55878bf729
* directory reorg - flows section * sidebar alignment - agents and mcp * sidebar - api, contribute, support * move docs for apify and assembly bundles * structure in cursor rules * delete unused assets * move images and files to static * more delete unused assets * move integrations to components * combine big query page with google bundle page * combine notion pages into 1 * combine notion * combine nvidia pages * majority of develop and deploy topics * move monitoring integrations to develop * preempt mc from 10027 * remove notion action that is not needed
1431 lines
95 KiB
JSON
1431 lines
95 KiB
JSON
{
|
|
"name": "AssemblyAI Transcription and Speech AI Flow",
|
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"icon": null,
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"is_component": false,
|
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"endpoint_name": null,
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"data": {
|
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"nodes": [
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{
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"id": "Prompt-IO8Cq",
|
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"type": "genericNode",
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"position": {
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"x": -1376.3296370680628,
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"y": 928.8860970980681
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},
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"data": {
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"type": "Prompt",
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"node": {
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"template": {
|
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"_type": "Component",
|
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"code": {
|
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"type": "code",
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"required": true,
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|
"placeholder": "",
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"list": false,
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"show": true,
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"multiline": true,
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"value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n name = \"Prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def _update_template(self, frontend_node: dict):\n prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n custom_fields = frontend_node[\"custom_fields\"]\n frontend_node_template = frontend_node[\"template\"]\n _ = process_prompt_template(\n template=prompt_template,\n name=\"template\",\n custom_fields=custom_fields,\n frontend_node_template=frontend_node_template,\n )\n return frontend_node\n\n def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n # Kept it duplicated for backwards compatibility\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n # and update the frontend_node with those values\n update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n return frontend_node\n\n def _get_fallback_input(self, **kwargs):\n return DefaultPromptField(**kwargs)\n",
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"fileTypes": [],
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"file_path": "",
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"password": false,
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"name": "code",
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|
"advanced": true,
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"dynamic": true,
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"info": "",
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"load_from_db": false,
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"title_case": false
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},
|
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"template": {
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"trace_as_input": true,
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"list": false,
|
|
"required": false,
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"placeholder": "",
|
|
"show": true,
|
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"name": "template",
|
|
"value": "Provide a brief summary of the transcript.",
|
|
"display_name": "Template",
|
|
"advanced": false,
|
|
"dynamic": false,
|
|
"info": "",
|
|
"title_case": false,
|
|
"type": "prompt",
|
|
"_input_type": "PromptInput"
|
|
}
|
|
},
|
|
"description": "Create a prompt template with dynamic variables.",
|
|
"icon": "prompts",
|
|
"is_input": null,
|
|
"is_output": null,
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|
"is_composition": null,
|
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"base_classes": [
|
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"Message"
|
|
],
|
|
"name": "",
|
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"display_name": "Prompt",
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"documentation": "",
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|
"custom_fields": {
|
|
"template": []
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},
|
|
"output_types": [],
|
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"full_path": null,
|
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"pinned": false,
|
|
"conditional_paths": [],
|
|
"frozen": false,
|
|
"outputs": [
|
|
{
|
|
"types": [
|
|
"Message"
|
|
],
|
|
"selected": "Message",
|
|
"name": "prompt",
|
|
"hidden": null,
|
|
"display_name": "Prompt Message",
|
|
"method": "build_prompt",
|
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"value": "__UNDEFINED__",
|
|
"cache": true
|
|
}
|
|
],
|
|
"field_order": [
|
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"template"
|
|
],
|
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"beta": false,
|
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"error": null,
|
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"edited": false,
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"lf_version": "1.0.18"
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},
|
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"id": "Prompt-IO8Cq"
|
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},
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"selected": false,
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"width": 384,
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"height": 324,
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"positionAbsolute": {
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"x": -1376.3296370680628,
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"y": 928.8860970980681
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},
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"dragging": false
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},
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{
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"id": "AssemblyAITranscriptionJobCreator-Idt7P",
|
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"type": "genericNode",
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"position": {
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"x": -1957.7132501771657,
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"y": 470.79685053457587
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},
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"data": {
