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import time
import json
from openai import OpenAI
import gradio as gr
class Backend:
def __init__(self):
self.return_instruction = """ Please only return in the following Json format:
{{
"Answer": "",
"Reference Sentences": [""]
}}"""
self.chat_history = []
def load_agent(self, openai_api_key, assistant_id):
client = OpenAI(api_key=openai_api_key)
assistant = client.beta.assistants.retrieve(assistant_id=assistant_id)
return client, assistant
def update_file(self, file_path):
file = open(file_path, 'rb')
file = self.client.files.create(file=file, purpose='assistants')
return file
def create_thread(self):
thread = self.client.beta.threads.create()
return thread
def delate_thread(self, thread):
self.client.beta.threads.delete(thread.id)
def create_message(self, question, thread, file):
message = self.client.beta.threads.messages.create(
thread_id=thread.id,
role="user",
content= question + self.return_instruction,
file_ids=[file.id]
)
return message
def delate_message(self, message):
self.client.beta.threads.messages.delete(message.id)
def create_run(self, thread, assistant):
run = self.client.beta.threads.runs.create(
thread_id=thread.id,
assistant_id=assistant.id,
# instructions="""Please read PDF and answer the qusetions asked by users with professional knowledge."""
)
return run
def delate_run(self, run):
self.client.beta.threads.runs.delete(run.id)
def get_massage(self, thread):
messages = self.client.beta.threads.messages.list(
thread_id=thread.id
)
return messages
def phrase_massage(self, question, messages):
mess = json.loads(messages.json())
output = mess['data'][0]['content'][0]['text']['value']
print(output)
try:
output = output.split("{")[1:]
output = "{" + "".join(output)
output = output.split("}")[:-1]
output = "".join(output) + "}"
print(output)
output = eval(output)
answer = output['Answer']
reference = output['Reference Sentences']
except:
self.detete_message(message)
answer = output
reference = []
reference = ' '.join(reference)
reference = self.processing_html(reference)
self.chat_history.append([question, answer])
return self.chat_history, reference
def phrase_massage_1(self, question, messages):
mess = json.loads(messages.json())
output = mess['data'][0]['content'][0]['text']['value']
self.chat_history.append([question, output])
return self.chat_history
def processing_html(self, text):
return f'<center><p> {text} </p></center>'
def submit_passage(self, openai_key, assistant_id, file):
# Create a new conversation
self.client, self.assistant = self.load_agent(openai_key, assistant_id)
# Update file
self.file = self.update_file(file.name)
# Create a new conversation
self.thread = self.create_thread()
gr.Info("Upload successful. Please can now chat with the assistant. Enjoy!")
def submit_question(self, question):
# print(question)
# print(self.thread.id)
# print(self.file.id)
# Create a new message
self.message = self.create_message(question, self.thread, self.file)
# Create a new run
run = self.create_run(self.thread, self.assistant)
# Wait for the run to complete
while True:
run = self.client.beta.threads.runs.retrieve(thread_id=self.thread.id, run_id=run.id)
if run.status not in ["queued", "in_progress"]:
break
time.sleep(1)
# Get the answer
messages = self.get_massage(self.thread)
answer, reference = self.phrase_massage(question, messages)
return answer, reference
def submit_question_another(self, question):
# Create a new message
self.message = self.create_message(question, self.thread, self.file)
# Create a new run
run = self.create_run(self.thread, self.assistant)
# Wait for the run to complete
while True:
run = self.client.beta.threads.runs.retrieve(thread_id=self.thread.id, run_id=run.id)
if run.status not in ["queued", "in_progress"]:
break
time.sleep(1)
# Get the answer
messages = self.get_massage(self.thread)
answer = self.phrase_massage_1(question, messages)
return answer |