🌿 Fern Regeneration -- November 6, 2024 (#211)

Co-authored-by: fern-api <115122769+fern-api[bot]@users.noreply.github.com>
Co-authored-by: twitchard <richard.marmorstein@gmail.com>

.mock/definition/empathic-voice/__package__.yml

@@ -1070,8 +1070,12 @@ types:
     enum:
       - value: claude-3-5-sonnet-latest
         name: Claude35SonnetLatest
+      - value: claude-3-5-haiku-latest
+        name: Claude35HaikuLatest
       - value: claude-3-5-sonnet-20240620
         name: Claude35Sonnet20240620
+      - value: claude-3-5-haiku-20241022
+        name: Claude35Haiku20241022
       - value: claude-3-opus-20240229
         name: Claude3Opus20240229
       - value: claude-3-sonnet-20240229
@@ -3086,6 +3090,23 @@ types:
           from a [User
           Input](/reference/empathic-voice-interface-evi/chat/chat#send.User%20Input.text)
           message.
+      interim:
+        type: boolean
+        docs: >-
+          Indicates if this message contains an immediate and unfinalized
+          transcript of the user’s audio input. If it does, words may be
+          repeated across successive `UserMessage` messages as our transcription
+          model becomes more confident about what was said with additional
+          context. Interim messages are useful to detect if the user is
+          interrupting during audio playback on the client. Even without a
+          finalized transcription, along with
+          [UserInterrupt](/reference/empathic-voice-interface-evi/chat/chat#receive.User%20Interruption.type)
+          messages, interim `UserMessages` are useful for detecting if the user
+          is interrupting during audio playback on the client, signaling to stop
+          playback in your application. Interim `UserMessages` will only be
+          received if the
+          [verbose_transcription](/reference/empathic-voice-interface-evi/chat/chat#request.query.verbose_transcription)
+          query parameter is set to `true` in the handshake request.
     source:
       openapi: assistant-asyncapi.json
   JsonMessage:

.mock/definition/empathic-voice/chat.yml

@@ -74,6 +74,16 @@ channel:
         Use the GET `/v0/evi/chat_groups` endpoint to obtain the Chat Group IDs
         of all Chat Groups associated with an API key. This endpoint returns a
         list of all available chat groups.
+    verbose_transcription:
+      type: optional<boolean>
+      docs: >-
+        A flag to enable verbose transcription. Set this query parameter to
+        `true` to have unfinalized user transcripts be sent to the client as
+        interim UserMessage messages. The
+        [interim](/reference/empathic-voice-interface-evi/chat/chat#receive.User%20Message.interim)
+        field on a
+        [UserMessage](/reference/empathic-voice-interface-evi/chat/chat#receive.User%20Message.type)
+        denotes whether the message is "interim" or "final."
     access_token:
       type: optional<string>
       docs: >-

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "hume"
-version = "0.7.4"
+version = "0.7.5"
 description = "A Python SDK for Hume AI"
 readme = "README.md"
 authors = []

src/hume/empathic_voice/chat/socket_client.py

@@ -44,6 +44,10 @@ class ChatConnectOptions(typing.TypedDict, total=False):
 
     secret_key: typing.Optional[str]
 
+    resumed_chat_group_id: typing.Optional[str]
+
+    verbose_transcription: typing.Optional[bool]
+
 
 class ChatWebsocketConnection:
     DEFAULT_NUM_CHANNELS: typing.ClassVar[int] = 1
@@ -204,6 +208,16 @@ async def _construct_ws_uri(self, options: typing.Optional[ChatConnectOptions]):
                 query_params = query_params.add(
                     "config_version", maybe_config_version
                 )
+            maybe_resumed_chat_group_id = options.get("resumed_chat_group_id")
+            if maybe_resumed_chat_group_id is not None:
+                query_params = query_params.add(
+                    "resumed_chat_group_id", maybe_resumed_chat_group_id
+                )
+            maybe_verbose_transcription = options.get("verbose_transcription")
+            if maybe_verbose_transcription is not None:
+                query_params = query_params.add(
+                    "verbose_transcription", "true" if maybe_verbose_transcription else "false"
+                )
             maybe_secret_key = options.get("secret_key")
             if maybe_secret_key is not None and api_key is not None:
                 query_params = query_params.add(

src/hume/empathic_voice/types/return_language_model_model_resource.py

@@ -5,7 +5,9 @@
 ReturnLanguageModelModelResource = typing.Union[
     typing.Literal[
         "claude-3-5-sonnet-latest",
+        "claude-3-5-haiku-latest",
         "claude-3-5-sonnet-20240620",
+        "claude-3-5-haiku-20241022",
         "claude-3-opus-20240229",
         "claude-3-sonnet-20240229",
         "claude-3-haiku-20240307",

src/hume/empathic_voice/types/user_message.py

@@ -46,6 +46,11 @@ class UserMessage(UniversalBaseModel):
     Indicates if this message was inserted into the conversation as text from a [User Input](/reference/empathic-voice-interface-evi/chat/chat#send.User%20Input.text) message.
     """
 
+    interim: bool = pydantic.Field()
+    """
+    Indicates if this message contains an immediate and unfinalized transcript of the user’s audio input. If it does, words may be repeated across successive `UserMessage` messages as our transcription model becomes more confident about what was said with additional context. Interim messages are useful to detect if the user is interrupting during audio playback on the client. Even without a finalized transcription, along with [UserInterrupt](/reference/empathic-voice-interface-evi/chat/chat#receive.User%20Interruption.type) messages, interim `UserMessages` are useful for detecting if the user is interrupting during audio playback on the client, signaling to stop playback in your application. Interim `UserMessages` will only be received if the [verbose_transcription](/reference/empathic-voice-interface-evi/chat/chat#request.query.verbose_transcription) query parameter is set to `true` in the handshake request.
+    """
+
     if IS_PYDANTIC_V2:
         model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow", frozen=True)  # type: ignore # Pydantic v2
     else: