Neum (Independent Publisher) (Preview)
With Neum AI, your context in prompts is always accurate and up to date. It enables you to create a pipeline that keeps your data synced between a source (ex. Document DB) and a sink (ex. Pinecone).
This connector is available in the following products and regions:
Service | Class | Regions |
---|---|---|
Logic Apps | Standard | All Logic Apps regions except the following: - Azure Government regions - Azure China regions - US Department of Defense (DoD) |
Power Automate | Premium | All Power Automate regions except the following: - US Government (GCC) - US Government (GCC High) - China Cloud operated by 21Vianet - US Department of Defense (DoD) |
Power Apps | Premium | All Power Apps regions except the following: - US Government (GCC) - US Government (GCC High) - China Cloud operated by 21Vianet - US Department of Defense (DoD) |
Contact | |
---|---|
Name | Troy Taylor |
URL | https://www.hitachisolutions.com |
ttaylor@hitachisolutions.com |
Connector Metadata | |
---|---|
Publisher | Troy Taylor |
Website | https://www.neum.ai/ |
Privacy policy | https://www.neum.ai/ |
Categories | AI |
The connector supports the following authentication types:
Default | Parameters for creating connection. | All regions | Not shareable |
Applicable: All regions
Parameters for creating connection.
This is not shareable connection. If the power app is shared with another user, another user will be prompted to create new connection explicitly.
Name | Type | Description | Required |
---|---|---|---|
API Key | securestring | The API Key for this api | True |
Name | Calls | Renewal Period |
---|---|---|
API calls per connection | 100 | 60 seconds |
Create a pipeline |
Creates a pipeline with an optional scheduled trigger. |
Test pipeline |
To test your new pipeline, Neum AI provides capabilities to quickly query the vector store that data is being pushed into. You can observe general information like the number of vectors in it as well as do quick queries using a provided text. |
Creates a pipeline with an optional scheduled trigger.
Parameters
Name | Key | Required | Type | Description |
---|---|---|---|---|
Source
|
source_name | True | string |
The source name. |
Connection String
|
connection_string | True | string |
The connection string. |
Container
|
container_name | True | string |
The container name. |
Name
|
embed_name | True | string |
The embed name. |
API Key
|
api_key | True | string |
The API key. |
Organization
|
organization | True | string |
The organization. |
Sink Name
|
sink_name | True | string |
The sink name. |
API Key
|
api_key | True | string |
The API key. |
Environment
|
environment | True | string |
The environment. |
Index
|
index | True | string |
The index. |
Namespace
|
namespace | True | string |
The namespace. |
Start Date
|
start_date | string |
The start date. |
|
Cadence
|
cadence | string |
The cadence. |
Returns
Name | Path | Type | Description |
---|---|---|---|
ID
|
id | string |
The identifier. |
Name
|
source.source_name | string |
The source name. |
Name
|
sink.sink_name | string |
The sink name. |
Name
|
embed.embed_name | string |
The embed name. |
Created
|
created | float |
When created. |
Start Date
|
trigger_schedule.start_date | string |
The start date. |
Cadence
|
trigger_schedule.cadence | string |
The cadence. |
To test your new pipeline, Neum AI provides capabilities to quickly query the vector store that data is being pushed into. You can observe general information like the number of vectors in it as well as do quick queries using a provided text.
Parameters
Name | Key | Required | Type | Description |
---|---|---|---|---|
Pipeline ID
|
pipeline_id | True | string |
The pipeline identifier. |
Query
|
query | True | string |
The query. |
Number Of Results
|
number_of_results | True | integer |
The number of results. |
Returns
Name | Path | Type | Description |
---|---|---|---|
Results
|
results | array of string |
The results. |