# mulesoft MuleSoft Vectors Connector - Full Documentation --- product: MuleSoft Vectors Connector version: 1.0 --- # Configuring Embedding Operations > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Configure the **\[Embedding\] Generate from text** operation. ## Configure the Embedding Generate from Text Operation The **\[Embedding\] Generate from text** operation splits the text into chunks of the provided size and creates numeric vectors for each text chunk. The **\[Embedding\] Generate from text** operation can be followed by either the **\[Store\] Add** operation or the **\[Store\] Query** operation. Both operations can use the output payload of the **\[Embedding\] Generate from text** operation without any transformation. When the **\[Embedding\] Generate from text** operation is used before the: - **\[Store\] Add** operation: The text along with the generated embeddings can be ingested into a vector store. - **\[Store\] Query** operation: The text is first used to generate an embedding that is then used to perform a query against the vector store. > [!NOTE] When generating an embedding from text for query purposes, don’t provide any > segmentation fields. Leave the **Max Segment Size (Characters)** and **Max Overlap Size > (Characters)** fields blank. To configure the **\[Embedding\] Generate from text** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Input Texts** Enter the input list of texts to generate embeddings from. - **Max Segment Size (Characters)** Enter the segment size of the document to be split in. This can be left blank as it is an optional input. - **Max Overlap Size (Characters)** Enter the overlap size of the segments to fine-tune the similarity search. This can be left blank as it is an optional input. - **Model (Deployment) Name** Enter the embedding model (deployment) name. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "embeddings": [ [-0.00683132, -0.0033572172, 0.02698761, -0.01291587, ...], [-0.0047172513, -0.03481483, 0.02046227, -0.037395656, ...], ... ] "text-segments": [ { "metadata": { "index": "0" }, "text": "In the modern world, technological advancements have become .", }, { "metadata": { "index": "1" }, "text": "E-commerce giants like Amazon and Alibaba have redefined ..", }, ... ], "dimension": 1536 } ``` - `embeddings`: List of generated embeddings. - `list-item` (embedding) - `text-segments`: List of segments. - `list-item` (text-segment) - `text`: Text segment. - `metadata`: Metadata key-value pairs. - `index`: Segment or chunk number for the uploaded data source. - `dimension`: Dimension of the embeddings. The operation also returns attributes that aren’t within the main JSON payload, that include information about token usage, for example: ```json { "embeddingModelDimension": 1536, "embeddingModelName": "sfdc_ai__DefaultOpenAITextEmbeddingAda_002", "tokenUsage": { "outputCount": 9, "totalCount": 18, "inputCount": 9 }, "additionalAttributes": {} } ``` - `embeddingModelDimension`: Dimension for the embedding model used. - `embeddingModelName`: Embedding model name used. - `tokenUsage`: Token usage metadata returned as attributes - `outputCount`: Number of tokens used to generate the output - `totalCount`: Total number of tokens used for input and output. - `inputCount`: Number of tokens used to process the input. ## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # Configuring Embedding Operations > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Configure the **\[Embedding\] Generate from text** operation. ## Configure the Embedding Generate from Text Operation The **\[Embedding\] Generate from text** operation splits the text into chunks of the provided size and creates numeric vectors for each text chunk. The **\[Embedding\] Generate from text** operation can be followed by either the **\[Store\] Add** operation or the **\[Store\] Query** operation. Both operations can use the output payload of the **\[Embedding\] Generate from text** operation without any transformation. When the **\[Embedding\] Generate from text** operation is used before the: - **\[Store\] Add** operation: The text along with the generated embeddings can be ingested into a vector store. - **\[Store\] Query** operation: The text is first used to generate an embedding that is then used to perform a query against the vector store. > [!NOTE] When generating an embedding from text for query purposes, don’t provide any > segmentation fields. Leave the **Max Segment Size (Characters)** and **Max Overlap Size > (Characters)** fields blank. To configure the **\[Embedding\] Generate from text** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Input Texts** Enter the input list of texts to generate embeddings from. - **Max Segment Size (Characters)** Enter the segment size of the document to be split in. This can be left blank as it is an optional input. - **Max Overlap Size (Characters)** Enter the overlap size of the segments to fine-tune the similarity search. This can be left blank as it is an optional input. - **Model (Deployment) Name** Enter the embedding model (deployment) name. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "embeddings": [ [-0.00683132, -0.0033572172, 0.02698761, -0.01291587, ...], [-0.0047172513, -0.03481483, 0.02046227, -0.037395656, ...], ... ] "text-segments": [ { "metadata": { "index": "0" }, "text": "In the modern world, technological advancements have become .", }, { "metadata": { "index": "1" }, "text": "E-commerce giants like Amazon and Alibaba have redefined ..", }, ... ], "dimension": 1536 } ``` - `embeddings`: List of generated embeddings. - `list-item` (embedding) - `text-segments`: List of segments. - `list-item` (text-segment) - `text`: Text segment. - `metadata`: Metadata key-value pairs. - `index`: Segment or chunk number for the uploaded data source. - `dimension`: Dimension of the embeddings. The operation also returns attributes that aren’t within the main JSON payload, that include information about token usage, for example: ```json { "embeddingModelDimension": 1536, "embeddingModelName": "sfdc_ai__DefaultOpenAITextEmbeddingAda_002", "tokenUsage": { "outputCount": 9, "totalCount": 18, "inputCount": 9 }, "additionalAttributes": {} } ``` - `embeddingModelDimension`: Dimension for the embedding model used. - `embeddingModelName`: Embedding model name used. - `tokenUsage`: Token usage metadata returned as attributes - `outputCount`: Number of tokens used to generate the output - `totalCount`: Total number of tokens used for input and output. - `inputCount`: Number of tokens used to process the input. ## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.0 --- # Configuring Store Operations > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Configure the **\[Store\] Add**, **\[Store\] Query**, **\[Store\] Query All**, and **\[Store\] Remove** operations. ## Configure the Store Add Operation The **\[Store\] Add** operation adds a document or text into an embedding store. The **\[Store\] Add** operation must be preceded by the **\[Embedding\] Generate from text** operation to ingest the text into a vector store. To configure the **\[Store\] Add** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Text Segments and Embeddings** Enter the text segments and embeddings to ingest into the vector database. It is typically the output of the **\[Embedding\] Generate from text** operation. - **Metadata entries** Enter a list-item (metadata entry), such as key (custom metadata key) and value (custom metadata value). This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "sourceId": "af44c7ef-4562-4712-af09-4498fc7f29a2", "embeddingIds": [ "81f257c6-6406-4936-8c22-0ae523cce5fd", "2127ef9b-08f4-4bfc-b769-1f488cdbf835", "639e9994-f406-4481-a08a-0058ed3d781e" ], "status": "updated" } ``` - `sourceId`: Unique identifier for the source document. - `embeddingIds`: List of unique identifiers for the embeddings added to the store. - `status`: Status of the operation. The operation also returns other attributes: - `storeName`: Name of the vector store collection. ## Configure the Store Query Operation The **\[Store\] Query** operation retrieves information from the embedding store based on an embedding (previously generated from a text prompt) and optionally a filter on metadata. It can be used for: - **Knowledge Management Systems** Retrieving documents from an organizational knowledge base. - **Customer Support** Storing customer interaction documents for quick retrieval and analysis. - **Content Management** Ingesting various types of documents (text, PDF, URL) into a centralized repository for easy access and searchability. The **\[Store\] Query** operation can be preceded by the **\[Embedding\] Generate from text** operation. The plain text to use when querying the store is first processed by the **\[Embedding\] Generate from text** operation that generates an embedding that can be used to perform the actual query and represents the input for the **\[Store\] Query** operation. > [!NOTE] When generating an embedding from text for query purposes, don’t provide any segmentation > fields. Leave the **Max Segment Size (Characters)** and **Max Overlap Size (Characters)** fields > blank. To configure the **\[Store\] Query** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Text Segments and Embeddings** Enter the text segments and embeddings to query into the vector database. It is typically the output of the **\[Embedding\] Generate from text** operation. Text segments and embeddings must have only one element. - **Max Results** Enter the maximum number of results to query back. - **Min Score** Enter the minimum score for the similarity search (0-1). - **Metadata Condition** Enter the condition used for filtering results based on metadata. It supports SQL-like syntax. - Comparison operators are `=`, `!=`, `<`, `⇐`, `>`, and `>=`. - Special operators: - `CONTAINS(field_name, 'value')` - Check if the field contains the value. - Logical operators are `AND` and `OR`. Here is an example: `index=1 AND (CONTAINS(file_name,'example.pdf') OR file_type='any')` > [!NOTE] Both `CONTAINS(field_name, 'value')` and `field_name LIKE '%value%'` work most of > the time, but the behavior might differ for each store provider. For example, for Azure AI > Search, it maps to `search.ismatch('value', field_name)`. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "question": "Tell me more about Cloudhub High Availability Feature", "sources": [ { "embeddingId": "", "text": "= CloudHub High Availability Features\nifndef::env-site,env-github[]\ninclude::_attributes.adoc[]\nendif::[]\n:page-aliases: runtime-manager::cloudhub-fabric.adoc,\....\n\n== Worker Scale-out", "score": 0.9282029356714594, "metadata": { "source_Id": "c426a871-1a6e-4a47-a8ab-027eec9303e1", "index": "0" "absolute_directory_path": "/Users//Documents/Downloads/patch 8", "file_name": "docs-runtime-manager__cloudhub_modules_ROOT_pages_cloudhub-fabric.adoc", "full_path": "/Users//Documents/Downloads/patch 8docs-runtime-manager__cloudhub_modules_ROOT_pages_cloudhub-fabric.adoc", "file_type": "any", "ingestion_datetime": "2024-11-20T20:34:41.691Z", "ingestion_timestamp": "1732134881691" } }, { ... }, { ... } ] "response": "= CloudHub High Availability Features\.. (...) \..distributes HTTP requests among your assigned workers.\n. Persistent message queues (see below)", "maxResults": 3, "storeName": "gettingstarted", "minimumScore": 0.7 } ``` - `question`: The question of the request. - `sources`: The sources identified by the similarity search. - `embeddingId`: The embedding UUID. - `text`: The relevant text segment. - `score`: The score of the similarity search based on the question. - `metadata`: The metadata key-value pairs. - `source_id`: The UUID for the uploaded data source. - `index`: The segment or chunk number for the uploaded data source. - `absolute_directory_path`: The full path to the file that contains relevant text segment. - `file_name`: The name of the file, in which the text segment is found. - `full_path`: The full path to the file. - `file_Type`: The file type. - `ingestion_datetime`: The ingestion date and time in ISO 8601 format (UTC). - `ingestion_timestamp`: The ingestion time in milliseconds. - `response`: The collected response of all relevant text segment. This is the response will is sent to the LLM. - `maxResults`: The maximum number of text segments considered. - `storeName`: The name of the vector store. - `minimumScore`: The minimum score for the result. The operation also returns other attributes: - `storeName`: Name of the vector store collection. - `metadataCondition` (Optional): Filter condition used to query embeddings. ## Configure the Store Query All Operation The **\[Store\] Query All** operation lists all sources into the embedding store. To configure the **\[Store\] Query All** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Retrieve Embeddings** If true, retrieve embeddings from the store. > [!NOTE] When querying the store along with embeddings using Azure AI Search, the connector > might return the > `Invalid expression: 'content_vector' is not a retrievable field. Only fields marked as retrievable in the index can be used in $select.\r\nParameter name: $select` > error. To resolve the issue, set \`content\_vector as a retrievable field. - **Page Size** Enter the page size to use when querying the store. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json [ { "embeddingId": "81f257c6-6406-4936-8c22-0ae523cce5fd", "text": "E-commerce giants like Amazon and Alibaba have redefined ..", "metadata": { "index": "0", "source": "s3://ms-vectors/invoicesample.pdf", "file_type": "any", "file_name": "invoicesample.pdf" ... }, "embeddings": [-0.00683132, -0.0033572172, 0.02698761, -0.01291587, ...] } ] ``` - `embeddingId`: The embedding UUID. - `text`: The relevant text segment. - `metadata`: The metadata key-value pairs. - `index`: The segment or chunk number for the uploaded data source. - `source`: The source of the text segment. - `file_type`: The file type. - `file_name`: The name of the file, in which the text segment is found. - `embeddings`: The embeddings for the text segment. The operation also returns other attributes: - `storeName`: Name of the vector store collection. ## Configure the Store Remove Operation The **\[Store\] Remove** operation removes all embeddings from the store based on a metadata filter. To configure the **\[Store\] Remove** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Ids** Enter the list of IDs to delete. - **Metadata Condition** Enter the condition used for filtering results based on metadata. It supports SQL-like syntax. - Comparison operators are `=`, `!=`, `<`, `⇐`, `>`, and `>=`. - Special operators: - `CONTAINS(field_name, 'value')` - Check if the field contains the value. - Logical operators are `AND` and `OR`. Here is an example: `index=1 AND (CONTAINS(file_name,'example.pdf') OR file_type='any')` > [!NOTE] Both `CONTAINS(field_name, 'value')` and `field_name LIKE '%value%'` work most of > the time, but the behavior might differ for each store provider. For example, for Azure AI > Search, it maps to `search.ismatch('value', field_name)`. