feat: Add support for get AI agent default

boxsdk/client/client.py

@@ -1784,7 +1784,8 @@ def send_ai_question(
         self,
         items: Iterable,
         prompt: str,
-        mode: Optional[str] = None
+        mode: Optional[str] = None,
+        ai_agent: Optional[dict] = None
     ) -> Any:
         """
         Sends an AI request to supported LLMs and returns an answer specifically focused on the user's
@@ -1801,6 +1802,8 @@ def send_ai_question(
             Selecting multiple_item_qa allows you to provide up to 25 items.
 
             Value is one of `multiple_item_qa`, `single_item_qa`
+        :param ai_agent:
+            The AI agent used to handle queries.
         :returns:
             A response including the answer from the LLM.
         """
@@ -1813,6 +1816,9 @@ def send_ai_question(
             'mode': mode
         }
 
+        if ai_agent is not None:
+            body['ai_agent'] = ai_agent
+
         box_response = self._session.post(url, data=json.dumps(body))
         response = box_response.json()
         return self.translator.translate(
@@ -1826,6 +1832,7 @@ def send_ai_text_gen(
         dialogue_history: Iterable,
         items: Iterable,
         prompt: str,
+        ai_agent: Optional[dict] = None
     ):
         """
         Sends an AI request to supported LLMs and returns an answer specifically focused on the creation of new text.
@@ -1838,6 +1845,8 @@ def send_ai_text_gen(
         :param prompt:
             The prompt provided by the client to be answered by the LLM.
             The prompt's length is limited to 10000 characters.
+        :param ai_agent:
+            The AI agent used for generating text.
         :returns:
             A response including the generated text from the LLM.
         """
@@ -1848,9 +1857,48 @@ def send_ai_text_gen(
             'prompt': prompt
         }
 
+        if ai_agent is not None:
+            body['ai_agent'] = ai_agent
+
         box_response = self._session.post(url, data=json.dumps(body))
         response = box_response.json()
         return self.translator.translate(
             session=self._session,
             response_object=response,
         )
+
+    @api_call
+    def get_ai_agent_default_config(
+            self,
+            mode: str,
+            language: Optional[str] = None,
+            model: Optional[str] = None,
+    ):
+        """
+        Get the AI agent default configuration.
+
+        :param mode:
+            The mode to filter the agent config to return.
+        :param language:
+            The ISO language code to return the agent config for.
+            If the language is not supported the default agent configuration is returned.
+        :param model:
+            The model to return the default agent config for.
+        :returns:
+            A default agent configuration.
+            This can be one of the following two objects:
+            AI agent for questions and AI agent for text generation.
+            The response depends on the agent configuration requested in this endpoint.
+        """
+        url = self._session.get_url('ai_agent_default')
+        params = {'mode': mode}
+        if language is not None:
+            params['language'] = language
+        if model is not None:
+            params['model'] = model
+
+        box_response = self._session.get(url, params=params)
+        return self.translator.translate(
+            session=self._session,
+            response_object=box_response.json(),
+        )

docs/usage/ai.md

@@ -8,13 +8,14 @@ AI allows to send an intelligence request to supported large language models and
 
 - [Send AI request](#send-ai-request)
 - [Send AI text generation request](#send-ai-text-generation-request)
+- [Get AI agent default configuration](#get-ai-agent-default-configuration)
 
 <!-- END doctoc generated TOC please keep comment here to allow auto update -->
 
 Send AI request
 ------------------------
 
-Calling the [`client.send_ai_question(items, prompt, mode)`][send-ai-question] method will send an AI request to the supported large language models. The `items` parameter is a list of items to be processed by the LLM, often files. The `prompt` provided by the client to be answered by the LLM. The prompt's length is limited to 10000 characters. 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.
+Calling the [`client.send_ai_question(items, prompt, mode, ai_agent)`][send-ai-question] method will send an AI request to the supported large language models. The `items` parameter is a list of items to be processed by the LLM, often files. The `prompt` provided by the client to be answered by the LLM. The prompt's length is limited to 10000 characters. 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. The `ai_agent` specifies the AI agent which will be used to handle queries.
 
