feat: Add ai_agent info to AiResponse (box/box-openapi#485) (#402)

.codegen.json

@@ -1 +1 @@
-{ "engineHash": "f073ce3", "specHash": "544d370", "version": "1.8.0" }
+{ "engineHash": "a839036", "specHash": "d7dfe68", "version": "1.8.0" }

box_sdk_gen/managers/ai.py

@@ -373,7 +373,10 @@ def create_ai_extract(
         """
         Sends an AI request to supported Large Language Models (LLMs) and extracts metadata in form of key-value pairs.
 
-        Freeform metadata extraction does not require any metadata template setup before sending the request.
+        In this request, both the prompt and the output can be freeform.
+
+
+        Metadata template setup before sending the request is not required.
 
         :param prompt: The prompt provided to a Large Language Model (LLM) in the request. The prompt can be up to 10000 characters long and it can be an XML or a JSON schema.
         :type prompt: str
@@ -414,7 +417,10 @@ def create_ai_extract_structured(
         """
                 Sends an AI request to supported Large Language Models (LLMs) and returns extracted metadata as a set of key-value pairs.
 
-                For this request, you need to use an already defined metadata template or a define a schema yourself.
+                For this request, you either need a metadata template or a list of fields you want to extract.
+
+
+                Input is **either** a metadata template or a list of fields to ensure the structure.
 
 
                 To learn more about creating templates, see [Creating metadata templates in the Admin Console](https://support.box.com/hc/en-us/articles/360044194033-Customizing-Metadata-Templates)

box_sdk_gen/schemas/__init__.py

@@ -1,5 +1,11 @@
+from box_sdk_gen.schemas.ai_agent_info import *
+
+from box_sdk_gen.schemas.ai_response import *
+
 from box_sdk_gen.schemas.ai_citation import *
 
+from box_sdk_gen.schemas.ai_response_full import *
+
 from box_sdk_gen.schemas.ai_dialogue_history import *
 
 from box_sdk_gen.schemas.ai_extract_response import *
@@ -40,10 +46,6 @@
 
 from box_sdk_gen.schemas.ai_ask import *
 
-from box_sdk_gen.schemas.ai_response import *
-
-from box_sdk_gen.schemas.ai_response_full import *
-
 from box_sdk_gen.schemas.app_item import *
 
 from box_sdk_gen.schemas.classification import *

box_sdk_gen/schemas/ai_agent_info.py

@@ -0,0 +1,49 @@
+from typing import Optional
+
+from box_sdk_gen.internal.base_object import BaseObject
+
+from typing import List
+
+from box_sdk_gen.box.errors import BoxSDKError
+
+
+class AiAgentInfoModelsField(BaseObject):
+    def __init__(
+        self,
+        *,
+        name: Optional[str] = None,
+        provider: Optional[str] = None,
+        supported_purpose: Optional[str] = None,
+        **kwargs
+    ):
+        """
+        :param name: The name of the model used for the request, defaults to None
+        :type name: Optional[str], optional
+        :param provider: The provider that owns the model used for the request, defaults to None
+        :type provider: Optional[str], optional
+        :param supported_purpose: The supported purpose utilized by the model used for the request, defaults to None
+        :type supported_purpose: Optional[str], optional
+        """
+        super().__init__(**kwargs)
+        self.name = name
+        self.provider = provider
+        self.supported_purpose = supported_purpose
+
+
+class AiAgentInfo(BaseObject):
+    def __init__(
+        self,
+        *,
+        models: Optional[List[AiAgentInfoModelsField]] = None,
+        processor: Optional[str] = None,
+        **kwargs
+    ):
+        """
+        :param models: The models used for the request, defaults to None
+        :type models: Optional[List[AiAgentInfoModelsField]], optional
+        :param processor: The processor used for the request, defaults to None
+        :type processor: Optional[str], optional
+        """
+        super().__init__(**kwargs)
+        self.models = models
+        self.processor = processor

box_sdk_gen/schemas/ai_response.py

@@ -2,6 +2,8 @@
 
 from box_sdk_gen.internal.base_object import BaseObject
 
+from box_sdk_gen.schemas.ai_agent_info import AiAgentInfo
+
 from box_sdk_gen.box.errors import BoxSDKError
 
 from box_sdk_gen.internal.utils import DateTime
@@ -14,6 +16,7 @@ def __init__(
         created_at: DateTime,
         *,
         completion_reason: Optional[str] = None,
+        ai_agent_info: Optional[AiAgentInfo] = None,
         **kwargs
     ):
         """
@@ -28,3 +31,4 @@ def __init__(
         self.answer = answer
         self.created_at = created_at
         self.completion_reason = completion_reason
+        self.ai_agent_info = ai_agent_info

box_sdk_gen/schemas/ai_response_full.py

@@ -4,6 +4,8 @@
 
 from box_sdk_gen.internal.utils import DateTime
 
+from box_sdk_gen.schemas.ai_agent_info import AiAgentInfo
+
 from box_sdk_gen.schemas.ai_response import AiResponse
 
 from box_sdk_gen.schemas.ai_citation import AiCitation
@@ -19,6 +21,7 @@ def __init__(
         *,
         citations: Optional[List[AiCitation]] = None,
         completion_reason: Optional[str] = None,
+        ai_agent_info: Optional[AiAgentInfo] = None,
         **kwargs
     ):
         """
@@ -35,6 +38,7 @@ def __init__(
             answer=answer,
             created_at=created_at,
             completion_reason=completion_reason,
+            ai_agent_info=ai_agent_info,
             **kwargs
         )
         self.citations = citations

docs/ai.md

@@ -159,7 +159,8 @@ This response can be one of the following four objects:
 ## Extract metadata (freeform)
 
 Sends an AI request to supported Large Language Models (LLMs) and extracts metadata in form of key-value pairs.
-Freeform metadata extraction does not require any metadata template setup before sending the request.
+In this request, both the prompt and the output can be freeform.
+Metadata template setup before sending the request is not required.
 
 This operation is performed by calling function `create_ai_extract`.
 
@@ -196,7 +197,8 @@ A response including the answer from the LLM.
 ## Extract metadata (structured)
 
 Sends an AI request to supported Large Language Models (LLMs) and returns extracted metadata as a set of key-value pairs.
-For this request, you need to use an already defined metadata template or a define a schema yourself.
+For this request, you either need a metadata template or a list of fields you want to extract.
+Input is **either** a metadata template or a list of fields to ensure the structure.
 To learn more about creating templates, see [Creating metadata templates in the Admin Console](https://support.box.com/hc/en-us/articles/360044194033-Customizing-Metadata-Templates)
 or use the [metadata template API](g://metadata/templates/create).