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "status": "deleted" } ``` - `status`: Status of the operation. The operation also returns other attributes: - `storeName`: Name of the vector store collection. - `ids` (Optional): IDs of the embeddings to remove. - `metadataCondition` (Optional): Filter condition used to remove embeddings. ## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # Configuring Store Operations > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Configure the **\[Store\] Add**, **\[Store\] Query**, **\[Store\] Query All**, and **\[Store\] Remove** operations. ## Configure the Store Add Operation The **\[Store\] Add** operation adds a document or text into an embedding store. The **\[Store\] Add** operation must be preceded by the **\[Embedding\] Generate from text** operation to ingest the text into a vector store. To configure the **\[Store\] Add** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Text Segments and Embeddings** Enter the text segments and embeddings to ingest into the vector database. It is typically the output of the **\[Embedding\] Generate from text** operation. - **Metadata entries** Enter a list-item (metadata entry), such as key (custom metadata key) and value (custom metadata value). This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "sourceId": "af44c7ef-4562-4712-af09-4498fc7f29a2", "embeddingIds": [ "81f257c6-6406-4936-8c22-0ae523cce5fd", "2127ef9b-08f4-4bfc-b769-1f488cdbf835", "639e9994-f406-4481-a08a-0058ed3d781e" ], "status": "updated" } ``` - `sourceId`: Unique identifier for the source document. - `embeddingIds`: List of unique identifiers for the embeddings added to the store. - `status`: Status of the operation. The operation also returns other attributes: - `storeName`: Name of the vector store collection. ## Configure the Store Query Operation The **\[Store\] Query** operation retrieves information from the embedding store based on an embedding (previously generated from a text prompt) and optionally a filter on metadata. It can be used for: - **Knowledge Management Systems** Retrieving documents from an organizational knowledge base. - **Customer Support** Storing customer interaction documents for quick retrieval and analysis. - **Content Management** Ingesting various types of documents (text, PDF, URL) into a centralized repository for easy access and searchability. The **\[Store\] Query** operation can be preceded by the **\[Embedding\] Generate from text** operation. The plain text to use when querying the store is first processed by the **\[Embedding\] Generate from text** operation that generates an embedding that can be used to perform the actual query and represents the input for the **\[Store\] Query** operation. > [!NOTE] When generating an embedding from text for query purposes, don’t provide any segmentation > fields. Leave the **Max Segment Size (Characters)** and **Max Overlap Size (Characters)** fields > blank. To configure the **\[Store\] Query** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Text Segments and Embeddings** Enter the text segments and embeddings to query into the vector database. It is typically the output of the **\[Embedding\] Generate from text** operation. Text segments and embeddings must have only one element. - **Max Results** Enter the maximum number of results to query back. - **Min Score** Enter the minimum score for the similarity search (0-1). - **Metadata Condition** Enter the condition used for filtering results based on metadata. It supports SQL-like syntax. - Comparison operators are `=`, `!=`, `<`, `⇐`, `>`, and `>=`. - Special operators: - `CONTAINS(field_name, 'value')` - Check if the field contains the value. - Logical operators are `AND` and `OR`. Here is an example: `index=1 AND (CONTAINS(file_name,'example.pdf') OR file_type='any')` > [!NOTE] Both `CONTAINS(field_name, 'value')` and `field_name LIKE '%value%'` work most of > the time, but the behavior might differ for each store provider. For example, for Azure AI > Search, it maps to `search.ismatch('value', field_name)`. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "question": "Tell me more about Cloudhub High Availability Feature", "sources": [ { "embeddingId": "", "text": "= CloudHub High Availability Features\nifndef::env-site,env-github[]\ninclude::_attributes.adoc[]\nendif::[]\n:page-aliases: runtime-manager::cloudhub-fabric.adoc,\....\n\n== Worker Scale-out", "score": 0.9282029356714594, "metadata": { "source_Id": "c426a871-1a6e-4a47-a8ab-027eec9303e1", "index": "0" "absolute_directory_path": "/Users//Documents/Downloads/patch 8", "file_name": "docs-runtime-manager__cloudhub_modules_ROOT_pages_cloudhub-fabric.adoc", "full_path": "/Users//Documents/Downloads/patch 8docs-runtime-manager__cloudhub_modules_ROOT_pages_cloudhub-fabric.adoc", "file_type": "any", "ingestion_datetime": "2024-11-20T20:34:41.691Z", "ingestion_timestamp": "1732134881691" } }, { ... }, { ... } ] "response": "= CloudHub High Availability Features\.. (...) \..distributes HTTP requests among your assigned workers.\n. Persistent message queues (see below)", "maxResults": 3, "storeName": "gettingstarted", "minimumScore": 0.7 } ``` - `question`: The question of the request. - `sources`: The sources identified by the similarity search. - `embeddingId`: The embedding UUID. - `text`: The relevant text segment. - `score`: The score of the similarity search based on the question. - `metadata`: The metadata key-value pairs. - `source_id`: The UUID for the uploaded data source. - `index`: The segment or chunk number for the uploaded data source. - `absolute_directory_path`: The full path to the file that contains relevant text segment. - `file_name`: The name of the file, in which the text segment is found. - `full_path`: The full path to the file. - `file_Type`: The file type. - `ingestion_datetime`: The ingestion date and time in ISO 8601 format (UTC). - `ingestion_timestamp`: The ingestion time in milliseconds. - `response`: The collected response of all relevant text segment. This is the response will is sent to the LLM. - `maxResults`: The maximum number of text segments considered. - `storeName`: The name of the vector store. - `minimumScore`: The minimum score for the result. The operation also returns other attributes: - `storeName`: Name of the vector store collection. - `metadataCondition` (Optional): Filter condition used to query embeddings. ## Configure the Store Query All Operation The **\[Store\] Query All** operation lists all sources into the embedding store. To configure the **\[Store\] Query All** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Retrieve Embeddings** If true, retrieve embeddings from the store. > [!NOTE] When querying the store along with embeddings using Azure AI Search, the connector > might return the > `Invalid expression: 'content_vector' is not a retrievable field. Only fields marked as retrievable in the index can be used in $select.\r\nParameter name: $select` > error. To resolve the issue, set \`content\_vector as a retrievable field. - **Page Size** Enter the page size to use when querying the store. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json [ { "embeddingId": "81f257c6-6406-4936-8c22-0ae523cce5fd", "text": "E-commerce giants like Amazon and Alibaba have redefined ..", "metadata": { "index": "0", "source": "s3://ms-vectors/invoicesample.pdf", "file_type": "any", "file_name": "invoicesample.pdf" ... }, "embeddings": [-0.00683132, -0.0033572172, 0.02698761, -0.01291587, ...] } ] ``` - `embeddingId`: The embedding UUID. - `text`: The relevant text segment. - `metadata`: The metadata key-value pairs. - `index`: The segment or chunk number for the uploaded data source. - `source`: The source of the text segment. - `file_type`: The file type. - `file_name`: The name of the file, in which the text segment is found. - `embeddings`: The embeddings for the text segment. The operation also returns other attributes: - `storeName`: Name of the vector store collection. ## Configure the Store Remove Operation The **\[Store\] Remove** operation removes all embeddings from the store based on a metadata filter. To configure the **\[Store\] Remove** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Store Name** Enter the name of the collection in the external vector database. - **Ids** Enter the list of IDs to delete. - **Metadata Condition** Enter the condition used for filtering results based on metadata. It supports SQL-like syntax. - Comparison operators are `=`, `!=`, `<`, `⇐`, `>`, and `>=`. - Special operators: - `CONTAINS(field_name, 'value')` - Check if the field contains the value. - Logical operators are `AND` and `OR`. Here is an example: `index=1 AND (CONTAINS(file_name,'example.pdf') OR file_type='any')` > [!NOTE] Both `CONTAINS(field_name, 'value')` and `field_name LIKE '%value%'` work most of > the time, but the behavior might differ for each store provider. For example, for Azure AI > Search, it maps to `search.ismatch('value', field_name)`. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { "status": "deleted" } ``` - `status`: Status of the operation. The operation also returns other attributes: - `storeName`: Name of the vector store collection. - `ids` (Optional): IDs of the embeddings to remove. - `metadataCondition` (Optional): Filter condition used to remove embeddings. ## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.0 --- # Configuring Transform Operations > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Configure the **\[Transform\] Parse document** and **\[Transform\] Chunk text** operations. ## Configure the Transform Parse Document Operation The **\[Transform\] Parse document** operation parses a document from a raw binary or Base64-encoded content. To configure the **\[Transform\] Parse document** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Document binary** Enter the raw binary or Base64-encoded content of the document to parse. - **Document parser** Enter the document parser to use. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { In the modern world, technological advancements have become essential for businesses to remain competitive. E-commerce giants have redefined the retail landscape through innovative use of technology and data analytics. } ``` ## Configure the Transform Chunk Text Operation The **\[Transform\] Chunk text** operation chunks the provided text into multiple segments based on the segmentation parameters. This operation splits the input text into smaller segments according to the maximum segment size and overlap size specified in the segmentation parameters. The result is returned as a JSON document containing the chunked text segments and associated metadata. To configure the **\[Transform\] Chunk text** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Text** Enter the text content to chunk. - **Max Segment Size (Characters)** Enter the maximum size of a segment in characters. - **Max Overlap Size (Characters)** Enter the maximum overlap between segments in characters. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json [ "In the modern world, technological advancements have become essential for businesses to", "remain competitive. E-commerce giants have redefined the retail landscape through innovative use of technology and data analytics" ] ``` ## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # Configuring Transform Operations > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Configure the **\[Transform\] Parse document** and **\[Transform\] Chunk text** operations. ## Configure the Transform Parse Document Operation The **\[Transform\] Parse document** operation parses a document from a raw binary or Base64-encoded content. To configure the **\[Transform\] Parse document** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Document binary** Enter the raw binary or Base64-encoded content of the document to parse. - **Document parser** Enter the document parser to use. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json { In the modern world, technological advancements have become essential for businesses to remain competitive. E-commerce giants have redefined the retail landscape through innovative use of technology and data analytics. } ``` ## Configure the Transform Chunk Text Operation The **\[Transform\] Chunk text** operation chunks the provided text into multiple segments based on the segmentation parameters. This operation splits the input text into smaller segments according to the maximum segment size and overlap size specified in the segmentation parameters. The result is returned as a JSON document containing the chunked text segments and associated metadata. To configure the **\[Transform\] Chunk text** operation: 1. Select the operation on the Anypoint Code Builder or Studio canvas. 2. In the **General** properties tab for the operation, enter these values: - **Text** Enter the text content to chunk. - **Max Segment Size (Characters)** Enter the maximum size of a segment in characters. - **Max Overlap Size (Characters)** Enter the maximum overlap between segments in characters. This is the XML for this operation: ```xml ``` ### Output Configuration This operation responds with a JSON payload. This is an example response: ```json [ "In the modern world, technological advancements have become essential for businesses to", "remain competitive. E-commerce giants have redefined the retail landscape through innovative use of technology and data analytics" ] ``` ## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.0 --- # MuleSoft Vectors Connector - Additional Configuration Information > For the full documentation index, see: https://docs.mulesoft.com/llms.txt MuleSoft Vectors Connector provides detailed configuration information for each operation type. Select the operation you want to configure. - [Configure Embedding Operations](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/configuring-embedding-operations) - [Configure Store Operations](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/configuring-store-operations) - [Configure Transform Operations](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/configuring-transform-operations) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # MuleSoft Vectors Connector - Additional Configuration Information > For the full documentation index, see: https://docs.mulesoft.com/llms.txt MuleSoft Vectors Connector provides detailed configuration information for each operation type. Select the operation you want to configure. - [Configure Embedding Operations](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/configuring-embedding-operations) - [Configure Store Operations](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/configuring-store-operations) - [Configure Transform Operations](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/configuring-transform-operations) --- product: MuleSoft Vectors Connector version: 1.0 --- # MuleSoft Vectors Connector 1.0 > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Anypoint Connector for MuleSoft Vectors (MuleSoft Vectors Connector) provides access to a broad number of external vector stores and databases. MuleSoft Vectors Connector can be used with other connectors (for example, MuleSoft Inference Connector or Einstein AI Connector) and provides seamless access to vector stores for implementing smarter search or Retrieval Augmented Generation (RAG) use cases. For information about compatibility and fixed issues, see the MuleSoft Vectors Connector release notes. ## Before You Begin To use this connector, you must be familiar with: - Anypoint Connectors - Mule runtime engine (Mule) - Elements and global elements in a Mule flow - How to create a Mule app using Anypoint Code Builder or Anypoint Studio Before creating an app, you must have: - Java 17 (required for compilation and runtime) - Apache Maven - Credentials to access the MuleSoft Vectors Connector target resources - Anypoint Platform - The latest versions of Anypoint Code Builder or Anypoint Studio ## Key Features MuleSoft Vectors Connector provides: - Accelerated AI-powered application development - Simplified vector database integration - Easy-to-build semantic search and RAG experiences without managing complex vector infrastructure > [!NOTE] Data is processed in in-memory, so if you do parallel processing (such as running multiple > flows in one go), you might encounter an out-of-memory issue. For example, if you process 1 MB > files in three flows, around 3 MB files will be loaded in-memory. This is due to the nature of > Apache Tika and LangChain4j libraries. ## Supported Vector Stores MuleSoft Vectors Connector supports these vector stores: - Azure AI Search (beta) - Chroma (beta) - Milvus (beta) - OpenSearch (beta) - PGVector (beta) > [!NOTE] PGVector is not FIPS-compliant. - Pinecone (beta) - Qdrant (beta) - MongoDB Atlas (beta) - Ephemeral File (beta) ### Supported Operations by Vector Stores This table provides a detailed view of operation support across all vector stores:
Vector StoreStoring MetadataFiltering by MetadataRemoving EmbeddingsList All Embeddings

