data, reactFlowNodes, incomingInput.question)
|
||||
nodeToExecuteData = reactFlowNodeData
|
||||
|
||||
this.chatflowPool.add(chatflowid, nodeToExecuteData)
|
||||
const startingNodes = nodes.filter((nd) => startingNodeIds.includes(nd.id))
|
||||
this.chatflowPool.add(chatflowid, nodeToExecuteData, startingNodes)
|
||||
}
|
||||
|
||||
const nodeInstanceFilePath = this.nodesPool.componentNodes[nodeToExecuteData.name].filePath as string
|
||||
|
||||
@@ -8,10 +8,14 @@ import {
|
||||
INodeDirectedGraph,
|
||||
INodeQueue,
|
||||
IReactFlowEdge,
|
||||
IReactFlowNode
|
||||
IReactFlowNode,
|
||||
IVariableDict,
|
||||
INodeData
|
||||
} from '../Interface'
|
||||
import { cloneDeep, get } from 'lodash'
|
||||
import { ICommonObject, INodeData } from 'flowise-components'
|
||||
import { ICommonObject, getInputVariables } from 'flowise-components'
|
||||
|
||||
const QUESTION_VAR_PREFIX = 'question'
|
||||
|
||||
/**
|
||||
* Returns the home folder path of the user if
|
||||
@@ -166,13 +170,15 @@ export const getEndingNode = (nodeDependencies: INodeDependencies, graph: INodeD
|
||||
* @param {INodeDirectedGraph} graph
|
||||
* @param {IDepthQueue} depthQueue
|
||||
* @param {IComponentNodes} componentNodes
|
||||
* @param {string} question
|
||||
*/
|
||||
export const buildLangchain = async (
|
||||
startingNodeIds: string[],
|
||||
reactFlowNodes: IReactFlowNode[],
|
||||
graph: INodeDirectedGraph,
|
||||
depthQueue: IDepthQueue,
|
||||
componentNodes: IComponentNodes
|
||||
componentNodes: IComponentNodes,
|
||||
question: string
|
||||
) => {
|
||||
const flowNodes = cloneDeep(reactFlowNodes)
|
||||
|
||||
@@ -200,9 +206,9 @@ export const buildLangchain = async (
|
||||
const nodeModule = await import(nodeInstanceFilePath)
|
||||
const newNodeInstance = new nodeModule.nodeClass()
|
||||
|
||||
const reactFlowNodeData: INodeData = resolveVariables(reactFlowNode.data, flowNodes)
|
||||
const reactFlowNodeData: INodeData = resolveVariables(reactFlowNode.data, flowNodes, question)
|
||||
|
||||
flowNodes[nodeIndex].data.instance = await newNodeInstance.init(reactFlowNodeData)
|
||||
flowNodes[nodeIndex].data.instance = await newNodeInstance.init(reactFlowNodeData, question)
|
||||
} catch (e: any) {
|
||||
console.error(e)
|
||||
throw new Error(e)
|
||||
@@ -247,11 +253,14 @@ export const buildLangchain = async (
|
||||
* Get variable value from outputResponses.output
|
||||
* @param {string} paramValue
|
||||
* @param {IReactFlowNode[]} reactFlowNodes
|
||||
* @param {string} question
|
||||
* @param {boolean} isAcceptVariable
|
||||
* @returns {string}
|
||||
*/
|
||||
export const getVariableValue = (paramValue: string, reactFlowNodes: IReactFlowNode[]) => {
|
||||
export const getVariableValue = (paramValue: string, reactFlowNodes: IReactFlowNode[], question: string, isAcceptVariable = false) => {
|
||||
let returnVal = paramValue
|
||||
const variableStack = []
|
||||
const variableDict = {} as IVariableDict
|
||||
let startIdx = 0
|
||||
const endIdx = returnVal.length - 1
|
||||
|
||||
@@ -269,17 +278,36 @@ export const getVariableValue = (paramValue: string, reactFlowNodes: IReactFlowN
|
||||
const variableEndIdx = startIdx
|
||||
const variableFullPath = returnVal.substring(variableStartIdx, variableEndIdx)
|
||||
|
||||
if (isAcceptVariable && variableFullPath === QUESTION_VAR_PREFIX) {
|
||||
variableDict[`{{${variableFullPath}}}`] = question
|
||||
}
|
||||
|
||||
// Split by first occurence of '.' to get just nodeId
|
||||
const [variableNodeId, _] = variableFullPath.split('.')
