{context} variable in the PromptThis component implements a Vector Store using Astra DB with search capabilities.
For more information, see the DataStax documentation.
Inputs
-| Name | Display Name | Info |
|---|---|---|
| collection_name | Collection Name | The name of the collection within Astra DB where the vectors will be stored (required) |
| token | Astra DB Application Token | Authentication token for accessing Astra DB (required) |
| api_endpoint | API Endpoint | API endpoint URL for the Astra DB service (required) |
| search_input | Search Input | Query string for similarity search |
| ingest_data | Ingest Data | Data to be ingested into the vector store |
| namespace | Namespace | Optional namespace within Astra DB to use for the collection |
| embedding_choice | Embedding Model or Astra Vectorize | Determines whether to use an Embedding Model or Astra Vectorize for the collection |
| embedding | Embedding Model | Allows an embedding model configuration (when using Embedding Model) |
| provider | Vectorize Provider | Provider for Astra Vectorize (when using Astra Vectorize) |
| metric | Metric | Optional distance metric for vector comparisons |
| batch_size | Batch Size | Optional number of data to process in a single batch |
| setup_mode | Setup Mode | Configuration mode for setting up the vector store (options: "Sync", "Async", "Off", default: "Sync") |
| pre_delete_collection | Pre Delete Collection | Boolean flag to determine whether to delete the collection before creating a new one |
| number_of_results | Number of Results | Number of results to return in similarity search (default: 4) |
| search_type | Search Type | Search type to use (options: "Similarity", "Similarity with score threshold", "MMR (Max Marginal Relevance)") |
| search_score_threshold | Search Score Threshold | Minimum similarity score threshold for search results |
| search_filter | Search Metadata Filter | Optional dictionary of filters to apply to the search query |
| Name | Display Name | Info |
|---|---|---|
| token | Astra DB Application Token | The authentication token for accessing Astra DB. |
| environment | Environment | The environment for the Astra DB API Endpoint. For example, dev or prod. |
| database_name | Database | The database name for the Astra DB instance. |
| api_endpoint | Astra DB API Endpoint | The API endpoint for the Astra DB instance. This supersedes the database selection. |
| collection_name | Collection | The name of the collection within Astra DB where the vectors are stored. |
| keyspace | Keyspace | An optional keyspace within Astra DB to use for the collection. |
| embedding_choice | Embedding Model or Astra Vectorize | Choose an embedding model or use Astra vectorize. |
| embedding_model | Embedding Model | Specify the embedding model. Not required for Astra vectorize collections. |
| number_of_results | Number of Search Results | The number of search results to return (default: 4). |
| search_type | Search Type | The search type to use. The options are Similarity, Similarity with score threshold, and MMR (Max Marginal Relevance). |
| search_score_threshold | Search Score Threshold | The minimum similarity score threshold for search results when using the Similarity with score threshold option. |
| advanced_search_filter | Search Metadata Filter | An optional dictionary of filters to apply to the search query. |
| autodetect_collection | Autodetect Collection | A boolean flag to determine whether to autodetect the collection. |
| content_field | Content Field | A field to use as the text content field for the vector store. |
| deletion_field | Deletion Based On Field | When provided, documents in the target collection with metadata field values matching the input metadata field value are deleted before new data is loaded. |
| ignore_invalid_documents | Ignore Invalid Documents | A boolean flag to determine whether to ignore invalid documents at runtime. |
| astradb_vectorstore_kwargs | AstraDBVectorStore Parameters | An optional dictionary of additional parameters for the AstraDBVectorStore. |
Outputs
-| Name | Display Name | Info |
|---|---|---|
| vector_store | Vector Store | Astra DB vector store instance configured with the specified parameters. |
| search_results | Search Results | The results of the similarity search as a list of Data objects. |
| Name | Display Name | Info |
|---|---|---|
| vector_store | Vector Store | Astra DB vector store instance configured with the specified parameters. |
| search_results | Search Results | The results of the similarity search as a list of Data objects. |
Generate embeddings
+The Astra DB Vector Store component offers two methods for generating embeddings.
+-
+
-
+
Embedding Model: Use your own embedding model by connecting an Embeddings component in Langflow.
+
+ -
+
Astra Vectorize: Use Astra DB's built-in embedding generation service. When creating a new collection, choose the embeddings provider and models, including NVIDIA's
+NV-Embed-QAmodel hosted by Datastax.
+
important
The embedding model selection is made when creating a new collection and cannot be changed later.
For an example of using the Astra DB Vector Store component with an embedding model, see the Vector Store RAG starter project.
+For more information, see the Astra DB Serverless documentation.
AstraDB Graph vector store
This component implements a Vector Store using AstraDB with graph capabilities. For more information, see the Astra DB Serverless documentation.
@@ -202,6 +215,6 @@ For more information, see the Inputs| Name | Type | Description |
|---|---|---|
| search_type | String | Type of search, such as "Similarity" or "MMR" |
| input_value | String | Search query |
| weaviate_url | String | Default instance URL |
| search_by_text | Boolean | Indicates whether to search by text |
| api_key | SecretString | Optional API key for authentication |
| index_name | String | Optional index name |
| text_key | String | Default text extraction key |
| embedding | Embeddings | Model used |
| attributes | List[String] | Optional additional attributes |
Outputs
-| Name | Type | Description |
|---|---|---|
| search_results | List[Data] | Results of similarity search |
| Name | Type | Description |
|---|---|---|
| search_results | List[Data] | Results of similarity search |