Azure AI Search

Yes

Yes

Yes

Yes

Chroma

Yes

Yes

Yes

Yes

Milvus

Yes

Yes

Yes

Yes

OpenSearch

Yes

Yes

Yes

No

PGVector

Yes

Yes

Yes

Yes

Pinecone

Yes

Yes

No

No

Qdrant

Yes

Yes

Yes

Yes

MongoDB Atlas

Yes

Yes

Yes

Yes

Ephemeral File

Yes

Yes

Yes

Yes

## Supported Model Providers MuleSoft Vectors Connector supports these model providers to generate embeddings: - Azure OpenAI - Azure Vision AI (beta) - Einstein - Hugging Face (beta) - Mistral AI (beta) - Nomic (beta) - Ollama (beta) - OpenAI ### Supported Embedding Types by Model Providers This table provides a detailed view of embedding type support across all model providers:
Model ProviderText EmbeddingImage EmbeddingVideo Embedding

Azure OpenAI

Yes

No

No

Azure Vision AI

Yes

No

No

Einstein

Yes

No

No

Hugging Face

Yes

No

No

Mistral AI

Yes

No

No

Nomic

Yes

No

No

Ollama

Yes

No

No

OpenAI

Yes

No

No

> [!NOTE] To keep pace with the rapidly evolving AI landscape, certain vector stores and LLMs are > marked as beta. These are early-stage integrations that may change based on stability, demand, or > provider updates. You can explore them but should do so with awareness that support might be > limited and subject to change. ## Supported Storage Options - **Local**: Load data from application local storage - [**Azure Blob Storage**](https://docs.mulesoft.com/azure-data-lake-storage-connector/latest/): Load data from Azure Blob Storage containers - [**Amazon S3**](https://docs.mulesoft.com/amazon-s3-connector/latest/): Load data from Amazon S3 buckets ## Next Step After you complete the prerequisites, you are ready to create an app and configure the connector using [Anypoint Studio](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-studio) or [Anypoint Code Builder](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-config-acb). ## See Also - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Using Anypoint Code Builder to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-acb) - [Using Studio to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-studio) - [MuleSoft Vectors - Additional Configuration Information](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-additional-config) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.0 --- # MuleSoft Vectors Connector 1.0 Reference > For the full documentation index, see: https://docs.mulesoft.com/llms.txt MuleSoft Vectors Connector provides operations to work with vector stores and embedding models. ## Configurations --- ### Embedding Config #### Parameters
NameTypeDescriptionDefault ValueRequired

Name

String

Name for this configuration. Connectors reference the configuration with this name.

x

Connection

Connection types for this configuration.

x

Name

String

ID used to reference this configuration.

x

Expiration Policy

Configures an expiration policy for the configuration.

#### Connection Types ##### Azure AI Vision ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Endpoint

String

Endpoint.

x

Api Key

String

API key.

x

Api Version

String

API version.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Azure OpenAI ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Endpoint

String

Endpoint.

x

Api Key

String

API key.

x

Api Version

String

API version.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Einstein ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Salesforce Org

String

Salesforce org.

x

Client Id

String

Client ID.

x

Client Secret

String

Client secret.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Hugging Face ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Mistral AI ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Total Timeout (ms)

Number

Total timeout in milliseconds for API requests.

60000

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Nomic ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Ollama ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Base URL

String

Ollama base URL.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### OpenAI ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

## Supported Operations - [\[Embedding\] Generate from text](#EmbeddingGenerateFromText) --- ### Store Config #### Parameters
NameTypeDescriptionDefault ValueRequired

Name

String

Name for this configuration. Connectors reference the configuration with this name.

x

Connection

Connection types for this configuration.

x

Name

String

ID used to reference this configuration.

x

Expiration Policy

Configures an expiration policy for the configuration.

#### Connection Types ##### AI Search ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Configuration

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Url

String

URL.

x

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Chroma ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Configuration

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Url

String

URL.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Ephemeral File ###### Parameters
NameTypeDescriptionDefault ValueRequired

Working Directory

String

Directory for creating store files.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Milvus ###### Parameters
NameTypeDescriptionDefault ValueRequired

Uri

String

URI.

Host

String

Host.

Port

Number

Port.

Token

String

Token.

Username

String

Username.

Password

String

Password.

Database Name

String

Database name.

Index Type

String

Index type.

FLAT

Metric Type

String

Metric type.

COSINE

Consistency Level

String

Consistency level.

EVENTUALLY

Auto Flush On Insert

Boolean

Determines whether to auto-flush on insert.

true

Id Field Name

String

ID field name.

ID

Text Field Name

String

Text field name.

text

Metadata Field Name

String

Metadata field name.

metadata

Vector Field Name

String

Vector field name.

vector

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### MongoDB Atlas ###### Parameters
NameTypeDescriptionDefault ValueRequired

Host

String

Host.

x

Port

Number

Port.

Username

String

Username.

Password

String

Password.

x

Database Name

String

Database name.

Options

String

Options.

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### OpenSearch ###### Parameters
NameTypeDescriptionDefault ValueRequired

Url

String

URL.

x

User

String

Username.

Password

String

Password.

x

Api Key

String

API key.

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### PGVector ###### Parameters
NameTypeDescriptionDefault ValueRequired

Host

String

Host.

x

Port

Number

Port.

x

Database

String

Database.

x

User

String

Username.

x

Password

String

Password.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Pinecone ###### Parameters
NameTypeDescriptionDefault ValueRequired

Cloud

String

Cloud.

x

Region

String

Region.

x

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Qdrant ###### Parameters
NameTypeDescriptionDefault ValueRequired

Host

String

Host.

x

GPRC Port

Number

gRPC port.

x

Use TLS

Boolean

Determines whether to use TLS.

false

Text Segment Key

String

Text segment key.

x

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

## Supported Operations - [\[Store\] Query](#Query) - [\[Store\] Query all](#QueryAll) - [\[Store\] Add](#StoreAdd) - [\[Store\] Remove](#StoreRemove) --- ### Transform Config #### Parameters
NameTypeDescriptionDefault ValueRequired

Name

String

Name for this configuration. Connectors reference the configuration with this name.

x

Name

String

ID used to reference this configuration.

x

## Supported Operations - [\[Transform\] Parse document](#TransformParseDocument) ## Operations ## \[Embedding\] Generate from text `` Generates embeddings from a given text string. The text can optionally be segmented before embedding. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Input Texts

Array of String

Input list of texts to generate embeddings from.

#[payload]

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

x

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Model (Deployment) Name

String

Embedding model (deployment) name.

x

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Embedding Config](#EmbeddingConfig) ### Throws - MS-VECTORS:AI\_SERVICES\_FAILURE - MS-VECTORS:AI\_SERVICES\_RATE\_LIMITING\_ERROR - MS-VECTORS:CONNECTIVITY - MS-VECTORS:EMBEDDING\_OPERATIONS\_FAILURE - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED ## \[Store\] Query `` Queries an embedding store based on the provided embedding and text segment, and applies a metadata filter. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store or collection to query.

x

Text Segment and Embedding

Any

Text segment and embedding generated from the question and used to query the store.

x

Max Results

Number

Maximum number of results (text segments) retrieved.

x

Min Score

Number

Minimum score used to filter retrieved results (text segments) (0-1).

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Metadata Condition

String

Metadata condition.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Store\] Query all `` Lists all sources in the specified embedding store. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store.

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Retrieve Embeddings

Boolean

Flag to indicate whether embeddings should be retrieved.

false

Page size

Number

Page size used when querying the vector store.

5000

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Array of Message of [Binary] payload and Store Response Attributes attributes

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Store\] Add `` Adds embeddings and text segments to the store. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store or collection to use for data ingestion.

x

Text Segments and Embeddings

Any

Text segments and embeddings to add to the store.

#[payload]

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Metadata entries

Object

Custom metadata key-value pairs to add to the vector store.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Store\] Remove `` Removes embeddings from the store based on the provided filter. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store.

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Ids

Array of String

List of IDs to remove.

Metadata Condition

String

Metadata condition.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Transform\] Parse document `` Parses a document from a raw binary or Base64-encoded content. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Document binary

Any

Raw binary or Base64-encoded content of the document to parse.

#[payload]

Document parser

Document parser to use.

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

### Output

Type

Binary

Attributes Type

### For Configurations - [Transform Config](#TransformConfig) ### Throws - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:TRANSFORM\_DOCUMENT\_PARSING\_FAILURE - MS-VECTORS:TRANSFORM\_OPERATIONS\_FAILURE ## \[Transform\] Chunk text `` Chunks the provided text into multiple segments based on the segmentation parameters. This operation splits the input text into smaller segments according to the maximum segment size and overlap size specified in the segmentation parameters. The result is returned as a JSON document containing the chunked text segments and associated metadata. ### Parameters
NameTypeDescriptionDefault ValueRequired

Text

Any

Input text to chunk.

#[payload]

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Max Segment Size (Characters)

Number

Maximum size of a segment in characters.

Max Overlap Size (Characters)

Number

Maximum overlap between segments in characters.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

### Output

Type

Array of String

Attributes Type

### Throws - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:TRANSFORM\_DOCUMENT\_PARSING\_FAILURE - MS-VECTORS:TRANSFORM\_OPERATIONS\_FAILURE ## Types ### TLS Configures TLS to provide secure communications for the Mule app.
FieldTypeDescriptionDefault ValueRequired

Enabled Protocols

String

Comma-separated list of protocols enabled for this context.

Enabled Cipher Suites

String

Comma-separated list of cipher suites enabled for this context.

Trust Store

Configures the TLS truststore.

Key Store

Configures the TLS keystore.

Revocation Check

Configures a revocation checking mechanism.

### Truststore Configures the truststore for TLS.
FieldTypeDescriptionDefault ValueRequired

Path

String

Path to the truststore. Mule resolves the path relative to the current classpath and file system.

Password

String

Password used to protect the truststore.

Type

String

Type of truststore.

Algorithm

String

Encryption algorithm that the truststore uses.

Insecure

Boolean

If true, Mule stops performing certificate validations. Setting this to true can make connections vulnerable to attacks.

### Keystore Configures the keystore for the TLS protocol. The keystore you generate contains a private key and a public certificate.
FieldTypeDescriptionDefault ValueRequired

Path

String

Path to the keystore. Mule resolves the path relative to the current classpath and file system.

Type

String

Type of keystore.

Alias

String

Alias of the key to use when the keystore contains multiple private keys. By default, Mule uses the first key in the file.

Key Password

String

Password used to protect the private key.

Password

String

Password used to protect the keystore.

Algorithm

String

Encryption algorithm that the keystore uses.

### Standard Revocation Check Configures standard revocation checks for TLS certificates.
FieldTypeDescriptionDefault ValueRequired

Only End Entities

Boolean

Which elements to verify in the certificate chain:

  • true

    Verify only the last element in the certificate chain.

  • false

    Verify all elements in the certificate chain.

Prefer Crls

Boolean

How to check certificate validity:

  • true

    Check the Certification Revocation List (CRL) for certificate validity.

  • false

    Use the Online Certificate Status Protocol (OCSP) to check certificate validity.

No Fallback

Boolean

Whether to use the secondary method to check certificate validity:

  • true

    Use the method that wasn’t specified in the Prefer Crls field (the secondary method) to check certificate validity.

  • false

    Do not use the secondary method to check certificate validity.

Soft Fail

Boolean

What to do if the revocation server can’t be reached or is busy:

  • true

    Avoid verification failure.

  • false

    Allow the verification to fail.

### Custom OCSP Responder Configures a custom OCSP responder for certification revocation checks.
FieldTypeDescriptionDefault ValueRequired

Url

String

URL of the OCSP responder.

Cert Alias

String

Alias of the signing certificate for the OCSP response. If specified, the alias must be in the truststore.

### CRL File Specifies the location of the certification revocation list (CRL) file.
FieldTypeDescriptionDefault ValueRequired

Path

String

Path to the CRL file.

### Reconnection Configures a reconnection strategy for an operation.
FieldTypeDescriptionDefault ValueRequired

Fails Deployment

Boolean

Configures a reconnection strategy to use when a connector operation fails to connect to an external server.

Reconnection Strategy

Reconnection strategy to use.

### Reconnect Configures a standard reconnection strategy, which specifies how often to reconnect and how many reconnection attempts the connector source or operation can make.
FieldTypeDescriptionDefault ValueRequired

Frequency

Number

How often to attempt to reconnect, in milliseconds.

Blocking

Boolean

If false, the reconnection strategy runs in a separate, non-blocking thread.

Count

Number

How many reconnection attempts the Mule app can make.

### Reconnect Forever Configures a forever reconnection strategy by which the connector source or operation attempts to reconnect at a specified frequency for as long as the Mule app runs.
FieldTypeDescriptionDefault ValueRequired

Frequency

Number

How often to attempt to reconnect, in milliseconds.

