fix: Integration tests (#41)

* fix: types

* test: Added some integration tests

* test: improvements

* test: test_paraphrase.py

* fix: doc

* fix: removed unused comment

* test: test_summarize.py

* test: Added tests for test_summarize_by_segment.py

* test: test_segmentation.py

* fix: file id in library response

* fix: example for library

* ci: Add rc branch prefix trigger for integration tests (#43)

* ci: rc branch trigger for integration test

* fix: wrapped in quotes

* fix: types

* test: Added some integration tests

* test: improvements

* test: test_paraphrase.py

* fix: doc

* fix: removed unused comment

* test: test_summarize.py

* test: Added tests for test_summarize_by_segment.py

* test: test_segmentation.py

* fix: file id in library response

* fix: example for library

* docs: docstrings

* fix: question

* fix: CR

* test: Added tests to segment type in embed

ai21/clients/common/answer_base.py

@@ -17,6 +17,15 @@ def create(
         mode: Optional[Mode] = None,
         **kwargs,
     ) -> AnswerResponse:
+        """
+
+        :param context: A string containing the document context for which the question will be answered
+        :param question: A string containing the question to be answered based on the provided context.
+        :param answer_length: Approximate length of the answer in words.
+        :param mode:
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> AnswerResponse:
@@ -26,7 +35,7 @@ def _create_body(
         self,
         context: str,
         question: str,
-        answer_length: Optional[str],
+        answer_length: Optional[AnswerLength],
         mode: Optional[str],
     ) -> Dict[str, Any]:
         return {"context": context, "question": question, "answerLength": answer_length, "mode": mode}

ai21/clients/common/chat_base.py

@@ -28,6 +28,25 @@ def create(
         count_penalty: Optional[Penalty] = None,
         **kwargs,
     ) -> ChatResponse:
+        """
+
+        :param model: model type you wish to interact with
+        :param messages: A sequence of messages ingested by the model, which then returns the assistant's response
+        :param system: Offers the model overarching guidance on its response approach, encapsulating context, tone,
+         guardrails, and more
+        :param max_tokens: The maximum number of tokens to generate per result
+        :param num_results: Number of completions to sample and return.
+        :param min_tokens: The minimum number of tokens to generate per result.
+        :param temperature: A value controlling the "creativity" of the model's responses.
+        :param top_p: A value controlling the diversity of the model's responses.
+        :param top_k_return: The number of top-scoring tokens to consider for each generation step.
+        :param stop_sequences: Stops decoding if any of the strings is generated
+        :param frequency_penalty: A penalty applied to tokens that are frequently generated.
+        :param presence_penalty:  A penalty applied to tokens that are already present in the prompt.
+        :param count_penalty: A penalty applied to tokens based on their frequency in the generated responses
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> ChatResponse:

ai21/clients/common/completion_base.py

@@ -28,6 +28,24 @@ def create(
         epoch: Optional[int] = None,
         **kwargs,
     ) -> CompletionsResponse:
+        """
+        :param model: model type you wish to interact with
+        :param prompt: Text for model to complete
+        :param max_tokens: The maximum number of tokens to generate per result
+        :param num_results: Number of completions to sample and return.
+        :param min_tokens: The minimum number of tokens to generate per result.
+        :param temperature: A value controlling the "creativity" of the model's responses.
+        :param top_p: A value controlling the diversity of the model's responses.
+        :param top_k_return: The number of top-scoring tokens to consider for each generation step.
+        :param custom_model:
+        :param stop_sequences: Stops decoding if any of the strings is generated
+        :param frequency_penalty: A penalty applied to tokens that are frequently generated.
+        :param presence_penalty:  A penalty applied to tokens that are already present in the prompt.
+        :param count_penalty: A penalty applied to tokens based on their frequency in the generated responses
+        :param epoch:
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> CompletionsResponse:

ai21/clients/common/custom_model_base.py

@@ -18,6 +18,16 @@ def create(
         num_epochs: Optional[int] = None,
         **kwargs,
     ) -> None:
+        """
+
+        :param dataset_id: The dataset you want to train your model on.
+        :param model_name: The name of your trained model
+        :param model_type: The type of model to train.
+        :param learning_rate: The learning rate used for training.
+        :param num_epochs: Number of epochs for training
+        :param kwargs:
+        :return:
+        """
         pass
 
