2080 lines
No EOL
108 KiB
JSON
2080 lines
No EOL
108 KiB
JSON
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{
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"data": {
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"id": "note-XPHsS",
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"node": {
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"description": "### 💡 Add your OpenAI API key here👇",
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{
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"data": {
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"id": "ChatInput-bqH7H",
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"node": {
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"base_classes": [
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"Message"
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],
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"beta": false,
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"category": "inputs",
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"conditional_paths": [],
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"custom_fields": {},
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"description": "Get chat inputs from the Playground.",
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"display_name": "Chat Input",
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"documentation": "",
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"edited": false,
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"field_order": [
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"input_value",
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"should_store_message",
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"sender",
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"sender_name",
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"session_id",
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"files",
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"background_color",
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"chat_icon",
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"text_color"
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],
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"frozen": false,
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"icon": "MessagesSquare",
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"key": "ChatInput",
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"legacy": false,
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"lf_version": "1.5.0.post1",
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"metadata": {},
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"minimized": true,
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"output_types": [],
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"outputs": [
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{
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"allows_loop": false,
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"cache": true,
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"display_name": "Chat Message",
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"group_outputs": false,
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"method": "message_response",
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"name": "message",
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"selected": "Message",
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"tool_mode": true,
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"types": [
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"Message"
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],
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"value": "__UNDEFINED__"
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}
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],
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"pinned": false,
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"score": 0.0020353564437605998,
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"template": {
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"_type": "Component",
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"background_color": {
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"_input_type": "MessageTextInput",
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"advanced": true,
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"display_name": "Background Color",
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"dynamic": false,
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"info": "The background color of the icon.",
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"input_types": [
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"Message"
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],
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"list": false,
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"list_add_label": "Add More",
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"load_from_db": false,
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"name": "background_color",
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"placeholder": "",
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"required": false,
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"show": true,
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"title_case": false,
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"type": "str",
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"value": ""
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},
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"chat_icon": {
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"_input_type": "MessageTextInput",
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"advanced": true,
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"display_name": "Icon",
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"dynamic": false,
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"info": "The icon of the message.",
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"input_types": [
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"Message"
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],
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"list": false,
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"list_add_label": "Add More",
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"load_from_db": false,
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"name": "chat_icon",
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"placeholder": "",
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"required": false,
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"show": true,
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"title_case": false,
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"type": "str",
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"value": ""
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},
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"code": {
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"advanced": true,
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"dynamic": true,
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"fileTypes": [],
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"file_path": "",
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"info": "",
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"list": false,
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"load_from_db": false,
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"multiline": true,
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"name": "code",
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"password": false,
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"placeholder": "",
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"required": true,
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"show": true,
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"title_case": false,
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"type": "code",
