Spaces:
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#1
by
KunaalNaik
- opened
app.py
CHANGED
@@ -3,15 +3,12 @@ from langchain_community.llms import OpenAI
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from langchain_core.prompts import PromptTemplate
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import streamlit as st
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# Set the page to wide mode
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st.set_page_config(layout="wide")
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mini_template = "You are an expert researcher. You\'ve talked to hundreds of {Target Audience}. \
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Each person in the niche of {Target Audience} has certain struggles that make it easier to sell {My Course}. \
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These are called Pain Points. There's a recipe for getting to the core of the Pain Points of {Target Audience}. \
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Namely, answer each of these Questions 3 times, each getting deeper in the issues of {Target Audience}, \
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appealing to their Emotions and uncertainties related to {My Course}. \
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The Questions (answer each QUESTION 3
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1. What keeps them awake at night?\
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2. What are they afraid of?\
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3. What are they angry about?\
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@@ -30,42 +27,22 @@ chain = LLMChain(llm=OpenAI(), prompt=prompt)
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#target_audience = "professionals looking for course on Power BI"
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#my_course = "Zero to Hero in PowerBI"
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my_course = st.sidebar.text_input("Enter your course name")
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if st.
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if target_audience and my_course:
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with st.spinner("Generating response..."):
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with st.expander("Show prompt", expanded=False):
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answer = chain.run({"Target Audience": target_audience, "My Course":
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# Assuming there are exactly three sections based on your output structure
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if len(sections) == 3:
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# Extract titles for tabs
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titles = [section.split('\n')[0] for section in sections]
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# Extract content for each section, removing the title
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contents = [section.split('\n')[1:] for section in sections]
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# Create tabs for each category
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tabs = st.tabs(titles)
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for i, tab in enumerate(tabs):
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with tab:
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st.header(titles[i])
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for content in contents[i]:
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st.markdown(content)
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else:
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st.error("The answer format does not match the expected structure.")
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st.success("Hope you like the response.❤")
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elif target_audience:
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st.error("Enter your course name.")
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elif my_course:
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st.error("Enter your target audience.")
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else:
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st.error("No input detected, Please provide the desired information.")
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from langchain_core.prompts import PromptTemplate
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import streamlit as st
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mini_template = "You are an expert researcher. You\'ve talked to hundreds of {Target Audience}. \
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Each person in the niche of {Target Audience} has certain struggles that make it easier to sell {My Course}. \
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These are called Pain Points. There's a recipe for getting to the core of the Pain Points of {Target Audience}. \
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Namely, answer each of these Questions 3 times, each getting deeper in the issues of {Target Audience}, \
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appealing to their Emotions and uncertainties related to {My Course}. \
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The Questions (answer each QUESTION 3 tiems in listicle format according to the instructions):\
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1. What keeps them awake at night?\
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2. What are they afraid of?\
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3. What are they angry about?\
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#target_audience = "professionals looking for course on Power BI"
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#my_course = "Zero to Hero in PowerBI"
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target_audience = st.text_input("Enter your target audience")
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my_course = st.text_input("Enter your course name")
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if st.button("Get resposne"):
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if target_audience and my_course:
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with st.spinner("Generating response..."):
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with st.expander("Show prompt", expanded=False):
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st.info(prompt.template)
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answer = chain.run({"Target Audience": target_audience, "My Course":my_course})
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st.write(answer)
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st.success("Hope you like the resposne.❤")
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elif target_audience:
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st.error("Enter your course name.")
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elif my_course:
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st.error("Enter your target audience.")
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else:
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st.error("No input detected, Please provide the desired information.")
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app0.py
DELETED
@@ -1,48 +0,0 @@
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from langchain.chains import LLMChain
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from langchain_community.llms import OpenAI
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from langchain_core.prompts import PromptTemplate
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import streamlit as st
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-
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mini_template = "You are an expert researcher. You\'ve talked to hundreds of {Target Audience}. \
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-
Each person in the niche of {Target Audience} has certain struggles that make it easier to sell {My Course}. \
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-
These are called Pain Points. There's a recipe for getting to the core of the Pain Points of {Target Audience}. \
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-
Namely, answer each of these Questions 3 times, each getting deeper in the issues of {Target Audience}, \
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appealing to their Emotions and uncertainties related to {My Course}. \
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-
The Questions (answer each QUESTION 3 tiems in listicle format according to the instructions):\
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1. What keeps them awake at night?\
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2. What are they afraid of?\
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3. What are they angry about?\
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"
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st.title("Saas Application")
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prompt = PromptTemplate(
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input_variables = ["Target Audience", "My Course"],
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template=mini_template,
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)
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chain = LLMChain(llm=OpenAI(), prompt=prompt)
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#target_audience = "professionals looking for course on Power BI"
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#my_course = "Zero to Hero in PowerBI"
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target_audience = st.text_input("Enter your target audience")
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my_course = st.text_input("Enter your course name")
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if st.button("Get resposne"):
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if target_audience and my_course:
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with st.spinner("Generating response..."):
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with st.expander("Show prompt", expanded=False):
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st.info(prompt.template)
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answer = chain.run({"Target Audience": target_audience, "My Course":my_course})
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st.write(answer)
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st.success("Hope you like the resposne.❤")
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elif target_audience:
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st.error("Enter your course name.")
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elif my_course:
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st.error("Enter your target audience.")
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else:
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st.error("No input detected, Please provide the desired information.")
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