chore: sync sdk code with DeepLearning repo

assemblyai/__version__.py

@@ -1 +1 @@
-__version__ = "0.43.1"
+__version__ = "0.44.2"

assemblyai/streaming/v3/models.py

@@ -60,6 +60,8 @@ class StreamingSessionParameters(BaseModel):
     min_end_of_turn_silence_when_confident: Optional[int] = None
     max_turn_silence: Optional[int] = None
     format_turns: Optional[bool] = None
+    keyterms_prompt: Optional[List[str]] = None
+    filter_profanity: Optional[bool] = None
 
 
 class Encoding(str, Enum):

assemblyai/types.py

@@ -525,6 +525,7 @@ def validate_max_speakers(cls, v, info):
                         "max_speakers_expected must be greater than or equal to min_speakers_expected"
                     )
             return v
+
     else:
 
         @validator("max_speakers_expected")
@@ -1607,6 +1608,7 @@ class Word(BaseModel):
         @field_validator("start", mode="before")
         def set_start_default(cls, v):
             return 0 if v is None else v
+
     else:
 
         @validator("start", pre=True)
@@ -2317,13 +2319,30 @@ class LemurUsage(BaseModel):
     "The number of output tokens generated by the model"
 
 
+class LemurRequestDetails(BaseModel):
+    request_endpoint: str
+    temperature: float
+    final_model: str
+    max_output_size: int
+    created_at: datetime
+    transcript_ids: Optional[List[str]] = None
+    input_text: Optional[str] = None
+    questions: Optional[List[LemurQuestion]] = None
+    prompt: Optional[str] = None
+    context: Optional[Union[dict, str]] = None
+    answer_format: Optional[str] = None
+
+
 class BaseLemurResponse(BaseModel):
     request_id: str
     "The unique identifier of your LeMUR request"
 
     usage: LemurUsage
     "The usage numbers for the LeMUR request"
 
+    request: Optional[LemurRequestDetails] = None
+    "The request details the user passed into the POST request. Optional since this only exists on the GET request."
+
 
 class LemurStringResponse(BaseLemurResponse):
     """

tests/unit/factories.py

@@ -246,6 +246,49 @@ class Meta:
     )
 
 
+class LemurRequestDetails(factory.Factory):
+    class Meta:
+        model = types.LemurRequestDetails
+
+    request_endpoint = factory.Faker("text")
+    temperature = factory.Faker("pyfloat")
+    final_model = factory.Faker("text")
+    max_output_size = factory.Faker("pyint")
+    created_at = factory.Faker("iso8601")
+
+
+class LemurTaskRequestDetails(LemurRequestDetails):
+    """Request details specific to LeMUR task operations"""
+
+    request_endpoint = "/lemur/v3/task"
+    prompt = factory.Faker("text")
+
+
+class LemurSummaryRequestDetails(LemurRequestDetails):
+    """Request details specific to LeMUR summary operations"""
+
+    request_endpoint = "/lemur/v3/summary"
+    context = factory.LazyFunction(lambda: {"key": "value"})
+    answer_format = factory.Faker("sentence")
+
+
+class LemurQuestionRequestDetails(LemurRequestDetails):
+    """Request details specific to LeMUR question-answer operations"""
+
+    request_endpoint = "/lemur/v3/question-answer"
+    questions = [
+        {
+            "question": "What is the main topic?",
+            "answer_format": "short sentence",
+            "context": "Meeting context",
+        },
+        {
+            "question": "What is the sentiment?",
+            "answer_options": ["positive", "negative", "neutral"],
+        },
+    ]
+
+
 class LemurUsage(factory.Factory):
     class Meta:
         model = types.LemurUsage
@@ -310,6 +353,43 @@ class Meta:
     request_id = factory.Faker("uuid4")
     usage = factory.SubFactory(LemurUsage)
     response = factory.Faker("text")
+    request = factory.SubFactory(LemurRequestDetails)
+
+
+# Factories specifically for get_response endpoint tests (include request field)
+class LemurTaskResponseWithRequest(factory.Factory):
+    class Meta:
+        model = types.LemurTaskResponse
+
+    request_id = factory.Faker("uuid4")
+    usage = factory.SubFactory(LemurUsage)
+    response = factory.Faker("text")
+    request = factory.SubFactory(LemurTaskRequestDetails)
+
+
+class LemurSummaryResponseWithRequest(factory.Factory):
+    class Meta:
+        model = types.LemurSummaryResponse
+
+    request_id = factory.Faker("uuid4")
+    usage = factory.SubFactory(LemurUsage)
+    response = factory.Faker("text")
+    request = factory.SubFactory(LemurSummaryRequestDetails)
+
+
+class LemurQuestionResponseWithRequest(factory.Factory):
+    class Meta:
+        model = types.LemurQuestionResponse
+
+    request_id = factory.Faker("uuid4")
+    usage = factory.SubFactory(LemurUsage)
+    response = factory.List(
+        [
+            factory.SubFactory(LemurQuestionAnswer),
+            factory.SubFactory(LemurQuestionAnswer),
+        ]
+    )
+    request = factory.SubFactory(LemurQuestionRequestDetails)
 
 
 class LemurPurgeResponse(factory.Factory):