 
 
@@ -25,10 +26,17 @@ items = [{
     "type": "file",
     "content": "More information about public APIs"
 }]
+ai_agent = {
+    'type': 'ai_agent_ask',
+    'basic_text_multi': {
+        'model': 'openai__gpt_3_5_turbo'
+    }
+}
 answer = client.send_ai_question(
     items=items, 
     prompt="What is this file?",
-    mode="single_item_qa"
+    mode="single_item_qa",
+    ai_agent=ai_agent
 )
 print(answer)
 ```
@@ -41,7 +49,7 @@ It usually takes a few seconds for the file to be indexed and available for the
 Send AI text generation request
 ------------------------
 
-Calling the [`client.send_ai_text_gen(dialogue_history, items, prompt)`][send-ai-text-gen] method will send an AI text generation request to the supported large language models. The `dialogue_history` parameter is history of prompts and answers previously passed to the LLM. This provides additional context to the LLM in generating the response. The `items` parameter is a list of items to be processed by the LLM, often files. The `prompt` provided by the client to be answered by the LLM. The prompt's length is limited to 10000 characters.
+Calling the [`client.send_ai_text_gen(dialogue_history, items, prompt, ai_agent)`][send-ai-text-gen] method will send an AI text generation request to the supported large language models. The `dialogue_history` parameter is history of prompts and answers previously passed to the LLM. This provides additional context to the LLM in generating the response. The `items` parameter is a list of items to be processed by the LLM, often files. The `prompt` provided by the client to be answered by the LLM. The prompt's length is limited to 10000 characters. The `ai_agent` specifies the AI agent which will be used for generating text.
 
 <!-- sample post_ai_text_gen -->
 ```python
@@ -60,12 +68,36 @@ dialogue_history = [{
         "answer": "Public API schemas provide necessary information to integrate with APIs...",
         "created_at": "2013-12-12T11:20:43-08:00"
 }]
+ai_agent = {
+    'type': 'ai_agent_text_gen',
+    'basic_gen': {
+        'model': 'openai__gpt_3_5_turbo_16k'
+    }
+}
 answer = client.send_ai_text_gen(
     dialogue_history=dialogue_history,
     items=items,
-    prompt="Write an email to a client about the importance of public APIs."
+    prompt="Write an email to a client about the importance of public APIs.",
+    ai_agent=ai_agent
 )
 print(answer)
 ```
 
 [send-ai-text-gen]: https://box-python-sdk.readthedocs.io/en/latest/boxsdk.client.html#boxsdk.client.client.Client.send_ai_text_gen
+
+Get AI agent default configuration
+------------------------
+
+To get an AI agent default configuration call the [`client.get_ai_agent_default_config(mode, language, model)`][get-ai-agent-default] method. The `mode` parameter filters the agent configuration to be returned. It can be either `ask` or `text_gen`. The `language` parameter specifies the ISO language code to return the agent config for. If the language is not supported, the default agent configuration is returned. The `model` parameter specifies the model for which the default agent configuration should be returned.
+
+<!-- sample get_ai_agent_default -->
+```python
+config = client.get_ai_agent_default_config(
+    mode='text_gen',
+    language='en',
+    model='openai__gpt_3_5_turbo'
+)
+print(config)
+```
+
+[get-ai-agent-default]: https://box-python-sdk.readthedocs.io/en/latest/boxsdk.client.html#boxsdk.client.client.Client.get_ai_agent_default_config

test/integration_new/object/ai_itest.py

@@ -22,10 +22,17 @@ def test_send_ai_question(parent_folder, small_file_path):
             'type': 'file',
             'content': 'The sun raises in the east.'
         }]
+        ai_agent = {
+            'type': 'ai_agent_ask',
+            'basic_text_multi': {
+                'model': 'openai__gpt_3_5_turbo'
+            }
+        }
         answer = CLIENT.send_ai_question(
             items=items,
             prompt='Which direction does the sun raise?',
-            mode='single_item_qa'
+            mode='single_item_qa',
+            ai_agent=ai_agent
         )
         assert 'east' in answer['answer'].lower()
         assert answer['completion_reason'] == 'done'
@@ -47,10 +54,27 @@ def test_send_ai_text_gen(parent_folder, small_file_path):
             'answer': 'It takes 24 hours for the sun to rise.',
             'created_at': '2013-12-12T11:20:43-08:00'
         }]
+        ai_agent = {
+            'type': 'ai_agent_text_gen',
+            'basic_gen': {
+                'model': 'openai__gpt_3_5_turbo_16k'
+            }
+        }
         answer = CLIENT.send_ai_text_gen(
             dialogue_history=dialogue_history,
             items=items,
-            prompt='Which direction does the sun raise?'
+            prompt='Which direction does the sun raise?',
+            ai_agent=ai_agent
         )
         assert 'east' in answer['answer'].lower()