|
||||
const executedNode = reactFlowNodes.find((nd) => nd.id === variableNodeId)
|
||||
if (executedNode) {
|
||||
const variableInstance = get(executedNode.data, 'instance')
|
||||
returnVal = variableInstance
|
||||
const variableValue = get(executedNode.data, 'instance')
|
||||
if (isAcceptVariable) {
|
||||
variableDict[`{{${variableFullPath}}}`] = variableValue
|
||||
} else {
|
||||
returnVal = variableValue
|
||||
}
|
||||
}
|
||||
variableStack.pop()
|
||||
}
|
||||
startIdx += 1
|
||||
}
|
||||
|
||||
if (isAcceptVariable) {
|
||||
const variablePaths = Object.keys(variableDict)
|
||||
variablePaths.sort() // Sort by length of variable path because longer path could possibly contains nested variable
|
||||
variablePaths.forEach((path) => {
|
||||
const variableValue = variableDict[path]
|
||||
// Replace all occurence
|
||||
returnVal = returnVal.split(path).join(variableValue)
|
||||
})
|
||||
return returnVal
|
||||
}
|
||||
return returnVal
|
||||
}
|
||||
|
||||
@@ -287,25 +315,26 @@ export const getVariableValue = (paramValue: string, reactFlowNodes: IReactFlowN
|
||||
* Loop through each inputs and resolve variable if neccessary
|
||||
* @param {INodeData} reactFlowNodeData
|
||||
* @param {IReactFlowNode[]} reactFlowNodes
|
||||
* @param {string} question
|
||||
* @returns {INodeData}
|
||||
*/
|
||||
export const resolveVariables = (reactFlowNodeData: INodeData, reactFlowNodes: IReactFlowNode[]): INodeData => {
|
||||
export const resolveVariables = (reactFlowNodeData: INodeData, reactFlowNodes: IReactFlowNode[], question: string): INodeData => {
|
||||
const flowNodeData = cloneDeep(reactFlowNodeData)
|
||||
const types = 'inputs'
|
||||
|
||||
const getParamValues = (paramsObj: ICommonObject) => {
|
||||
for (const key in paramsObj) {
|
||||
const paramValue: string = paramsObj[key]
|
||||
|
||||
if (Array.isArray(paramValue)) {
|
||||
const resolvedInstances = []
|
||||
for (const param of paramValue) {
|
||||
const resolvedInstance = getVariableValue(param, reactFlowNodes)
|
||||
const resolvedInstance = getVariableValue(param, reactFlowNodes, question)
|
||||
resolvedInstances.push(resolvedInstance)
|
||||
}
|
||||
paramsObj[key] = resolvedInstances
|
||||
} else {
|
||||
const resolvedInstance = getVariableValue(paramValue, reactFlowNodes)
|
||||
const isAcceptVariable = reactFlowNodeData.inputParams.find((param) => param.name === key)?.acceptVariable ?? false
|
||||
const resolvedInstance = getVariableValue(paramValue, reactFlowNodes, question, isAcceptVariable)
|
||||
paramsObj[key] = resolvedInstance
|
||||
}
|
||||
}
|
||||
@@ -317,3 +346,19 @@ export const resolveVariables = (reactFlowNodeData: INodeData, reactFlowNodes: I
|
||||
|
||||
return flowNodeData
|
||||
}
|
||||
|
||||
/**
|
||||
* Rebuild flow if LLMChain has dependency on other chains
|
||||
* User Question => Prompt_0 => LLMChain_0 => Prompt-1 => LLMChain_1
|
||||
* @param {IReactFlowNode[]} startingNodes
|
||||
* @returns {boolean}
|
||||
*/
|
||||
export const isStartNodeDependOnInput = (startingNodes: IReactFlowNode[]): boolean => {
|
||||
for (const node of startingNodes) {
|
||||
for (const inputName in node.data.inputs) {
|
||||
const inputVariables = getInputVariables(node.data.inputs[inputName])
|
||||
if (inputVariables.length > 0) return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user