fix(spec, sdk): remove references of Claude 1 and Basic models (#7201)

GitOrigin-RevId: ad669bfbc9b07a31d10cde02894e2b65010e4403

Author: marcusolsson

.github/workflows/test.yml

@@ -19,6 +19,7 @@ jobs:
           - "3.11"
           - "3.10"
           - "3.9"
+          - "3.8"
         os:
           - ubuntu-22.04
     steps:

assemblyai/__version__.py

@@ -1 +1 @@
-__version__ = "0.40.2"
+__version__ = "0.36.0"

assemblyai/types.py

@@ -1,16 +1,6 @@
 from datetime import datetime
 from enum import Enum, EnumMeta
-from typing import (
-    TYPE_CHECKING,
-    Annotated,
-    Any,
-    Dict,
-    List,
-    Optional,
-    Sequence,
-    Tuple,
-    Union,
-)
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Tuple, Union
 from urllib.parse import parse_qs, urlparse
 from warnings import warn
 
@@ -19,13 +9,13 @@
 
 try:
     # pydantic v2 import
-    from pydantic import UUID4, BaseModel, ConfigDict, Field, field_validator
+    from pydantic import UUID4, BaseModel, ConfigDict, Field
     from pydantic_settings import BaseSettings, SettingsConfigDict
 
     pydantic_v2 = True
 except ImportError:
     # pydantic v1 import
-    from pydantic.v1 import UUID4, BaseModel, BaseSettings, ConfigDict, Field, validator
+    from pydantic.v1 import UUID4, BaseModel, BaseSettings, ConfigDict, Field
 
     pydantic_v2 = False
 
@@ -482,12 +472,6 @@ class SpeechModel(str, Enum):
     nano = "nano"
     "A lightweight, lower cost model for a wide range of languages."
 
-    slam_1 = "slam-1"
-    "A Speech Language Model optimized explicitly for speech-to-text tasks"
-
-    universal = "universal"
-    "The model optimized for accuracy, low latency, ease of use, and multi-language support"
-
 
 class RawTranscriptionConfig(BaseModel):
     language_code: Optional[Union[str, LanguageCode]] = None
@@ -600,13 +584,6 @@ class RawTranscriptionConfig(BaseModel):
     """
     The speech model to use for the transcription.
     """
-
-    prompt: Optional[str] = None
-    "The prompt used to generate the transcript with the Slam-1 speech model. Can't be used together with `keyterms_prompt`."
-
-    keyterms_prompt: Optional[List[str]] = None
-    "The list of key terms used to generate the transcript with the Slam-1 speech model. Can't be used together with `prompt`."
-
     model_config = ConfigDict(extra="allow")
 
 
@@ -650,8 +627,6 @@ def __init__(
         speech_threshold: Optional[float] = None,
         raw_transcription_config: Optional[RawTranscriptionConfig] = None,
         speech_model: Optional[SpeechModel] = None,
-        prompt: Optional[str] = None,
-        keyterms_prompt: Optional[List[str]] = None,
     ) -> None:
         """
         Args:
@@ -740,8 +715,6 @@ def __init__(
         self.language_confidence_threshold = language_confidence_threshold
         self.speech_threshold = speech_threshold
         self.speech_model = speech_model
-        self.prompt = prompt
-        self.keyterms_prompt = keyterms_prompt
 
     @property
     def raw(self) -> RawTranscriptionConfig:
@@ -770,26 +743,6 @@ def speech_model(self, speech_model: Optional[SpeechModel]) -> None:
         "Sets the speech model to use for the transcription."
         self._raw_transcription_config.speech_model = speech_model
 
-    @property
-    def prompt(self) -> Optional[str]:
-        "The prompt to use for the transcription."
-        return self._raw_transcription_config.prompt
-
-    @prompt.setter
-    def prompt(self, prompt: Optional[str]) -> None:
-        "Sets the prompt to use for the transcription."
-        self._raw_transcription_config.prompt = prompt
-
-    @property
-    def keyterms_prompt(self) -> Optional[List[str]]:
-        "The keyterms_prompt to use for the transcription."
-        return self._raw_transcription_config.keyterms_prompt
-
-    @keyterms_prompt.setter
-    def keyterms_prompt(self, keyterms_prompt: Optional[List[str]]) -> None:
-        "Sets the prompt to use for the transcription."
-        self._raw_transcription_config.keyterms_prompt = keyterms_prompt
-
     @property
     def punctuate(self) -> Optional[bool]:
         "Returns the status of the Automatic Punctuation feature."
@@ -1471,19 +1424,6 @@ class Word(BaseModel):
     speaker: Optional[str] = None
     channel: Optional[str] = None
 
-    # This is a workaround to address an issue where sentiment_analysis_results
-    # may return contains sentiments where `start` is null.
-    if pydantic_v2:
-
-        @field_validator("start", mode="before")
-        def set_start_default(cls, v):
-            return 0 if v is None else v
-    else:
-
-        @validator("start", pre=True)
-        def set_start_default(cls, v):
-            return 0 if v is None else v
-
 
 class UtteranceWord(Word):
     channel: Optional[str] = None
@@ -1765,12 +1705,6 @@ class BaseTranscript(BaseModel):
     speech_model: Optional[SpeechModel] = None
     "The speech model to use for the transcription."
 
