feat: parametrise chunked uploads endpoint urls (box/box-openapi#444)

.codegen.json

@@ -1 +1 @@
-{ "engineHash": "ab2fc63", "specHash": "871a814", "version": "1.2.0" }
+{ "engineHash": "d1cb68d", "specHash": "9919482", "version": "1.2.0" }

box_sdk_gen/managers/ai.py

@@ -16,16 +16,14 @@
 
 from typing import Union
 
-from box_sdk_gen.schemas.ai_dialogue_history import AiDialogueHistory
+from box_sdk_gen.internal.utils import DateTime
 
-from box_sdk_gen.schemas.ai_ask_response import AiAskResponse
+from box_sdk_gen.schemas.ai_response import AiResponse
 
 from box_sdk_gen.schemas.client_error import ClientError
 
 from box_sdk_gen.schemas.ai_ask import AiAsk
 
-from box_sdk_gen.schemas.ai_response import AiResponse
-
 from box_sdk_gen.schemas.ai_text_gen import AiTextGen
 
 from box_sdk_gen.schemas.ai_agent_ask import AiAgentAsk
@@ -116,6 +114,29 @@ def __init__(
         self.content = content
 
 
+class CreateAiTextGenDialogueHistory(BaseObject):
+    def __init__(
+        self,
+        *,
+        prompt: Optional[str] = None,
+        answer: Optional[str] = None,
+        created_at: Optional[DateTime] = None,
+        **kwargs
+    ):
+        """
+        :param prompt: The prompt previously provided by the client and answered by the LLM., defaults to None
+        :type prompt: Optional[str], optional
+        :param answer: The answer previously provided by the LLM., defaults to None
+        :type answer: Optional[str], optional
+        :param created_at: The ISO date formatted timestamp of when the previous answer to the prompt was created., defaults to None
+        :type created_at: Optional[DateTime], optional
+        """
+        super().__init__(**kwargs)
+        self.prompt = prompt
+        self.answer = answer
+        self.created_at = created_at
+
+
 class GetAiAgentDefaultConfigMode(str, Enum):
     ASK = 'ask'
     TEXT_GEN = 'text_gen'
@@ -139,11 +160,9 @@ def create_ai_ask(
         prompt: str,
         items: List[CreateAiAskItems],
         *,
-        dialogue_history: Optional[List[AiDialogueHistory]] = None,
-        include_citations: Optional[bool] = None,
         ai_agent: Optional[AiAgentAsk] = None,
         extra_headers: Optional[Dict[str, Optional[str]]] = None
-    ) -> AiAskResponse:
+    ) -> AiResponse:
         """
                 Sends an AI request to supported LLMs and returns an answer specifically focused on the user's question given the provided context.
                 :param mode: The mode specifies if this request is for a single or multiple items. If you select `single_item_qa` the `items` array can have one element only. Selecting `multiple_item_qa` allows you to provide up to 25 items.
@@ -156,10 +175,6 @@ def create_ai_ask(
         If the file size exceeds 1MB, the first 1MB of text representation will be processed.
         If you set `mode` parameter to `single_item_qa`, the `items` array can have one element only.
                 :type items: List[CreateAiAskItems]
-                :param dialogue_history: The history of prompts and answers previously passed to the LLM. This provides additional context to the LLM in generating the response., defaults to None
-                :type dialogue_history: Optional[List[AiDialogueHistory]], optional
-                :param include_citations: A flag to indicate whether citations should be returned., defaults to None
-                :type include_citations: Optional[bool], optional
                 :param extra_headers: Extra headers that will be included in the HTTP request., defaults to None
                 :type extra_headers: Optional[Dict[str, Optional[str]]], optional
         """
@@ -169,8 +184,6 @@ def create_ai_ask(
             'mode': mode,
             'prompt': prompt,
             'items': items,
-            'dialogue_history': dialogue_history,
-            'include_citations': include_citations,
             'ai_agent': ai_agent,
         }
         headers_map: Dict[str, str] = prepare_params({**extra_headers})
@@ -186,14 +199,14 @@ def create_ai_ask(
                 network_session=self.network_session,
             ),
         )
-        return deserialize(response.data, AiAskResponse)
+        return deserialize(response.data, AiResponse)
 