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"type": "AssemblyAITranscriptionJobCreator",
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"node": {
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"template": {
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"_type": "Component",
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"audio_file": {
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"trace_as_metadata": true,
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"file_path": "fa69381c-d1c4-4535-bc23-bc2fb4956e1e/2024-09-26_16-47-01_sports_injuries.mp3",
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"fileTypes": [
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"3ga",
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"8svx",
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"aac",
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"ac3",
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"aif",
|
|
"aiff",
|
|
"alac",
|
|
"amr",
|
|
"ape",
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|
"au",
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"dss",
|
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"flac",
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"flv",
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"m4a",
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"m4b",
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"m4p",
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"m4r",
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"mp3",
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"mpga",
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"ogg",
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|
"oga",
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|
"mogg",
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"opus",
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"qcp",
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"tta",
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"voc",
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"wav",
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"wma",
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"wv",
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"webm",
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"mts",
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"m2ts",
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"ts",
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"mov",
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"mp2",
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"mp4",
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"m4p",
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"m4v",
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"mxf"
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],
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"list": false,
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"required": false,
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"placeholder": "",
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"show": true,
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"name": "audio_file",
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"value": "sports_injuries.mp3",
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"display_name": "Audio File",
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|
"advanced": false,
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|
"dynamic": false,
|
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"info": "The audio file to transcribe",
|
|
"title_case": false,
|
|
"type": "file",
|
|
"_input_type": "FileInput",
|
|
"load_from_db": false
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},
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"api_key": {
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"load_from_db": false,
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"required": false,
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"placeholder": "",
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"show": true,
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"name": "api_key",
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"value": null,
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"display_name": "Assembly API Key",
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|
"advanced": false,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Your AssemblyAI API key. You can get one from https://www.assemblyai.com/",
|
|
"title_case": false,
|
|
"password": true,
|
|
"type": "str",
|
|
"_input_type": "SecretStrInput"
|
|
},
|
|
"audio_file_url": {
|
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"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
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"show": true,
|
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"name": "audio_file_url",
|
|
"value": "",
|
|
"display_name": "Audio File URL",
|
|
"advanced": true,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "The URL of the audio file to transcribe (Can be used instead of a File)",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MessageTextInput"
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},
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"code": {
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"type": "code",
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"required": true,
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"placeholder": "",
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"list": false,
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"show": true,
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"multiline": true,
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"value": "import os\n\nimport assemblyai as aai\nfrom loguru import logger\n\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DropdownInput, FileInput, MessageTextInput, Output, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass AssemblyAITranscriptionJobCreator(Component):\n display_name = \"AssemblyAI Start Transcript\"\n description = \"Create a transcription job for an audio file using AssemblyAI with advanced options\"\n documentation = \"https://www.assemblyai.com/docs\"\n icon = \"AssemblyAI\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Assembly API Key\",\n info=\"Your AssemblyAI API key. You can get one from https://www.assemblyai.com/\",\n ),\n FileInput(\n name=\"audio_file\",\n display_name=\"Audio File\",\n file_types=[\n \"3ga\",\n \"8svx\",\n \"aac\",\n \"ac3\",\n \"aif\",\n \"aiff\",\n \"alac\",\n \"amr\",\n \"ape\",\n \"au\",\n \"dss\",\n \"flac\",\n \"flv\",\n \"m4a\",\n \"m4b\",\n \"m4p\",\n \"m4r\",\n \"mp3\",\n \"mpga\",\n \"ogg\",\n \"oga\",\n \"mogg\",\n \"opus\",\n \"qcp\",\n \"tta\",\n \"voc\",\n \"wav\",\n \"wma\",\n \"wv\",\n \"webm\",\n \"mts\",\n \"m2ts\",\n \"ts\",\n \"mov\",\n \"mp2\",\n \"mp4\",\n \"m4p\",\n \"m4v\",\n \"mxf\",\n ],\n info=\"The audio file to transcribe\",\n ),\n MessageTextInput(\n name=\"audio_file_url\",\n display_name=\"Audio File URL\",\n info=\"The URL of the audio file to transcribe (Can be used instead of a File)\",\n advanced=True,\n ),\n DropdownInput(\n name=\"speech_model\",\n display_name=\"Speech Model\",\n options=[\n \"best\",\n \"nano\",\n ],\n value=\"best\",\n info=\"The speech model to use for the transcription\",\n advanced=True,\n ),\n BoolInput(\n name=\"language_detection\",\n display_name=\"Automatic Language Detection\",\n info=\"Enable automatic language detection\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"language_code\",\n display_name=\"Language\",\n info=\"\"\"\n The language of the audio file. Can be set manually if automatic language detection is disabled. \n See https://www.assemblyai.com/docs/getting-started/supported-languages for a list of supported language codes.