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import streamlit as st
import g4f
from g4f.client import Client
import sqlite3
import google.generativeai as genai
# import pyttsx3
import pyperclip
import requests
from PIL import Image
import io
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
headers = {"Authorization": "Bearer Your_huggingface_Api_key"}
def local_css(file_name):
with open(file_name) as f:
st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
local_css("style.css")
# Create a connection to the database
conn = sqlite3.connect('chat_history.db')
c = conn.cursor()
# Create table if not exists
try:
c.execute('''CREATE TABLE IF NOT EXISTS chat_history
(conversation_id INTEGER, role TEXT, content TEXT)''')
conn.commit()
except Exception as e:
st.error(f"An error occurred: {e}")
def generate_image_from_model(prompt):
response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
image_bytes = response.content
image = Image.open(io.BytesIO(image_bytes))
return image
def generate_image(prompt):
response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
image_bytes = response.content
image = Image.open(io.BytesIO(image_bytes))
return image
# Streamlit app
def main():
try:
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
if "conversation_id" not in st.session_state:
st.session_state.conversation_id = 1
models = {
"🚀 Airoboros 70B": "airoboros-70b",
"🔮 Gemini Pro": "gemini-pro",
"📷 StabilityAI": "stabilityai/stable-diffusion-xl-base-1.0"
}
columns = st.columns(3) # Split the layout into three columns
with columns[0]:
st.header("DarkGPT")
with columns[2]:
selected_model_display_name = st.selectbox("Select Model", list(models.keys()), index=0)
with columns[1]:
selected_model = models[selected_model_display_name]
# Sidebar (left side) - New chat button
if st.sidebar.button("✨ New Chat", key="new_chat_button"):
st.session_state.chat_history.clear()
st.session_state.conversation_id += 1
# Sidebar (left side) - Display saved chat
st.sidebar.write("Chat History")
c.execute("SELECT DISTINCT conversation_id FROM chat_history")
conversations = c.fetchall()
for conv_id in reversed(conversations):
c.execute("SELECT content FROM chat_history WHERE conversation_id=? AND role='bot' LIMIT 1",
(conv_id[0],))
first_bot_response = c.fetchone()
if first_bot_response:
if st.sidebar.button(" ".join(first_bot_response[0].split()[0:5])):
display_conversation(conv_id[0])
# Sidebar (left side) - Clear Chat History button
if st.sidebar.button("Clear Chat History ✖️"):
st.session_state.chat_history.clear()
c.execute("DELETE FROM chat_history")
conn.commit()
# Main content area (center)
st.markdown("---")
user_input = st.chat_input("Ask Anything ...")
if user_input:
if selected_model == "gemini-pro":
try:
if user_input.startswith("/image"):
prompt = user_input[len("/image"):].strip() # Extract prompt after "/image"
# Use Gemini Pro to generate content based on the prompt
GOOGLE_API_KEY = "AIzaSyC8_gwU5LSVQJk3iIXyj5xJ94ArNK11dXU"
genai.configure(api_key=GOOGLE_API_KEY)
model = genai.GenerativeModel('gemini-1.0-pro')
response = model.generate_content(prompt)
bot_response = response.candidates[0].content.parts[0].text
# Generate image based on the generated text prompt
generated_image = generate_image(bot_response)
st.session_state.chat_history.append({"role": "user", "content": user_input})
st.session_state.chat_history.append({"role": "bot", "content": generated_image})
# Display the generated image
for index, chat in enumerate(st.session_state.chat_history):
with st.chat_message(chat["role"]):
if chat["role"] == "user":
st.markdown(user_input)
elif chat["role"] == "bot":
st.image(generated_image, width=400)
else:
GOOGLE_API_KEY = "your_Gemini_Api_key"
genai.configure(api_key=GOOGLE_API_KEY)
model = genai.GenerativeModel('gemini-1.0-pro')
prompt = user_input
response = model.generate_content(prompt)
bot_response = response.candidates[0].content.parts[0].text
st.session_state.chat_history.append({"role": "user", "content": user_input})
st.session_state.chat_history.append({"role": "bot", "content": bot_response})
# Store chat in the database
for chat in st.session_state.chat_history:
c.execute("INSERT INTO chat_history VALUES (?, ?, ?)",
(st.session_state.conversation_id, chat["role"], chat["content"]))
conn.commit()
for index, chat in enumerate(st.session_state.chat_history):
with st.chat_message(chat["role"]):
if chat["role"] == "user":
st.markdown(chat["content"])
elif chat["role"] == "bot":
st.markdown(chat["content"])
except Exception as e:
st.error(f"An error occurred: {e}")
elif selected_model == "stabilityai/stable-diffusion-xl-base-1.0":
prompt = user_input
generated_image = generate_image_from_model(prompt)
for index, chat in enumerate(st.session_state.chat_history):
with st.chat_message(chat["role"]):
if chat["role"] == "user":
st.markdown(user_input)
elif chat["role"] == "bot":
st.image(generated_image, width=400)
else:
try:
client = Client()
response = client.chat.completions.create(
model=models[selected_model_display_name],
messages=[{"role": "user", "content": user_input}],
)
bot_response = response.choices[0].message.content
st.session_state.chat_history.append({"role": "user", "content": user_input})
st.session_state.chat_history.append({"role": "bot", "content": bot_response})
# Store chat in the database
for chat in st.session_state.chat_history:
c.execute("INSERT INTO chat_history VALUES (?, ?, ?)",
(st.session_state.conversation_id, chat["role"], chat["content"]))
conn.commit()
# Display chat history
for index, chat in enumerate(st.session_state.chat_history):
with st.chat_message(chat["role"]):
if chat["role"] == "user":
st.markdown(chat["content"])
elif chat["role"] == "bot":
st.markdown(chat["content"])
except Exception as e:
st.error(f"An error occurred: {e}")
except Exception as e:
st.error(f"An error occurred: {e}")
def display_conversation(conversation_id):
c.execute("SELECT * FROM chat_history WHERE conversation_id=?", (conversation_id,))
chats = c.fetchall()
st.markdown(f"### Conversation")
for chat in chats:
st.markdown(f"{chat[1]}")
st.markdown(f"{chat[2]}")
if __name__ == "__main__":
main()
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