updated flows and components with right ids
This commit is contained in:
Lucas Oliveira
parent
ce9859a031
commit
3c5f818dca
4 changed files with 726 additions and 821 deletions
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@ -76,7 +76,7 @@
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"dynamic": false,
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"info": "The API Key to use for the model.",
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"input_types": [],
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"load_from_db": false,
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"load_from_db": true,
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"name": "api_key",
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"password": true,
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"placeholder": "",
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@ -84,7 +84,7 @@
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"show": true,
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"title_case": false,
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"type": "str",
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"value": ""
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"value": "WATSONX_API_KEY"
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},
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"code": {
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"advanced": true,
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@ -150,7 +150,7 @@
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"info": "The project ID or deployment space ID that is associated with the foundation model.",
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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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"load_from_db": true,
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"name": "project_id",
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"placeholder": "",
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"required": true,
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@ -159,7 +159,7 @@
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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": ""
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"value": "WATSONX_PROJECT_ID"
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},
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"truncate_input_tokens": {
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"_input_type": "IntInput",
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@ -289,7 +289,7 @@
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"info": "The project ID or deployment space ID that is associated with the foundation model.",
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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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"load_from_db": true,
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"name": "project_id",
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"placeholder": "",
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"required": true,
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@ -298,7 +298,7 @@
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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": ""
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"value": "WATSONX_PROJECT_ID"
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},
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"seed": {
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"_input_type": "IntInput",
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@ -30,34 +30,6 @@
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"target": "OpenSearchHybrid-Ve6bS",
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"targetHandle": "{œfieldNameœ:œingest_dataœ,œidœ:œOpenSearchHybrid-Ve6bSœ,œinputTypesœ:[œDataœ,œDataFrameœ],œtypeœ:œotherœ}"
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},
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{
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"animated": false,
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"className": "",
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"data": {
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"sourceHandle": {
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"dataType": "OpenAIEmbeddings",
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"id": "OpenAIEmbeddings-joRJ6",
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"name": "embeddings",
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"output_types": [
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"Embeddings"
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]
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},
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"targetHandle": {
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"fieldName": "embedding",
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"id": "OpenSearchHybrid-Ve6bS",
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"inputTypes": [
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"Embeddings"
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],
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"type": "other"
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}
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},
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"id": "xy-edge__OpenAIEmbeddings-joRJ6{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-joRJ6œ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-OpenSearchHybrid-Ve6bS{œfieldNameœ:œembeddingœ,œidœ:œOpenSearchHybrid-Ve6bSœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}",
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"selected": false,
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"source": "OpenAIEmbeddings-joRJ6",
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"sourceHandle": "{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-joRJ6œ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}",
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"target": "OpenSearchHybrid-Ve6bS",
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"targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œOpenSearchHybrid-Ve6bSœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}"
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},
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{
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"animated": false,
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"className": "",
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@ -87,6 +59,31 @@
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"sourceHandle": "{œdataTypeœ:œFileœ,œidœ:œFile-PSU37œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}",
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"target": "SplitText-QIKhg",
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"targetHandle": "{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-QIKhgœ,œinputTypesœ:[œDataœ,œDataFrameœ,œMessageœ],œtypeœ:œotherœ}"
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},
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{
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"data": {
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"sourceHandle": {
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"dataType": "EmbeddingModel",
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"id": "EmbeddingModel-eZ6bT",
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"name": "embeddings",
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"output_types": [
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"Embeddings"
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]
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},
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"targetHandle": {
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"fieldName": "embedding",
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"id": "OpenSearchHybrid-Ve6bS",
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"inputTypes": [
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"Embeddings"
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],
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"type": "other"
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}
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},
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"id": "xy-edge__EmbeddingModel-eZ6bT{œdataTypeœ:œEmbeddingModelœ,œidœ:œEmbeddingModel-eZ6bTœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-OpenSearchHybrid-Ve6bS{œfieldNameœ:œembeddingœ,œidœ:œOpenSearchHybrid-Ve6bSœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}",
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"source": "EmbeddingModel-eZ6bT",
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"sourceHandle": "{œdataTypeœ:œEmbeddingModelœ,œidœ:œEmbeddingModel-eZ6bTœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}",
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"target": "OpenSearchHybrid-Ve6bS",
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"targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œOpenSearchHybrid-Ve6bSœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}"
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}
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],
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"nodes": [
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@ -332,550 +329,6 @@
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"type": "genericNode",
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"width": 320
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},
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{
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"data": {
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"id": "OpenAIEmbeddings-joRJ6",
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"node": {
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"base_classes": [
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"Embeddings"