Blocking

Boolean

If false, the reconnection strategy runs in a separate, non-blocking thread.

### Expiration Policy Configures an expiration policy strategy.
FieldTypeDescriptionDefault ValueRequired

Max Idle Time

Number

Configures the maximum amount of time that a dynamic configuration instance can remain idle before Mule considers it eligible for expiration.

Time Unit

Enumeration, one of:

  • NANOSECONDS

  • MICROSECONDS

  • MILLISECONDS

  • SECONDS

  • MINUTES

  • HOURS

  • DAYS

Time unit for the Max Idle Time field.

### Embedding Response Attributes Configures the response attributes for the embedding operation.
FieldTypeDescriptionDefault ValueRequired

Embedding Model Dimension

Number

Embedding model dimension.

Embedding Model Name

String

Embedding model name.

Other Attributes

Object

Other attributes.

Token Usage

Token usage.

### Token Usage Configures token usage metadata returned as attributes.
FieldTypeDescriptionDefault ValueRequired

Input Count

Number

Number of tokens used to process the input.

Output Count

Number

Number of tokens used to generate the output.

Total Count

Number

Total number of tokens used for input and output.

### Repeatable In Memory Stream Configures the in-memory streaming strategy by which the request fails if the data exceeds the MAX buffer size. Always run performance tests to find the optimal buffer size for your specific use case.
FieldTypeDescriptionDefault ValueRequired

Initial Buffer Size

Number

Initial amount of memory to allocate to the data stream. If the streamed data exceeds this value, the buffer expands by Buffer Size Increment, with an upper limit of Max Buffer Size.

Buffer Size Increment

Number

This is by how much the buffer size expands if it exceeds its initial size. Setting a value of zero or lower means that the buffer should not expand, meaning that a STREAM_MAXIMUM_SIZE_EXCEEDED error is raised when the buffer gets full.

Max Buffer Size

Number

Maximum size of the buffer. If the buffer size exceeds this value, Mule raises a STREAM_MAXIMUM_SIZE_EXCEEDED error. A value of less than or equal to 0 means no limit.

Buffer Unit

Enumeration, one of:

  • BYTE

  • KB

  • MB

  • GB

Unit for the Initial Buffer Size, Buffer Size Increment, and Max Buffer Size fields.

### Repeatable File Store Stream Configures the repeatable file-store streaming strategy by which Mule keeps a portion of the stream content in memory. If the stream content is larger than the configured buffer size, Mule backs up the buffer’s content to disk and then clears the memory.
FieldTypeDescriptionDefault ValueRequired

In Memory Size

Number

Maximum amount of memory that the stream can use for data. If the amount of memory exceeds this value, Mule buffers the content to disk. To optimize performance:

  • Configure a larger buffer size to avoid the number of times Mule needs to write the buffer on disk. This increases performance, but it also limits the number of concurrent requests your application can process, because it requires additional memory.

  • Configure a smaller buffer size to decrease memory load at the expense of response time.

Buffer Unit

Enumeration, one of:

  • BYTE

  • KB

  • MB

  • GB

Unit for the In Memory Size field.

### Error Mapping Configures error mapping.
FieldTypeDescriptionDefault ValueRequired

Source

Enumeration, one of:

  • ANY

  • REDELIVERY_EXHAUSTED

  • TRANSFORMATION

  • EXPRESSION

  • SECURITY

  • CLIENT_SECURITY

  • SERVER_SECURITY

  • ROUTING

  • CONNECTIVITY

  • RETRY_EXHAUSTED

  • TIMEOUT

Source of the error.

Target

String

Target of the error.

x

### Store Response Attributes Configures the response attributes for the store operation.
FieldTypeDescriptionDefault ValueRequired

Ids

Array of String

IDs.

Metadata Condition

String

Metadata condition.

Other Attributes

Object

Other attributes.

Store Name

String

Name of the store.

### Repeatable In Memory Iterable Configures the repeatable in memory iterable type.
FieldTypeDescriptionDefault ValueRequired

Initial Buffer Size

Number

Amount of instances to initially keep in memory to consume the stream and provide random access to it. If the stream contains more data than can fit into this buffer, then the buffer expands according to the Buffer Size Increment attribute, with an upper limit of Max Buffer Size. Default value is 100 instances.

Buffer Size Increment

Number

This is by how much the buffer size expands if it exceeds its initial size. Setting a value of 0 or lower means that the buffer must not expand, meaning that a STREAM_MAXIMUM_SIZE_EXCEEDED error is raised when the buffer gets full. Default value is 100 instances.

Max Buffer Size

Number

Maximum amount of memory to use. If more than that is used, a STREAM_MAXIMUM_SIZE_EXCEEDED error is raised. A value lower than or equal to 0 means no limit.

### Repeatable File Store Iterable Configures the repeatable file store iterable type.
FieldTypeDescriptionDefault ValueRequired

In Memory Objects

Number

Maximum amount of instances to keep in memory. If more than that is required, content on the disk is buffered.

Buffer Unit

Enumeration, one of:

  • BYTE

  • KB

  • MB

  • GB

Unit for the In Memory Objects field.

### Parser Response Attributes Configures the response attributes for the parser.
FieldTypeDescriptionDefault ValueRequired

Document Parser Name

String

Document parser name.

### Chunk Response Attributes Configures the response attributes for the chunk.
FieldTypeDescriptionDefault ValueRequired

Max Overlap Size In Chars

Number

Maximum overlap size in characters.

Max Segment Size In Chars

Number

Maximum segment size in characters.

### Multiformat Document Parser Parameters Configures the parameters for the multiformat document parser.
FieldTypeDescriptionDefault ValueRequired

Include Metadata

Boolean

Determines whether to include metadata.

false

### Text Document Parser Parameters Configures the parameters for the text document parser.
FieldTypeDescriptionDefault ValueRequired

Document Parser

DocumentParser

Document parser.

Name

String

Document parser name.

## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/) - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.0 --- # MuleSoft Vectors Connector 1.0.0 XML and Maven Support > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Although you can manually code a Mule app in XML, it is more efficient to use Anypoint Code Builder or Studio: - If you manually code a Mule runtime engine (Mule) app in XML, either from the Anypoint Code Builder or Studio XML editor, or from a text editor, you can access the connector from your app by adding reference statements to both your XML Mule flow and the Apache Maven `pom.xml` file. - If you add the connector in Anypoint Code Builder or Studio, the XML is automatically populated the code with the connector’s namespace and schema location and it also adds a dependency to the `pom.xml` file. ## Add a Namespace for the Connector Paste the following code inside the `mule` tag of the header of your configuration XML: ```xml http://www.mulesoft.org/schema/mule/ms-vectors http://www.mulesoft.org/schema/mule/ms-vectors/current/mule-ms-vectors.xsd ``` This example shows how the namespace statements are placed in the `` XML block: ```xml ``` ## Add a POM File Dependency The Apache Maven `pom.xml` file generated by Anypoint Studio contains dependencies for a Mule app. If you code a Mule app manually, include this XML snippet in your `pom.xml` file to enable access to this connector: ```xml com.mulesoft.connectors mule4-vectors-connector x.x.x mule-plugin ``` Replace `x.x.x` with the version that corresponds to the connector you are using. To obtain the most up-to-date `pom.xml` file information: 1. Go to [Anypoint Exchange](https://www.mulesoft.com/exchange/). 2. In Exchange, click **Login** and supply your Anypoint Platform username and password. 3. In Exchange, search for `vectors`. 4. Select the connector. 5. Click **Dependency Snippets** near the upper right of the screen. ## See Also - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # MuleSoft Vectors Connector 1.1 > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Anypoint Connector for MuleSoft Vectors (MuleSoft Vectors Connector) provides access to a broad number of external vector stores and databases. MuleSoft Vectors Connector can be used with other connectors (for example, MuleSoft Inference Connector or Einstein AI Connector) and provides seamless access to vector stores for implementing smarter search or Retrieval Augmented Generation (RAG) use cases. For information about compatibility and fixed issues, see the MuleSoft Vectors Connector release notes. ## Before You Begin To use this connector, you must be familiar with: - Anypoint Connectors - Mule runtime engine (Mule) - Elements and global elements in a Mule flow - How to create a Mule app using Anypoint Code Builder or Anypoint Studio Before creating an app, you must have: - Java 17 (required for compilation and runtime) - Apache Maven - Credentials to access the MuleSoft Vectors Connector target resources - Anypoint Platform - The latest versions of Anypoint Code Builder or Anypoint Studio ## Key Features MuleSoft Vectors Connector provides: - Accelerated AI-powered application development - Simplified vector database integration - Easy-to-build semantic search and RAG experiences without managing complex vector infrastructure > [!NOTE] Data is processed in in-memory, so if you do parallel processing (such as running multiple > flows in one go), you might encounter an out-of-memory issue. For example, if you process 1 MB > files in three flows, around 3 MB files will be loaded in-memory. This is due to the nature of > Apache Tika and LangChain4j libraries. ## Supported Vector Stores MuleSoft Vectors Connector supports these vector stores: - Azure AI Search (beta) - Chroma (beta) - Milvus (beta) - OpenSearch (beta) - PGVector (beta) > [!NOTE] PGVector is not FIPS-compliant. - Pinecone (beta) - Qdrant (beta) - MongoDB Atlas (beta) - Ephemeral File (beta) ### Supported Operations by Vector Stores This table provides a detailed view of operation support across all vector stores:
Vector StoreStoring MetadataFiltering by MetadataRemoving EmbeddingsList All Embeddings

Azure AI Search

Yes

Yes

Yes

Yes

Chroma

Yes

Yes

Yes

Yes

Milvus

Yes

Yes

Yes

Yes

OpenSearch

Yes

Yes

Yes

No

PGVector

Yes

Yes

Yes

Yes

Pinecone

Yes

Yes

No

No

Qdrant

Yes

Yes

Yes

Yes

MongoDB Atlas

Yes

Yes

Yes

Yes

Ephemeral File

Yes

Yes

Yes

Yes

## Supported Model Providers MuleSoft Vectors Connector supports these model providers to generate embeddings: - Azure OpenAI - Azure Vision AI (beta) - Einstein - Hugging Face (beta) - Mistral AI (beta) - Nomic (beta) - Ollama (beta) - OpenAI ### Supported Embedding Types by Model Providers This table provides a detailed view of embedding type support across all model providers:
Model ProviderText EmbeddingImage EmbeddingVideo Embedding

Azure OpenAI

Yes

No

No

Azure Vision AI

Yes

No

No

Einstein

Yes

No

No

Hugging Face

Yes

No

No

Mistral AI

Yes

No

No

Nomic

Yes

No

No

Ollama

Yes

No

No

OpenAI

Yes

No

No

> [!NOTE] To keep pace with the rapidly evolving AI landscape, certain vector stores and LLMs are > marked as beta. These are early-stage integrations that may change based on stability, demand, or > provider updates. You can explore them but should do so with awareness that support might be > limited and subject to change. ## Supported Storage Options - **Local**: Load data from application local storage - [**Azure Blob Storage**](https://docs.mulesoft.com/azure-data-lake-storage-connector/latest/): Load data from Azure Blob Storage containers - [**Amazon S3**](https://docs.mulesoft.com/amazon-s3-connector/latest/): Load data from Amazon S3 buckets ## Next Step After you complete the prerequisites, you are ready to create an app and configure the connector using [Anypoint Studio](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-studio) or [Anypoint Code Builder](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-config-acb). ## See Also - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Using Anypoint Code Builder to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-acb) - [Using Studio to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-studio) - [MuleSoft Vectors - Additional Configuration Information](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-additional-config) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # MuleSoft Vectors Connector 1.1 Reference > For the full documentation index, see: https://docs.mulesoft.com/llms.txt MuleSoft Vectors Connector provides operations to work with vector stores and embedding models. ## Configurations --- ### Embedding Config #### Parameters
NameTypeDescriptionDefault ValueRequired

Name

String

Name for this configuration. Connectors reference the configuration with this name.

x

Connection

Connection types for this configuration.

x

Name

String

ID used to reference this configuration.

x

Expiration Policy

Configures an expiration policy for the configuration.

#### Connection Types ##### Azure AI Vision ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Endpoint

String

Endpoint.

x

Api Key

String

API key.

x

Api Version

String

API version.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Azure OpenAI ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Endpoint

String

Endpoint.

x

Api Key

String

API key.

x

Api Version

String

API version.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Einstein ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Salesforce Org

String

Salesforce org.

x

Client Id

String

Client ID.

x

Client Secret

String

Client secret.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Hugging Face ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Mistral AI ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Total Timeout (ms)

Number

Total timeout in milliseconds for API requests.

60000

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Nomic ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Ollama ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Base URL

String

Ollama base URL.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### OpenAI ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Config

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Timeout

Number

Timeout for the operation in milliseconds.

60000

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

## Supported Operations - [\[Embedding\] Generate from text](#EmbeddingGenerateFromText) --- ### Store Config #### Parameters
NameTypeDescriptionDefault ValueRequired

Name

String

Name for this configuration. Connectors reference the configuration with this name.

x

Connection

Connection types for this configuration.

x

Name

String

ID used to reference this configuration.

x

Expiration Policy

Configures an expiration policy for the configuration.

