Merge pull request #108 from Aleph-Alpha/v3

v3 Release

Changelog.md

@@ -1,5 +1,17 @@
 # Changelog
 
+## 3.0.0
+
+### Breaking Changes
+
+- Removed deprecated `AlephAlphaClient` and `AlephAlphaModel`. Use `Client` or `AsyncClient` instead.
+- Removed deprecated `ImagePrompt`. Import `Image` instead for image prompt items.
+- New Q&A interface. We've improved the Q&A implementation, and most parameters are no longer needed.
+  - You only need to specify your documents, a query, and (optional) the max number of answers you want to receive.
+  - You no longer specify a model.
+- Removed "model" parameter from summarize method
+- Removed "model_version" from `SummarizationResponse`
+
 ## 2.17.0
 
 ### Features

aleph_alpha_client/__init__.py

@@ -2,7 +2,6 @@
     ControlTokenOverlap,
     Image,
     ImageControl,
-    ImagePrompt,
     Prompt,
     Text,
     TextControl,
@@ -11,12 +10,10 @@
 )
 from .aleph_alpha_client import (
     POOLING_OPTIONS,
-    AlephAlphaClient,
     AsyncClient,
     Client,
     QuotaError,
 )
-from .aleph_alpha_model import AlephAlphaModel
 from .completion import CompletionRequest, CompletionResponse
 from .detokenization import DetokenizationRequest, DetokenizationResponse
 from .document import Document
@@ -52,8 +49,6 @@
 from .version import __version__
 
 __all__ = [
-    "AlephAlphaClient",
-    "AlephAlphaModel",
     "AsyncClient",
     "Client",
     "CompletionRequest",
@@ -73,7 +68,6 @@
     "ExplanationResponse",
     "Image",
     "ImageControl",
-    "ImagePrompt",
     "ImagePromptItemExplanation",
     "ImageScore",
     "POOLING_OPTIONS",

aleph_alpha_client/explanation.py

@@ -12,6 +12,8 @@
 # Import Literal with Python 3.7 fallback
 from typing_extensions import Literal
 
+from aleph_alpha_client import Text
+
 from aleph_alpha_client.prompt import ControlTokenOverlap, Image, Prompt, PromptItem
 
 
@@ -204,6 +206,20 @@ def from_json(score: Any) -> "TextScore":
             score=score["score"],
         )
 
+class TextScoreWithRaw(NamedTuple):
+    start: int
+    length: int
+    score: float
+    text: str
+
+    @staticmethod
+    def from_text_score(score: TextScore, prompt: Text) -> "TextScoreWithRaw":
+        return TextScoreWithRaw(
+            start=score.start,
+            length=score.length,
+            score=score.score,
+            text=prompt.text[score.start:score.start + score.length],
+        )
 
 class ImageScore(NamedTuple):
     left: float
@@ -236,6 +252,20 @@ def from_json(score: Any) -> "TargetScore":
             score=score["score"],
         )
 
+class TargetScoreWithRaw(NamedTuple):
+    start: int
+    length: int
+    score: float
+    text: str
+
+    @staticmethod
+    def from_target_score(score: TargetScore, target: str) -> "TargetScoreWithRaw":
+        return TargetScoreWithRaw(
+            start=score.start,
+            length=score.length,
+            score=score.score,
+            text=target[score.start:score.start + score.length],
+        )
 
 class TokenScore(NamedTuple):
     score: float
@@ -275,23 +305,37 @@ def in_pixels(self, prompt_item: PromptItem) -> "ImagePromptItemExplanation":
 
 
 class TextPromptItemExplanation(NamedTuple):
-    scores: List[TextScore]
+    scores: List[Union[TextScore, TextScoreWithRaw]]
 
     @staticmethod
     def from_json(item: Dict[str, Any]) -> "TextPromptItemExplanation":
         return TextPromptItemExplanation(
             scores=[TextScore.from_json(score) for score in item["scores"]]
         )
+
+    def with_text(self, prompt: Text) -> "TextPromptItemExplanation":
+        return TextPromptItemExplanation(
+            scores=[TextScoreWithRaw.from_text_score(score, prompt) if isinstance(score, TextScore) else score for score in self.scores]
+        )
+
 
 
 class TargetPromptItemExplanation(NamedTuple):
-    scores: List[TargetScore]
+    scores: List[Union[TargetScore, TargetScoreWithRaw]]
 
     @staticmethod
     def from_json(item: Dict[str, Any]) -> "TargetPromptItemExplanation":
         return TargetPromptItemExplanation(
             scores=[TargetScore.from_json(score) for score in item["scores"]]
         )
+
+    def with_text(self, prompt: str) -> "TargetPromptItemExplanation":
+        return TargetPromptItemExplanation(
+            scores=[TargetScoreWithRaw.from_target_score(score, prompt) if isinstance(score, TargetScore) else score for score in self.scores]
+        )
+
+
+
 
 
 class TokenPromptItemExplanation(NamedTuple):
@@ -352,6 +396,31 @@ def with_image_prompt_items_in_pixels(self, prompt: Prompt) -> "Explanation":
             ],
         )
 
+    def with_text_from_prompt(self, prompt: Prompt, target: str) -> "Explanation":
+        items: List[Union[
+            TextPromptItemExplanation,
+            ImagePromptItemExplanation,
+            TargetPromptItemExplanation,
+            TokenPromptItemExplanation,
+        ]] = []
+        for item_index, item in enumerate(self.items): 
+            if isinstance(item, TextPromptItemExplanation):
+                # separate variable to fix linting error
+                prompt_item = prompt.items[item_index]
+                if isinstance(prompt_item, Text): 
+                    items.append(item.with_text(prompt_item))
+                else:
+                    items.append(item)
+            elif isinstance(item, TargetPromptItemExplanation):
+                items.append(item.with_text(target))
+            else:
+                items.append(item)
+        return Explanation(
+            target=self.target,
+            items=items,
+        )
+
+
 
 class ExplanationResponse(NamedTuple):
     model_version: str
@@ -375,3 +444,12 @@ def with_image_prompt_items_in_pixels(
             for explanation in self.explanations
         ]
         return ExplanationResponse(self.model_version, mapped_explanations)
+
+    def with_text_from_prompt(
+        self, request: ExplanationRequest
+    ) -> "ExplanationResponse":
+        mapped_explanations = [
+            explanation.with_text_from_prompt(request.prompt, request.target)
+            for explanation in self.explanations
+        ]
+        return ExplanationResponse(self.model_version, mapped_explanations)