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Update app.py
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app.py
CHANGED
@@ -3,14 +3,11 @@ import tiktoken
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import datetime
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import json
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import time
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import os
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openai.api_key = os.getenv('API_KEY')
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openai.request_times = 0
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all_dialogue = []
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def ask(question, history, behavior):
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openai.request_times += 1
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print(f"request times {openai.request_times}: {datetime.datetime.now()}: {question}")
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@@ -37,7 +34,6 @@ def ask(question, history, behavior):
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print(e)
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response = 'Timeout! Please wait a few minutes and retry'
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history = history + [question, response]
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record_dialogue(history)
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return history
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def num_tokens_from_messages(messages, model="gpt-3.5-turbo"):
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@@ -68,65 +64,54 @@ def forget_long_term(messages, max_num_tokens=4000):
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messages = messages[1:]
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return messages
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def record_dialogue(history):
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dialogue = json.dumps(history, ensure_ascii=False)
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for i in range(len(all_dialogue)):
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if dialogue[1:-1].startswith(all_dialogue[i][1:-1]):
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all_dialogue[i] = dialogue
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return
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all_dialogue.append(dialogue)
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return
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import gradio as gr
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def to_md(content):
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is_inside_code_block = False
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count_backtick = 0
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output_spans = []
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for i in range(len(content)):
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if content[i]=="\n":
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if
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output_spans.append("
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else:
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output_spans.append("
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elif content[i]=="`":
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count_backtick += 1
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if count_backtick == 3:
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count_backtick = 0
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is_inside_code_block = not is_inside_code_block
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output_spans.append(content[i])
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else:
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output_spans.append(content[i])
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return "".join(output_spans)
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def predict(question, history=[], behavior=[]):
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if question.startswith(f"{openai.api_key}:"):
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return adminInstruct(question, history)
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history = ask(question, history, behavior)
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response = [(to_md(history[i]),to_md(history[i+1])) for i in range(0,len(history)-1,2)]
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return "", history, response
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def retry(question, history=[], behavior=[]):
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if len(history)<2:
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return "", history, [], gr.File.update(value=None, visible=False)
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question = history[-2]
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history = history[:-2]
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return predict(question, history, behavior)
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def adminInstruct(question, history):
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if "download all dialogue" in question:
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filename = f"./all_dialogue_{len(all_dialogue)}.jsonl"
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with open(filename, "w", encoding="utf-8") as f:
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for dialogue in all_dialogue:
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f.write(dialogue + "\n")
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response = [(to_md(history[i]),to_md(history[i+1])) for i in range(0,len(history)-1,2)]
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return "", history, response, gr.File.update(value=filename, visible=True)
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return "", history, response, gr.File.update(value=None, visible=False)
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with gr.Blocks() as demo:
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@@ -173,15 +158,12 @@ with gr.Blocks() as demo:
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txt = gr.Textbox(show_label=False, placeholder="输入你想让ChatGPT回答的问题").style(container=False)
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with gr.Row():
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button_gen = gr.Button("Submit")
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button_rtr = gr.Button("Retry")
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button_clr = gr.Button("Clear")
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downloadfile = gr.File(None, interactive=False, show_label=False, visible=False)
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gr.Examples(examples=examples_bhv, inputs=bhv, label="Examples for setting behavior")
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gr.Examples(examples=examples_txt, inputs=txt, label="Examples for asking question")
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txt.submit(predict, [txt, state, behavior], [txt, state, chatbot])
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button_gen.click(fn=predict, inputs=[txt, state, behavior], outputs=[txt, state, chatbot
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button_rtr.click(fn=retry, inputs=[txt, state, behavior], outputs=[txt, state, chatbot, downloadfile])
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button_clr.click(fn=lambda :([],[]), inputs=None, outputs=[chatbot, state])
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demo.queue(concurrency_count=3, max_size=10)
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import datetime
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import json
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import os
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openai.api_key = os.getenv('API_KEY')
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openai.request_times = 0
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def ask(question, history, behavior):
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openai.request_times += 1
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print(f"request times {openai.request_times}: {datetime.datetime.now()}: {question}")
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print(e)
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response = 'Timeout! Please wait a few minutes and retry'
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history = history + [question, response]
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return history
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def num_tokens_from_messages(messages, model="gpt-3.5-turbo"):
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messages = messages[1:]
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return messages
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import gradio as gr
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def to_md(content):
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is_inside_code_block = False
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output_spans = []
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for i in range(len(content)):
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if content[i]=="\n" and not is_inside_code_block:
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if len(output_spans)>0 and output_spans[-1].endswith("```"):
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output_spans.append("\n")
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else:
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output_spans.append("<br>")
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elif content[i]=="`":
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output_spans.append(content[i])
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if len(output_spans)>=3 and all([output_spans[j]=="`" for j in [-3,-2,-1]]):
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is_inside_code_block = not is_inside_code_block
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output_spans = output_spans[:-3]
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if is_inside_code_block:
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if len(output_spans)==0:
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output_spans.append("```")
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elif output_spans[-1]=="<br>":
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output_spans[-1] = "\n"
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output_spans.append("```")
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elif output_spans[-1].endswith("\n"):
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output_spans.append("```")
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else:
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output_spans.append("\n```")
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if i+1<len(content) and content[i+1]!="\n":
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output_spans.append("\n")
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else:
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if output_spans[-1].endswith("\n"):
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output_spans.append("```")
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else:
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output_spans.append("\n```")
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if i+1<len(content) and content[i+1]!="\n":
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output_spans.append("\n")
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else:
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output_spans.append(content[i])
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return "".join(output_spans)
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def predict(question, history=[], behavior=[]):
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history = ask(question, history, behavior)
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response = [(to_md(history[i]),to_md(history[i+1])) for i in range(0,len(history)-1,2)]
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return "", history, response
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with gr.Blocks() as demo:
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txt = gr.Textbox(show_label=False, placeholder="输入你想让ChatGPT回答的问题").style(container=False)
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with gr.Row():
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button_gen = gr.Button("Submit")
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button_clr = gr.Button("Clear")
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gr.Examples(examples=examples_bhv, inputs=bhv, label="Examples for setting behavior")
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gr.Examples(examples=examples_txt, inputs=txt, label="Examples for asking question")
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txt.submit(predict, [txt, state, behavior], [txt, state, chatbot])
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button_gen.click(fn=predict, inputs=[txt, state, behavior], outputs=[txt, state, chatbot])
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button_clr.click(fn=lambda :([],[]), inputs=None, outputs=[chatbot, state])
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demo.queue(concurrency_count=3, max_size=10)
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