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First implementation of streamlit chat app in gui folder

This commit is contained in:
noptuno 2023-04-27 19:18:41 -04:00
parent 952f7dbee9
commit 194acff111

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@ -101,63 +101,3 @@ def query(user_input: str, selected_method: str = "Random") -> str:
__all__ = ['query', 'avail_query_methods']
# def query_ora(question:str)->str:
# result =""
# try:
# gpt4_chatbot_ids = ['b8b12eaa-5d47-44d3-92a6-4d706f2bcacf', 'fbe53266-673c-4b70-9d2d-d247785ccd91', 'bd5781cf-727a-45e9-80fd-a3cfce1350c6', '993a0102-d397-47f6-98c3-2587f2c9ec3a', 'ae5c524e-d025-478b-ad46-8843a5745261', 'cc510743-e4ab-485e-9191-76960ecb6040', 'a5cd2481-8e24-4938-aa25-8e26d6233390', '6bca5930-2aa1-4bf4-96a7-bea4d32dcdac', '884a5f2b-47a2-47a5-9e0f-851bbe76b57c', 'd5f3c491-0e74-4ef7-bdca-b7d27c59e6b3', 'd72e83f6-ef4e-4702-844f-cf4bd432eef7', '6e80b170-11ed-4f1a-b992-fd04d7a9e78c', '8ef52d68-1b01-466f-bfbf-f25c13ff4a72', 'd0674e11-f22e-406b-98bc-c1ba8564f749', 'a051381d-6530-463f-be68-020afddf6a8f', '99c0afa1-9e32-4566-8909-f4ef9ac06226', '1be65282-9c59-4a96-99f8-d225059d9001', 'dba16bd8-5785-4248-a8e9-b5d1ecbfdd60', '1731450d-3226-42d0-b41c-4129fe009524', '8e74635d-000e-4819-ab2c-4e986b7a0f48', 'afe7ed01-c1ac-4129-9c71-2ca7f3800b30', 'e374c37a-8c44-4f0e-9e9f-1ad4609f24f5']
# chatbot_id = random.choice(gpt4_chatbot_ids)
# model = ora.CompletionModel.load(chatbot_id, 'gpt-4')
# response = ora.Completion.create(model, question)
# result = response.completion.choices[0].text
# except Exception as e:
# print(f"Error : {e}")
# result = "😵 Sorry, some error occurred please try again."
# return result
# def query_writesonic(question:str)->str:
# account = writesonic.Account.create(logging = False)
# response = writesonic.Completion.create(
# api_key = account.key,
# prompt = question,
# )
# return response.completion.choices[0].text
# def query_t3nsor(question: str) -> str:
# messages = []
# user = question
# t3nsor_cmpl = t3nsor.Completion.create(
# prompt=user,
# messages=messages
# )
# messages.extend([
# {'role': 'user', 'content': user},
# {'role': 'assistant', 'content': t3nsor_cmpl.completion.choices[0].text}
# ])
# return t3nsor_cmpl.completion.choices[0].text
# def query_phind(question:str)->str:
# phind.cf_clearance = 'KvXc1rh.TFQG1rNF0eMlcpJbsdmJkYgvmqS42OOfqUk-1682393898-0-160'
# # phind.cf_clearance = 'heguhSRBB9d0sjLvGbQECS8b80m2BQ31xEmk9ChshKI-1682268995-0-160'
# # phind.user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36'
# phind.user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.4.1 Safari/605.1.15'
# result = phind.Completion.create(
# model = 'gpt-4',
# prompt = question,
# results = phind.Search.create(question, actualSearch = False),
# creative = False,
# detailed = False,
# codeContext = '')
# # print(result.completion.choices[0].text)
# return result.completion.choices[0].text