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],
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"beta": false,
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"conditional_paths": [],
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"custom_fields": {},
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"description": "Generate embeddings using OpenAI models.",
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"display_name": "OpenAI Embeddings",
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"documentation": "",
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"edited": false,
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"field_order": [
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"default_headers",
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"default_query",
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"chunk_size",
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"client",
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"deployment",
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"embedding_ctx_length",
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"max_retries",
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"model",
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"model_kwargs",
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"openai_api_key",
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"openai_api_base",
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"openai_api_type",
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"openai_api_version",
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"openai_organization",
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"openai_proxy",
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"request_timeout",
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"show_progress_bar",
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"skip_empty",
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"tiktoken_model_name",
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"tiktoken_enable",
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"dimensions"
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],
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"frozen": false,
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"icon": "OpenAI",
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"legacy": false,
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"lf_version": "1.5.0.post2",
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"metadata": {
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"code_hash": "2691dee277c9",
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"dependencies": {
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"dependencies": [
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{
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"name": "langchain_openai",
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"version": "0.3.23"
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},
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{
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"name": "langflow",
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"version": "1.5.0.post2"
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}
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],
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"total_dependencies": 2
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},
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"module": "langflow.components.openai.openai.OpenAIEmbeddingsComponent"
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},
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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": "Embedding Model",
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"group_outputs": false,
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"method": "build_embeddings",
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"name": "embeddings",
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"selected": "Embeddings",
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"tool_mode": true,
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"types": [
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"Embeddings"
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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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"template": {
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"_type": "Component",
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"chunk_size": {
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"_input_type": "IntInput",
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"advanced": true,
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"display_name": "Chunk Size",
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"dynamic": false,
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"info": "",
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"list": false,
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"name": "chunk_size",
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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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"trace_as_metadata": true,
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"type": "int",
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"value": 1000
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},
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"client": {
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"_input_type": "MessageTextInput",
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"advanced": true,
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"display_name": "Client",
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"dynamic": false,
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"info": "",
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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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"load_from_db": false,
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"name": "client",
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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 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 BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n name = \"OpenAIEmbeddings\"\n\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=OPENAI_EMBEDDING_MODEL_NAMES,\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\", value=\"OPENAI_API_KEY\", required=True),\n MessageTextInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n MessageTextInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\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 ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n client=self.client or None,\n model=self.model,\n dimensions=self.dimensions or None,\n deployment=self.deployment or None,\n api_version=self.openai_api_version or None,\n base_url=self.openai_api_base or None,\n openai_api_type=self.openai_api_type or None,\n openai_proxy=self.openai_proxy or None,\n embedding_ctx_length=self.embedding_ctx_length,\n api_key=self.openai_api_key or None,\n organization=self.openai_organization or None,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n max_retries=self.max_retries,\n timeout=self.request_timeout or None,\n tiktoken_enabled=self.tiktoken_enable,\n tiktoken_model_name=self.tiktoken_model_name or None,\n show_progress_bar=self.show_progress_bar,\n model_kwargs=self.model_kwargs,\n skip_empty=self.skip_empty,\n default_headers=self.default_headers or None,\n default_query=self.default_query or None,\n )\n"
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},
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"default_headers": {
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"_input_type": "DictInput",
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"advanced": true,
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"display_name": "Default Headers",
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"dynamic": false,
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"info": "Default headers to use for the API request.",
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"list": false,
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"name": "default_headers",
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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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"trace_as_input": true,
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"type": "dict",
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"value": {}
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},
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"default_query": {
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"_input_type": "DictInput",
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"advanced": true,
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"display_name": "Default Query",
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"dynamic": false,
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"info": "Default query parameters to use for the API request.",
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"list": false,
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"name": "default_query",
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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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"trace_as_input": true,
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"type": "dict",
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"value": {}
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},
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"deployment": {
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"_input_type": "MessageTextInput",
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"advanced": true,
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"display_name": "Deployment",
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"dynamic": false,
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"info": "",