\n \"\"\",\n advanced=True,\n ),\n BoolInput(\n name=\"speaker_labels\",\n display_name=\"Enable Speaker Labels\",\n info=\"Enable speaker diarization\",\n ),\n MessageTextInput(\n name=\"speakers_expected\",\n display_name=\"Expected Number of Speakers\",\n info=\"Set the expected number of speakers (optional, enter a number)\",\n advanced=True,\n ),\n BoolInput(\n name=\"punctuate\",\n display_name=\"Punctuate\",\n info=\"Enable automatic punctuation\",\n advanced=True,\n value=True,\n ),\n BoolInput(\n name=\"format_text\",\n display_name=\"Format Text\",\n info=\"Enable text formatting\",\n advanced=True,\n value=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Transcript ID\", name=\"transcript_id\", method=\"create_transcription_job\"),\n ]\n\n def create_transcription_job(self) -> Data:\n aai.settings.api_key = self.api_key\n\n # Convert speakers_expected to int if it's not empty\n speakers_expected = None\n if self.speakers_expected and self.speakers_expected.strip():\n try:\n speakers_expected = int(self.speakers_expected)\n except ValueError:\n self.status = \"Error: Expected Number of Speakers must be a valid integer\"\n return Data(data={\"error\": \"Error: Expected Number of Speakers must be a valid integer\"})\n\n language_code = self.language_code if self.language_code else None\n\n config = aai.TranscriptionConfig(\n speech_model=self.speech_model,\n language_detection=self.language_detection,\n language_code=language_code,\n speaker_labels=self.speaker_labels,\n speakers_expected=speakers_expected,\n punctuate=self.punctuate,\n format_text=self.format_text,\n )\n\n audio = None\n if self.audio_file:\n if self.audio_file_url:\n logger.warning(\"Both an audio file an audio URL were specified. The audio URL was ignored.\")\n\n # Check if the file exists\n if not os.path.exists(self.audio_file):\n self.status = \"Error: Audio file not found\"\n return Data(data={\"error\": \"Error: Audio file not found\"})\n audio = self.audio_file\n elif self.audio_file_url:\n audio = self.audio_file_url\n else:\n self.status = \"Error: Either an audio file or an audio URL must be specified\"\n return Data(data={\"error\": \"Error: Either an audio file or an audio URL must be specified\"})\n\n try:\n transcript = aai.Transcriber().submit(audio, config=config)\n\n if transcript.error:\n self.status = transcript.error\n return Data(data={\"error\": transcript.error})\n else:\n result = Data(data={\"transcript_id\": transcript.id})\n self.status = result\n return result\n except Exception as e:\n self.status = f\"An error occurred: {str(e)}\"\n return Data(data={\"error\": f\"An error occurred: {str(e)}\"})\n",
|
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"fileTypes": [],
|
|
"file_path": "",
|
|
"password": false,
|
|
"name": "code",
|
|
"advanced": true,
|
|
"dynamic": true,
|
|
"info": "",
|
|
"load_from_db": false,
|
|
"title_case": false
|
|
},
|
|
"format_text": {
|
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"trace_as_metadata": true,
|
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"list": false,
|
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"required": false,
|
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"placeholder": "",
|
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"show": true,
|
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"name": "format_text",
|
|
"value": true,
|
|
"display_name": "Format Text",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "Enable text formatting",
|
|
"title_case": false,
|
|
"type": "bool",
|
|
"_input_type": "BoolInput"
|
|
},
|
|
"language_code": {
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "language_code",
|
|
"value": "",
|
|
"display_name": "Language",
|
|
"advanced": true,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "\n The language of the audio file. Can be set manually if automatic language detection is disabled. \n See https://www.assemblyai.com/docs/getting-started/supported-languages for a list of supported language codes.\n ",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MessageTextInput"
|
|
},
|
|
"language_detection": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
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"placeholder": "",
|
|
"show": true,
|
|
"name": "language_detection",
|
|
"value": false,
|
|
"display_name": "Automatic Language Detection",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "Enable automatic language detection",
|
|
"title_case": false,
|
|
"type": "bool",
|
|
"_input_type": "BoolInput"
|
|
},
|
|
"punctuate": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "punctuate",
|
|
"value": true,
|
|
"display_name": "Punctuate",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "Enable automatic punctuation",
|
|
"title_case": false,
|
|
"type": "bool",
|
|
"_input_type": "BoolInput"
|
|
},
|
|
"speaker_labels": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
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"placeholder": "",
|
|
"show": true,
|
|
"name": "speaker_labels",
|
|
"value": true,
|
|
"display_name": "Enable Speaker Labels",
|
|
"advanced": false,
|
|
"dynamic": false,
|
|
"info": "Enable speaker diarization",
|
|
"title_case": false,
|
|
"type": "bool",
|
|
"_input_type": "BoolInput",
|
|
"load_from_db": false
|
|
},
|
|
"speakers_expected": {
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "speakers_expected",
|
|
"value": "",
|
|
"display_name": "Expected Number of Speakers",
|
|
"advanced": true,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Set the expected number of speakers (optional, enter a number)",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MessageTextInput"
|
|
},
|
|
"speech_model": {
|
|
"trace_as_metadata": true,
|
|
"options": [
|
|
"best",
|
|
"nano"
|
|
],
|
|
"combobox": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "speech_model",
|
|
"value": "best",
|
|
"display_name": "Speech Model",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "The speech model to use for the transcription",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "DropdownInput"
|
|
}
|
|
},
|
|
"description": "Create a transcription job for an audio file using AssemblyAI with advanced options",
|
|
"icon": "AssemblyAI",
|
|
"base_classes": [
|
|
"Data"
|
|
],
|
|
"display_name": "AssemblyAI Start Transcript",
|
|
"documentation": "https://www.assemblyai.com/docs",
|
|
"custom_fields": {},
|
|
"output_types": [],
|
|
"pinned": false,
|
|
"conditional_paths": [],
|
|
"frozen": true,
|
|
"outputs": [
|
|
{
|
|
"types": [
|
|
"Data"
|
|
],
|
|
"selected": "Data",
|
|
"name": "transcript_id",
|
|
"display_name": "Transcript ID",
|
|
"method": "create_transcription_job",
|
|
"value": "__UNDEFINED__",
|
|
"cache": true
|
|
}
|
|
],
|
|
"field_order": [
|
|
"api_key",
|
|
"audio_file",
|
|
"audio_file_url",
|
|
"speech_model",
|
|
"language_detection",
|
|
"language_code",
|
|
"speaker_labels",
|
|
"speakers_expected",
|
|
"punctuate",
|
|
"format_text"
|
|
],
|
|
"beta": false,
|
|
"edited": false,
|
|
"lf_version": "1.0.18"
|
|
},
|
|
"id": "AssemblyAITranscriptionJobCreator-Idt7P",
|
|
"description": "Create a transcription job for an audio file using AssemblyAI with advanced options",
|
|
"display_name": "AssemblyAI Start Transcript"
|
|
},
|
|
"selected": false,
|
|
"width": 384,
|
|
"height": 482,
|
