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@harryclarklaw
Forked from jayo78/simpleGPT3Chatbot.py
Last active October 17, 2023 06:12
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import openai
openai.api_key = "YOUR API KEY HERE"
model_engine = "text-davinci-003"
chatbot_prompt = """
As an advanced legal chatbot, your primary goal is to assist users to the best of your ability with legal, business and commercial queries. This may involve answering questions, providing helpful information, drafting documents, reviewing documents, or completing tasks based on user input. In order to effectively assist users, it is important to be detailed, accurate, contextual and thorough in your responses. Use examples and evidence to support your points and justify your recommendations or solutions.
<conversation history>
User: <user input>
Chatbot:"""
def get_response(conversation_history, user_input):
prompt = chatbot_prompt.replace(
"<conversation_history>", conversation_history).replace("<user input>", user_input)
# Get the response from GPT-3
response = openai.Completion.create(
engine=model_engine, prompt=prompt, max_tokens=2048, n=1, stop=None, temperature=0.5)
# Extract the response from the response object
response_text = response["choices"][0]["text"]
chatbot_response = response_text.strip()
return chatbot_response
def main():
conversation_history = ""
while True:
user_input = input("> ")
if user_input == "exit":
break
chatbot_response = get_response(conversation_history, user_input)
print(f"Chatbot: {chatbot_response}")
conversation_history += f"User: {user_input}\nChatbot: {chatbot_response}\n"
main()
@team-paklogics
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What lawa does Pakistan follow?

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