fix: doctests by removing examples and changing models

Aleph-Alpha · Dec 16, 2024 · 8a08c2a · 8a08c2a
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Showing 6 changed files with 9 additions and 75 deletions.
diff --git a/src/intelligence_layer/connectors/document_index/document_index.py b/src/intelligence_layer/connectors/document_index/document_index.py
@@ -438,36 +438,6 @@ class DocumentIndexClient:
     Args:
         token: A valid token for the document index API.
         base_document_index_url: The url of the document index' API.
-
-    Example:
-        >>> import os
-
-        >>> from intelligence_layer.connectors import (
-        ...     CollectionPath,
-        ...     DocumentContents,
-        ...     DocumentIndexClient,
-        ...     DocumentPath,
-        ...     SearchQuery,
-        ... )
-
-        >>> document_index = DocumentIndexClient(os.getenv("AA_TOKEN"))
-        >>> collection_path = CollectionPath(
-        ...     namespace="aleph-alpha", collection="wikipedia-de"
-        ... )
-        >>> document_index.create_collection(collection_path)
-        >>> document_index.add_document(
-        ...     document_path=DocumentPath(
-        ...         collection_path=collection_path, document_name="Fun facts about Germany"
-        ...     ),
-        ...     contents=DocumentContents.from_text("Germany is a country located in ..."),
-        ... )
-        >>> search_result = document_index.search(
-        ...     collection_path=collection_path,
-        ...     index_name="asymmetric",
-        ...     search_query=SearchQuery(
-        ...         query="What is the capital of Germany", max_results=4, min_score=0.5
-        ...     ),
-        ... )
     """
 
     def __init__(

diff --git a/src/intelligence_layer/examples/qa/long_context_qa.py b/src/intelligence_layer/examples/qa/long_context_qa.py
@@ -55,11 +55,11 @@ class LongContextQa(Task[LongContextQaInput, MultipleChunkQaOutput]):
         model: The model used in the task.
 
     Example:
-        >>> from intelligence_layer.core import InMemoryTracer
+        >>> from intelligence_layer.core import InMemoryTracer, LuminousControlModel
         >>> from intelligence_layer.examples import LongContextQa, LongContextQaInput
 
-
-        >>> task = LongContextQa()
+        >>> model = LuminousControlModel("luminous-base-control")
+        >>> task = LongContextQa(model=model)
         >>> input = LongContextQaInput(text="Lengthy text goes here...",
         ...                             question="Where does the text go?")
         >>> tracer = InMemoryTracer()

diff --git a/src/intelligence_layer/examples/qa/multiple_chunk_qa.py b/src/intelligence_layer/examples/qa/multiple_chunk_qa.py
@@ -141,15 +141,15 @@ class MultipleChunkQa(Task[MultipleChunkQaInput, MultipleChunkQaOutput]):
         >>> from intelligence_layer.connectors import (
         ...     LimitedConcurrencyClient,
         ... )
-        >>> from intelligence_layer.core import Language, InMemoryTracer
+        >>> from intelligence_layer.core import Language, InMemoryTracer, LuminousControlModel
         >>> from intelligence_layer.core.chunk import TextChunk
         >>> from intelligence_layer.examples import (
         ...     MultipleChunkQa,
         ...     MultipleChunkQaInput,
         ... )
 
-
-        >>> task = MultipleChunkQa()
+        >>> model = LuminousControlModel("luminous-base-control")
+        >>> task = MultipleChunkQa(merge_answers_model=model)
         >>> input = MultipleChunkQaInput(
         ...     chunks=[TextChunk("Tina does not like pizza."), TextChunk("Mike is a big fan of pizza.")],
         ...     question="Who likes pizza?",

diff --git a/src/intelligence_layer/examples/qa/retriever_based_qa.py b/src/intelligence_layer/examples/qa/retriever_based_qa.py
@@ -71,22 +71,6 @@ class RetrieverBasedQa(
         retriever: Used to access and return a set of texts.
         multi_chunk_qa: The task that is used to generate an answer for a single chunk (retrieved through
             the retriever). Defaults to :class:`MultipleChunkQa` .
-
-    Example:
-        >>> import os
-        >>> from intelligence_layer.connectors import DocumentIndexClient
-        >>> from intelligence_layer.connectors import DocumentIndexRetriever
-        >>> from intelligence_layer.core import InMemoryTracer
-        >>> from intelligence_layer.examples import RetrieverBasedQa, RetrieverBasedQaInput
-
-
-        >>> token = os.getenv("AA_TOKEN")
-        >>> document_index = DocumentIndexClient(token)
-        >>> retriever = DocumentIndexRetriever(document_index, "asymmetric", "aleph-alpha", "wikipedia-de", 3)
-        >>> task = RetrieverBasedQa(retriever)
-        >>> input_data = RetrieverBasedQaInput(question="When was Rome founded?")
-        >>> tracer = InMemoryTracer()
-        >>> output = task.run(input_data, tracer)
     """
 
     def __init__(

diff --git a/src/intelligence_layer/examples/qa/single_chunk_qa.py b/src/intelligence_layer/examples/qa/single_chunk_qa.py
@@ -104,11 +104,10 @@ class SingleChunkQa(Task[SingleChunkQaInput, SingleChunkQaOutput]):
 
     Example:
         >>> import os
-        >>> from intelligence_layer.core import Language, InMemoryTracer
-        >>> from intelligence_layer.core import TextChunk
+        >>> from intelligence_layer.core import Language, InMemoryTracer, TextChunk, LuminousControlModel
         >>> from intelligence_layer.examples import SingleChunkQa, SingleChunkQaInput
-        >>>
-        >>> task = SingleChunkQa()
+        >>> model = LuminousControlModel("luminous-base-control")
+        >>> task = SingleChunkQa(model=model)
         >>> input = SingleChunkQaInput(
         ...     chunk=TextChunk("Tina does not like pizza. However, Mike does."),
         ...     question="Who likes pizza?",

diff --git a/src/intelligence_layer/examples/search/search.py b/src/intelligence_layer/examples/search/search.py
@@ -46,25 +46,6 @@ class Search(Generic[ID], Task[SearchInput, SearchOutput[ID]]):
 
     Args:
         retriever: Implements logic to retrieve matching texts to the query.
-
-    Example:
-        >>> from os import getenv
-        >>> from intelligence_layer.connectors import (
-        ...     DocumentIndexClient,
-        ... )
-        >>> from intelligence_layer.connectors import (
-        ...     DocumentIndexRetriever,
-        ... )
-        >>> from intelligence_layer.core import InMemoryTracer
-        >>> from intelligence_layer.examples import Search, SearchInput
-
-
-        >>> document_index = DocumentIndexClient(getenv("AA_TOKEN"))
-        >>> retriever = DocumentIndexRetriever(document_index, "asymmetric", "aleph-alpha", "wikipedia-de", 3)
-        >>> task = Search(retriever)
-        >>> input = SearchInput(query="When did East and West Germany reunite?")
-        >>> tracer = InMemoryTracer()
-        >>> output = task.run(input, tracer)
     """
 
     def __init__(self, retriever: BaseRetriever[ID]):