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"positionAbsolute": {
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"x": -1957.7132501771657,
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"y": 470.79685053457587
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},
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"dragging": false
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},
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{
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"id": "AssemblyAITranscriptionJobPoller-F46nf",
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"type": "genericNode",
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"position": {
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"x": -1408.0967182254753,
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},
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"data": {
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"type": "AssemblyAITranscriptionJobPoller",
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"node": {
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"template": {
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"_type": "Component",
|
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"transcript_id": {
|
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"trace_as_metadata": true,
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"list": false,
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"trace_as_input": true,
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"required": false,
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"placeholder": "",
|
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"show": true,
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"name": "transcript_id",
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"value": "",
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"display_name": "Transcript ID",
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"advanced": false,
|
|
"input_types": [
|
|
"Data"
|
|
],
|
|
"dynamic": false,
|
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"info": "The ID of the transcription job to poll",
|
|
"title_case": false,
|
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"type": "other",
|
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"_input_type": "DataInput"
|
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},
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"api_key": {
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"load_from_db": false,
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"required": false,
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"placeholder": "",
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"show": true,
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"name": "api_key",
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"value": null,
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"display_name": "Assembly API Key",
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"advanced": false,
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"input_types": [
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"Message"
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],
|
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"dynamic": false,
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"info": "Your AssemblyAI API key. You can get one from https://www.assemblyai.com/",
|
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"title_case": false,
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"password": true,
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"type": "str",
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"_input_type": "SecretStrInput"
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},
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"code": {
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"type": "code",
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"required": true,
|
|
"placeholder": "",
|
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"list": false,
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"show": true,
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"multiline": true,
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"value": "import assemblyai as aai\n\nfrom langflow.custom import Component\nfrom langflow.io import DataInput, FloatInput, Output, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass AssemblyAITranscriptionJobPoller(Component):\n display_name = \"AssemblyAI Poll Transcript\"\n description = \"Poll for the status of a transcription job using AssemblyAI\"\n documentation = \"https://www.assemblyai.com/docs\"\n icon = \"AssemblyAI\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Assembly API Key\",\n info=\"Your AssemblyAI API key. You can get one from https://www.assemblyai.com/\",\n ),\n DataInput(\n name=\"transcript_id\",\n display_name=\"Transcript ID\",\n info=\"The ID of the transcription job to poll\",\n ),\n FloatInput(\n name=\"polling_interval\",\n display_name=\"Polling Interval\",\n value=3.0,\n info=\"The polling interval in seconds\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Transcription Result\", name=\"transcription_result\", method=\"poll_transcription_job\"),\n ]\n\n def poll_transcription_job(self) -> Data:\n \"\"\"Polls the transcription status until completion and returns the Data.\"\"\"\n aai.settings.api_key = self.api_key\n aai.settings.polling_interval = self.polling_interval\n\n # check if it's an error message from the previous step\n if self.transcript_id.data.get(\"error\"):\n self.status = self.transcript_id.data[\"error\"]\n return self.transcript_id\n\n try:\n transcript = aai.Transcript.get_by_id(self.transcript_id.data[\"transcript_id\"])\n except Exception as e:\n error = f\"Getting transcription failed: {str(e)}\"\n self.status = error\n return Data(data={\"error\": error})\n\n if transcript.status == aai.TranscriptStatus.completed:\n json_response = transcript.json_response\n text = json_response.pop(\"text\", None)\n utterances = json_response.pop(\"utterances\", None)\n transcript_id = json_response.pop(\"id\", None)\n sorted_data = { \"text\": text, \"utterances\": utterances, \"id\": transcript_id}\n sorted_data.update(json_response)\n data = Data(data=sorted_data)\n self.status = data\n return data\n else:\n self.status = transcript.error\n return Data(data={\"error\": transcript.error})\n",
|
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"fileTypes": [],
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"file_path": "",
|
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"password": false,
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"name": "code",
|
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"advanced": true,
|
|
"dynamic": true,
|
|
"info": "",
|
|
"load_from_db": false,
|
|
"title_case": false
|
|
},
|
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"polling_interval": {
|
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"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "polling_interval",
|
|
"value": 3,
|
|
"display_name": "Polling Interval",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "The polling interval in seconds",
|
|
"title_case": false,
|
|
"type": "float",
|
|
"_input_type": "FloatInput"
|
|
}
|
|
},
|
|
"description": "Poll for the status of a transcription job using AssemblyAI",
|
|
"icon": "AssemblyAI",
|
|
"base_classes": [
|
|
"Data"
|
|
],
|
|
"display_name": "AssemblyAI Poll Transcript",
|
|
"documentation": "https://www.assemblyai.com/docs",
|