#### Connection Types ##### AI Search ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Configuration

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Url

String

URL.

x

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Chroma ###### Parameters
NameTypeDescriptionDefault ValueRequired

Proxy Configuration

HttpProxyConfig

Configures a proxy for outbound connections.

TLS Configuration

If HTTPS is configured as a protocol, then you must configure at least the keystore configuration.

Url

String

URL.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Ephemeral File ###### Parameters
NameTypeDescriptionDefault ValueRequired

Working Directory

String

Directory for creating store files.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Milvus ###### Parameters
NameTypeDescriptionDefault ValueRequired

Uri

String

URI.

Host

String

Host.

Port

Number

Port.

Token

String

Token.

Username

String

Username.

Password

String

Password.

Database Name

String

Database name.

Index Type

String

Index type.

FLAT

Metric Type

String

Metric type.

COSINE

Consistency Level

String

Consistency level.

EVENTUALLY

Auto Flush On Insert

Boolean

Determines whether to auto-flush on insert.

true

Id Field Name

String

ID field name.

ID

Text Field Name

String

Text field name.

text

Metadata Field Name

String

Metadata field name.

metadata

Vector Field Name

String

Vector field name.

vector

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### MongoDB Atlas ###### Parameters
NameTypeDescriptionDefault ValueRequired

Host

String

Host.

x

Port

Number

Port.

Username

String

Username.

Password

String

Password.

x

Database Name

String

Database name.

Options

String

Options.

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### OpenSearch ###### Parameters
NameTypeDescriptionDefault ValueRequired

Url

String

URL.

x

User

String

Username.

Password

String

Password.

x

Api Key

String

API key.

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### PGVector ###### Parameters
NameTypeDescriptionDefault ValueRequired

Host

String

Host.

x

Port

Number

Port.

x

Database

String

Database.

x

User

String

Username.

x

Password

String

Password.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Pinecone ###### Parameters
NameTypeDescriptionDefault ValueRequired

Cloud

String

Cloud.

x

Region

String

Region.

x

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

##### Qdrant ###### Parameters
NameTypeDescriptionDefault ValueRequired

Host

String

Host.

x

GPRC Port

Number

gRPC port.

x

Use TLS

Boolean

Determines whether to use TLS.

false

Text Segment Key

String

Text segment key.

x

Api Key

String

API key.

x

Reconnection

When the application is deployed, a connectivity test is performed on all connectors. If set to true, deployment fails if the test doesn’t pass after exhausting the associated reconnection strategy.

## Supported Operations - [\[Store\] Query](#Query) - [\[Store\] Query all](#QueryAll) - [\[Store\] Add](#StoreAdd) - [\[Store\] Remove](#StoreRemove) --- ### Transform Config #### Parameters
NameTypeDescriptionDefault ValueRequired

Name

String

Name for this configuration. Connectors reference the configuration with this name.

x

Name

String

ID used to reference this configuration.

x

## Supported Operations - [\[Transform\] Parse document](#TransformParseDocument) ## Operations ## \[Embedding\] Generate from text `` Generates embeddings from a given text string. The text can optionally be segmented before embedding. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Input Texts

Array of String

Input list of texts to generate embeddings from.

#[payload]

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

x

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Model (Deployment) Name

String

Embedding model (deployment) name.

x

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Embedding Config](#EmbeddingConfig) ### Throws - MS-VECTORS:AI\_SERVICES\_FAILURE - MS-VECTORS:AI\_SERVICES\_RATE\_LIMITING\_ERROR - MS-VECTORS:CONNECTIVITY - MS-VECTORS:EMBEDDING\_OPERATIONS\_FAILURE - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED ## \[Store\] Query `` Queries an embedding store based on the provided embedding and text segment, and applies a metadata filter. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store or collection to query.

x

Text Segment and Embedding

Any

Text segment and embedding generated from the question and used to query the store.

x

Max Results

Number

Maximum number of results (text segments) retrieved.

x

Min Score

Number

Minimum score used to filter retrieved results (text segments) (0-1).

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Metadata Condition

String

Metadata condition.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Store\] Query all `` Lists all sources in the specified embedding store. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store.

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Retrieve Embeddings

Boolean

Flag to indicate whether embeddings should be retrieved.

false

Page size

Number

Page size used when querying the vector store.

5000

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Array of Message of [Binary] payload and Store Response Attributes attributes

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Store\] Add `` Adds embeddings and text segments to the store. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store or collection to use for data ingestion.

x

Text Segments and Embeddings

Any

Text segments and embeddings to add to the store.

#[payload]

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Metadata entries

Object

Custom metadata key-value pairs to add to the vector store.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Store\] Remove `` Removes embeddings from the store based on the provided filter. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Store Name

String

Name of the store.

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Ids

Array of String

List of IDs to remove.

Metadata Condition

String

Metadata condition.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

Reconnection Strategy

Retry strategy in case of connectivity errors.

### Output

Type

Any

Attributes Type

### For Configurations - [Store Config](#StoreConfig) ### Throws - MS-VECTORS:CONNECTIVITY - MS-VECTORS:INVALID\_CONNECTION - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:RETRY\_EXHAUSTED - MS-VECTORS:STORE\_OPERATIONS\_FAILURE - MS-VECTORS:STORE\_SERVICES\_FAILURE - MS-VECTORS:STORE\_UNSUPPORTED\_OPERATION ## \[Transform\] Parse document `` Parses a document from a raw binary or Base64-encoded content. ### Parameters
NameTypeDescriptionDefault ValueRequired

Configuration

String

Name of the configuration to use.

x

Document binary

Any

Raw binary or Base64-encoded content of the document to parse.

#[payload]

Document parser

Document parser to use.

x

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Config Ref

ConfigurationProvider

Name of the configuration to use to execute this component.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

### Output

Type

Binary

Attributes Type

### For Configurations - [Transform Config](#TransformConfig) ### Throws - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:TRANSFORM\_DOCUMENT\_PARSING\_FAILURE - MS-VECTORS:TRANSFORM\_OPERATIONS\_FAILURE ## \[Transform\] Chunk text `` Chunks the provided text into multiple segments based on the segmentation parameters. This operation splits the input text into smaller segments according to the maximum segment size and overlap size specified in the segmentation parameters. The result is returned as a JSON document containing the chunked text segments and associated metadata. ### Parameters
NameTypeDescriptionDefault ValueRequired

Text

Any

Input text to chunk.

#[payload]

Output Mime Type

String

MIME type of the payload that this operation outputs.

Output Encoding

String

Encoding of the payload that this operation outputs.

Streaming Strategy

Configures how Mule processes streams. Repeatable streams are the default behavior.

Max Segment Size (Characters)

Number

Maximum size of a segment in characters.

Max Overlap Size (Characters)

Number

Maximum overlap between segments in characters.

Target Variable

String

Name of the variable that stores the operation’s output.

Target Value

String

Expression that evaluates the operation’s output. The outcome of the expression is stored in the Target Variable field.

#[payload]

Error Mappings

Array of Error Mapping

Set of error mappings.

### Output

Type

Array of String

Attributes Type

### Throws - MS-VECTORS:INVALID\_PARAMETER - MS-VECTORS:TRANSFORM\_DOCUMENT\_PARSING\_FAILURE - MS-VECTORS:TRANSFORM\_OPERATIONS\_FAILURE ## Types ### TLS Configures TLS to provide secure communications for the Mule app.
FieldTypeDescriptionDefault ValueRequired

Enabled Protocols

String

Comma-separated list of protocols enabled for this context.

Enabled Cipher Suites

String

Comma-separated list of cipher suites enabled for this context.

Trust Store

Configures the TLS truststore.

Key Store

Configures the TLS keystore.

Revocation Check

Configures a revocation checking mechanism.

### Truststore Configures the truststore for TLS.
FieldTypeDescriptionDefault ValueRequired

Path

String

Path to the truststore. Mule resolves the path relative to the current classpath and file system.

Password

String

Password used to protect the truststore.

Type

String

Type of truststore.

Algorithm

String

Encryption algorithm that the truststore uses.

Insecure

Boolean

If true, Mule stops performing certificate validations. Setting this to true can make connections vulnerable to attacks.

### Keystore Configures the keystore for the TLS protocol. The keystore you generate contains a private key and a public certificate.
FieldTypeDescriptionDefault ValueRequired

Path

String

Path to the keystore. Mule resolves the path relative to the current classpath and file system.

Type

String

Type of keystore.

Alias

String

Alias of the key to use when the keystore contains multiple private keys. By default, Mule uses the first key in the file.

Key Password

String

Password used to protect the private key.

Password

String

Password used to protect the keystore.

Algorithm

String

Encryption algorithm that the keystore uses.

### Standard Revocation Check Configures standard revocation checks for TLS certificates.
FieldTypeDescriptionDefault ValueRequired

Only End Entities

Boolean

Which elements to verify in the certificate chain:

  • true

    Verify only the last element in the certificate chain.

  • false

    Verify all elements in the certificate chain.

Prefer Crls

Boolean

How to check certificate validity:

  • true

    Check the Certification Revocation List (CRL) for certificate validity.

  • false

    Use the Online Certificate Status Protocol (OCSP) to check certificate validity.

No Fallback

Boolean

Whether to use the secondary method to check certificate validity:

  • true

    Use the method that wasn’t specified in the Prefer Crls field (the secondary method) to check certificate validity.

  • false

    Do not use the secondary method to check certificate validity.

Soft Fail

Boolean

What to do if the revocation server can’t be reached or is busy:

  • true

    Avoid verification failure.

  • false

    Allow the verification to fail.

### Custom OCSP Responder Configures a custom OCSP responder for certification revocation checks.
FieldTypeDescriptionDefault ValueRequired

Url

String

URL of the OCSP responder.

Cert Alias

String

Alias of the signing certificate for the OCSP response. If specified, the alias must be in the truststore.

### CRL File Specifies the location of the certification revocation list (CRL) file.
FieldTypeDescriptionDefault ValueRequired

Path

String

Path to the CRL file.

### Reconnection Configures a reconnection strategy for an operation.
FieldTypeDescriptionDefault ValueRequired

Fails Deployment

Boolean

Configures a reconnection strategy to use when a connector operation fails to connect to an external server.

Reconnection Strategy

Reconnection strategy to use.

### Reconnect Configures a standard reconnection strategy, which specifies how often to reconnect and how many reconnection attempts the connector source or operation can make.
FieldTypeDescriptionDefault ValueRequired

Frequency

Number

How often to attempt to reconnect, in milliseconds.

Blocking

Boolean

If false, the reconnection strategy runs in a separate, non-blocking thread.

Count

Number

How many reconnection attempts the Mule app can make.

### Reconnect Forever Configures a forever reconnection strategy by which the connector source or operation attempts to reconnect at a specified frequency for as long as the Mule app runs.
FieldTypeDescriptionDefault ValueRequired

Frequency

Number

How often to attempt to reconnect, in milliseconds.

Blocking

Boolean

If false, the reconnection strategy runs in a separate, non-blocking thread.

### Expiration Policy Configures an expiration policy strategy.
FieldTypeDescriptionDefault ValueRequired

Max Idle Time

Number

Configures the maximum amount of time that a dynamic configuration instance can remain idle before Mule considers it eligible for expiration.

Time Unit

Enumeration, one of:

  • NANOSECONDS

  • MICROSECONDS

  • MILLISECONDS

  • SECONDS

  • MINUTES

  • HOURS

  • DAYS

Time unit for the Max Idle Time field.

### Embedding Response Attributes Configures the response attributes for the embedding operation.
FieldTypeDescriptionDefault ValueRequired

Embedding Model Dimension

Number

Embedding model dimension.

Embedding Model Name

String

Embedding model name.

Other Attributes

Object

Other attributes.

Token Usage

Token usage.

### Token Usage Configures token usage metadata returned as attributes.
FieldTypeDescriptionDefault ValueRequired

Input Count

Number

Number of tokens used to process the input.

Output Count

Number

Number of tokens used to generate the output.

Total Count

Number

Total number of tokens used for input and output.

### Repeatable In Memory Stream Configures the in-memory streaming strategy by which the request fails if the data exceeds the MAX buffer size. Always run performance tests to find the optimal buffer size for your specific use case.
FieldTypeDescriptionDefault ValueRequired

Initial Buffer Size

Number

Initial amount of memory to allocate to the data stream. If the streamed data exceeds this value, the buffer expands by Buffer Size Increment, with an upper limit of Max Buffer Size.

Buffer Size Increment

Number

This is by how much the buffer size expands if it exceeds its initial size. Setting a value of zero or lower means that the buffer should not expand, meaning that a STREAM_MAXIMUM_SIZE_EXCEEDED error is raised when the buffer gets full.

Max Buffer Size

Number

Maximum size of the buffer. If the buffer size exceeds this value, Mule raises a STREAM_MAXIMUM_SIZE_EXCEEDED error. A value of less than or equal to 0 means no limit.

Buffer Unit

Enumeration, one of:

  • BYTE

  • KB

  • MB

  • GB

Unit for the Initial Buffer Size, Buffer Size Increment, and Max Buffer Size fields.