         assert answer['completion_reason'] == 'done'
+
+
+def test_get_ai_agent_default_config():
+    config = CLIENT.get_ai_agent_default_config(
+        mode='text_gen',
+        language='en',
+        model='openai__gpt_3_5_turbo'
+    )
+    assert config['type'] == 'ai_agent_text_gen'
+    assert config['basic_gen']['model'] == 'openai__gpt_3_5_turbo'

test/unit/client/test_client.py

@@ -1776,6 +1776,37 @@ def mock_ai_question_response():
     return mock_ai_question_response
 
 
+@pytest.fixture(scope='module')
+def mock_ai_agent_default_config_response():
+    mock_ai_agent_default_config_response = {
+        'type': 'ai_agent_text_gen',
+        'basic_gen': {
+            'content_template': '---{content}---',
+            'embeddings': {
+                'model': 'openai__text_embedding_ada_002',
+                'strategy': {
+                    'id': 'basic',
+                    'num_tokens_per_chunk': 64
+                }
+            },
+            'llm_endpoint_params': {
+                'type': 'openai_params',
+                'frequency_penalty': 1.5,
+                'presence_penalty': 1.5,
+                'stop': '<|im_end|>',
+                'temperature': 0,
+                'top_p': 1
+            },
+            'model': 'openai__gpt_3_5_turbo',
+            'num_tokens_for_completion': 8400,
+            'prompt_template': 'It is `{current_date}`, and I have $8000 and want to spend a week in the Azores. What '
+                               'should I see?',
+            'system_message': 'You are a helpful travel assistant specialized in budget travel'
+        }
+    }
+    return mock_ai_agent_default_config_response
+
+
 def test_get_sign_requests(mock_client, mock_box_session, mock_sign_request_response):
     expected_url = f'{API.BASE_API_URL}/sign_requests'
 
@@ -1963,13 +1994,25 @@ def test_send_ai_question(mock_client, mock_box_session, mock_ai_question_respon
     }]
     question = 'Why are public APIs important?'
     mode = 'single_item_qa'
+    ai_agent = {
+        'type': 'ai_agent_ask',
+        'basic_text_multi': {
+            'model': 'openai__gpt_3_5_turbo'
+        }
+    }
 
-    answer = mock_client.send_ai_question(items, question, mode)
+    answer = mock_client.send_ai_question(items, question, mode, ai_agent)
 
     mock_box_session.post.assert_called_once_with(expected_url, data=json.dumps({
         'items': items,
         'prompt': question,
-        'mode': mode
+        'mode': mode,
+        'ai_agent': {
+            'type': 'ai_agent_ask',
+            'basic_text_multi': {
+                'model': 'openai__gpt_3_5_turbo'
+            }
+        }
     }))
     assert answer['answer'] == 'Public APIs are important because of key and important reasons.'
     assert answer['completion_reason'] == 'done'
@@ -1993,17 +2036,41 @@ def test_send_ai_text_gen(mock_client, mock_box_session, mock_ai_question_respon
         "answer": "Public API schemas provide necessary information to integrate with APIs...",
         "created_at": "2013-12-12T11:20:43-08:00"
     }]
+    ai_agent = {
+        'type': 'ai_agent_text_gen',
+        'basic_gen': {
+            'model': 'openai__gpt_3_5_turbo_16k'
+        }
+    }
     answer = mock_client.send_ai_text_gen(
         dialogue_history=dialogue_history,
         items=items,
-        prompt="Write an email to a client about the importance of public APIs."
+        prompt="Write an email to a client about the importance of public APIs.",
+        ai_agent=ai_agent
     )
 
     mock_box_session.post.assert_called_once_with(expected_url, data=json.dumps({
         'dialogue_history': dialogue_history,
         'items': items,
-        'prompt': "Write an email to a client about the importance of public APIs."
+        'prompt': "Write an email to a client about the importance of public APIs.",
+        'ai_agent': ai_agent
     }))
     assert answer['answer'] == 'Public APIs are important because of key and important reasons.'
     assert answer['completion_reason'] == 'done'
     assert answer['created_at'] == '2021-04-26T08:12:13.982Z'
+
+
+def test_get_ai_agent_default_config(mock_client, mock_box_session, mock_ai_agent_default_config_response):
+    expected_url = f'{API.BASE_API_URL}/ai_agent_default'
+    mock_box_session.get.return_value.json.return_value = mock_ai_agent_default_config_response
+
+    config = mock_client.get_ai_agent_default_config(
+        mode='text_gen',
+        language='en',
+        model='openai__gpt_3_5_turbo'
+    )
+
+    mock_box_session.get.assert_called_once_with(expected_url, params={'mode': 'text_gen', 'language': 'en', 'model': 'openai__gpt_3_5_turbo'})
+    assert config['type'] == 'ai_agent_text_gen'
+    assert config['basic_gen']['model'] == 'openai__gpt_3_5_turbo'
+    assert config['basic_gen']['embeddings']['model'] == 'openai__text_embedding_ada_002'