diff --git a/boxsdk/client/client.py b/boxsdk/client/client.py index aa965af8..e6b12049 100644 --- a/boxsdk/client/client.py +++ b/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(), + ) diff --git a/docs/usage/ai.md b/docs/usage/ai.md index cddeb5f3..0a9d4da5 100644 --- a/docs/usage/ai.md +++ b/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) 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. ```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. + + +```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 diff --git a/test/integration_new/object/ai_itest.py b/test/integration_new/object/ai_itest.py index 3fb9499f..53deaa4e 100644 --- a/test/integration_new/object/ai_itest.py +++ b/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' diff --git a/test/unit/client/test_client.py b/test/unit/client/test_client.py index 51c0c742..0c3b0e90 100644 --- a/test/unit/client/test_client.py +++ b/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'