gpt-4 / networks /message_outputer.py
Hansimov's picture
:zap: [Enhance] Prettify format of searching queries and results
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import json
import re
class OpenaiStreamOutputer:
"""
Create chat completion - OpenAI API Documentation
* https://platform.openai.com/docs/api-reference/chat/create
"""
def data_to_string(self, data={}, content_type=""):
# return (json.dumps(data) + "\n").encode("utf-8")
data_str = f"{json.dumps(data)}"
return data_str
def output(self, content=None, content_type=None) -> str:
data = {
"created": 1677825464,
"id": "chatcmpl-bing",
"object": "chat.completion.chunk",
# "content_type": content_type,
"model": "bing",
"choices": [],
}
if content_type == "Role":
data["choices"] = [
{
"index": 0,
"delta": {"role": "assistant"},
"finish_reason": None,
}
]
elif content_type == "Completions":
data["choices"] = [
{
"index": 0,
"delta": {"content": content},
"finish_reason": None,
}
]
elif content_type == "InternalSearchQuery":
search_str = f"Searching: [**{content.strip()}**]\n"
data["choices"] = [
{
"index": 0,
"delta": {"content": search_str},
"finish_reason": None,
}
]
elif content_type == "InternalSearchResult":
invocation = content["invocation"]
web_search_results = content["web_search_results"]
matches = re.search('\(query="(.*)"\)', invocation)
if matches:
search_query = matches.group(1)
else:
search_query = invocation
search_str = f"Searching: [**{search_query.strip()}**]"
search_results_str_list = []
for idx, search_result in enumerate(web_search_results):
search_results_str_list.append(
f"{idx+1}. [{search_result['title']}]({search_result['url']})"
)
search_results_str = "\n".join(search_results_str_list)
search_results_str = (
f"<details>\n"
f"<summary>\n{search_str}\n</summary>\n"
f"{search_results_str}\n"
f"</details>\n"
)
data["choices"] = [
{
"index": 0,
"delta": {"content": search_results_str},
"finish_reason": None,
}
]
elif content_type == "SuggestedResponses":
suggestion_texts_str = "\n\n---\n\n**Suggested Questions:**\n"
suggestion_texts_str += "\n".join(f"- {item}" for item in content)
data["choices"] = [
{
"index": 0,
"delta": {"content": suggestion_texts_str},
"finish_reason": None,
}
]
elif content_type == "Finished":
data["choices"] = [
{
"index": 0,
"delta": {},
"finish_reason": "stop",
}
]
else:
data["choices"] = [
{
"index": 0,
"delta": {},
"finish_reason": None,
}
]
return self.data_to_string(data, content_type)