     def create_ai_text_gen(
         self,
         prompt: str,
         items: List[CreateAiTextGenItems],
         *,
-        dialogue_history: Optional[List[AiDialogueHistory]] = None,
+        dialogue_history: Optional[List[CreateAiTextGenDialogueHistory]] = None,
         ai_agent: Optional[AiAgentTextGen] = None,
         extra_headers: Optional[Dict[str, Optional[str]]] = None
     ) -> AiResponse:
@@ -208,7 +221,7 @@ def create_ai_text_gen(
         If the file size exceeds 1MB, the first 1MB of text representation will be processed.
                 :type items: List[CreateAiTextGenItems]
                 :param dialogue_history: The history of prompts and answers previously passed to the LLM. This provides additional context to the LLM in generating the response., defaults to None
-                :type dialogue_history: Optional[List[AiDialogueHistory]], optional
+                :type dialogue_history: Optional[List[CreateAiTextGenDialogueHistory]], optional
                 :param extra_headers: Extra headers that will be included in the HTTP request., defaults to None
                 :type extra_headers: Optional[Dict[str, Optional[str]]], optional
         """

box_sdk_gen/networking/fetch.py

@@ -159,8 +159,6 @@ def fetch(url: str, options: FetchOptions) -> FetchResponse:
             )
         )
 
-        if options.file_stream and options.file_stream.seekable():
-            options.file_stream.seek(0)
         attempt_nr += 1
 
     __raise_on_unsuccessful_request(request=request, response=response)

box_sdk_gen/schemas/__init__.py

@@ -340,18 +340,12 @@
 
 from box_sdk_gen.schemas.ai_agent_text_gen import *
 
+from box_sdk_gen.schemas.ai_text_gen import *
+
 from box_sdk_gen.schemas.ai_agent_basic_text_tool_ask import *
 
 from box_sdk_gen.schemas.ai_agent_ask import *
 
-from box_sdk_gen.schemas.ai_citation import *
-
-from box_sdk_gen.schemas.ai_ask_response import *
-
-from box_sdk_gen.schemas.ai_dialogue_history import *
-
-from box_sdk_gen.schemas.ai_text_gen import *
-
 from box_sdk_gen.schemas.ai_ask import *
 
 from box_sdk_gen.schemas.completion_rule_variable import *

box_sdk_gen/schemas/ai_agent_ask.py

@@ -19,16 +19,16 @@ class AiAgentAsk(BaseObject):
     def __init__(
         self,
         *,
-        type: AiAgentAskTypeField = AiAgentAskTypeField.AI_AGENT_ASK.value,
+        type: Optional[AiAgentAskTypeField] = None,
         long_text: Optional[AiAgentLongTextTool] = None,
         basic_text: Optional[AiAgentBasicTextToolAsk] = None,
         long_text_multi: Optional[AiAgentLongTextTool] = None,
         basic_text_multi: Optional[AiAgentBasicTextToolAsk] = None,
         **kwargs
     ):
         """
-        :param type: The type of AI agent used to handle queries., defaults to AiAgentAskTypeField.AI_AGENT_ASK.value
-        :type type: AiAgentAskTypeField, optional
+        :param type: The type of AI agent used to handle queries., defaults to None
+        :type type: Optional[AiAgentAskTypeField], optional
         """
         super().__init__(**kwargs)
         self.type = type

box_sdk_gen/schemas/ai_agent_text_gen.py

@@ -17,13 +17,13 @@ class AiAgentTextGen(BaseObject):
     def __init__(
         self,
         *,
-        type: AiAgentTextGenTypeField = AiAgentTextGenTypeField.AI_AGENT_TEXT_GEN.value,
+        type: Optional[AiAgentTextGenTypeField] = None,
         basic_gen: Optional[AiAgentBasicGenTool] = None,
         **kwargs
     ):
         """
-        :param type: The type of AI agent used for generating text., defaults to AiAgentTextGenTypeField.AI_AGENT_TEXT_GEN.value
-        :type type: AiAgentTextGenTypeField, optional
+        :param type: The type of AI agent used for generating text., defaults to None
+        :type type: Optional[AiAgentTextGenTypeField], optional
         """
         super().__init__(**kwargs)
         self.type = type

box_sdk_gen/schemas/ai_ask.py

@@ -6,8 +6,6 @@
 
 from typing import List
 
-from box_sdk_gen.schemas.ai_dialogue_history import AiDialogueHistory
-
 from box_sdk_gen.schemas.ai_agent_ask import AiAgentAsk
 
