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updates and chat hack

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This commit is contained in:
Chad Bailey
2024-02-15 19:49:46 +00:00
parent 0cae54e79e
commit 5a47a3d5cd
6 changed files with 59 additions and 23 deletions
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24
src/dailyai/queue_aggregators.py
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@@ -61,28 +61,38 @@ class LLMContextAggregator(AIService):
# TODO: split up transcription by participant
if self.complete_sentences:
self.sentence += frame.text # type: ignore -- the linter thinks this isn't a TextQueueFrame, even though we check it above
# type: ignore -- the linter thinks this isn't a TextQueueFrame, even though we check it above
self.sentence += frame.text
if self.sentence.endswith((".", "?", "!")):
self.messages.append({"role": self.role, "content": self.sentence})
self.messages.append(
{"role": self.role, "content": self.sentence})
self.sentence = ""
for message in self.messages:
print(f"{message['role']}: {message['content']}")
yield LLMMessagesQueueFrame(self.messages)
else:
self.messages.append({"role": self.role, "content": frame.text}) # type: ignore -- the linter thinks this isn't a TextQueueFrame, even though we check it above
# type: ignore -- the linter thinks this isn't a TextQueueFrame, even though we check it above
self.messages.append({"role": self.role, "content": frame.text})
for message in self.messages:
print(f"{message['role']}: {message['content']}")
yield LLMMessagesQueueFrame(self.messages)
async def finalize(self) -> AsyncGenerator[QueueFrame, None]:
# Send any dangling words that weren't finished with punctuation.
if self.complete_sentences and self.sentence:
self.messages.append({"role": self.role, "content": self.sentence})
for message in self.messages:
print(f"{message['role']}: {message['content']}")
yield LLMMessagesQueueFrame(self.messages)
class LLMUserContextAggregator(LLMContextAggregator):
def __init__(self,
messages: list[dict],
bot_participant_id=None,
complete_sentences=True):
super().__init__(messages, "user", bot_participant_id, complete_sentences, pass_through=False)
messages: list[dict],
bot_participant_id=None,
complete_sentences=True):
super().__init__(messages, "user", bot_participant_id,
complete_sentences, pass_through=False)
class LLMAssistantContextAggregator(LLMContextAggregator):