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"value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs.inputs import BoolInput\nfrom langflow.io import (\n DropdownInput,\n FileInput,\n MessageTextInput,\n MultilineInput,\n Output,\n)\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import (\n MESSAGE_SENDER_AI,\n MESSAGE_SENDER_NAME_USER,\n MESSAGE_SENDER_USER,\n)\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n documentation: str = \"https://docs.langflow.org/components-io#chat-input\"\n icon = \"MessagesSquare\"\n name = \"ChatInput\"\n minimized = True\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Input Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n input_types=[],\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_USER,\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_USER,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n temp_file=True,\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Chat Message\", name=\"message\", method=\"message_response\"),\n ]\n\n async def message_response(self) -> Message:\n background_color = self.background_color\n text_color = self.text_color\n icon = self.chat_icon\n\n message = await Message.create(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n properties={\n \"background_color\": background_color,\n \"text_color\": text_color,\n \"icon\": icon,\n },\n )\n if self.session_id and isinstance(message, Message) and self.should_store_message:\n stored_message = await self.send_message(\n message,\n )\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n"
|
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},
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"files": {
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"_input_type": "FileInput",
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"advanced": true,
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"display_name": "Files",
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"dynamic": false,
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"fileTypes": [
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"txt",
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|
"md",
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|
"mdx",
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"csv",
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"json",
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"yaml",
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"yml",
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"xml",
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"html",
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"htm",
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"pdf",
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"docx",
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"py",
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"sh",
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"sql",
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"js",
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"ts",
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"tsx",
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"jpg",
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"jpeg",
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|
"png",
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"bmp",
|
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"image"
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],
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"file_path": "",
|
|
"info": "Files to be sent with the message.",
|
|
"list": true,
|
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"list_add_label": "Add More",
|
|
"name": "files",
|
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"placeholder": "",
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"required": false,
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"show": true,
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"temp_file": true,
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"title_case": false,
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"trace_as_metadata": true,
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"type": "file",
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"value": ""
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},
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"input_value": {
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"_input_type": "MultilineInput",
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"advanced": false,
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"copy_field": false,
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"display_name": "Input Text",
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"dynamic": false,
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"info": "Message to be passed as input.",
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"input_types": [],
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"list": false,
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"list_add_label": "Add More",
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"load_from_db": false,
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"multiline": true,
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"name": "input_value",
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"placeholder": "",
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"required": false,
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"show": true,
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"title_case": false,
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"type": "str",
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"value": ""
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},
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"sender": {
|
|
"_input_type": "DropdownInput",
|
|
"advanced": true,
|
|
"combobox": false,
|
|
"dialog_inputs": {},
|
|
"display_name": "Sender Type",
|
|
"dynamic": false,
|
|
"info": "Type of sender.",
|
|
"name": "sender",
|
|
"options": [
|
|
"Machine",
|
|
"User"
|
|
],
|
|
"options_metadata": [],
|
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"placeholder": "",
|
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"required": false,
|
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"show": true,
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"title_case": false,
|
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"tool_mode": false,
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"trace_as_metadata": true,
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"type": "str",
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"value": "User"
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},
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"sender_name": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Sender Name",
|
|
"dynamic": false,
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|
"info": "Name of the sender.",
|
|
"input_types": [
|
|
"Message"
|
|
],
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|
"list": false,
|
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"list_add_label": "Add More",
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"load_from_db": false,
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"name": "sender_name",
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"placeholder": "",
|
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"required": false,
|
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"show": true,
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"title_case": false,
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"type": "str",
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"value": "User"
|
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},
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"session_id": {
|
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"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Session ID",
|
|
"dynamic": false,
|
|
"info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
|
|
"input_types": [
|
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"Message"
|
|
],
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"list": false,
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"list_add_label": "Add More",
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"load_from_db": false,
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"name": "session_id",
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"placeholder": "",
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"required": false,
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"show": true,
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"title_case": false,
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"type": "str",
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"value": ""
|
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},
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"should_store_message": {
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"_input_type": "BoolInput",
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"advanced": true,
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"display_name": "Store Messages",
|
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"dynamic": false,
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"info": "Store the message in the history.",
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"list": false,
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"list_add_label": "Add More",
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"name": "should_store_message",
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"placeholder": "",
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"required": false,
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"show": true,
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"title_case": false,
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"tool_mode": false,
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"trace_as_metadata": true,
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"type": "bool",
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"value": true
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},
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"text_color": {
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"_input_type": "MessageTextInput",
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"advanced": true,
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"display_name": "Text Color",
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"dynamic": false,
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"info": "The text color of the name",
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"input_types": [
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"Message"
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],
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"list": false,
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"list_add_label": "Add More",
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"load_from_db": false,
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"name": "text_color",
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"placeholder": "",
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"required": false,
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"show": true,
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"title_case": false,
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"tool_mode": false,
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"trace_as_input": true,
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"trace_as_metadata": true,
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"type": "str",
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"value": ""
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}
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},
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"tool_mode": false
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},
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"selected_output": "message",
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"showNode": false,
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"type": "ChatInput"
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},
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"dragging": false,
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"id": "ChatInput-bqH7H",
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"measured": {
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"height": 48,
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"width": 192
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},
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"position": {
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"y": 897.5992294662233
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},
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"selected": false,
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"type": "genericNode"
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},
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{
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"data": {
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"id": "ChatOutput-BMVN5",
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"node": {
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"base_classes": [
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"Message"
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],
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"beta": false,
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"category": "outputs",
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"conditional_paths": [],
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"custom_fields": {},
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"description": "Display a chat message in the Playground.",
|
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"display_name": "Chat Output",
|
|
"documentation": "",
|
|
"edited": false,
|
|
"field_order": [
|
|
"input_value",
|
|
"should_store_message",
|
|
"sender",
|
|
"sender_name",
|
|
"session_id",
|
|
"data_template",
|
|
"background_color",
|
|
"chat_icon",
|
|
"text_color",
|
|
"clean_data"
|
|
],
|
|
"frozen": false,
|
|
"icon": "MessagesSquare",
|
|
"key": "ChatOutput",
|
|
"legacy": false,
|
|
"lf_version": "1.5.0.post1",
|
|
"metadata": {},
|
|
"minimized": true,
|
|
"output_types": [],
|
|
"outputs": [
|
|
{
|
|
"allows_loop": false,
|
|
"cache": true,
|
|
"display_name": "Output Message",
|
|
"group_outputs": false,
|
|
"method": "message_response",
|
|
"name": "message",
|
|
"selected": "Message",
|
|
"tool_mode": true,
|
|
"types": [
|
|
"Message"
|
|
],
|
|
"value": "__UNDEFINED__"
|
|
}
|
|
],
|
|
"pinned": false,
|
|
"score": 0.003169567463043492,
|
|
"template": {
|
|
"_type": "Component",
|
|
"background_color": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Background Color",
|
|
"dynamic": false,
|
|
"info": "The background color of the icon.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "background_color",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": ""
|
|
},
|
|
"chat_icon": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Icon",
|
|
"dynamic": false,
|
|
"info": "The icon of the message.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "chat_icon",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": ""
|
|
},
|
|
"clean_data": {
|
|
"_input_type": "BoolInput",
|
|
"advanced": true,
|
|
"display_name": "Basic Clean Data",
|
|
"dynamic": false,
|
|
"info": "Whether to clean the data",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "clean_data",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "bool",
|
|
"value": true
|
|
},
|
|
"code": {
|
|
"advanced": true,
|
|
"dynamic": true,
|
|
"fileTypes": [],
|
|
"file_path": "",
|
|
"info": "",
|
|
"list": false,
|
|
"load_from_db": false,
|
|
"multiline": true,
|
|
"name": "code",
|
|
"password": false,
|
|
"placeholder": "",
|
|
"required": true,
|
|
"show": true,
|
|
"title_case": false,
|
|
"type": "code",
|
|
"value": "from collections.abc import Generator\nfrom typing import Any\n\nimport orjson\nfrom fastapi.encoders import jsonable_encoder\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.helpers.data import safe_convert\nfrom langflow.inputs.inputs import BoolInput, DropdownInput, HandleInput, MessageTextInput\nfrom langflow.schema.data import Data\nfrom langflow.schema.dataframe import DataFrame\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.template.field.base import Output\nfrom langflow.utils.constants import (\n MESSAGE_SENDER_AI,\n MESSAGE_SENDER_NAME_AI,\n MESSAGE_SENDER_USER,\n)\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n documentation: str = \"https://docs.langflow.org/components-io#chat-output\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n minimized = True\n\n inputs = [\n HandleInput(\n name=\"input_value\",\n display_name=\"Inputs\",\n info=\"Message to be passed as output.\",\n input_types=[\"Data\", \"DataFrame\", \"Message\"],\n required=True,\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n MessageTextInput(\n name=\"background_color\",\n display_name=\"Background Color\",\n info=\"The background color of the icon.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"chat_icon\",\n display_name=\"Icon\",\n info=\"The icon of the message.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"text_color\",\n display_name=\"Text Color\",\n info=\"The text color of the name\",\n advanced=True,\n ),\n BoolInput(\n name=\"clean_data\",\n display_name=\"Basic Clean Data\",\n value=True,\n info=\"Whether to clean the data\",\n advanced=True,\n ),\n ]\n outputs = [\n Output(\n display_name=\"Output Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, id_: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if id_:\n source_dict[\"id\"] = id_\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n # Handle case where source is a ChatOpenAI object\n if hasattr(source, \"model_name\"):\n source_dict[\"source\"] = source.model_name\n elif hasattr(source, \"model\"):\n source_dict[\"source\"] = str(source.model)\n else:\n source_dict[\"source\"] = str(source)\n return Source(**source_dict)\n\n async def message_response(self) -> Message:\n # First convert the input to string if needed\n text = self.convert_to_string()\n\n # Get source properties\n source, icon, display_name, source_id = self.get_properties_from_source_component()\n background_color = self.background_color\n text_color = self.text_color\n if self.chat_icon:\n icon = self.chat_icon\n\n # Create or use existing Message object\n if isinstance(self.input_value, Message):\n message = self.input_value\n # Update message properties\n message.text = text\n else:\n message = Message(text=text)\n\n # Set message properties\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(source_id, display_name, source)\n message.properties.icon = icon\n message.properties.background_color = background_color\n message.properties.text_color = text_color\n\n # Store message if needed\n if self.session_id and self.should_store_message:\n stored_message = await self.send_message(message)\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n\n def _serialize_data(self, data: Data) -> str:\n \"\"\"Serialize Data object to JSON string.\"\"\"\n # Convert data.data to JSON-serializable format\n serializable_data = jsonable_encoder(data.data)\n # Serialize with orjson, enabling pretty printing with indentation\n json_bytes = orjson.dumps(serializable_data, option=orjson.OPT_INDENT_2)\n # Convert bytes to string and wrap in Markdown code blocks\n return \"```json\\n\" + json_bytes.decode(\"utf-8\") + \"\\n```\"\n\n def _validate_input(self) -> None:\n \"\"\"Validate the input data and raise ValueError if invalid.\"\"\"\n if self.input_value is None:\n msg = \"Input data cannot be None\"\n raise ValueError(msg)\n if isinstance(self.input_value, list) and not all(\n isinstance(item, Message | Data | DataFrame | str) for item in self.input_value\n ):\n invalid_types = [\n type(item).__name__\n for item in self.input_value\n if not isinstance(item, Message | Data | DataFrame | str)\n ]\n msg = f\"Expected Data or DataFrame or Message or str, got {invalid_types}\"\n raise TypeError(msg)\n if not isinstance(\n self.input_value,\n Message | Data | DataFrame | str | list | Generator | type(None),\n ):\n type_name = type(self.input_value).__name__\n msg = f\"Expected Data or DataFrame or Message or str, Generator or None, got {type_name}\"\n raise TypeError(msg)\n\n def convert_to_string(self) -> str | Generator[Any, None, None]:\n \"\"\"Convert input data to string with proper error handling.\"\"\"\n self._validate_input()\n if isinstance(self.input_value, list):\n return \"\\n\".join([safe_convert(item, clean_data=self.clean_data) for item in self.input_value])\n if isinstance(self.input_value, Generator):\n return self.input_value\n return safe_convert(self.input_value)\n"
|
|
},
|
|
"data_template": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Data Template",
|
|
"dynamic": false,
|
|
"info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "data_template",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": "{text}"
|
|
},
|
|
"input_value": {
|
|
"_input_type": "HandleInput",
|
|
"advanced": false,
|
|
"display_name": "Inputs",
|
|
"dynamic": false,
|
|
"info": "Message to be passed as output.",
|
|
"input_types": [
|
|
"Data",
|
|
"DataFrame",
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "input_value",
|
|
"placeholder": "",
|
|
"required": true,
|
|
"show": true,
|
|
"title_case": false,
|
|
"trace_as_metadata": true,
|
|
"type": "other",
|
|
"value": ""
|
|
},
|
|
"sender": {
|
|
"_input_type": "DropdownInput",
|
|
"advanced": true,
|
|
"combobox": false,
|
|
"dialog_inputs": {},
|
|
"display_name": "Sender Type",
|
|
"dynamic": false,
|
|
"info": "Type of sender.",
|
|
"name": "sender",
|
|
"options": [
|
|
"Machine",
|
|
"User"
|
|
],
|
|
"options_metadata": [],
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": "Machine"
|
|
},
|
|
"sender_name": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Sender Name",
|
|
"dynamic": false,
|
|
"info": "Name of the sender.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "sender_name",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": "AI"
|
|
},
|
|
"session_id": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Session ID",
|
|
"dynamic": false,
|
|
"info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "session_id",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": ""
|
|
},
|
|
"should_store_message": {
|
|
"_input_type": "BoolInput",
|
|
"advanced": true,
|
|
"display_name": "Store Messages",
|
|
"dynamic": false,
|
|
"info": "Store the message in the history.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "should_store_message",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "bool",
|
|
"value": true
|
|
},
|
|
"text_color": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": true,
|
|
"display_name": "Text Color",
|
|
"dynamic": false,
|
|
"info": "The text color of the name",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "text_color",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": ""
|
|
}
|
|
},
|
|
"tool_mode": false
|
|
},
|
|
"showNode": false,
|
|
"type": "ChatOutput"
|
|
},
|
|
"id": "ChatOutput-BMVN5",
|
|
"measured": {
|
|
"height": 48,
|
|
"width": 192
|
|
},
|
|
"position": {
|
|
"x": 2145,
|
|
"y": 660
|
|
},
|
|
"selected": false,
|
|
"type": "genericNode"
|
|
},
|
|
{
|
|
"data": {
|
|
"id": "Agent-cDM4a",
|
|
"node": {
|
|
"base_classes": [
|
|
"Message"
|
|
],
|
|
"beta": false,
|
|
"conditional_paths": [],
|
|
"custom_fields": {},
|
|
"description": "Define the agent's instructions, then enter a task to complete using tools.",
|
|
"display_name": "Agent",
|
|
"documentation": "",
|
|
"edited": false,
|
|
"field_order": [
|
|
"agent_llm",
|
|
"max_tokens",
|
|
"model_kwargs",
|
|
"json_mode",
|
|
"model_name",
|
|
"openai_api_base",
|
|
"api_key",
|
|
"temperature",
|
|
"seed",
|
|
"max_retries",
|
|
"timeout",
|
|
"system_prompt",
|
|
"n_messages",
|
|
"tools",
|
|
"input_value",
|
|
"handle_parsing_errors",
|
|
"verbose",
|
|
"max_iterations",
|
|
"agent_description",
|
|
"add_current_date_tool"
|
|
],
|
|
"frozen": false,
|
|
"icon": "bot",
|
|
"last_updated": "2025-07-16T07:49:33.622Z",
|
|
"legacy": false,
|
|
"lf_version": "1.5.0.post1",
|
|
"metadata": {},
|
|
"minimized": false,
|
|
"output_types": [],
|
|
"outputs": [
|
|
{
|
|
"allows_loop": false,
|
|
"cache": true,
|
|
"display_name": "Response",
|
|
"group_outputs": false,
|
|
"hidden": null,
|
|
"method": "message_response",
|
|
"name": "response",
|
|
"options": null,
|
|
"required_inputs": null,
|
|
"selected": "Message",
|
|
"tool_mode": true,
|
|
"types": [
|
|
"Message"
|
|
],
|
|
"value": "__UNDEFINED__"
|
|
}
|
|
],
|
|
"pinned": false,
|
|
"template": {
|
|
"_type": "Component",
|
|
"add_current_date_tool": {
|
|
"_input_type": "BoolInput",
|
|
"advanced": true,
|
|
"display_name": "Current Date",
|
|
"dynamic": false,
|
|
"info": "If true, will add a tool to the agent that returns the current date.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "add_current_date_tool",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "bool",
|
|
"value": true
|
|
},
|
|
"agent_description": {
|
|
"_input_type": "MultilineInput",
|
|
"advanced": true,
|
|
"copy_field": false,
|
|
"display_name": "Agent Description [Deprecated]",
|
|
"dynamic": false,
|
|
"info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically. This feature is deprecated and will be removed in future versions.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"multiline": true,
|
|
"name": "agent_description",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": "A helpful assistant with access to the following tools:"
|
|
},
|
|
"agent_llm": {
|
|
"_input_type": "DropdownInput",
|
|
"advanced": false,
|
|
"combobox": false,
|
|
"dialog_inputs": {},
|
|
"display_name": "Model Provider",
|
|
"dynamic": false,
|
|
"info": "The provider of the language model that the agent will use to generate responses.",
|
|
"input_types": [],
|
|
"name": "agent_llm",
|
|
"options": [
|
|
"Anthropic",
|
|
"Google Generative AI",
|
|
"Groq",
|
|
"OpenAI",
|
|
"Custom"
|
|
],
|
|
"options_metadata": [
|
|
{
|
|
"icon": "Anthropic"
|
|
},
|
|
{
|
|
"icon": "GoogleGenerativeAI"
|
|
},
|
|
{
|
|
"icon": "Groq"
|
|
},
|
|
{
|
|
"icon": "OpenAI"
|
|
},
|
|
{
|
|
"icon": "brain"
|
|
}
|
|
],
|
|
"placeholder": "",
|
|
"real_time_refresh": true,
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"toggle": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": "OpenAI"
|
|
},
|
|
"api_key": {
|
|
"_input_type": "SecretStrInput",
|
|
"advanced": false,
|
|
"display_name": "OpenAI API Key",
|
|
"dynamic": false,
|
|
"info": "The OpenAI API Key to use for the OpenAI model.",
|
|
"input_types": [],
|
|
"load_from_db": true,
|
|
"name": "api_key",
|
|
"password": true,
|
|
"placeholder": "",
|
|
"real_time_refresh": true,
|
|
"required": true,
|
|
"show": true,
|
|
"title_case": false,
|
|
"type": "str",
|
|
"value": "OPENAI_API_KEY"
|
|
},
|
|
"code": {
|
|
"advanced": true,
|
|
"dynamic": true,
|
|
"fileTypes": [],
|
|
"file_path": "",
|
|
"info": "",
|
|
"list": false,
|
|
"load_from_db": false,
|
|
"multiline": true,
|
|
"name": "code",
|
|
"password": false,
|
|
"placeholder": "",
|
|
"required": true,
|
|
"show": true,
|
|
"title_case": false,
|
|
"type": "code",
|
|
"value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.agents.events import ExceptionWithMessageError\nfrom langflow.base.models.model_input_constants import (\n ALL_PROVIDER_FIELDS,\n MODEL_DYNAMIC_UPDATE_FIELDS,\n MODEL_PROVIDERS,\n MODEL_PROVIDERS_DICT,\n MODELS_METADATA,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers.current_date import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.custom.custom_component.component import _get_component_toolkit\nfrom langflow.custom.utils import update_component_build_config\nfrom langflow.field_typing import Tool\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MultilineInput, Output\nfrom langflow.logging import logger\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n component_input.advanced = True\n return component_input\n\n\nMODEL_PROVIDERS_LIST = [\"Anthropic\", \"Google Generative AI\", \"Groq\", \"OpenAI\"]\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n display_name: str = \"Agent\"\n description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n documentation: str = \"https://docs.langflow.org/agents\"\n icon = \"bot\"\n beta = False\n name = \"Agent\"\n\n memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n inputs = [\n DropdownInput(\n name=\"agent_llm\",\n display_name=\"Model Provider\",\n info=\"The provider of the language model that the agent will use to generate responses.\",\n options=[*MODEL_PROVIDERS_LIST, \"Custom\"],\n value=\"OpenAI\",\n real_time_refresh=True,\n input_types=[],\n options_metadata=[MODELS_METADATA[key] for key in MODEL_PROVIDERS_LIST] + [{\"icon\": \"brain\"}],\n ),\n *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n MultilineInput(\n name=\"system_prompt\",\n display_name=\"Agent Instructions\",\n info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n advanced=False,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Chat History Messages\",\n value=100,\n info=\"Number of chat history messages to retrieve.\",\n advanced=True,\n show=True,\n ),\n *LCToolsAgentComponent._base_inputs,\n # removed memory inputs from agent component\n # *memory_inputs,\n BoolInput(\n name=\"add_current_date_tool\",\n display_name=\"Current Date\",\n advanced=True,\n info=\"If true, will add a tool to the agent that returns the current date.\",\n value=True,\n ),\n ]\n outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n async def message_response(self) -> Message:\n try:\n # Get LLM model and validate\n llm_model, display_name = self.get_llm()\n if llm_model is None:\n msg = \"No language model selected. Please choose a model to proceed.\"\n raise ValueError(msg)\n self.model_name = get_model_name(llm_model, display_name=display_name)\n\n # Get memory data\n self.chat_history = await self.get_memory_data()\n if isinstance(self.chat_history, Message):\n self.chat_history = [self.chat_history]\n\n # Add current date tool if enabled\n if self.add_current_date_tool:\n if not isinstance(self.tools, list): # type: ignore[has-type]\n self.tools = []\n current_date_tool = (await CurrentDateComponent(**self.get_base_args()).to_toolkit()).pop(0)\n if not isinstance(current_date_tool, StructuredTool):\n msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n raise TypeError(msg)\n self.tools.append(current_date_tool)\n # note the tools are not required to run the agent, hence the validation removed.\n\n # Set up and run agent\n self.set(\n llm=llm_model,\n tools=self.tools or [],\n chat_history=self.chat_history,\n input_value=self.input_value,\n system_prompt=self.system_prompt,\n )\n agent = self.create_agent_runnable()\n return await self.run_agent(agent)\n\n except (ValueError, TypeError, KeyError) as e:\n logger.error(f\"{type(e).__name__}: {e!s}\")\n raise\n except ExceptionWithMessageError as e:\n logger.error(f\"ExceptionWithMessageError occurred: {e}\")\n raise\n except Exception as e:\n logger.error(f\"Unexpected error: {e!s}\")\n raise\n\n async def get_memory_data(self):\n # TODO: This is a temporary fix to avoid message duplication. We should develop a function for this.\n messages = (\n await MemoryComponent(**self.get_base_args())\n .set(session_id=self.graph.session_id, order=\"Ascending\", n_messages=self.n_messages)\n .retrieve_messages()\n )\n return [\n message for message in messages if getattr(message, \"id\", None) != getattr(self.input_value, \"id\", None)\n ]\n\n def get_llm(self):\n if not isinstance(self.agent_llm, str):\n return self.agent_llm, None\n\n try:\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if not provider_info:\n msg = f\"Invalid model provider: {self.agent_llm}\"\n raise ValueError(msg)\n\n component_class = provider_info.get(\"component_class\")\n display_name = component_class.display_name\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\", \"\")\n\n return self._build_llm_model(component_class, inputs, prefix), display_name\n\n except Exception as e:\n logger.error(f\"Error building {self.agent_llm} language model: {e!s}\")\n msg = f\"Failed to initialize language model: {e!s}\"\n raise ValueError(msg) from e\n\n def _build_llm_model(self, component, inputs, prefix=\"\"):\n model_kwargs = {}\n for input_ in inputs:\n if hasattr(self, f\"{prefix}{input_.name}\"):\n model_kwargs[input_.name] = getattr(self, f\"{prefix}{input_.name}\")\n return component.set(**model_kwargs).build_model()\n\n def set_component_params(self, component):\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n inputs = provider_info.get(\"inputs\")\n prefix = provider_info.get(\"prefix\")\n model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n\n return component.set(**model_kwargs)\n return component\n\n def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n \"\"\"Delete specified fields from build_config.\"\"\"\n for field in fields:\n build_config.pop(field, None)\n\n def update_input_types(self, build_config: dotdict) -> dotdict:\n \"\"\"Update input types for all fields in build_config.