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"custom_fields": {},
|
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"output_types": [],
|
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"pinned": false,
|
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"conditional_paths": [],
|
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"frozen": false,
|
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"outputs": [
|
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{
|
|
"types": [
|
|
"Data"
|
|
],
|
|
"selected": "Data",
|
|
"name": "transcription_result",
|
|
"display_name": "Transcription Result",
|
|
"method": "poll_transcription_job",
|
|
"value": "__UNDEFINED__",
|
|
"cache": true
|
|
}
|
|
],
|
|
"field_order": [
|
|
"api_key",
|
|
"transcript_id",
|
|
"polling_interval"
|
|
],
|
|
"beta": false,
|
|
"edited": false,
|
|
"lf_version": "1.0.18"
|
|
},
|
|
"id": "AssemblyAITranscriptionJobPoller-F46nf",
|
|
"description": "Poll for the status of a transcription job using AssemblyAI",
|
|
"display_name": "AssemblyAI Poll Transcript"
|
|
},
|
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"selected": false,
|
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"width": 384,
|
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"height": 368,
|
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"positionAbsolute": {
|
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"x": -1408.0967182254753,
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"y": 461.5039554434261
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},
|
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"dragging": false
|
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},
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{
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"id": "AssemblyAIGetSubtitles-3sjU6",
|
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"type": "genericNode",
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"position": {
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"x": -867.5862690424032,
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"y": 368.91683022842676
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},
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"data": {
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"type": "AssemblyAIGetSubtitles",
|
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"node": {
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"template": {
|
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"_type": "Component",
|
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"transcription_result": {
|
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"trace_as_metadata": true,
|
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"list": false,
|
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"trace_as_input": true,
|
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"required": false,
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"placeholder": "",
|
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"show": true,
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"name": "transcription_result",
|
|
"value": "",
|
|
"display_name": "Transcription Result",
|
|
"advanced": false,
|
|
"input_types": [
|
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"Data"
|
|
],
|
|
"dynamic": false,
|
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"info": "The transcription result from AssemblyAI",
|
|
"title_case": false,
|
|
"type": "other",
|
|
"_input_type": "DataInput"
|
|
},
|
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"api_key": {
|
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"load_from_db": false,
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"required": false,
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"placeholder": "",
|
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"show": true,
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"name": "api_key",
|
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"value": null,
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"display_name": "Assembly API Key",
|
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"advanced": false,
|
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"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Your AssemblyAI API key. You can get one from https://www.assemblyai.com/",
|
|
"title_case": false,
|
|
"password": true,
|
|
"type": "str",
|
|
"_input_type": "SecretStrInput"
|
|
},
|
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"chars_per_caption": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "chars_per_caption",
|
|
"value": 0,
|
|
"display_name": "Characters per Caption",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "The maximum number of characters per caption (0 for no limit)",
|
|
"title_case": false,
|
|
"type": "int",
|
|
"_input_type": "IntInput"
|
|
},
|
|
"code": {
|
|
"type": "code",
|
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"required": true,
|
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"placeholder": "",
|
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"list": false,
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"show": true,
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"multiline": true,
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"value": "import assemblyai as aai\n\nfrom langflow.custom import Component\nfrom langflow.io import DataInput, DropdownInput, IntInput, Output, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass AssemblyAIGetSubtitles(Component):\n display_name = \"AssemblyAI Get Subtitles\"\n description = \"Export your transcript in SRT or VTT format for subtitles and closed captions\"\n documentation = \"https://www.assemblyai.com/docs\"\n icon = \"AssemblyAI\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Assembly API Key\",\n info=\"Your AssemblyAI API key. You can get one from https://www.assemblyai.com/\",\n ),\n DataInput(\n name=\"transcription_result\",\n display_name=\"Transcription Result\",\n info=\"The transcription result from AssemblyAI\",\n ),\n DropdownInput(\n name=\"subtitle_format\",\n display_name=\"Subtitle Format\",\n options=[\"srt\", \"vtt\"],\n value=\"srt\",\n info=\"The format of the captions (SRT or VTT)\",\n ),\n IntInput(\n name=\"chars_per_caption\",\n display_name=\"Characters per Caption\",\n info=\"The maximum number of characters per caption (0 for no limit)\",\n value=0,\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Subtitles\", name=\"subtitles\", method=\"get_subtitles\"),\n ]\n\n def get_subtitles(self) -> Data:\n aai.settings.api_key = self.api_key\n\n # check if it's an error message from the previous step\n if self.transcription_result.data.get(\"error\"):\n self.status = self.transcription_result.data[\"error\"]\n return self.transcription_result\n\n try:\n transcript_id = self.transcription_result.data[\"id\"]\n transcript = aai.Transcript.get_by_id(transcript_id)\n except Exception as e:\n error = f\"Getting transcription failed: {str(e)}\"\n self.status = error\n return Data(data={\"error\": error})\n\n if transcript.status == aai.TranscriptStatus.completed:\n subtitles = None\n chars_per_caption = self.chars_per_caption if self.chars_per_caption > 0 else None\n if self.subtitle_format == \"srt\":\n subtitles = transcript.export_subtitles_srt(chars_per_caption)\n else:\n subtitles = transcript.export_subtitles_vtt(chars_per_caption)\n\n result = Data(\n subtitles=subtitles,\n format=self.subtitle_format,\n transcript_id=transcript_id,\n chars_per_caption=chars_per_caption,\n )\n\n self.status = result\n return result\n else:\n self.status = transcript.error\n return Data(data={\"error\": transcript.error})\n",