### Repeatable File Store Stream Configures the repeatable file-store streaming strategy by which Mule keeps a portion of the stream content in memory. If the stream content is larger than the configured buffer size, Mule backs up the buffer’s content to disk and then clears the memory.
FieldTypeDescriptionDefault ValueRequired

In Memory Size

Number

Maximum amount of memory that the stream can use for data. If the amount of memory exceeds this value, Mule buffers the content to disk. To optimize performance:

  • Configure a larger buffer size to avoid the number of times Mule needs to write the buffer on disk. This increases performance, but it also limits the number of concurrent requests your application can process, because it requires additional memory.

  • Configure a smaller buffer size to decrease memory load at the expense of response time.

Buffer Unit

Enumeration, one of:

  • BYTE

  • KB

  • MB

  • GB

Unit for the In Memory Size field.

### Error Mapping Configures error mapping.
FieldTypeDescriptionDefault ValueRequired

Source

Enumeration, one of:

  • ANY

  • REDELIVERY_EXHAUSTED

  • TRANSFORMATION

  • EXPRESSION

  • SECURITY

  • CLIENT_SECURITY

  • SERVER_SECURITY

  • ROUTING

  • CONNECTIVITY

  • RETRY_EXHAUSTED

  • TIMEOUT

Source of the error.

Target

String

Target of the error.

x

### Store Response Attributes Configures the response attributes for the store operation.
FieldTypeDescriptionDefault ValueRequired

Ids

Array of String

IDs.

Metadata Condition

String

Metadata condition.

Other Attributes

Object

Other attributes.

Store Name

String

Name of the store.

### Repeatable In Memory Iterable Configures the repeatable in memory iterable type.
FieldTypeDescriptionDefault ValueRequired

Initial Buffer Size

Number

Amount of instances to initially keep in memory to consume the stream and provide random access to it. If the stream contains more data than can fit into this buffer, then the buffer expands according to the Buffer Size Increment attribute, with an upper limit of Max Buffer Size. Default value is 100 instances.

Buffer Size Increment

Number

This is by how much the buffer size expands if it exceeds its initial size. Setting a value of 0 or lower means that the buffer must not expand, meaning that a STREAM_MAXIMUM_SIZE_EXCEEDED error is raised when the buffer gets full. Default value is 100 instances.

Max Buffer Size

Number

Maximum amount of memory to use. If more than that is used, a STREAM_MAXIMUM_SIZE_EXCEEDED error is raised. A value lower than or equal to 0 means no limit.

### Repeatable File Store Iterable Configures the repeatable file store iterable type.
FieldTypeDescriptionDefault ValueRequired

In Memory Objects

Number

Maximum amount of instances to keep in memory. If more than that is required, content on the disk is buffered.

Buffer Unit

Enumeration, one of:

  • BYTE

  • KB

  • MB

  • GB

Unit for the In Memory Objects field.

### Parser Response Attributes Configures the response attributes for the parser.
FieldTypeDescriptionDefault ValueRequired

Document Parser Name

String

Document parser name.

### Chunk Response Attributes Configures the response attributes for the chunk.
FieldTypeDescriptionDefault ValueRequired

Max Overlap Size In Chars

Number

Maximum overlap size in characters.

Max Segment Size In Chars

Number

Maximum segment size in characters.

### Multiformat Document Parser Parameters Configures the parameters for the multiformat document parser.
FieldTypeDescriptionDefault ValueRequired

Include Metadata

Boolean

Determines whether to include metadata.

false

### Text Document Parser Parameters Configures the parameters for the text document parser.
FieldTypeDescriptionDefault ValueRequired

Document Parser

DocumentParser

Document parser.

Name

String

Document parser name.

## See Also - [MuleSoft Vectors Connector Overview](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/) - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # MuleSoft Vectors Connector 1.1.0 XML and Maven Support > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Although you can manually code a Mule app in XML, it is more efficient to use Anypoint Code Builder or Studio: - If you manually code a Mule runtime engine (Mule) app in XML, either from the Anypoint Code Builder or Studio XML editor, or from a text editor, you can access the connector from your app by adding reference statements to both your XML Mule flow and the Apache Maven `pom.xml` file. - If you add the connector in Anypoint Code Builder or Studio, the XML is automatically populated the code with the connector’s namespace and schema location and it also adds a dependency to the `pom.xml` file. ## Add a Namespace for the Connector Paste the following code inside the `mule` tag of the header of your configuration XML: ```xml http://www.mulesoft.org/schema/mule/ms-vectors http://www.mulesoft.org/schema/mule/ms-vectors/current/mule-ms-vectors.xsd ``` This example shows how the namespace statements are placed in the `` XML block: ```xml ``` ## Add a POM File Dependency The Apache Maven `pom.xml` file generated by Anypoint Studio contains dependencies for a Mule app. If you code a Mule app manually, include this XML snippet in your `pom.xml` file to enable access to this connector: ```xml com.mulesoft.connectors mule4-vectors-connector x.x.x mule-plugin ``` Replace `x.x.x` with the version that corresponds to the connector you are using. To obtain the most up-to-date `pom.xml` file information: 1. Go to [Anypoint Exchange](https://www.mulesoft.com/exchange/). 2. In Exchange, click **Login** and supply your Anypoint Platform username and password. 3. In Exchange, search for `vectors`. 4. Select the connector. 5. Click **Dependency Snippets** near the upper right of the screen. ## See Also - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.0 --- # MuleSoft Vectors Connector Examples > For the full documentation index, see: https://docs.mulesoft.com/llms.txt These examples show you how to use MuleSoft Vectors Connector. ## Example: File This flow listens for HTTP requests on `/store01`, retrieves a file from an Amazon S3 bucket using a provided or default key, and parses its content into text using a text parser. The text is then split into smaller overlapping chunks, converted into embeddings using an embedding model, and stored in a vector store named `loadf02`. ```xml ``` ## Example: PDF This flow listens for HTTP requests on `/store02`, retrieves a PDF from an Amazon S3 bucket using a provided or default key, and parses its content into text using a MultiFormat Document parser. The text is then split into smaller overlapping chunks, converted into embeddings using an embedding model, and stored in a vector store named `loadf02`. ```xml ``` ## See Also - [MuleSoft Vectors - Additional Configuration Information](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-additional-config) - [Using Anypoint Studio to Configure MuleSoft Vectors Connector](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-studio) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-reference) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # MuleSoft Vectors Connector Examples > For the full documentation index, see: https://docs.mulesoft.com/llms.txt These examples show you how to use MuleSoft Vectors Connector. ## Example: File This flow listens for HTTP requests on `/store01`, retrieves a file from an Amazon S3 bucket using a provided or default key, and parses its content into text using a text parser. The text is then split into smaller overlapping chunks, converted into embeddings using an embedding model, and stored in a vector store named `loadf02`. ```xml ``` ## Example: PDF This flow listens for HTTP requests on `/store02`, retrieves a PDF from an Amazon S3 bucket using a provided or default key, and parses its content into text using a MultiFormat Document parser. The text is then split into smaller overlapping chunks, converted into embeddings using an embedding model, and stored in a vector store named `loadf02`. ```xml ``` ## See Also - [MuleSoft Vectors - Additional Configuration Information](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-additional-config) - [Using Anypoint Studio to Configure MuleSoft Vectors Connector](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-studio) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-reference) --- product: MuleSoft Vectors Connector version: 1.0 --- # Using Anypoint Code Builder to Configure MuleSoft Vectors Connector 1.0 > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Cloud IDE (Beta) is scheduled for retirement on August 31, 2026. August 30, 2026 is the last day you can access Cloud IDE (Beta). Download your projects to work from Desktop IDE. Learn more in [Migrate a Project from Cloud IDE to Desktop IDE](https://docs.mulesoft.com/anypoint-code-builder/int-import-mule-project#migrate-cloud-to-desktop). To use Anypoint Code Builder to configure a connector or module, create a basic integration project in Anypoint Code Builder, add connectors and other components to your Mule application to process your business logic, and configure the attributes. ## Before You Begin Before creating an integration project, you must: - [Set up and access the Anypoint Code Builder web or desktop IDE](https://docs.mulesoft.com/anypoint-code-builder/start-acb) - Have credentials to access the connector’s API - Ensure that the Visual Studio Code Extension Pack for Java is installed. To use this connector, you must be familiar with: - The connector’s API - Anypoint Connectors - Mule runtime engine (Mule) ## Create a New Integration Project To create a new integration project: 1. In the activity bar of the IDE, click the ![Anypoint Code Builder icon](/mulesoft/current/en-us/connectors/_images/acb-icon-ms-logo.png) (**Anypoint Code Builder**) icon. 2. From **Quick Actions**, click **Develop an Integration**: ![Develop an Integration link highlighted in the Getting started section](/mulesoft/current/en-us/anypoint-code-builder/_images/develop-integration-option-mat.png) 3. Complete the following in the **Develop an Integration** form:
AttributeValue

Project Name

Unique name for your project.

This name is used as the title and name of the integration project file. For example, if the project name is "Salesforce Integration," the project file name is salesforce-integration.

Project Location

Your home directory or another directory you create. Click Browse to select a different directory for the integration project.

Don’t create the project within another project directory.

4. Select the type of project to create by selecting either the **Empty Project** or **Template or Example** card. 5. Select the **Mule runtime** and **Java Version** for your app. 6. Click **Create Project**. ## Add the Connector to Your Integration Project Anypoint Connectors provide operations for retrieving, modifying, and sending data to and from systems. In addition to the [built-in connectors](https://docs.mulesoft.com/anypoint-code-builder/acb-reference#builtin-connectors) that Anypoint Code Builder provides, you can download many other connectors from Anypoint Exchange. To import a connector from Exchange and add it to your configuration: 1. In the Explorer view, open the configuration XML file for your project, such as `my-project-name.xml`. 2. Click the ![Show Mule graphical mode icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-tree-view.png) (**Show Mule graphical mode**) icon in the activity bar to open the canvas UI if it doesn’t open automatically. 3. Add the connector the same way you added other components from the canvas UI: 1. In the canvas UI, click the ![Add component icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-plus.png) (**Add component**) icon. 2. In the **Add Component** panel, click **Connectors**. 3. Click the connector name and then click the operation to add, such as **Publish**: ![Add Publish operation from Anypoint MQ Connector](/mulesoft/current/en-us/anypoint-code-builder/_images/int-add-connector-operation.png) If the connector is not available locally, click the ![Search in Exchange icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-search-exchange.png) (**Search in Exchange**) toggle: ![Search in Exchange toggle](/mulesoft/current/en-us/anypoint-code-builder/_images/int-connector-search-exchange.png)
1Search locally
2Search in Exchange
4. Select the connector to add to your project. 5. Select the operation from the **Add Component** panel. Adding a connector to an integration project does not make that connector available to other projects in your Anypoint Code Builder workspace. ## Configure the Source For the Flow A trigger (source) starts the flow when specified conditions are met. If a connector has its own associated sources, you can use a connector-specific trigger to initiate the flow. Each connector trigger has a unique configuration. You can configure the following sources for this connector: - **HTTP > Listener** Initiates a flow each time it receives a request on the configured host and port - **Scheduler** Initiates a flow when a time-based condition is met For example, to configure an HTTP Listener trigger, follow these steps: 1. Click the **Listener** component on the canvas UI. 2. (Optional) Click the edit icon to change the name of the **Listener** component. 3. (Optional) If you created a configuration file for the connector, select it. 4. In the **General** tab, in the **Path** field, enter the relative path for the path set in the HTTP configuration element. See [Configure Paths](https://docs.mulesoft.com/http-connector/latest/http-listener-ref#configure-paths). 5. Select the **Advanced** tab to configure the following attributes:
AttributeDescriptionRequired

Allowed methods

To allow all HTTP methods (default), do not define this attribute. To restrict certain methods, specify all allowed HTTP methods, for example, GET, POST, as a comma-separated list.

No

Response streaming mode

Whether to use streaming when the response is sent.

No

Output MIME type

MIME type of the payload that this component outputs.

No

Parameters

Appends a key-value pair for a reader property to the value of the Output MIME attribute. Multiple key-value pairs are allowed.

No

Output encoding

Encoding of the payload that this component outputs.

No

Streaming Strategy

Configures the way data streams are consumed in Mule apps.

No

Primary node only

Select this option to execute the Listener trigger on the primary node only when running in a cluster.

No

Redelivery policy

Configures the redelivery policy for executing requests that generate errors. You can add a redelivery policy to any source in a flow.

No

Reconnection strategy

When an operation in a Mule application fails to connect to an external server, the default behavior is for the operation to fail immediately and return a connectivity error. You can modify the default behavior by configuring the reconnection strategy for the operation.

No

Response

See HTTP Response Attributes.

No

Error Response

HTTP error response returns a status code for the error.

No

Body

Body of the error message.

No

Headers

Headers to include in the error message.

No

Status code

Status code of the error response, for example, 500.

No

Reason phrase

Reason for the error, for example, Gateway Timeout or Internal Server Error.

