gpt-4 / networks /message_parser.py
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:zap: [Enhance] OpenAI API to bing chat: Fix suggestions output, and unnecessary data line
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from utils.logger import logger
from networks import OpenaiStreamOutputer
class MessageParser:
def __init__(self, outputer=OpenaiStreamOutputer()):
self.delta_content_pointer = 0
self.outputer = outputer
def parse(self, data, return_output=False):
arguments = data["arguments"][0]
if arguments.get("throttling"):
throttling = arguments.get("throttling")
# pprint.pprint(throttling)
if arguments.get("messages"):
for message in arguments.get("messages"):
message_type = message.get("messageType")
# Message: Displayed answer
if message_type is None:
content = message["adaptiveCards"][0]["body"][0]["text"]
delta_content = content[self.delta_content_pointer :]
logger.line(delta_content, end="")
self.delta_content_pointer = len(content)
# Message: Suggested Questions
if message.get("suggestedResponses"):
logger.note("\nSuggested Questions: ")
suggestion_texts = [
suggestion.get("text")
for suggestion in message.get("suggestedResponses")
]
for suggestion_text in suggestion_texts:
logger.file(f"- {suggestion_text}")
if return_output:
completions_output = self.outputer.output(
delta_content, content_type="Completions"
)
if message.get("suggestedResponses"):
suggestion_texts_str = "\nSuggested Questions:\n"
suggestion_texts_str += "\n".join(
f"- {item}" for item in suggestion_texts
)
suggestions_output = self.outputer.output(
suggestion_texts_str,
content_type="SuggestedResponses",
)
return [completions_output, suggestions_output]
else:
return completions_output
# Message: Search Query
elif message_type in ["InternalSearchQuery"]:
message_hidden_text = message["hiddenText"]
search_str = f"[Searching: [{message_hidden_text}]]"
logger.note(search_str)
if return_output:
return self.outputer.output(
search_str, content_type="InternalSearchQuery"
)
# Message: Internal Search Results
elif message_type in ["InternalSearchResult"]:
analysis_str = f"[Analyzing search results ...]"
logger.note(analysis_str)
if return_output:
return self.outputer.output(
analysis_str, content_type="InternalSearchResult"
)
# Message: Loader status, such as "Generating Answers"
elif message_type in ["InternalLoaderMessage"]:
# logger.note("[Generating answers ...]\n")
pass
# Message: Internal thoughts, such as "I will generate my response to the user message"
elif message_type in ["Internal"]:
pass
# Message: Internal Action Marker, no value
elif message_type in ["InternalActionMarker"]:
continue
# Message: Render Cards for Webpages
elif message_type in ["RenderCardRequest"]:
continue
elif message_type in ["ChatName"]:
continue
# Message: Not Implemented
else:
raise NotImplementedError(
f"Not Supported Message Type: {message_type}"
)
return self.outputer.output(content="", content_type="NotImplemented")