-    prompt: Optional[str] = None
-    "The prompt used to generate the transcript with the Slam-1 speech model. Can't be used together with `keyterms_prompt`."
-
-    keyterms_prompt: Optional[List[str]] = None
-    "The list of key terms used to generate the transcript with the Slam-1 speech model. Can't be used together with `prompt`."
-
 
 class TranscriptRequest(BaseTranscript):
     """
@@ -1836,12 +1770,6 @@ class TranscriptResponse(BaseTranscript):
     speech_model: Optional[SpeechModel] = None
     "The speech model used for the transcription"
 
-    prompt: Optional[str] = None
-    "When Slam-1 is enabled, the prompt used to generate the transcript"
-
-    keyterms_prompt: Optional[List[str]] = None
-    "When Slam-1 is enabled, the list of key terms used to generate the transcript"
-
     def __init__(self, **data: Any):
         # cleanup the response before creating the object
         if not data.get("iab_categories_result") or (
@@ -1879,14 +1807,8 @@ class ListTranscriptParameters(BaseModel):
     status: Optional[TranscriptStatus] = None
     "Filter by transcript status"
 
-    throttled_only: Annotated[
-        Optional[bool],
-        Field(
-            deprecated="`throttled_only` is deprecated and will be removed in a future release.",
-        ),
-    ] = None
+    throttled_only: Optional[bool] = None
     "Get only throttled transcripts, overrides the status filter"
-
     model_config = ConfigDict(use_enum_values=True)
 
 
@@ -2047,29 +1969,19 @@ class LemurModel(str, Enum):
     LeMUR features different model modes that allow you to configure your request to suit your needs.
     """
 
-    claude3_7_sonnet_20250219 = "anthropic/claude-3-7-sonnet-20250219"
-    """
-    Claude 3.7 Sonnet is the most intelligent model to date, providing the highest level of intelligence and capability with toggleable extended thinking.
-    """
-
     claude3_5_sonnet = "anthropic/claude-3-5-sonnet"
     """
-    Claude 3.5 Sonnet is the previous most intelligent model to date, providing high level of intelligence and capability.
+    Claude 3.5 Sonnet is the most intelligent model to date, outperforming Claude 3 Opus on a wide range of evaluations, with the speed and cost of Claude 3 Sonnet.
     """
 
     claude3_opus = "anthropic/claude-3-opus"
     """
     Claude 3 Opus is good at handling complex analysis, longer tasks with many steps, and higher-order math and coding tasks.
     """
 
-    claude3_5_haiku_20241022 = "anthropic/claude-3-5-haiku-20241022"
-    """
-    Claude 3.5 Haiku is the fastest model, providing intelligence at blazing speeds.
-    """
-
     claude3_haiku = "anthropic/claude-3-haiku"
     """
-    Claude 3 Haiku is the fastest and most compact model for near-instant responsiveness.
+    Claude 3 Haiku is the fastest model that can execute lightweight actions.
     """
 
     claude3_sonnet = "anthropic/claude-3-sonnet"

tests/unit/test_sentiment_analysis.py

@@ -76,33 +76,3 @@ def test_sentiment_analysis_enabled(httpx_mock: HTTPXMock):
         assert (
             transcript_sentiment_result.speaker == response_sentiment_result["speaker"]
         )
-
-
-def test_sentiment_analysis_null_start(httpx_mock: HTTPXMock):
-    """
-    Tests that `start` converts null values to 0.
-    """
-    mock_response = {
-        "audio_url": "https://example/audio.mp3",
-        "status": "completed",
-        "sentiment_analysis_results": [
-            {
-                "text": "hi",
-                "start": None,
-                "end": 100,
-                "confidence": 0.99,
-                "sentiment": "POSITIVE",
-            }
-        ],
-    }
-    request_body, transcript = unit_test_utils.submit_mock_transcription_request(
-        httpx_mock,
-        mock_response=mock_response,
-        config=aai.TranscriptionConfig(sentiment_analysis=True),
-    )
-
-    for response_sentiment_result, transcript_sentiment_result in zip(
-        mock_response["sentiment_analysis_results"],
-        transcript.sentiment_analysis,
-    ):
-        assert transcript_sentiment_result.start == 0