No

## Add Components to Your Project Add components to your integration project to build a flow: 1. In the **Explorer** view, open the XML file for your project, such as `my-project-name.xml`. 2. Select **Build a Flow** from the start card to create an empty flow: ![Anypoint Code Builder canvas with starting cards with the options to start from scratch, build a flow, or build a subflow](/mulesoft/current/en-us/connectors/_images/acb-build-flow.png) 3. Change the name of the flow: 1. Click **Flow**. 2. Click the edit icon. ![Arrow pointing to the flow name edit pencil icon](/mulesoft/current/en-us/connectors/_images/acb-change-flow-name.png) 3. Enter the flow name, and click the checkmark. 4. In the canvas UI, click the ![Add component icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-plus.png) (**Add component**) icon. 5. In the **Add Component** panel, search for and select your component from the results. The following example shows the **Listener** component from the **HTTP** search results: ![Listener component highlighted in the Add Component section](/mulesoft/current/en-us/anypoint-code-builder/_images/main-tutorial-add-first-listener.png) The configuration XML file now includes the XML for the HTTP Listener into the `` element, for example: ```XML ``` ## Configure the Component Attributes After you add components to your integration project, configure the attributes in the component UI, or configure the attributes directly in the XML code editor. Connector XML tags start with a namespace followed by an operation, following the syntax `namespace:operation`, such as `` for a **Select** operation in Anypoint Connector for Database (Database Connector). You can use autocomplete from an expression (**fx**) field for a component to select DataWeave functions from the Core module and other values accepted in this field. ## Create a New Configuration XML File Anypoint Code Builder creates the initial Mule configuration XML file in `src/main/mule` within the Mule project. This file contains global configurations and flow structures. You can create additional configuration files, for example, to store global configurations. To create a new XML configuration file: 1. In the Explorer view, right-click the **mule** folder (`src/main/mule`) and select **New File**. Alternatively, use the menu. Show me how Select the `mule` folder, and then: - In the desktop IDE, select **File** > **New Mule Configuration File**. - In the cloud IDE, click the ![](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-menu.png) (menu) icon, and select **File** > **New File**. 2. Enter a name for the new file with the `.xml` extension. 3. In the Editor view for the new file, press Ctrl+Space to display available options. 4. Select **Empty mule configuration**: ![New Mule configuration option in auto-correct](/mulesoft/current/en-us/anypoint-code-builder/_images/int-new-mule-config.png) This command adds the following code to the file: ```xml ``` ## Debug the App Debug your Mule application using the embedded debugger in Anypoint Code Builder. See [Debugging Mule Applications](https://docs.mulesoft.com/anypoint-code-builder/int-debug-mule-apps). ## See Also - [Anypoint Code Builder Overview](https://docs.mulesoft.com/anypoint-code-builder/) - [Creating Integrations](https://docs.mulesoft.com/anypoint-code-builder/int-create-integrations) - [Using Anypoint Code Builder to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-acb) - [Anypoint Code Builder Components and Commands Reference](https://docs.mulesoft.com/anypoint-code-builder/acb-reference) - [Defining and Securing Properties for a Mule Application](https://docs.mulesoft.com/anypoint-code-builder/int-create-secure-configs) - [Triggering Flows in Your Development Environment](https://docs.mulesoft.com/anypoint-code-builder/int-trigger-flows) - [Configuring Components](https://docs.mulesoft.com/anypoint-code-builder/int-configure-components) - [Debugging Mule Applications](https://docs.mulesoft.com/anypoint-code-builder/int-debug-mule-apps) - [Salesforce Help](https://help.salesforce.com) - [Deployment Options](https://docs.mulesoft.com/runtime-manager/deployment-strategies) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # Using Anypoint Code Builder to Configure MuleSoft Vectors Connector 1.1 > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Cloud IDE (Beta) is scheduled for retirement on August 31, 2026. August 30, 2026 is the last day you can access Cloud IDE (Beta). Download your projects to work from Desktop IDE. Learn more in [Migrate a Project from Cloud IDE to Desktop IDE](https://docs.mulesoft.com/anypoint-code-builder/int-import-mule-project#migrate-cloud-to-desktop). To use Anypoint Code Builder to configure a connector or module, create a basic integration project in Anypoint Code Builder, add connectors and other components to your Mule application to process your business logic, and configure the attributes. ## Before You Begin Before creating an integration project, you must: - [Set up and access the Anypoint Code Builder web or desktop IDE](https://docs.mulesoft.com/anypoint-code-builder/start-acb) - Have credentials to access the connector’s API - Ensure that the Visual Studio Code Extension Pack for Java is installed. To use this connector, you must be familiar with: - The connector’s API - Anypoint Connectors - Mule runtime engine (Mule) ## Create a New Integration Project To create a new integration project: 1. In the activity bar of the IDE, click the ![Anypoint Code Builder icon](/mulesoft/current/en-us/connectors/_images/acb-icon-ms-logo.png) (**Anypoint Code Builder**) icon. 2. From **Quick Actions**, click **Develop an Integration**: ![Develop an Integration link highlighted in the Getting started section](/mulesoft/current/en-us/anypoint-code-builder/_images/develop-integration-option-mat.png) 3. Complete the following in the **Develop an Integration** form:
AttributeValue

Project Name

Unique name for your project.

This name is used as the title and name of the integration project file. For example, if the project name is "Salesforce Integration," the project file name is salesforce-integration.

Project Location

Your home directory or another directory you create. Click Browse to select a different directory for the integration project.

Don’t create the project within another project directory.

4. Select the type of project to create by selecting either the **Empty Project** or **Template or Example** card. 5. Select the **Mule runtime** and **Java Version** for your app. 6. Click **Create Project**. ## Add the Connector to Your Integration Project Anypoint Connectors provide operations for retrieving, modifying, and sending data to and from systems. In addition to the [built-in connectors](https://docs.mulesoft.com/anypoint-code-builder/acb-reference#builtin-connectors) that Anypoint Code Builder provides, you can download many other connectors from Anypoint Exchange. To import a connector from Exchange and add it to your configuration: 1. In the Explorer view, open the configuration XML file for your project, such as `my-project-name.xml`. 2. Click the ![Show Mule graphical mode icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-tree-view.png) (**Show Mule graphical mode**) icon in the activity bar to open the canvas UI if it doesn’t open automatically. 3. Add the connector the same way you added other components from the canvas UI: 1. In the canvas UI, click the ![Add component icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-plus.png) (**Add component**) icon. 2. In the **Add Component** panel, click **Connectors**. 3. Click the connector name and then click the operation to add, such as **Publish**: ![Add Publish operation from Anypoint MQ Connector](/mulesoft/current/en-us/anypoint-code-builder/_images/int-add-connector-operation.png) If the connector is not available locally, click the ![Search in Exchange icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-search-exchange.png) (**Search in Exchange**) toggle: ![Search in Exchange toggle](/mulesoft/current/en-us/anypoint-code-builder/_images/int-connector-search-exchange.png)
1Search locally
2Search in Exchange
4. Select the connector to add to your project. 5. Select the operation from the **Add Component** panel. Adding a connector to an integration project does not make that connector available to other projects in your Anypoint Code Builder workspace. ## Configure the Source For the Flow A trigger (source) starts the flow when specified conditions are met. If a connector has its own associated sources, you can use a connector-specific trigger to initiate the flow. Each connector trigger has a unique configuration. You can configure the following sources for this connector: - **HTTP > Listener** Initiates a flow each time it receives a request on the configured host and port - **Scheduler** Initiates a flow when a time-based condition is met For example, to configure an HTTP Listener trigger, follow these steps: 1. Click the **Listener** component on the canvas UI. 2. (Optional) Click the edit icon to change the name of the **Listener** component. 3. (Optional) If you created a configuration file for the connector, select it. 4. In the **General** tab, in the **Path** field, enter the relative path for the path set in the HTTP configuration element. See [Configure Paths](https://docs.mulesoft.com/http-connector/latest/http-listener-ref#configure-paths). 5. Select the **Advanced** tab to configure the following attributes:
AttributeDescriptionRequired

Allowed methods

To allow all HTTP methods (default), do not define this attribute. To restrict certain methods, specify all allowed HTTP methods, for example, GET, POST, as a comma-separated list.

No

Response streaming mode

Whether to use streaming when the response is sent.

No

Output MIME type

MIME type of the payload that this component outputs.

No

Parameters

Appends a key-value pair for a reader property to the value of the Output MIME attribute. Multiple key-value pairs are allowed.

No

Output encoding

Encoding of the payload that this component outputs.

No

Streaming Strategy

Configures the way data streams are consumed in Mule apps.

No

Primary node only

Select this option to execute the Listener trigger on the primary node only when running in a cluster.

No

Redelivery policy

Configures the redelivery policy for executing requests that generate errors. You can add a redelivery policy to any source in a flow.

No

Reconnection strategy

When an operation in a Mule application fails to connect to an external server, the default behavior is for the operation to fail immediately and return a connectivity error. You can modify the default behavior by configuring the reconnection strategy for the operation.

No

Response

See HTTP Response Attributes.

No

Error Response

HTTP error response returns a status code for the error.

No

Body

Body of the error message.

No

Headers

Headers to include in the error message.

No

Status code

Status code of the error response, for example, 500.

No

Reason phrase

Reason for the error, for example, Gateway Timeout or Internal Server Error.

