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•
d378f2a
1
Parent(s):
d5b5de9
removed system from gpt
Browse files
app.py
CHANGED
@@ -20,20 +20,18 @@ def update_api_key(new_key):
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os.environ['OPENAI_API_TOKEN'] = new_key
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openai.api_key = os.environ['OPENAI_API_TOKEN']
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-
def chat(
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''' Normal call of OpenAI API '''
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response = openai.ChatCompletion.create(
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temperature = temperature,
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model=model,
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messages=[
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-
{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt}
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])
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res = response['choices'][0]['message']['content']
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if verbose:
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-
print('System prompt:', system_prompt)
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print('User prompt:', user_prompt)
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print('GPT response:', res)
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@@ -52,10 +50,9 @@ def gpt_respond(have_key, tab_name, message, chat_history, max_convo_length = 10
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return "", chat_history
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formatted_prompt = format_chat_prompt(message, chat_history, max_convo_length)
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-
print('Prompt + Context:')
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print(formatted_prompt)
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bot_message = chat(
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user_prompt = formatted_prompt)
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chat_history.insert(0, (message, bot_message))
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return "", chat_history
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@@ -117,10 +114,9 @@ def gpt_strategies_respond(have_key, strategy, task_name, task_ling_ent, message
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formatted_system_prompt = f'''"{demon_chunk}". Using the POS tag structure above, POS tag the following sentence: "{message}"'''
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formatted_prompt = format_chat_prompt(message, chat_history, max_convo_length)
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print('Prompt + Context:')
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print(formatted_prompt)
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bot_message = chat(
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user_prompt = formatted_prompt)
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chat_history.insert(0, (message, bot_message))
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return "", chat_history
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@@ -251,12 +247,12 @@ def interface():
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outputs=[ling_ents_prompt, gpt_ling_ents_chatbot])
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# Event Handler for LLaMA Chatbot
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ling_ents_btn.click(llama_respond, inputs=[linguistic_entities, ling_ents_prompt, llama_ling_ents_chatbot],
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-
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# Event Handler for Vicuna Chatbot
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ling_ents_btn.click(vicuna_respond, inputs=[linguistic_entities, ling_ents_prompt, vicuna_ling_ents_chatbot],
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-
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with gr.Tab("CoreNLP"):
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with gr.Row():
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@@ -349,8 +345,8 @@ def interface():
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# outputs=[task, task_prompt, llama_S1_chatbot])
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# task_btn.click(llama_strategies_respond, inputs=[strategy2, task, task_linguistic_entities, task_prompt, llama_S2_chatbot],
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# outputs=[task, task_prompt, llama_S2_chatbot])
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task_btn.click(llama_strategies_respond, inputs=[strategy3, task, task_linguistic_entities, task_prompt, llama_S3_chatbot],
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-
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# vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_history):
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# Event Handlers for Vicuna Chatbot POS/Chunk
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@@ -358,8 +354,8 @@ def interface():
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# outputs=[task, task_prompt, vicuna_S1_chatbot])
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# task_btn.click(vicuna_strategies_respond, inputs=[strategy2, task, task_linguistic_entities, task_prompt, vicuna_S2_chatbot],
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# outputs=[task, task_prompt, vicuna_S2_chatbot])
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task_btn.click(vicuna_strategies_respond, inputs=[strategy3, task, task_linguistic_entities, task_prompt, vicuna_S3_chatbot],
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-
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("""
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os.environ['OPENAI_API_TOKEN'] = new_key
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openai.api_key = os.environ['OPENAI_API_TOKEN']
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+
def chat(user_prompt, model = 'gpt-3.5-turbo', temperature = 0, verbose = False):
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''' Normal call of OpenAI API '''
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response = openai.ChatCompletion.create(
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temperature = temperature,
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model=model,
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messages=[
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{"role": "user", "content": user_prompt}
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])
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res = response['choices'][0]['message']['content']
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if verbose:
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print('User prompt:', user_prompt)
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print('GPT response:', res)
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return "", chat_history
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formatted_prompt = format_chat_prompt(message, chat_history, max_convo_length)
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print('GPT ling ents Prompt + Context:')
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print(formatted_prompt)
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bot_message = chat(user_prompt = f'''Generate the output only for the assistant. Output any <{tab_name}> in the following sentence one per line: "{formatted_prompt}"''')
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chat_history.insert(0, (message, bot_message))
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return "", chat_history
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formatted_system_prompt = f'''"{demon_chunk}". Using the POS tag structure above, POS tag the following sentence: "{message}"'''
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formatted_prompt = format_chat_prompt(message, chat_history, max_convo_length)
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print('GPT coreNLP Prompt + Context:')
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print(formatted_prompt)
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bot_message = chat(user_prompt = formatted_system_prompt)
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chat_history.insert(0, (message, bot_message))
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return "", chat_history
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outputs=[ling_ents_prompt, gpt_ling_ents_chatbot])
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# Event Handler for LLaMA Chatbot
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# ling_ents_btn.click(llama_respond, inputs=[linguistic_entities, ling_ents_prompt, llama_ling_ents_chatbot],
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# outputs=[linguistic_entities, ling_ents_prompt, llama_ling_ents_chatbot])
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# Event Handler for Vicuna Chatbot
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# ling_ents_btn.click(vicuna_respond, inputs=[linguistic_entities, ling_ents_prompt, vicuna_ling_ents_chatbot],
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# outputs=[linguistic_entities, ling_ents_prompt, vicuna_ling_ents_chatbot])
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with gr.Tab("CoreNLP"):
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with gr.Row():
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# outputs=[task, task_prompt, llama_S1_chatbot])
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# task_btn.click(llama_strategies_respond, inputs=[strategy2, task, task_linguistic_entities, task_prompt, llama_S2_chatbot],
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# outputs=[task, task_prompt, llama_S2_chatbot])
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# task_btn.click(llama_strategies_respond, inputs=[strategy3, task, task_linguistic_entities, task_prompt, llama_S3_chatbot],
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# outputs=[task, task_prompt, llama_S3_chatbot])
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# vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_history):
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# Event Handlers for Vicuna Chatbot POS/Chunk
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# outputs=[task, task_prompt, vicuna_S1_chatbot])
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# task_btn.click(vicuna_strategies_respond, inputs=[strategy2, task, task_linguistic_entities, task_prompt, vicuna_S2_chatbot],
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# outputs=[task, task_prompt, vicuna_S2_chatbot])
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# task_btn.click(vicuna_strategies_respond, inputs=[strategy3, task, task_linguistic_entities, task_prompt, vicuna_S3_chatbot],
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# outputs=[task, task_prompt, vicuna_S3_chatbot])
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("""
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