|
|
"fileTypes": [],
|
|
"file_path": "",
|
|
"password": false,
|
|
"name": "code",
|
|
"advanced": true,
|
|
"dynamic": true,
|
|
"info": "",
|
|
"load_from_db": false,
|
|
"title_case": false
|
|
},
|
|
"subtitle_format": {
|
|
"trace_as_metadata": true,
|
|
"options": [
|
|
"srt",
|
|
"vtt"
|
|
],
|
|
"combobox": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "subtitle_format",
|
|
"value": "srt",
|
|
"display_name": "Subtitle Format",
|
|
"advanced": false,
|
|
"dynamic": false,
|
|
"info": "The format of the captions (SRT or VTT)",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "DropdownInput"
|
|
}
|
|
},
|
|
"description": "Export your transcript in SRT or VTT format for subtitles and closed captions",
|
|
"icon": "AssemblyAI",
|
|
"base_classes": [
|
|
"Data"
|
|
],
|
|
"display_name": "AssemblyAI Get Subtitles",
|
|
"documentation": "https://www.assemblyai.com/docs",
|
|
"custom_fields": {},
|
|
"output_types": [],
|
|
"pinned": false,
|
|
"conditional_paths": [],
|
|
"frozen": false,
|
|
"outputs": [
|
|
{
|
|
"types": [
|
|
"Data"
|
|
],
|
|
"selected": "Data",
|
|
"name": "subtitles",
|
|
"display_name": "Subtitles",
|
|
"method": "get_subtitles",
|
|
"value": "__UNDEFINED__",
|
|
"cache": true
|
|
}
|
|
],
|
|
"field_order": [
|
|
"api_key",
|
|
"transcription_result",
|
|
"subtitle_format",
|
|
"chars_per_caption"
|
|
],
|
|
"beta": false,
|
|
"edited": false,
|
|
"lf_version": "1.0.18"
|
|
},
|
|
"id": "AssemblyAIGetSubtitles-3sjU6",
|
|
"description": "Export your transcript in SRT or VTT format for subtitles and closed captions",
|
|
"display_name": "AssemblyAI Get Subtitles"
|
|
},
|
|
"selected": false,
|
|
"width": 384,
|
|
"height": 454,
|
|
"positionAbsolute": {
|
|
"x": -867.5862690424032,
|
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"y": 368.91683022842676
|
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},
|
|
"dragging": false
|
|
},
|
|
{
|
|
"id": "AssemblyAIListTranscripts-3prc4",
|
|
"type": "genericNode",
|
|
"position": {
|
|
"x": -380.99808133361984,
|
|
"y": 401.2674645310267
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|
},
|
|
"data": {
|
|
"type": "AssemblyAIListTranscripts",
|
|
"node": {
|
|
"template": {
|
|
"_type": "Component",
|
|
"api_key": {
|
|
"load_from_db": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "api_key",
|
|
"value": null,
|
|
"display_name": "Assembly API Key",
|
|
"advanced": false,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Your AssemblyAI API key. You can get one from https://www.assemblyai.com/",
|
|
"title_case": false,
|
|
"password": true,
|
|
"type": "str",
|
|
"_input_type": "SecretStrInput"
|
|
},
|
|
"code": {
|
|
"type": "code",
|
|
"required": true,
|
|
"placeholder": "",
|
|
"list": false,
|
|
"show": true,
|
|
"multiline": true,
|
|
"value": "import assemblyai as aai\n\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, Output, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass AssemblyAIListTranscripts(Component):\n display_name = \"AssemblyAI List Transcripts\"\n description = \"Retrieve a list of transcripts from AssemblyAI with filtering options\"\n documentation = \"https://www.assemblyai.com/docs\"\n icon = \"AssemblyAI\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Assembly API Key\",\n info=\"Your AssemblyAI API key. You can get one from https://www.assemblyai.com/\",\n ),\n IntInput(\n name=\"limit\",\n display_name=\"Limit\",\n info=\"Maximum number of transcripts to retrieve (default: 20, use 0 for all)\",\n value=20,\n ),\n DropdownInput(\n name=\"status_filter\",\n display_name=\"Status Filter\",\n options=[\"all\", \"queued\", \"processing\", \"completed\", \"error\"],\n value=\"all\",\n info=\"Filter by transcript status\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"created_on\",\n display_name=\"Created On\",\n info=\"Only get transcripts created on this date (YYYY-MM-DD)\",\n advanced=True,\n ),\n BoolInput(\n name=\"throttled_only\",\n display_name=\"Throttled Only\",\n info=\"Only get throttled transcripts, overrides the status filter\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Transcript List\", name=\"transcript_list\", method=\"list_transcripts\"),\n ]\n\n def list_transcripts(self) -> list[Data]:\n aai.settings.api_key = self.api_key\n\n params = aai.ListTranscriptParameters()\n if self.limit:\n params.limit = self.limit\n if self.status_filter != \"all\":\n params.status = self.status_filter\n if self.created_on and self.created_on.text:\n params.created_on = self.created_on.text\n if self.throttled_only:\n params.throttled_only = True\n\n try:\n transcriber = aai.Transcriber()\n\n def convert_page_to_data_list(page):\n return [Data(**t.dict()) for t in page.transcripts]\n\n if self.limit == 0:\n # paginate over all pages\n params.limit = 100\n page = transcriber.list_transcripts(params)\n transcripts = convert_page_to_data_list(page)\n\n while page.page_details.before_id_of_prev_url is not None:\n params.before_id = page.page_details.before_id_of_prev_url\n page = transcriber.list_transcripts(params)\n transcripts.extend(convert_page_to_data_list(page))\n else:\n # just one page\n page = transcriber.list_transcripts(params)\n transcripts = convert_page_to_data_list(page)\n\n self.status = transcripts\n return transcripts\n except Exception as e:\n error_data = Data(data={\"error\": f\"An error occurred: {str(e)}\"})\n self.status = [error_data]\n return [error_data]\n",
|
|
"fileTypes": [],
|
|
"file_path": "",
|
|
"password": false,
|
|
"name": "code",
|
|
"advanced": true,
|
|
"dynamic": true,
|
|
"info": "",
|
|
"load_from_db": false,
|
|
"title_case": false
|
|
},
|
|
"created_on": {
|
|
"trace_as_input": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "created_on",
|
|
"value": "",
|
|
"display_name": "Created On",
|
|
"advanced": true,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Only get transcripts created on this date (YYYY-MM-DD)",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MessageTextInput"
|
|
},
|
|
"limit": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "limit",
|
|
"value": 20,
|
|
"display_name": "Limit",
|
|
"advanced": false,
|
|
"dynamic": false,
|
|
"info": "Maximum number of transcripts to retrieve (default: 20, use 0 for all)",
|
|
"title_case": false,
|
|
"type": "int",
|
|
"_input_type": "IntInput"
|
|
},
|
|
"status_filter": {
|
|
"trace_as_metadata": true,
|
|
"options": [
|
|
"all",
|
|
"queued",
|
|
"processing",
|
|
"completed",
|
|
"error"
|
|
],
|
|
"combobox": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "status_filter",
|
|
"value": "all",
|
|
"display_name": "Status Filter",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "Filter by transcript status",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "DropdownInput"
|
|
},
|
|
"throttled_only": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "throttled_only",
|
|
"value": false,
|
|
"display_name": "Throttled Only",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "Only get throttled transcripts, overrides the status filter",
|
|
"title_case": false,
|
|
"type": "bool",
|
|
"_input_type": "BoolInput"
|
|
}
|
|
},
|
|
"description": "Retrieve a list of transcripts from AssemblyAI with filtering options",
|
|
"icon": "AssemblyAI",
|
|
"base_classes": [
|
|
"Data"
|
|
],
|
|
"display_name": "AssemblyAI List Transcripts",
|
|
"documentation": "https://www.assemblyai.com/docs",
|
|
"custom_fields": {},
|
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"output_types": [],
|