     @abstractmethod

ai21/clients/common/dataset_base.py

@@ -19,6 +19,17 @@ def create(
         split_ratio: Optional[float] = None,
         **kwargs,
     ):
+        """
+
+        :param file_path: Local path to dataset
+        :param dataset_name: Dataset name. Must be unique
+        :param selected_columns: Mapping of the columns in the dataset file to prompt and completion columns.
+        :param approve_whitespace_correction: Automatically correct examples that violate best practices
+        :param delete_long_rows: Allow removal of examples where prompt + completion lengths exceeds 2047 tokens
+        :param split_ratio:
+        :param kwargs:
+        :return:
+        """
         pass
 
     @abstractmethod

ai21/clients/common/embed_base.py

@@ -10,6 +10,14 @@ class Embed(ABC):
 
     @abstractmethod
     def create(self, texts: List[str], *, type: Optional[EmbedType] = None, **kwargs) -> EmbedResponse:
+        """
+
+        :param texts: A list of strings, each representing a document or segment of text to be embedded.
+        :param type: For retrieval/search use cases, indicates whether the texts that were
+         sent are segments or the query.
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> EmbedResponse:

ai21/clients/common/gec_base.py

@@ -9,6 +9,12 @@ class GEC(ABC):
 
     @abstractmethod
     def create(self, text: str, **kwargs) -> GECResponse:
+        """
+
+        :param text: The input text to be corrected.
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> GECResponse:

ai21/clients/common/improvements_base.py

@@ -10,6 +10,13 @@ class Improvements(ABC):
 
     @abstractmethod
     def create(self, text: str, types: List[ImprovementType], **kwargs) -> ImprovementsResponse:
+        """
+
+        :param text: The input text to be improved.
+        :param types: Types of improvements to apply.
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> ImprovementsResponse:

ai21/clients/common/paraphrase_base.py

@@ -18,6 +18,16 @@ def create(
         end_index: Optional[int] = None,
         **kwargs,
     ) -> ParaphraseResponse:
+        """
+
+        :param text: The input text to be paraphrased.
+        :param style: Controls length and tone
+        :param start_index: Specifies the starting position of the paraphrasing process in the given text
+        :param end_index: specifies the position of the last character to be paraphrased, including the character
+         following it. If the parameter is not provided, the default value is set to the length of the given text.
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> ParaphraseResponse:

ai21/clients/common/segmentation_base.py

@@ -10,6 +10,13 @@ class Segmentation(ABC):
 
     @abstractmethod
     def create(self, source: str, source_type: DocumentType, **kwargs) -> SegmentationResponse:
+        """
+
+        :param source: Raw input text, or URL of a web page.
+        :param source_type: The type of the source - either TEXT or URL.
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> SegmentationResponse:

ai21/clients/common/summarize_base.py

@@ -16,6 +16,14 @@ def create(
         summary_method: Optional[SummaryMethod] = None,
         **kwargs,
     ) -> SummarizeResponse:
+        """
+        :param source: The input text, or URL of a web page to be summarized.
+        :param source_type: Either TEXT or URL
+        :param focus: Summaries focused on a topic of your choice.
+        :param summary_method:
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> SummarizeResponse:

ai21/clients/common/summarize_by_segment_base.py

@@ -19,6 +19,14 @@ def create(
         focus: Optional[str] = None,
         **kwargs,
     ) -> SummarizeBySegmentResponse:
+        """
+
+        :param source: The input text, or URL of a web page to be summarized.
+        :param source_type: Either TEXT or URL
+        :param focus: Summaries focused on a topic of your choice.
+        :param kwargs:
+        :return:
+        """
         pass
 
     def _json_to_response(self, json: Dict[str, Any]) -> SummarizeBySegmentResponse:

ai21/clients/studio/resources/studio_embed.py

@@ -2,11 +2,12 @@
 
 from ai21.clients.common.embed_base import Embed
 from ai21.clients.studio.resources.studio_resource import StudioResource
+from ai21.models.embed_type import EmbedType
 from ai21.models.responses.embed_response import EmbedResponse
 
 
 class StudioEmbed(StudioResource, Embed):
-    def create(self, texts: List[str], type: Optional[str] = None, **kwargs) -> EmbedResponse:
+    def create(self, texts: List[str], type: Optional[EmbedType] = None, **kwargs) -> EmbedResponse:
         url = f"{self._client.get_base_url()}/{self._module_name}"
         body = self._create_body(texts=texts, type=type)
         response = self._post(url=url, body=body)

ai21/clients/studio/resources/studio_summarize.py

@@ -18,7 +18,6 @@ def create(
         summary_method: Optional[SummaryMethod] = None,
         **kwargs,
     ) -> SummarizeResponse:
-        # Make a summarize request to the AI21 API. Returns the response either as a string or a AI21Summarize object.
         body = self._create_body(
             source=source,
             source_type=source_type,

ai21/models/responses/library_answer_response.py

@@ -6,7 +6,7 @@
 
 @dataclass
 class SourceDocument(AI21BaseModelMixin):
-    field_id: str
+    file_id: str
     name: str
     highlights: List[str]
     public_url: Optional[str] = None

examples/studio/library.py

@@ -22,7 +22,12 @@ def validate_file_deleted():
 file_path = os.getcwd()
 
 path = os.path.join(file_path, file_name)
-file_utils.create_file(file_path, file_name, content="test content" * 100)
+_SOURCE_TEXT = """Holland is a geographical region and former province on the western coast of the
+Netherlands. From the 10th to the 16th century, Holland proper was  a unified political
+ region within the Holy Roman Empire as a county ruled by the counts of Holland.
+  By the 17th century, the province of Holland had risen to become a maritime and economic power,
+   dominating the other provinces of the newly independent Dutch Republic."""
+file_utils.create_file(file_path, file_name, content=_SOURCE_TEXT)
 
 file_id = client.library.files.create(
     file_path=path,
@@ -31,6 +36,7 @@ def validate_file_deleted():
     public_url="www.example.com",
 )
 print(file_id)
+
 files = client.library.files.list()
 print(files)
 uploaded_file = client.library.files.get(file_id)

examples/studio/library_answer.py

@@ -2,5 +2,5 @@
 
 
 client = AI21Client()
-response = client.library.answer.create(question="Where is Thailand?")
+response = client.library.answer.create(question="Can you tell me something about Holland?")
 print(response)

tests/integration_tests/clients/studio/test_answer.py

@@ -0,0 +1,38 @@
+import pytest
+from ai21 import AI21Client
+from ai21.models import AnswerLength, Mode
+
+_CONTEXT = (
+    "Holland is a geographical region[2] and former province on the western coast of"
+    " the Netherlands. From the "
+    "10th to the 16th century, Holland proper was a unified political region within the Holy Roman Empire as a county "
+    "ruled by the counts of Holland. By the 17th century, the province of Holland had risen to become a maritime and "
+    "economic power, dominating the other provinces of the newly independent Dutch Republic."
+)
+
+
+@pytest.mark.parametrize(
+    ids=[
+        "when_answer_is_in_context",
+        "when_answer_not_in_context",
+    ],
+    argnames=["question", "is_answer_in_context", "expected_answer_type"],
+    argvalues=[
+        ("When did Holland become an economic power?", True, str),
+        ("Is the ocean blue?", False, None),
+    ],
+)
+def test_answer(question: str, is_answer_in_context: bool, expected_answer_type: type):
+    client = AI21Client()
+    response = client.answer.create(
+        context=_CONTEXT,
+        question=question,
+        answer_length=AnswerLength.LONG,
+        mode=Mode.FLEXIBLE,
+    )
+
+    assert response.answer_in_context == is_answer_in_context
+    if is_answer_in_context:
+        assert isinstance(response.answer, str)
+    else:
+        assert response.answer is None