Code interpreter for developers

/// <summary>
/// Retrieves AI models from Dataverse that match the specified model name pattern.
/// </summary>
/// <param name="service">The IOrganizationService instance used to connect to Dataverse</param>
/// <param name="modelName">The model name prefix to search for (uses BeginsWith matching)</param>
/// <remarks>
/// This method queries the msdyn_aimodel table using a BeginsWith condition, which means it will find
/// models whose names start with the specified modelName string. The search is case-insensitive.
/// If no matching models are found, a message is displayed to the console.
/// </remarks>
/// <example>
/// <code>
/// RetrieveAIModelsExample(service, "GPT");
/// // This will find all AI models whose names start with "GPT"
/// </code>
/// </example>
static void RetrieveAIModelsExample(IOrganizationService service, string modelName)
{
    var query = new QueryExpression("msdyn_aimodel")
    {
        ColumnSet = new ColumnSet("msdyn_name", "msdyn_aimodelid"),
        Criteria = new FilterExpression(LogicalOperator.And)
        {
            Conditions = {
                new ConditionExpression(
                    attributeName:"msdyn_name",
                    conditionOperator: ConditionOperator.BeginsWith,
                    value: modelName
                 )
            }
        }
    };

    var results = service.RetrieveMultiple(query);

    if (results.Entities.Any())
    {
        foreach (var entity in results.Entities)
        {
            Console.WriteLine($"Model Name: {entity["msdyn_name"]}, ID: {entity["msdyn_aimodelid"]}");
        }
    }
    else
    {
        Console.WriteLine($"No model with a name starting with '{modelName}' was found.");
    }
}

Learn how to query data using QueryExpression

This example will retrieve all AI model records with a name starting with 'example'.

Request:

GET [Organization URI]/api/data/v9.2/msdyn_aimodels?$select=msdyn_name&$filter=startswith(msdyn_name, 'example')
Accept: application/json  
OData-MaxVersion: 4.0  
OData-Version: 4.0

Response:

HTTP/1.1 200 OK  
Content-Type: application/json; odata.metadata=minimal  
OData-Version: 4.0  

{
 "@odata.context": "[Organization URI]/api/data/v9.2/$metadata#msdyn_aimodels(msdyn_name)",
 "value": [
  {
   "@odata.etag": "W/\"9275465\"",
   "msdyn_aimodelid": "b412c9a3-1b4f-45c4-956d-33bd4412be33",
   "msdyn_name": "Example Sales Proposal document"
  },
  {
   "@odata.etag": "W/\"9259792\"",
   "msdyn_aimodelid": "6ed18606-78da-4903-a868-73c7b462b336",
   "msdyn_name": "Example Interactive Row Summary Chart"
  }
 ]
}

Learn how to use OData to query data

With the SDK for .NET, use the Entity class and set the Attributes collection with the values. The key difference in this scenario is that the Entity instance doesn't have a LogicalName set, so it doesn't refer to a specific Dataverse table.

The following PredictActionExample sample method uses the OrganizationRequest class to use the Predict message as described in Use messages with the SDK for .NET. Alternatively, you can generate a pair of typed PredictRequest and PredictResponse classes. Learn how to generate early-bound classes for the SDK for .NET

This example also shows how to set the Target parameter with an EntityReference that refers to the msdyn_AIModel record using the ID.

static PredictActionExample (IOrganizationService service, Guid yourAiModelId)
{
 // Create the nested 'patient' entity
 var patientEntity = new Entity
 {
     Attributes =
     {
         { "firstname", "John" },
         { "lastname", "Smith" }
     }
 };
 
 // Create the main 'requestv2' entity
 var requestV2Entity = new Entity
 {
     Attributes =
     {
         { "pai_sex", 1 },
         { "pai_age", 10 },
         { "patient", patientEntity }
     }
 };
 
 // Create the Predict action request
 var predictRequest = new OrganizationRequest("Predict")
 {
     Parameters = new ParameterCollection
     {
         { "version", "2.0" },
         { "requestv2", requestV2Entity },
         { "Target", new EntityReference("msdyn_aimodel", new Guid(yourAiModelId)) }
     }
 };
 
 // Execute the request
 var response = service.Execute(predictRequest);
 
 Console.WriteLine("Prediction Result:");
 Console.WriteLine(response.Results);
}

The Predict Action is bound to the msdyn_aimodel entity type. When you use actions bound to a table, you pass the reference in the URL and invoke the action using the fully qualified name: Microsoft.Dynamics.CRM.Predict.

As explained in Use Entity as a dictionary, set the requestv2 property with a dictionary that includes an @odata.type property set to "Microsoft.Dynamics.CRM.expando". This indicates the value is an open type.

Notice how this example uses nested dictionaries.

Request:

POST msdyn_aimodels(<AI Model ID>)/Microsoft.Dynamics.CRM.Predict
Accept: application/json  
OData-MaxVersion: 4.0  
OData-Version: 4.0

{
    "version": "2.0",
    "requestv2": {
        "@odata.type": "#Microsoft.Dynamics.CRM.expando",
        "pai_sex": 1,
        "pai_age": 10,
        "patient": {
            "@odata.type": "#Microsoft.Dynamics.CRM.expando",
            "firstname": "John",
            "lastname": "Smith"
        }
    }
}

Response:

HTTP/1.1 200 OK  
Content-Type: application/json; odata.metadata=minimal  
OData-Version: 4.0  

{
    "@odata.context": "[Organization URI]/api/data/v9.2/$metadata#Microsoft.Dynamics.CRM.PredictResponse",
    "response": null,
    "overrideHttpStatusCode": null,
    "overrideLocation": null,
    "overrideRetryAfter": null,
    "responsev2": {
        "@odata.type": "#Microsoft.Dynamics.CRM.expando",
        "operationStatus": "Success",
        "predictionOutput": {
            "@odata.type": "#Microsoft.Dynamics.CRM.expando",
            "text":"<content returned from code execution>",
            "mimetype":"text/markdown",
            "textMimeType":"text/markdown",
            "finishReason":"stop",
            "code":"<Python code that was executed to generate the content>",
            "signature":"<a Base64‑encoded, versioned metadata and integrity token >",
            "logs": "<Output of the steps executed by the python code>"
            "codeThinking":{
                "@odata.type": "#Microsoft.Dynamics.CRM.expando"
            },
            "files@odata.type": "#Collection(Microsoft.Dynamics.CRM.crmbaseentity)",
            "files": [
                {
                    "@odata.type": "#Microsoft.Dynamics.CRM.expando",
                    "base64_content": "[Example_Document.pdf base64 content]",
                    "content_type": "application/pdf",
                    "file_name": "Example_Document.pdf"
                }
            ],
            "structuredOutput": {
                "@odata.type": "#Microsoft.Dynamics.CRM.expando",
                "mimetype": "text/markdown",
                "text": "# Example Document\n\nExample document for Example record Example 2.\n\n[Download the PDF document here](Example_Document.pdf)"
            },
            "artifacts":{
                "@odata.type": "#Microsoft.Dynamics.CRM.expando",
                "Example_Document": {
                    "@odata.type": "#Microsoft.Dynamics.CRM.expando",
                    "artifactName": "Example_Document.pdf",
                    "mimeType": "application/pdf",
                    "base64Content": "[Example_Document.pdf base64 content]"
        }
      }
    }
  }
}