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"pinned": false,
|
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"conditional_paths": [],
|
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"frozen": false,
|
|
"outputs": [
|
|
{
|
|
"types": [
|
|
"Data"
|
|
],
|
|
"selected": "Data",
|
|
"name": "transcript_list",
|
|
"display_name": "Transcript List",
|
|
"method": "list_transcripts",
|
|
"value": "__UNDEFINED__",
|
|
"cache": true
|
|
}
|
|
],
|
|
"field_order": [
|
|
"api_key",
|
|
"limit",
|
|
"status_filter",
|
|
"created_on",
|
|
"throttled_only"
|
|
],
|
|
"beta": false,
|
|
"edited": false,
|
|
"lf_version": "1.0.18"
|
|
},
|
|
"id": "AssemblyAIListTranscripts-3prc4",
|
|
"description": "Retrieve a list of transcripts from AssemblyAI with filtering options",
|
|
"display_name": "AssemblyAI List Transcripts"
|
|
},
|
|
"selected": false,
|
|
"width": 384,
|
|
"height": 410,
|
|
"positionAbsolute": {
|
|
"x": -380.99808133361984,
|
|
"y": 401.2674645310267
|
|
},
|
|
"dragging": false
|
|
},
|
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{
|
|
"id": "AssemblyAILeMUR-jzwHZ",
|
|
"type": "genericNode",
|
|
"position": {
|
|
"x": -875.6482330011189,
|
|
"y": 887.1705799007382
|
|
},
|
|
"data": {
|
|
"type": "AssemblyAILeMUR",
|
|
"node": {
|
|
"template": {
|
|
"_type": "Component",
|
|
"transcription_result": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"trace_as_input": true,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "transcription_result",
|
|
"value": "",
|
|
"display_name": "Transcription Result",
|
|
"advanced": false,
|
|
"input_types": [
|
|
"Data"
|
|
],
|
|
"dynamic": false,
|
|
"info": "The transcription result from AssemblyAI",
|
|
"title_case": false,
|
|
"type": "other",
|
|
"_input_type": "DataInput"
|
|
},
|
|
"api_key": {
|
|
"load_from_db": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "api_key",
|
|
"value": null,
|
|
"display_name": "Assembly API Key",
|
|
"advanced": false,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Your AssemblyAI API key. You can get one from https://www.assemblyai.com/",
|
|
"title_case": false,
|
|
"password": true,
|
|
"type": "str",
|
|
"_input_type": "SecretStrInput"
|
|
},
|
|
"code": {
|
|
"type": "code",
|
|
"required": true,
|
|
"placeholder": "",
|
|
"list": false,
|
|
"show": true,
|
|
"multiline": true,
|
|
"value": "import assemblyai as aai\n\nfrom langflow.custom import Component\nfrom langflow.io import DataInput, DropdownInput, FloatInput, IntInput, MultilineInput, Output, SecretStrInput\nfrom langflow.schema import Data\n\n\nclass AssemblyAILeMUR(Component):\n display_name = \"AssemblyAI LeMUR\"\n description = \"Apply Large Language Models to spoken data using the AssemblyAI LeMUR framework\"\n documentation = \"https://www.assemblyai.com/docs/lemur\"\n icon = \"AssemblyAI\"\n\n inputs = [\n SecretStrInput(\n name=\"api_key\",\n display_name=\"Assembly API Key\",\n info=\"Your AssemblyAI API key. You can get one from https://www.assemblyai.com/\",\n advanced=False,\n ),\n DataInput(\n name=\"transcription_result\",\n display_name=\"Transcription Result\",\n info=\"The transcription result from AssemblyAI\",\n ),\n MultilineInput(\n name=\"prompt\",\n display_name=\"Input Prompt\",\n info=\"The text to prompt the model\",\n ),\n DropdownInput(\n name=\"final_model\",\n display_name=\"Final Model\",\n options=[\"claude3_5_sonnet\", \"claude3_opus\", \"claude3_haiku\", \"claude3_sonnet\"],\n value=\"claude3_5_sonnet\",\n info=\"The model that is used for the final prompt after compression is performed\",\n advanced=True,\n ),\n FloatInput(\n name=\"temperature\",\n display_name=\"Temperature\",\n advanced=True,\n value=0.0,\n info=\"The temperature to use for the model\",\n ),\n IntInput(\n name=\"max_output_size\",\n display_name=\" Max Output Size\",\n advanced=True,\n value=2000,\n info=\"Max output size in tokens, up to 4000\",\n ),\n DropdownInput(\n name=\"endpoint\",\n display_name=\"Endpoint\",\n options=[\"task\", \"summary\", \"question-answer\"],\n value=\"task\",\n info=\"The LeMUR endpoint to use. For 'summary' and 'question-answer', no prompt input is needed. See https://www.assemblyai.com/docs/api-reference/lemur/ for more info.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"questions\",\n display_name=\"Questions\",\n info=\"Comma-separated list of your questions. Only used if Endpoint is 'question-answer'\",\n advanced=True,\n ),\n MultilineInput(\n name=\"transcript_ids\",\n display_name=\"Transcript IDs\",\n info=\"Comma-separated list of transcript IDs. LeMUR can perform actions over multiple transcripts. If provided, the Transcription Result is ignored.\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"LeMUR Response\", name=\"lemur_response\", method=\"run_lemur\"),\n ]\n\n def run_lemur(self) -> Data:\n \"\"\"Use the LeMUR task endpoint to input the LLM prompt.\"\"\"\n aai.settings.api_key = self.api_key\n\n if not self.transcription_result and not self.transcript_ids:\n error = \"Either a Transcription Result or Transcript IDs must be provided\"\n self.status = error\n return Data(data={\"error\": error})\n elif self.transcription_result and self.transcription_result.data.get(\"error\"):\n # error message from the previous step\n self.status = self.transcription_result.data[\"error\"]\n return self.transcription_result\n elif self.endpoint == \"task\" and not self.prompt:\n self.status = \"No prompt specified for the task endpoint\"\n return Data(data={\"error\": \"No prompt specified\"})\n elif self.endpoint == \"question-answer\" and not self.questions:\n error = \"No Questions were provided for the question-answer endpoint\"\n self.status = error\n return Data(data={\"error\": error})\n\n # Check for valid transcripts\n transcript_ids = None\n if self.transcription_result and \"id\" in self.transcription_result.data:\n transcript_ids = [self.transcription_result.data[\"id\"]]\n elif self.transcript_ids:\n transcript_ids = self.transcript_ids.split(\",\")\n transcript_ids = [t.strip() for t in transcript_ids]\n \n if not transcript_ids:\n error = \"Either a valid Transcription Result or valid Transcript IDs must be provided\"\n self.status = error\n return Data(data={\"error\": error})\n\n # Get TranscriptGroup and check if there is any error\n transcript_group = aai.TranscriptGroup(transcript_ids=transcript_ids)\n transcript_group, failures = transcript_group.wait_for_completion(return_failures=True)\n if failures:\n error = f\"Getting transcriptions failed: {failures[0]}\"\n self.status = error\n return Data(data={\"error\": error})\n \n for t in transcript_group.transcripts:\n if t.status == aai.TranscriptStatus.error:\n self.status = t.error\n return Data(data={\"error\": t.error})\n\n # Perform LeMUR action\n try:\n response = self.perform_lemur_action(transcript_group, self.endpoint)\n result = Data(data=response)\n self.status = result\n return result\n except Exception as e:\n error = f\"An Error happened: {str(e)}\"\n self.status = error\n return Data(data={\"error\": error})\n\n def perform_lemur_action(self, transcript_group: aai.TranscriptGroup, endpoint: str) -> dict:\n print(\"Endpoint:\", endpoint, type(endpoint))\n if endpoint == \"task\":\n result = transcript_group.lemur.task(\n prompt=self.prompt,\n final_model=self.get_final_model(self.final_model),\n temperature=self.temperature,\n max_output_size=self.max_output_size,\n )\n elif endpoint == \"summary\":\n result = transcript_group.lemur.summarize(\n final_model=self.get_final_model(self.final_model),\n temperature=self.temperature,\n max_output_size=self.max_output_size,\n )\n elif endpoint == \"question-answer\":\n questions = self.questions.split(\",\")\n questions = [aai.LemurQuestion(question=q) for q in questions]\n result = transcript_group.lemur.question(\n questions=questions,\n final_model=self.get_final_model(self.final_model),\n temperature=self.temperature,\n max_output_size=self.max_output_size,\n )\n else:\n raise ValueError(f\"Endpoint not supported: {endpoint}\")\n\n return result.dict()\n \n def get_final_model(self, model_name: str) -> aai.LemurModel:\n if model_name == \"claude3_5_sonnet\":\n return aai.LemurModel.claude3_5_sonnet\n elif model_name == \"claude3_opus\":\n return aai.LemurModel.claude3_opus\n elif model_name == \"claude3_haiku\":\n return aai.LemurModel.claude3_haiku\n elif model_name == \"claude3_sonnet\":\n return aai.LemurModel.claude3_sonnet\n else:\n raise ValueError(f\"Model name not supported: {model_name}\")\n",