 
@@ -52,8 +50,6 @@ def __init__(
         prompt: str,
         items: List[AiAskItemsField],
         *,
-        dialogue_history: Optional[List[AiDialogueHistory]] = None,
-        include_citations: Optional[bool] = None,
         ai_agent: Optional[AiAgentAsk] = None,
         **kwargs
     ):
@@ -68,15 +64,9 @@ def __init__(
         If the file size exceeds 1MB, the first 1MB of text representation will be processed.
         If you set `mode` parameter to `single_item_qa`, the `items` array can have one element only.
                 :type items: List[AiAskItemsField]
-                :param dialogue_history: The history of prompts and answers previously passed to the LLM. This provides additional context to the LLM in generating the response., defaults to None
-                :type dialogue_history: Optional[List[AiDialogueHistory]], optional
-                :param include_citations: A flag to indicate whether citations should be returned., defaults to None
-                :type include_citations: Optional[bool], optional
         """
         super().__init__(**kwargs)
         self.mode = mode
         self.prompt = prompt
         self.items = items
-        self.dialogue_history = dialogue_history
-        self.include_citations = include_citations
         self.ai_agent = ai_agent

box_sdk_gen/schemas/ai_text_gen.py

@@ -6,10 +6,10 @@
 
 from typing import List
 
-from box_sdk_gen.schemas.ai_dialogue_history import AiDialogueHistory
-
 from box_sdk_gen.schemas.ai_agent_text_gen import AiAgentTextGen
 
+from box_sdk_gen.internal.utils import DateTime
+
 
 class AiTextGenItemsTypeField(str, Enum):
     FILE = 'file'
@@ -40,13 +40,36 @@ def __init__(
         self.content = content
 
 
+class AiTextGenDialogueHistoryField(BaseObject):
+    def __init__(
+        self,
+        *,
+        prompt: Optional[str] = None,
+        answer: Optional[str] = None,
+        created_at: Optional[DateTime] = None,
+        **kwargs
+    ):
+        """
+        :param prompt: The prompt previously provided by the client and answered by the LLM., defaults to None
+        :type prompt: Optional[str], optional
+        :param answer: The answer previously provided by the LLM., defaults to None
+        :type answer: Optional[str], optional
+        :param created_at: The ISO date formatted timestamp of when the previous answer to the prompt was created., defaults to None
+        :type created_at: Optional[DateTime], optional
+        """
+        super().__init__(**kwargs)
+        self.prompt = prompt
+        self.answer = answer
+        self.created_at = created_at
+
+
 class AiTextGen(BaseObject):
     def __init__(
         self,
         prompt: str,
         items: List[AiTextGenItemsField],
         *,
-        dialogue_history: Optional[List[AiDialogueHistory]] = None,
+        dialogue_history: Optional[List[AiTextGenDialogueHistoryField]] = None,
         ai_agent: Optional[AiAgentTextGen] = None,
         **kwargs
     ):
@@ -60,7 +83,7 @@ def __init__(
         If the file size exceeds 1MB, the first 1MB of text representation will be processed.
                 :type items: List[AiTextGenItemsField]
                 :param dialogue_history: The history of prompts and answers previously passed to the LLM. This provides additional context to the LLM in generating the response., defaults to None
-                :type dialogue_history: Optional[List[AiDialogueHistory]], optional
+                :type dialogue_history: Optional[List[AiTextGenDialogueHistoryField]], optional
         """
         super().__init__(**kwargs)
         self.prompt = prompt