\"\"\"\n for key, value in build_config.items():\n if isinstance(value, dict):\n if value.get(\"input_types\") is None:\n build_config[key][\"input_types\"] = []\n elif hasattr(value, \"input_types\") and value.input_types is None:\n value.input_types = []\n return build_config\n\n async def update_build_config(\n self, build_config: dotdict, field_value: str, field_name: str | None = None\n ) -> dotdict:\n # Iterate over all providers in the MODEL_PROVIDERS_DICT\n # Existing logic for updating build_config\n if field_name in (\"agent_llm\",):\n build_config[\"agent_llm\"][\"value\"] = field_value\n provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call the component class's update_build_config method\n build_config = await update_component_build_config(\n component_class, build_config, field_value, \"model_name\"\n )\n\n provider_configs: dict[str, tuple[dict, list[dict]]] = {\n provider: (\n MODEL_PROVIDERS_DICT[provider][\"fields\"],\n [\n MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n for other_provider in MODEL_PROVIDERS_DICT\n if other_provider != provider\n ],\n )\n for provider in MODEL_PROVIDERS_DICT\n }\n if field_value in provider_configs:\n fields_to_add, fields_to_delete = provider_configs[field_value]\n\n # Delete fields from other providers\n for fields in fields_to_delete:\n self.delete_fields(build_config, fields)\n\n # Add provider-specific fields\n if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n build_config.update(fields_to_add)\n else:\n build_config.update(fields_to_add)\n # Reset input types for agent_llm\n build_config[\"agent_llm\"][\"input_types\"] = []\n elif field_value == \"Custom\":\n # Delete all provider fields\n self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n # Update with custom component\n custom_component = DropdownInput(\n name=\"agent_llm\",\n display_name=\"Language Model\",\n options=[*sorted(MODEL_PROVIDERS), \"Custom\"],\n value=\"Custom\",\n real_time_refresh=True,\n input_types=[\"LanguageModel\"],\n options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())]\n + [{\"icon\": \"brain\"}],\n )\n build_config.update({\"agent_llm\": custom_component.to_dict()})\n # Update input types for all fields\n build_config = self.update_input_types(build_config)\n\n # Validate required keys\n default_keys = [\n \"code\",\n \"_type\",\n \"agent_llm\",\n \"tools\",\n \"input_value\",\n \"add_current_date_tool\",\n \"system_prompt\",\n \"agent_description\",\n \"max_iterations\",\n \"handle_parsing_errors\",\n \"verbose\",\n ]\n missing_keys = [key for key in default_keys if key not in build_config]\n if missing_keys:\n msg = f\"Missing required keys in build_config: {missing_keys}\"\n raise ValueError(msg)\n if (\n isinstance(self.agent_llm, str)\n and self.agent_llm in MODEL_PROVIDERS_DICT\n and field_name in MODEL_DYNAMIC_UPDATE_FIELDS\n ):\n provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n if provider_info:\n component_class = provider_info.get(\"component_class\")\n component_class = self.set_component_params(component_class)\n prefix = provider_info.get(\"prefix\")\n if component_class and hasattr(component_class, \"update_build_config\"):\n # Call each component class's update_build_config method\n # remove the prefix from the field_name\n if isinstance(field_name, str) and isinstance(prefix, str):\n field_name = field_name.replace(prefix, \"\")\n build_config = await update_component_build_config(\n component_class, build_config, field_value, \"model_name\"\n )\n return dotdict({k: v.to_dict() if hasattr(v, \"to_dict\") else v for k, v in build_config.items()})\n\n async def _get_tools(self) -> list[Tool]:\n component_toolkit = _get_component_toolkit()\n tools_names = self._build_tools_names()\n agent_description = self.get_tool_description()\n # TODO: Agent Description Depreciated Feature to be removed\n description = f\"{agent_description}{tools_names}\"\n tools = component_toolkit(component=self).get_tools(\n tool_name=\"Call_Agent\", tool_description=description, callbacks=self.get_langchain_callbacks()\n )\n if hasattr(self, \"tools_metadata\"):\n tools = component_toolkit(component=self, metadata=self.tools_metadata).update_tools_metadata(tools=tools)\n return tools\n"
|
|
},
|
|
"handle_parsing_errors": {
|
|
"_input_type": "BoolInput",
|
|
"advanced": true,
|
|
"display_name": "Handle Parse Errors",
|
|
"dynamic": false,
|
|
"info": "Should the Agent fix errors when reading user input for better processing?",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "handle_parsing_errors",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "bool",
|
|
"value": true
|
|
},
|
|
"input_value": {
|
|
"_input_type": "MessageTextInput",
|
|
"advanced": false,
|
|
"display_name": "Input",
|
|
"dynamic": false,
|
|
"info": "The input provided by the user for the agent to process.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "input_value",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": true,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": ""
|
|
},
|
|
"json_mode": {
|
|
"_input_type": "BoolInput",
|
|
"advanced": true,
|
|
"display_name": "JSON Mode",
|
|
"dynamic": false,
|
|
"info": "If True, it will output JSON regardless of passing a schema.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "json_mode",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "bool",
|
|
"value": false
|
|
},
|
|
"max_iterations": {
|
|
"_input_type": "IntInput",
|
|
"advanced": true,
|
|
"display_name": "Max Iterations",
|
|
"dynamic": false,
|
|
"info": "The maximum number of attempts the agent can make to complete its task before it stops.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "max_iterations",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "int",
|
|
"value": 15
|
|
},
|
|
"max_retries": {
|
|
"_input_type": "IntInput",
|
|
"advanced": true,
|
|
"display_name": "Max Retries",
|
|
"dynamic": false,
|
|
"info": "The maximum number of retries to make when generating.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "max_retries",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "int",
|
|
"value": 5
|
|
},
|
|
"max_tokens": {
|
|
"_input_type": "IntInput",
|
|
"advanced": true,
|
|
"display_name": "Max Tokens",
|
|
"dynamic": false,
|
|
"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "max_tokens",
|
|
"placeholder": "",
|
|
"range_spec": {
|
|
"max": 128000,
|
|
"min": 0,
|
|
"step": 0.1,
|
|
"step_type": "float"
|
|
},
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "int",
|
|
"value": ""
|
|
},
|
|
"model_kwargs": {
|
|
"_input_type": "DictInput",
|
|
"advanced": true,
|
|
"display_name": "Model Kwargs",
|
|
"dynamic": false,
|
|
"info": "Additional keyword arguments to pass to the model.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "model_kwargs",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"type": "dict",
|
|
"value": {}
|
|
},
|
|
"model_name": {
|
|
"_input_type": "DropdownInput",
|
|
"advanced": false,
|
|
"combobox": true,
|
|
"dialog_inputs": {},
|
|
"display_name": "Model Name",
|
|
"dynamic": false,
|
|
"info": "To see the model names, first choose a provider. Then, enter your API key and click the refresh button next to the model name.",
|
|
"load_from_db": false,
|
|
"name": "model_name",
|
|
"options": [
|
|
"gpt-4o-mini",
|
|
"gpt-4o",
|
|
"gpt-4.1",
|
|
"gpt-4.1-mini",
|
|
"gpt-4.1-nano",
|
|
"gpt-4.5-preview",
|
|
"gpt-4-turbo",
|
|
"gpt-4-turbo-preview",
|
|
"gpt-4",
|
|
"gpt-3.5-turbo",
|
|
"o1"
|
|
],
|
|
"options_metadata": [],
|
|
"placeholder": "",
|
|
"real_time_refresh": false,
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"toggle": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": "gpt-4.1"
|
|
},
|
|
"n_messages": {
|
|
"_input_type": "IntInput",
|
|
"advanced": true,
|
|
"display_name": "Number of Chat History Messages",
|
|
"dynamic": false,
|
|
"info": "Number of chat history messages to retrieve.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "n_messages",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "int",
|
|
"value": 100
|
|
},
|
|
"openai_api_base": {
|
|
"_input_type": "StrInput",
|
|
"advanced": true,
|
|
"display_name": "OpenAI API Base",
|
|
"dynamic": false,
|
|
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"name": "openai_api_base",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": ""
|
|
},
|
|
"seed": {
|
|
"_input_type": "IntInput",
|
|
"advanced": true,
|
|
"display_name": "Seed",
|
|
"dynamic": false,
|
|
"info": "The seed controls the reproducibility of the job.",
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"name": "seed",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_metadata": true,
|
|
"type": "int",
|
|
"value": 1
|
|
},
|
|
"system_prompt": {
|
|
"_input_type": "MultilineInput",
|
|
"advanced": false,
|
|
"copy_field": false,
|
|
"display_name": "Agent Instructions",
|
|
"dynamic": false,
|
|
"info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.",
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"list": false,
|
|
"list_add_label": "Add More",
|
|
"load_from_db": false,
|
|
"multiline": true,
|
|
"name": "system_prompt",
|
|
"placeholder": "",
|
|
"required": false,
|
|
"show": true,
|
|
"title_case": false,
|
|
"tool_mode": false,
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"type": "str",
|
|
"value": "You are a helpful assistant that can use tools to answer questions and perform tasks."
