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bodhi.py
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import streamlit as st
from streamlit_extras.bottom_container import bottom
from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate
from langchain_core.messages import SystemMessage
from langchain_core.prompts import HumanMessagePromptTemplate
from langchain_mistralai.chat_models import ChatMistralAI
import os
import urllib.parse
import streamlit.components.v1 as components
def init_session(): # Session State initializations
if 'key' not in st.session_state:
st.session_state.key = 0
def main():
#Main Header contents
st.set_page_config(page_title="Bodhi", page_icon="🌳")
init_session() #Initialize session
sidebar_content() #Sidebar content
def app_page(): #Main app page content
st.header('Buildspace - Project Bodhi')
st.write('Drop your content and template in this window to generate an automatic post! 🤖📟')
tab1, tab2 = st.tabs(["Content", "Template"])
with tab1:
content_inp = st.text_area("Enter your content",key=1)
st.write(f"Character count: {len(content_inp)}")
with tab2:
template_inp = st.text_area("Enter your template",key=2)
st.write(f"Character count: {len(template_inp)}")
models = ["gpt-4","mistral-large-latest"]
option = st.selectbox("Select your model:",models)
donate_url = 'https://donate.stripe.com/8wM4gS7lx6mS5Ne5kk' #Donate link URL
st.link_button("Donate", donate_url) #Donate button
if st.button("Generate Content"):
with st.spinner(f"Generating content from {option}..."):
if option == "gpt-4":
output_content = model_gpt(content_inp, template_inp)
elif option == "mistral-large-latest":
output_content = model_Mistral(content_inp, template_inp)
#output_content = "This is MistralAI"
else:
output_content = "Error! Error! Try a different model. Report error via DM or Github"
st.session_state.generated_content = output_content
st.subheader("Generated Content:")
st.write("Here is your output 👇🏾 Share responsibly ❤")
st.code(output_content, language="markdown")
st.subheader("Share your generated content:")
share_buttons(output_content)
def share_buttons(content): # Function to copy generated content to Social Media sites
# LinkedIn & X (Twitter) share button
linkedin_url = f"https://www.linkedin.com/sharing/share-offsite/?url={urllib.parse.quote('https://www.linkedin.com/')}&title={urllib.parse.quote('Hi👋🏾')}&summary={urllib.parse.quote(content)}"
twitter_url = f"https://twitter.com/intent/tweet?text={urllib.parse.quote(content)}"
st.write(f"[]({linkedin_url}) "+f" []({twitter_url}) ")
def sidebar_content():
# Add tabs to the sidebar
st.sidebar.title('Welcome 👋🏾')
st.sidebar.header('Buildspace - Project Bodhi')
st.sidebar.write('[](https://x.com/_the_real_ng_/) [](https://www.instagram.com/nikki_builds/) [](https://www.linkedin.com/in/nikhil-gnanavel/)')
tabs = ["Bodhi : Content-to-template generator", "Feedback"]
tab = st.sidebar.selectbox('', options=tabs,label_visibility="collapsed")
if tab == 'Bodhi : Content-to-template generator':
app_page()
elif tab == 'Feedback':
feedback()
st.sidebar.image("assets/face logo.jpg")
st.sidebar.header("About:")
st.sidebar.code('''Heyo 😁,
Nikhil here.
Thanks for taking time to check this out.
If you like this project and want to see some more cool GenAI projects,
hit me up through the feedback page.
All contributions here will be added to future project and keeping this page active 💓''')
donate_url = 'https://donate.stripe.com/8wM4gS7lx6mS5Ne5kk' #Donate link URL
st.sidebar.link_button("Donate", donate_url) #Donate button
def feedback():
# Replace 'YOUR_TALLY_FORM_URL' with the actual URL of your Tally form
tally_form_url = """
<iframe data-tally-src="https://tally.so/embed/w2rdMV?transparentBackground=1&dynamicHeight=1" loading="lazy" width="100%" height="2004" frameborder="0" marginheight="0" marginwidth="0" title="Progress Update"></iframe><script>var d=document,w="https://tally.so/widgets/embed.js",v=function(){"undefined"!=typeof Tally?Tally.loadEmbeds():d.querySelectorAll("iframe[data-tally-src]:not([src])").forEach((function(e){e.src=e.dataset.tallySrc}))};if("undefined"!=typeof Tally)v();else if(d.querySelector('script[src="'+w+'"]')==null){var s=d.createElement("script");s.src=w,s.onload=v,s.onerror=v,d.body.appendChild(s);}</script>
"""
# Embed the Tally form using an iframe
components.html(tally_form_url,height=2200,width = 800, scrolling = True)
## GPT model functions
def model_gpt(user_content,user_template):
# Set up the language model
chat_model = ChatOpenAI(model="gpt-4",temperature=1,max_tokens=100, top_p=1, frequency_penalty=0,presence_penalty=0)
# Create the chat prompt
prompt = ChatPromptTemplate.from_messages([
SystemMessage(content=("Make my content in form of the template. Do not perform any other action.")),
HumanMessagePromptTemplate.from_template("Content = \"{content_model}\" \ntemplate = \"{template_model}\""),
])
# Format the messages with user input
messages = prompt.format_messages(
content_model=user_content,
template_model=user_template
)
# Generate the response
response = chat_model(messages)
return response.content
def model_Mistral(user_content,user_template):
# Set up the language model
chat_model = ChatMistralAI(model="mistral-large-latest",temperature=1,max_tokens=300, top_p=1, frequency_penalty=0,presence_penalty=0)
# Create the chat prompt
prompt = ChatPromptTemplate.from_messages([
SystemMessage(content=("Make my content in form of the template. Do not perform any other action.")),
HumanMessagePromptTemplate.from_template("Content = \"{content_model}\" \ntemplate = \"{template_model}\""),
])
# Format the messages with user input
messages = prompt.format_messages(
content_model=user_content,
template_model=user_template
)
# Generate the response
response = chat_model(messages)
return response.content
if __name__ == "__main__":
# Access secrets from the secrets.toml file
os.environ["OPENAI_API_KEY"] = st.secrets["api_keys"]["OPENAI_API_KEY"]
os.environ["MISTRAL_API_KEY"] = st.secrets["api_keys"]["MISTRAL_API_KEY"]
main()