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import gradio as gr
from gradio.components import Textbox
import requests
from requests.structures import CaseInsensitiveDict
import time
MAX_QUESTIONS_COUNT = 25
MAX_TAGS_COUNT = 5
MAX_ATTEMPS = 3
WAIT_TIME = 3
CHATGPT_URL = "https://free.churchless.tech/v1/chat/completions"
def get_answer(question):
headers = CaseInsensitiveDict()
headers["Content-Type"] = "application/json; charset=utf-8"
data = """
{{
"model": "gpt-3.5-turbo",
"messages": [
{{
"role": "user",
"content": "{}"
}}
]
}}
""".format(question).encode('utf-8')
try:
response = requests.post(CHATGPT_URL, headers=headers, data=data)
return {
'status': True,
'content': response.json()['choices'][0]['message']['content']
}
except:
return {
'status': False,
}
def format_results(results):
output = ""
for i, (question, answer) in enumerate(results):
output += f"Question №{i+1}: {question}\n"
output += f"Answer: {answer}\n"
if i < len(results) - 1:
output += "--------------------------------------\n\n"
output = output.strip()
return output
def find_answers(tags, questions):
tags = tags.split('\n')
questions = questions.split('\n')
if len(tags) == 0:
raise gr.Error("Validation error. It is necessary to set at least one tag")
if len(tags) > MAX_TAGS_COUNT:
raise gr.Error(f"Validation error. The maximum allowed number of tags is {MAX_TAGS_COUNT}.")
if len(questions) == 0:
raise gr.Error("Validation error. It is necessary to ask at least one question")
if len(questions) > MAX_QUESTIONS_COUNT:
raise gr.Error(f"Validation error. The maximum allowed number of questions is {MAX_QUESTIONS_COUNT}.")
configured_tags = ['[' + tag + ']' for tag in tags]
results = []
for question in questions:
tagged_question = ''.join(configured_tags) + ' ' + question
attempt = 0
while attempt < MAX_ATTEMPS:
answer = get_answer(tagged_question)
if answer['status']:
results.append((question, answer['content']))
break
else:
attempt += 1
if attempt == MAX_ATTEMPS:
results.append((question, 'An error occurred while receiving data.'))
else:
time.sleep(WAIT_TIME)
continue
return format_results(results)
inputs = [
Textbox(label="Enter tags (each line is a separate tag). Maximum: 5.", lines=5),
Textbox(label="Enter questions (each line is a separate question). Maximum 25.", lines=25)
]
outputs = [
Textbox(label="Answers")
]
gradio_interface = gr.Interface(fn=find_answers, inputs=inputs, outputs=outputs)
gradio_interface.launch() |