|
|
},
|
|
"temperature": {
|
|
"_input_type": "SliderInput",
|
|
"advanced": true,
|
|
"display_name": "Temperature",
|
|
"dynamic": false,
|
|
"info": "",
|
|
"max_label": "",
|
|
"max_label_icon": "",
|
|
"min_label": "",
|
|
"min_label_icon": "",
|
|
"name": "temperature",
|
|
"placeholder": "",
|
|
"range_spec": {
|
|
"max": 1,
|
|
"min": 0,
|
|
"step": 0.01,
|
|
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"value": "import json\nfrom typing import Any\n\nfrom opensearchpy import OpenSearch, helpers\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store\nfrom langflow.base.vectorstores.vector_store_connection_decorator import vector_store_connection\nfrom langflow.io import (\n BoolInput,\n HandleInput,\n IntInput,\n MultilineInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema.data import Data\n\n\n@vector_store_connection\nclass OpenSearchRawJVectorComponent(LCVectorStoreComponent):\n \"\"\"OpenSearch + JVector via opensearch-py.\"\"\"\n display_name: str = \"OpenSearch\"\n name: str = \"OpenSearch\"\n icon: str = \"OpenSearch\"\n description: str = \"Use raw opensearch-py + JVector KNN\"\n\n inputs = [\n StrInput(\n name=\"opensearch_url\",\n display_name=\"OpenSearch URL\",\n value=\"http://localhost:9200\",\n info=\"URL for your OpenSearch cluster.\"\n ),\n StrInput(\n name=\"index_name\",\n display_name=\"Index Name\",\n value=\"langflow\",\n info=\"The index where vectors live.\"\n ),\n *LCVectorStoreComponent.inputs,\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding\",\n input_types=[\"Embeddings\"]\n ),\n BoolInput(\n name=\"use_jvector\",\n display_name=\"Use JVector KNN Search\",\n value=True,\n info=\"Toggle raw JVector knn vs. fallback search.\"\n ),\n StrInput(\n name=\"vector_field\",\n display_name=\"Vector Field\",\n value=\"chunk_embedding\",\n advanced=True,\n info=\"Name of the JVector field in your index.\"\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n value=10,\n advanced=True,\n info=\"How many hits to return.\"\n ),\n StrInput(\n name=\"username\",\n display_name=\"Username\",\n value=\"admin\",\n advanced=True\n ),\n SecretStrInput(\n name=\"password\",\n display_name=\"Password\",\n value=\"admin\",\n advanced=True\n ),\n BoolInput(\n name=\"use_ssl\",\n display_name=\"Use SSL\",\n value=True,\n advanced=True\n ),\n BoolInput(\n name=\"verify_certs\",\n display_name=\"Verify Certificates\",\n value=False,\n advanced=True\n ),\n MultilineInput(\n name=\"hybrid_search_query\",\n display_name=\"Hybrid Search Query\",\n value=\"\",\n advanced=True,\n info=\"Raw JSON for combining vector + keyword search.\"\n ),\n ]\n\n def build_client(self) -> OpenSearch:\n return OpenSearch(\n hosts=[self.opensearch_url],\n http_auth=(self.username, self.password),\n use_ssl=self.use_ssl,\n verify_certs=self.verify_certs,\n ssl_assert_hostname=False,\n ssl_show_warn=False,\n )\n\n @check_cached_vector_store\n def build_vector_store(self) -> OpenSearch:\n # We return the raw OpenSearch client as our “vector store.”\n return self.build_client()\n\n def _add_documents_to_vector_store(self, client: OpenSearch) -> None:\n docs = self._prepare_ingest_data() or []\n if not docs:\n self.log(\"No documents to ingest.\")\n return\n\n # Embed all docs in batch\n texts = [d.to_lc_document().page_content for d in docs]\n vectors = self.embedding.embed_documents(texts)\n\n actions = []\n for doc_obj, vec in zip(docs, vectors):\n lc_doc = doc_obj.to_lc_document()\n body = {\n **lc_doc.metadata,\n \"text\": lc_doc.page_content,\n self.vector_field: vec,\n }\n actions.append({\n \"_op_type\": \"index\",\n \"_index\": self.index_name,\n \"_source\": body,\n })\n\n self.log(f\"Indexing {len(actions)} docs into '{self.index_name}'…\")\n helpers.bulk(client, actions)\n\n def search(self, query: str | None = None) -> list[dict[str, Any]]:\n client = self.build_client()\n q = (query or \"\").strip()\n size = self.number_of_results\n\n # 1) Raw JVector KNN\n if self.use_jvector:\n vec = self.embedding.embed_query(q)\n body = {\n \"query\": {\n \"knn\": {\n self.vector_field: {\n \"vector\": vec,\n \"k\": size\n }\n }\n },\n \"_source\": [\"*\"],\n \"size\": size,\n }\n self.log(f\"Running JVector KNN on '{self.vector_field}' (k={size})\")\n resp = client.search(index=self.index_name, body=body)\n hits = resp.get(\"hits\", {}).get(\"hits\", [])\n return [\n {\n \"page_content\": hit[\"_source\"].get(\"text\", \"\"),\n \"metadata\": {k: v for k, v in