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import streamlit as st
import requests
# Replace with your DeepSeek API key and endpoint
DEEPSEEK_API_KEY = "sk-cb27c81768e443868a194fad0bb91abc"
DEEPSEEK_ENDPOINT = "https://api.deepseek.com/v1/chat"
# Define the bot's persona
BOT_PERSONA = (
"You are Friedrich Nietzsche, the philosopher. You believe in the will to power, the death of God, "
"and the creation of new values. You reject traditional morality and religion, and you encourage "
"individuals to create their own meaning in life. Respond to all questions from this perspective."
)
def chat_with_nietzsche(user_input):
headers = {
"Authorization": f"Bearer {DEEPSEEK_API_KEY}",
"Content-Type": "application/json"
}
# Define the conversation history
messages = [
{"role": "system", "content": BOT_PERSONA},
{"role": "user", "content": user_input}
]
# Send the request to the DeepSeek API
data = {
"model": "deepseek-chat", # Replace with the appropriate model
"messages": messages
}
response = requests.post(DEEPSEEK_ENDPOINT, headers=headers, json=data)
response_data = response.json()
# Extract the bot's reply
if response.status_code == 200:
return response_data["choices"][0]["message"]["content"]
else:
return "Error: Unable to get a response from the bot."
# Streamlit app
def main():
st.title("Nietzsche Chatbot")
st.markdown("Ask Friedrich Nietzsche anything, and he will respond from his philosophical perspective.")
# Initialize session state for conversation history
if "history" not in st.session_state:
st.session_state.history = []
# Display conversation history
for user_input, bot_response in st.session_state.history:
st.text_area("You", value=user_input, height=68, disabled=True)
st.text_area("Nietzsche", value=bot_response, height=150, disabled=True)
# User input
user_input = st.text_input("Your Question", placeholder="Ask Nietzsche...")
# Submit button
if st.button("Submit"):
if user_input.strip(): # Check if input is not empty
bot_response = chat_with_nietzsche(user_input)
st.session_state.history.append((user_input, bot_response))
st.rerun() # Refresh the app to display the new response
# Run the Streamlit app
if __name__ == "__main__":
main() |