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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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"load_from_db": false,
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"name": "deployment",
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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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"dimensions": {
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"_input_type": "IntInput",
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"advanced": true,
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"display_name": "Dimensions",
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"dynamic": false,
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"info": "The number of dimensions the resulting output embeddings should have. Only supported by certain models.",
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"list": false,
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"name": "dimensions",
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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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"trace_as_metadata": true,
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"type": "int",
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"value": ""
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},
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"embedding_ctx_length": {
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"_input_type": "IntInput",
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"advanced": true,
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"display_name": "Embedding Context Length",
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"dynamic": false,
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"info": "",
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"list": false,
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"name": "embedding_ctx_length",
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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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"trace_as_metadata": true,
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"type": "int",
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"value": 1536
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},
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"max_retries": {
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"_input_type": "IntInput",
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"advanced": true,
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"display_name": "Max Retries",
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"dynamic": false,
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"info": "",
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"list": false,
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"name": "max_retries",
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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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"trace_as_metadata": true,
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"type": "int",
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"value": 3
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},
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"model": {
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"_input_type": "DropdownInput",
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"advanced": false,
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"combobox": false,
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"display_name": "Model",
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"dynamic": false,
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"info": "",
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"name": "model",
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"options": [
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"text-embedding-3-small",
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"text-embedding-3-large",
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"text-embedding-ada-002"
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],
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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": "text-embedding-3-small"
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},
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"model_kwargs": {
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"_input_type": "DictInput",
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"advanced": true,
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"display_name": "Model Kwargs",
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"dynamic": false,
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"info": "",
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"list": false,
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"name": "model_kwargs",
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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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"trace_as_input": true,
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"type": "dict",
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"value": {}
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},
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"openai_api_base": {
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"_input_type": "MessageTextInput",
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"advanced": true,
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"display_name": "OpenAI API Base",
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"dynamic": false,
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"info": "",
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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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"load_from_db": false,
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"name": "openai_api_base",
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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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|
||||
"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"
|
||||
},
|
||||
"dimensions": {
|
||||
"_input_type": "IntInput",
|
||||
"advanced": true,
|
||||
"display_name": "Dimensions",
|
||||
"dynamic": false,
|
||||
"info": "The number of dimensions the resulting output embeddings should have. Only supported by certain models.",
|
||||
"list": false,
|
||||
"list_add_label": "Add More",
|
||||
"name": "dimensions",
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
"show": true,
|
||||
"title_case": false,
|
||||
"tool_mode": false,
|
||||
"trace_as_metadata": true,
|
||||
"type": "int",
|
||||
"value": ""
|
||||
},
|
||||
"max_retries": {
|
||||
"_input_type": "IntInput",
|
||||
"advanced": true,
|
||||
"display_name": "Max Retries",
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"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": 3
|
||||
},
|
||||
"model": {
|
||||
"_input_type": "DropdownInput",
|
||||
"advanced": false,
|
||||
"combobox": false,
|
||||
"dialog_inputs": {},
|
||||
"display_name": "Model Name",
|
||||
"dynamic": false,
|
||||
"info": "Select the embedding model to use",
|
||||
"name": "model",
|
||||
"options": [
|
||||
"text-embedding-3-small",
|
||||
"text-embedding-3-large",
|
||||
"text-embedding-ada-002"
|
||||
],
|
||||
"options_metadata": [],
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
"show": true,
|
||||
"title_case": false,
|
||||
"toggle": false,
|
||||
"tool_mode": false,
|
||||
"trace_as_metadata": true,
|
||||
"type": "str",
|
||||
"value": "text-embedding-3-small"
|
||||
},
|
||||
"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": {}
|
||||
},
|
||||
"provider": {
|
||||
"_input_type": "DropdownInput",
|
||||
"advanced": false,
|
||||
"combobox": false,
|
||||
"dialog_inputs": {},
|
||||
"display_name": "Model Provider",
|
||||
"dynamic": false,
|
||||
"info": "Select the embedding model provider",
|
||||
"name": "provider",
|
||||
"options": [
|
||||
"OpenAI"
|
||||
],
|
||||
"options_metadata": [
|
||||
{
|
||||
"icon": "OpenAI"
|
||||
}
|
||||
],
|
||||
"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"
|
||||
},
|
||||
"request_timeout": {
|
||||
"_input_type": "FloatInput",
|
||||
"advanced": true,
|
||||
"display_name": "Request Timeout",
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"list": false,
|
||||
"list_add_label": "Add More",
|
||||
"name": "request_timeout",
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
"show": true,
|
||||
"title_case": false,
|
||||
"tool_mode": false,
|
||||
"trace_as_metadata": true,
|
||||
"type": "float",
|
||||
"value": ""
|
||||
},
|
||||
"show_progress_bar": {
|
||||
"_input_type": "BoolInput",
|
||||
"advanced": true,
|
||||
"display_name": "Show Progress Bar",
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"list": false,
|
||||
"list_add_label": "Add More",
|
||||
"name": "show_progress_bar",
|
||||
"placeholder": "",
|
||||
"required": false,
|
||||
"show": true,
|
||||
"title_case": false,
|
||||
"tool_mode": false,
|
||||
"trace_as_metadata": true,
|
||||
"type": "bool",
|
||||
"value": false
|
||||
}
|
||||
},
|
||||
"tool_mode": false
|
||||
},
|
||||
"showNode": true,
|
||||
"type": "EmbeddingModel"
|
||||
},
|
||||
"dragging": false,
|
||||
"id": "EmbeddingModel-eZ6bT",
|
||||
"measured": {
|
||||
"height": 369,
|
||||
"width": 320
|
||||
},
|
||||
"position": {
|
||||
"x": 1726.6943524438122,
|
||||
"y": 1800.5330404375484
|
||||
},
|
||||
"selected": true,
|
||||
"type": "genericNode"
|
||||
}
|
||||
],
|
||||
"viewport": {
|
||||
"x": -919.0070567185035,
|
||||
"y": -955.5333976627492,
|
||||
"zoom": 0.8337061732891438
|
||||
"x": -816.160132796055,
|
||||
"y": -860.347743678783,
|
||||
"zoom": 0.7338647578262055
|
||||
}
|
||||
},
|
||||
"description": "Load your data for chat context with Retrieval Augmented Generation.",
|
||||
|
|
|
|||
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Add table
Reference in a new issue