hit[\"_source\"].items() if k != \"text\"},\n \"score\": hit.get(\"_score\"),\n }\n for hit in hits\n ]\n\n # 2) Hybrid JSON path\n if self.hybrid_search_query.strip():\n try:\n hybrid = json.loads(self.hybrid_search_query)\n except json.JSONDecodeError as e:\n raise ValueError(f\"Invalid hybrid JSON: {e}\") from e\n resp = client.search(index=self.index_name, body=hybrid)\n hits = resp.get(\"hits\", {}).get(\"hits\", [])\n return [\n {\n \"page_content\": h[\"_source\"].get(\"text\", \"\"),\n \"metadata\": h[\"_source\"],\n }\n for h in hits\n ]\n\n # 3) Fallback: match_all\n resp = client.search(\n index=self.index_name,\n body={\"query\": {\"match_all\": {}}, \"size\": size}\n )\n hits = resp.get(\"hits\", {}).get(\"hits\", [])\n return [\n {\n \"page_content\": h[\"_source\"].get(\"text\", \"\"),\n \"metadata\": h[\"_source\"],\n }\n for h in hits\n ]\n\n def search_documents(self) -> list[Data]:\n try:\n raw = self.search(self.search_query or \"\")\n return [\n Data(file_path=hit[\"metadata\"].get(\"file_path\", \"\"), text=hit[\"page_content\"])\n for hit in raw\n ]\n except Exception as e:\n self.log(f\"search_documents error: {e}\")\n raise\n"
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"value": "from typing import Any\n\nfrom langchain_openai import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.base.models.openai_constants import OPENAI_EMBEDDING_MODEL_NAMES\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageTextInput,\n SecretStrInput,\n)\nfrom langflow.schema.dotdict import dotdict\n\n\nclass EmbeddingModelComponent(LCEmbeddingsModel):\n display_name = \"Embedding Model\"\n description = \"Generate embeddings using a specified provider.\"\n documentation: str = \"https://docs.langflow.org/components-embedding-models\"\n icon = \"binary\"\n name = \"EmbeddingModel\"\n category = \"models\"\n\n inputs = [\n DropdownInput(\n name=\"provider\",\n display_name=\"Model Provider\",\n options=[\"OpenAI\"],\n value=\"OpenAI\",\n info=\"Select the embedding model provider\",\n real_time_refresh=True,\n options_metadata=[{\"icon\": \"OpenAI\"}],\n ),\n DropdownInput(\n name=\"model\",\n display_name=\"Model Name\",\n options=OPENAI_EMBEDDING_MODEL_NAMES,\n value=OPENAI_EMBEDDING_MODEL_NAMES[0],\n info=\"Select the embedding model to use\",\n ),\n SecretStrInput(\n name=\"api_key\",\n display_name=\"OpenAI API Key\",\n info=\"Model Provider API key\",\n required=True,\n show=True,\n real_time_refresh=True,\n ),\n MessageTextInput(\n name=\"api_base\",\n display_name=\"API Base URL\",\n info=\"Base URL for the API. Leave empty for default.\",\n advanced=True,\n ),\n IntInput(\n name=\"dimensions\",\n display_name=\"Dimensions\",\n info=\"The number of dimensions the resulting output embeddings should have. \"\n \"Only supported by certain models.\",\n advanced=True,\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", advanced=True, value=3),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n DictInput(\n name=\"model_kwargs\",\n display_name=\"Model Kwargs\",\n advanced=True,\n info=\"Additional keyword arguments to pass to the model.\",\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n provider = self.provider\n model = self.model\n api_key = self.api_key\n api_base = self.api_base\n dimensions = self.dimensions\n chunk_size = self.chunk_size\n request_timeout = self.request_timeout\n max_retries = self.max_retries\n show_progress_bar = self.show_progress_bar\n model_kwargs = self.model_kwargs or {}\n\n if provider == \"OpenAI\":\n if not api_key:\n msg = \"OpenAI API key is required when using OpenAI provider\"\n raise ValueError(msg)\n return OpenAIEmbeddings(\n model=model,\n dimensions=dimensions or None,\n base_url=api_base or None,\n api_key=api_key,\n chunk_size=chunk_size,\n max_retries=max_retries,\n timeout=request_timeout or None,\n show_progress_bar=show_progress_bar,\n model_kwargs=model_kwargs,\n )\n msg = f\"Unknown provider: {provider}\"\n raise ValueError(msg)\n\n def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None) -> dotdict:\n if field_name == \"provider\" and field_value == \"OpenAI\":\n build_config[\"model\"][\"options\"] = OPENAI_EMBEDDING_MODEL_NAMES\n build_config[\"model\"][\"value\"] = OPENAI_EMBEDDING_MODEL_NAMES[0]\n build_config[\"api_key\"][\"display_name\"] = \"OpenAI API Key\"\n build_config[\"api_base\"][\"display_name\"] = \"OpenAI API Base URL\"\n return build_config\n"
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