No

## Add Components to Your Project Add components to your integration project to build a flow: 1. In the **Explorer** view, open the XML file for your project, such as `my-project-name.xml`. 2. Select **Build a Flow** from the start card to create an empty flow: ![Anypoint Code Builder canvas with starting cards with the options to start from scratch, build a flow, or build a subflow](/mulesoft/current/en-us/connectors/_images/acb-build-flow.png) 3. Change the name of the flow: 1. Click **Flow**. 2. Click the edit icon. ![Arrow pointing to the flow name edit pencil icon](/mulesoft/current/en-us/connectors/_images/acb-change-flow-name.png) 3. Enter the flow name, and click the checkmark. 4. In the canvas UI, click the ![Add component icon](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-plus.png) (**Add component**) icon. 5. In the **Add Component** panel, search for and select your component from the results. The following example shows the **Listener** component from the **HTTP** search results: ![Listener component highlighted in the Add Component section](/mulesoft/current/en-us/anypoint-code-builder/_images/main-tutorial-add-first-listener.png) The configuration XML file now includes the XML for the HTTP Listener into the `` element, for example: ```XML ``` ## Configure the Component Attributes After you add components to your integration project, configure the attributes in the component UI, or configure the attributes directly in the XML code editor. Connector XML tags start with a namespace followed by an operation, following the syntax `namespace:operation`, such as `` for a **Select** operation in Anypoint Connector for Database (Database Connector). You can use autocomplete from an expression (**fx**) field for a component to select DataWeave functions from the Core module and other values accepted in this field. ## Create a New Configuration XML File Anypoint Code Builder creates the initial Mule configuration XML file in `src/main/mule` within the Mule project. This file contains global configurations and flow structures. You can create additional configuration files, for example, to store global configurations. To create a new XML configuration file: 1. In the Explorer view, right-click the **mule** folder (`src/main/mule`) and select **New File**. Alternatively, use the menu. Show me how Select the `mule` folder, and then: - In the desktop IDE, select **File** > **New Mule Configuration File**. - In the cloud IDE, click the ![](/mulesoft/current/en-us/anypoint-code-builder/_images/icon-menu.png) (menu) icon, and select **File** > **New File**. 2. Enter a name for the new file with the `.xml` extension. 3. In the Editor view for the new file, press Ctrl+Space to display available options. 4. Select **Empty mule configuration**: ![New Mule configuration option in auto-correct](/mulesoft/current/en-us/anypoint-code-builder/_images/int-new-mule-config.png) This command adds the following code to the file: ```xml ``` ## Debug the App Debug your Mule application using the embedded debugger in Anypoint Code Builder. See [Debugging Mule Applications](https://docs.mulesoft.com/anypoint-code-builder/int-debug-mule-apps). ## See Also - [Anypoint Code Builder Overview](https://docs.mulesoft.com/anypoint-code-builder/) - [Creating Integrations](https://docs.mulesoft.com/anypoint-code-builder/int-create-integrations) - [Using Anypoint Code Builder to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-acb) - [Anypoint Code Builder Components and Commands Reference](https://docs.mulesoft.com/anypoint-code-builder/acb-reference) - [Defining and Securing Properties for a Mule Application](https://docs.mulesoft.com/anypoint-code-builder/int-create-secure-configs) - [Triggering Flows in Your Development Environment](https://docs.mulesoft.com/anypoint-code-builder/int-trigger-flows) - [Configuring Components](https://docs.mulesoft.com/anypoint-code-builder/int-configure-components) - [Debugging Mule Applications](https://docs.mulesoft.com/anypoint-code-builder/int-debug-mule-apps) - [Salesforce Help](https://help.salesforce.com) - [Deployment Options](https://docs.mulesoft.com/runtime-manager/deployment-strategies) --- product: MuleSoft Vectors Connector version: 1.0 --- # Using Anypoint Studio to Configure MuleSoft Vectors Connector 1.0 > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Anypoint Studio (Studio) editors help you design and update your Mule applications, properties, and configuration files. To add and configure a connector in Studio: 1. [Create a Mule project](#create-mule-project). 2. [Add the connector to your Mule project](#add-connector-to-project). 3. [Configure shared libraries](#configure-shared-libraries). 4. [Configure a source for the connector’s flow](#configure-source). 5. [Add a connector operation to the flow](#add-connector-operation). 6. [Configure a global element for the connector](#configure-global-element). 7. [Configure the other connector fields](#configure-other-fields). When you run the connector, you can view the app log to check for problems in real time, as described in [View the App Log](#view-app-log). If you are new to configuring connectors in Studio, see [Using Anypoint Studio to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-studio). If, after reading this topic, you need additional information about the connector fields, see the [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-reference). ## Create a Mule Project In Studio, create a new Mule project in which to add and configure Anypoint Connector for MuleSoft Vectors (MuleSoft Vectors Connector): 1. In Studio, select **File > New > Mule Project**. 2. Enter a name for your Mule project and click **Finish**. ## Add the Connector to Your Mule Project Add MuleSoft Vectors Connector to your Mule project to automatically populate the XML code with the connector’s namespace and schema location and add the required dependencies to the project’s `pom.xml` file: 1. In **Mule Palette**, click **(X) Search in Exchange**. 2. In **Add Dependencies to Project**, type `mulesoft vectors` in the search field. 3. Click **MuleSoft Vectors Connector** in **Available modules**. 4. Click **Add**. 5. Click **Finish**. Adding a connector to a Mule project in Studio does not make that connector available to other projects in your Studio workspace. ## Configure Shared Libraries To reduce the overall size of the connector and avoid adding dependencies that are not required, all the optional libraries are removed from the connector and only the required ones can be added depending on the specific use case. You can use the Mule Maven plugin to add the required dependencies to the project’s `pom.xml` file. For more information about how to configure shared libraries, see [Configure Shared Libraries](https://docs.mulesoft.com/mule-runtime/latest/mmp-concept#configure-shared-libraries). ### Embedding Models #### Configuration ```xml ... dev.langchain4j langchain4j-core ... ... dev.langchain4j langchain4j-core 1.0.1 ... ... ``` ### Vector Stores #### Connections - Azure AI Search - AlloyDB - Chroma - Elasticsearch - Milvus - Amazon OpenSearch - PGVector - Pinecone - Qdrant - Weaviate - MongoDB Atlas - Ephemeral File ```xml ... dev.langchain4j langchain4j-azure-ai-search ... ... dev.langchain4j langchain4j-azure-ai-search 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-community-alloydb-pg ... ... dev.langchain4j langchain4j-community-alloydb-pg 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-chroma ... ... dev.langchain4j langchain4j-chroma 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-elasticsearch ... ... dev.langchain4j langchain4j-elasticsearch 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-milvus ... ... dev.langchain4j langchain4j-milvus 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-opensearch ... ... dev.langchain4j langchain4j-opensearch 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-pgvector ... ... dev.langchain4j langchain4j-pgvector 1.0.1-beta6 ... ... ``` > [!NOTE] You can’t use Pinecone with Milvus or Qdrant. ```xml ... dev.langchain4j langchain4j-pinecone ... ... dev.langchain4j langchain4j-pinecone 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-qdrant io.grpc grpc-netty-shaded ... ... dev.langchain4j langchain4j-qdrant 1.0.1-beta6 io.grpc grpc-netty-shaded 1.65.1 ... ... ``` ```xml ... dev.langchain4j langchain4j-weaviate ... ... dev.langchain4j langchain4j-weaviate 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-mongodb-atlas ... ... dev.langchain4j langchain4j-mongodb-atlas 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j ... ... dev.langchain4j langchain4j 1.0.1 ... ... ``` ## Configure a Source A source initiates a flow when a specified condition is met. You can configure one of these sources to use with MuleSoft Vectors Connector: - **HTTP > Listener** Initiates a flow each time it receives a request on the configured host and port - **Scheduler** Initiates a flow when a time-based condition is met For example, to configure an **HTTP > Listener** source, follow these steps: 1. In **Mule Palette**, select **HTTP > Listener**. 2. Drag **Listener** to the Studio canvas. 3. On the **Listener** configuration screen, optionally change the value of the **Display Name** field. 4. Specify a value for the **Path** field. 5. Click the plus sign (**+**) next to the **Connector configuration** field to configure a global element that can be used by all instances of the **HTTP > Listener** source in the app. 6. On the **General** tab, specify the connection information for the connector. 7. On the **TLS** tab, optionally specify the TLS information for the connector. 8. On the **Advanced** tab, optionally specify reconnection information, including a reconnection strategy. 9. Click **Test Connection** to confirm that Mule can connect with the specified server. 10. Click **OK**. ## Add a Connector Operation to the Flow When you add a connector operation to your flow, you are specifying an action for that connector to perform. To add an operation for MuleSoft Vectors Connector, follow these steps: 1. In **Mule Palette**, select **MuleSoft Vectors Connector** and then select the operation to add. 2. Drag the operation onto the Studio canvas, next to the source. ## Configure a Global Element for the Connector When you configure a connector, configure a global element that all instances of that connector in the app can use. Configuring a global element requires you to provide the authentication credentials that the connector requires to access the target vector stores and embedding providers. You can reference a configuration file that contains ANT-style property placeholders (recommended), or you can enter your authorization credentials in the global configuration properties. For information about the benefits of using property placeholders and how to configure them, see [Anypoint Connector Configuration](https://docs.mulesoft.com/connectors/introduction/intro-connector-configuration-overview). To configure the global element for MuleSoft Vectors Connector, follow these steps. 1. Select the operation in the Studio canvas. 2. On the properties screen for the operation, click the Add (**+**) icon to access the global element configuration fields. 3. Choose from these configs. - Embedding Config - Store Config - Transform Config 4. Fill out the fields depending on the operation type. 5. Click **OK**. ## Configure Additional Connector Fields After you configure a global element for the connector, configure the other required fields. The required fields vary depending on which connector operation you use. For detailed configuration information for each operation type, see [MuleSoft Vectors - Additional Configuration Information](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-additional-config). ## View the App Log To check for problems, you can view the app log as follows: - If you’re running the app from Anypoint Platform, the app log output is visible on the Anypoint Studio console window. - If you’re running the app using Mule from the command line, the app log output is visible in your operating system console. Unless the log file path is customized in the app’s log file (`log4j2.xml`), you can also view the app log in the default location `MULE_HOME/logs/.log`. You can configure the location of the log path in the app log file `log4j2.xml`. ## See Also - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Using Studio to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-studio) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/1.0/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com) --- product: MuleSoft Vectors Connector version: 1.1 is-latest-version: true --- # Using Anypoint Studio to Configure MuleSoft Vectors Connector 1.1 > For the full documentation index, see: https://docs.mulesoft.com/llms.txt Anypoint Studio (Studio) editors help you design and update your Mule applications, properties, and configuration files. To add and configure a connector in Studio: 1. [Create a Mule project](#create-mule-project). 2. [Add the connector to your Mule project](#add-connector-to-project). 3. [Configure shared libraries](#configure-shared-libraries). 4. [Configure a source for the connector’s flow](#configure-source). 5. [Add a connector operation to the flow](#add-connector-operation). 6. [Configure a global element for the connector](#configure-global-element). 7. [Configure the other connector fields](#configure-other-fields). When you run the connector, you can view the app log to check for problems in real time, as described in [View the App Log](#view-app-log). If you are new to configuring connectors in Studio, see [Using Anypoint Studio to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-studio). If, after reading this topic, you need additional information about the connector fields, see the [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-reference). ## Create a Mule Project In Studio, create a new Mule project in which to add and configure Anypoint Connector for MuleSoft Vectors (MuleSoft Vectors Connector): 1. In Studio, select **File > New > Mule Project**. 2. Enter a name for your Mule project and click **Finish**. ## Add the Connector to Your Mule Project Add MuleSoft Vectors Connector to your Mule project to automatically populate the XML code with the connector’s namespace and schema location and add the required dependencies to the project’s `pom.xml` file: 1. In **Mule Palette**, click **(X) Search in Exchange**. 2. In **Add Dependencies to Project**, type `mulesoft vectors` in the search field. 3. Click **MuleSoft Vectors Connector** in **Available modules**. 4. Click **Add**. 5. Click **Finish**. Adding a connector to a Mule project in Studio does not make that connector available to other projects in your Studio workspace. ## Configure Shared Libraries To reduce the overall size of the connector and avoid adding dependencies that are not required, all the optional libraries are removed from the connector and only the required ones can be added depending on the specific use case. You can use the Mule Maven plugin to add the required dependencies to the project’s `pom.xml` file. For more information about how to configure shared libraries, see [Configure Shared Libraries](https://docs.mulesoft.com/mule-runtime/latest/mmp-concept#configure-shared-libraries). ### Embedding Models #### Configuration ```xml ... dev.langchain4j langchain4j-core ... ... dev.langchain4j langchain4j-core 1.0.1 ... ... ``` ### Vector Stores #### Connections - Azure AI Search - AlloyDB - Chroma - Elasticsearch - Milvus - Amazon OpenSearch - PGVector - Pinecone - Qdrant - Weaviate - MongoDB Atlas - Ephemeral File ```xml ... dev.langchain4j langchain4j-azure-ai-search ... ... dev.langchain4j langchain4j-azure-ai-search 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-community-alloydb-pg ... ... dev.langchain4j langchain4j-community-alloydb-pg 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-chroma ... ... dev.langchain4j langchain4j-chroma 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-elasticsearch ... ... dev.langchain4j langchain4j-elasticsearch 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-milvus ... ... dev.langchain4j langchain4j-milvus 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-opensearch ... ... dev.langchain4j langchain4j-opensearch 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-pgvector ... ... dev.langchain4j langchain4j-pgvector 1.0.1-beta6 ... ... ``` > [!NOTE] You can’t use Pinecone with Milvus or Qdrant. ```xml ... dev.langchain4j langchain4j-pinecone ... ... dev.langchain4j langchain4j-pinecone 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-qdrant io.grpc grpc-netty-shaded ... ... dev.langchain4j langchain4j-qdrant 1.0.1-beta6 io.grpc grpc-netty-shaded 1.65.1 ... ... ``` ```xml ... dev.langchain4j langchain4j-weaviate ... ... dev.langchain4j langchain4j-weaviate 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j-mongodb-atlas ... ... dev.langchain4j langchain4j-mongodb-atlas 1.0.1-beta6 ... ... ``` ```xml ... dev.langchain4j langchain4j ... ... dev.langchain4j langchain4j 1.0.1 ... ... ``` ## Configure a Source A source initiates a flow when a specified condition is met. You can configure one of these sources to use with MuleSoft Vectors Connector: - **HTTP > Listener** Initiates a flow each time it receives a request on the configured host and port - **Scheduler** Initiates a flow when a time-based condition is met For example, to configure an **HTTP > Listener** source, follow these steps: 1. In **Mule Palette**, select **HTTP > Listener**. 2. Drag **Listener** to the Studio canvas. 3. On the **Listener** configuration screen, optionally change the value of the **Display Name** field. 4. Specify a value for the **Path** field. 5. Click the plus sign (**+**) next to the **Connector configuration** field to configure a global element that can be used by all instances of the **HTTP > Listener** source in the app. 6. On the **General** tab, specify the connection information for the connector. 7. On the **TLS** tab, optionally specify the TLS information for the connector. 8. On the **Advanced** tab, optionally specify reconnection information, including a reconnection strategy. 9. Click **Test Connection** to confirm that Mule can connect with the specified server. 10. Click **OK**. ## Add a Connector Operation to the Flow When you add a connector operation to your flow, you are specifying an action for that connector to perform. To add an operation for MuleSoft Vectors Connector, follow these steps: 1. In **Mule Palette**, select **MuleSoft Vectors Connector** and then select the operation to add. 2. Drag the operation onto the Studio canvas, next to the source. ## Configure a Global Element for the Connector When you configure a connector, configure a global element that all instances of that connector in the app can use. Configuring a global element requires you to provide the authentication credentials that the connector requires to access the target vector stores and embedding providers. You can reference a configuration file that contains ANT-style property placeholders (recommended), or you can enter your authorization credentials in the global configuration properties. For information about the benefits of using property placeholders and how to configure them, see [Anypoint Connector Configuration](https://docs.mulesoft.com/connectors/introduction/intro-connector-configuration-overview). To configure the global element for MuleSoft Vectors Connector, follow these steps. 1. Select the operation in the Studio canvas. 2. On the properties screen for the operation, click the Add (**+**) icon to access the global element configuration fields. 3. Choose from these configs. - Embedding Config - Store Config - Transform Config 4. Fill out the fields depending on the operation type. 5. Click **OK**. ## Configure Additional Connector Fields After you configure a global element for the connector, configure the other required fields. The required fields vary depending on which connector operation you use. For detailed configuration information for each operation type, see [MuleSoft Vectors - Additional Configuration Information](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-additional-config). ## View the App Log To check for problems, you can view the app log as follows: - If you’re running the app from Anypoint Platform, the app log output is visible on the Anypoint Studio console window. - If you’re running the app using Mule from the command line, the app log output is visible in your operating system console. Unless the log file path is customized in the app’s log file (`log4j2.xml`), you can also view the app log in the default location `MULE_HOME/logs/.log`. You can configure the location of the log path in the app log file `log4j2.xml`. ## See Also - [Introduction to Anypoint Connectors](https://docs.mulesoft.com/connectors/introduction/introduction-to-anypoint-connectors) - [Using Studio to Configure a Connector](https://docs.mulesoft.com/connectors/introduction/intro-config-use-studio) - [MuleSoft Vectors Connector Reference](https://docs.mulesoft.com/mulesoft-vectors-connector/latest/mulesoft-vectors-connector-reference) - [Salesforce Help](https://help.salesforce.com)