|
|
"fileTypes": [],
|
|
"file_path": "",
|
|
"password": false,
|
|
"name": "code",
|
|
"advanced": true,
|
|
"dynamic": true,
|
|
"info": "",
|
|
"load_from_db": false,
|
|
"title_case": false
|
|
},
|
|
"endpoint": {
|
|
"trace_as_metadata": true,
|
|
"options": [
|
|
"task",
|
|
"summary",
|
|
"question-answer"
|
|
],
|
|
"combobox": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "endpoint",
|
|
"value": "task",
|
|
"display_name": "Endpoint",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "The LeMUR endpoint to use. For 'summary' and 'question-answer', no prompt input is needed. See https://www.assemblyai.com/docs/api-reference/lemur/ for more info.",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "DropdownInput"
|
|
},
|
|
"final_model": {
|
|
"trace_as_metadata": true,
|
|
"options": [
|
|
"claude3_5_sonnet",
|
|
"claude3_opus",
|
|
"claude3_haiku",
|
|
"claude3_sonnet"
|
|
],
|
|
"combobox": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "final_model",
|
|
"value": "claude3_5_sonnet",
|
|
"display_name": "Final Model",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "The model that is used for the final prompt after compression is performed",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "DropdownInput"
|
|
},
|
|
"max_output_size": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "max_output_size",
|
|
"value": 2000,
|
|
"display_name": " Max Output Size",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "Max output size in tokens, up to 4000",
|
|
"title_case": false,
|
|
"type": "int",
|
|
"_input_type": "IntInput"
|
|
},
|
|
"prompt": {
|
|
"trace_as_input": true,
|
|
"multiline": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "prompt",
|
|
"value": "",
|
|
"display_name": "Input Prompt",
|
|
"advanced": false,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "The text to prompt the model",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MultilineInput"
|
|
},
|
|
"questions": {
|
|
"trace_as_input": true,
|
|
"multiline": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "questions",
|
|
"value": "",
|
|
"display_name": "Questions",
|
|
"advanced": true,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Comma-separated list of your questions. Only used if Endpoint is 'question-answer'",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MultilineInput"
|
|
},
|
|
"temperature": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "temperature",
|
|
"value": 0,
|
|
"display_name": "Temperature",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "The temperature to use for the model",
|
|
"title_case": false,
|
|
"type": "float",
|
|
"_input_type": "FloatInput"
|
|
},
|
|
"transcript_ids": {
|
|
"trace_as_input": true,
|
|
"multiline": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "transcript_ids",
|
|
"value": "",
|
|
"display_name": "Transcript IDs",
|
|
"advanced": true,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "Comma-separated list of transcript IDs. LeMUR can perform actions over multiple transcripts. If provided, the Transcription Result is ignored.",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MultilineInput"
|
|
}
|
|
},
|
|
"description": "Apply Large Language Models to spoken data using the AssemblyAI LeMUR framework",
|
|
"icon": "AssemblyAI",
|
|
"base_classes": [
|
|
"Data"
|
|
],
|
|
"display_name": "AssemblyAI LeMUR",
|
|
"documentation": "https://www.assemblyai.com/docs/lemur",
|
|
"custom_fields": {},
|
|
"output_types": [],
|
|
"pinned": false,
|
|
"conditional_paths": [],
|
|
"frozen": false,
|
|
"outputs": [
|
|
{
|
|
"types": [
|
|
"Data"
|
|
],
|
|
"selected": "Data",
|
|
"name": "lemur_response",
|
|
"display_name": "LeMUR Response",
|
|
"method": "run_lemur",
|
|
"value": "__UNDEFINED__",
|
|
"cache": true
|
|
}
|
|
],
|
|
"field_order": [
|
|
"api_key",
|
|
"transcription_result",
|
|
"prompt",
|
|
"final_model",
|
|
"temperature",
|
|
"max_output_size",
|
|
"endpoint",
|
|
"questions",
|
|
"transcript_ids"
|
|
],
|
|
"beta": false,
|
|
"edited": false,
|
|
"lf_version": "1.0.18"
|
|
},
|
|
"id": "AssemblyAILeMUR-jzwHZ",
|
|
"description": "Apply Large Language Models to spoken data using the AssemblyAI LeMUR framework",
|
|
"display_name": "AssemblyAI LeMUR"
|
|
},
|
|
"selected": false,
|
|
"width": 384,
|
|
"height": 454,
|
|
"positionAbsolute": {
|
|
"x": -875.6482330011189,
|
|
"y": 887.1705799007382
|
|
},
|
|
"dragging": false
|
|
},
|
|
{
|
|
"id": "ParseData-th7JM",
|
|
"type": "genericNode",
|
|
"position": {
|
|
"x": -862.5843195492909,
|
|
"y": -56.71774780191424
|
|
},
|
|
"data": {
|
|
"type": "ParseData",
|
|
"node": {
|
|
"template": {
|
|
"_type": "Component",
|
|
"data": {
|
|
"trace_as_metadata": true,
|
|
"list": false,
|
|
"trace_as_input": true,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "data",
|
|
"value": "",
|
|
"display_name": "Data",
|
|
"advanced": false,
|
|
"input_types": [
|
|
"Data"
|
|
],
|
|
"dynamic": false,
|
|
"info": "The data to convert to text.",
|
|
"title_case": false,
|
|
"type": "other",
|
|
"_input_type": "DataInput"
|
|
},
|
|
"code": {
|
|
"type": "code",
|
|
"required": true,
|
|
"placeholder": "",
|
|
"list": false,
|
|
"show": true,
|
|
"multiline": true,
|
|
"value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n name = \"ParseData\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n",
|
|
"fileTypes": [],
|
|
"file_path": "",
|
|
"password": false,
|
|
"name": "code",
|
|
"advanced": true,
|
|
"dynamic": true,
|
|
"info": "",
|
|
"load_from_db": false,
|
|
"title_case": false
|
|
},
|
|
"sep": {
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "sep",
|
|
"value": "\n",
|
|
"display_name": "Separator",
|
|
"advanced": true,
|
|
"dynamic": false,
|
|
"info": "",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "StrInput"
|
|
},
|
|
"template": {
|
|
"trace_as_input": true,
|
|
"multiline": true,
|
|
"trace_as_metadata": true,
|
|
"load_from_db": false,
|
|
"list": false,
|
|
"required": false,
|
|
"placeholder": "",
|
|
"show": true,
|
|
"name": "template",
|
|
"value": "{text}",
|
|
"display_name": "Template",
|
|
"advanced": false,
|
|
"input_types": [
|
|
"Message"
|
|
],
|
|
"dynamic": false,
|
|
"info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.",
|
|
"title_case": false,
|
|
"type": "str",
|
|
"_input_type": "MultilineInput"
|
|
}
|
|
},
|
|
"description": "Convert Data into plain text following a specified template.",
|
|
"icon": "braces",
|
|
"base_classes": [
|
|
"Message"
|
|
],
|
|
"display_name": "Parse Data",
|
|
"documentation": "",
|
|
"custom_fields": {},
|
|
"output_types": [],
|
|
"pinned": false,
|
|
"conditional_paths": [],
|
|
"frozen": false,
|
|
"outputs": [
|
|
{
|
|
"types": [
|
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