Upload 3 files
Browse files- .env +3 -0
- app.py +187 -0
- requirements.txt +0 -0
.env
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GROQ_API_KEY="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"
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LANGCHAIN_API_KEY="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"
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# OPENAI_API_KEY=""
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app.py
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import streamlit as st
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from langchain_groq import ChatGroq
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from langchain.chains import LLMMathChain, LLMChain
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from langchain.prompts import PromptTemplate
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from langchain_community.utilities import WikipediaAPIWrapper
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from langchain.agents.agent_types import AgentType
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from langchain.agents import Tool, initialize_agent
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from langchain.callbacks import StreamlitCallbackHandler
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import os
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Streamlit page configuration
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st.set_page_config(
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page_title="AI Math Problem Solver & Research Assistant",
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page_icon="๐งฎ",
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layout="wide"
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)
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# Custom CSS styling
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st.markdown("""
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<style>
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.main {
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background-color: #f5f5f5;
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}
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.stTitle {
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color: #1e3d59;
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font-size: 2.5rem !important;
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font-weight: 700 !important;
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padding-bottom: 1rem;
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}
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.stTextArea textarea {
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background-color: #ffffff;
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border-radius: 10px;
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border: 1px solid #e0e0e0;
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padding: 10px;
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}
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.stButton button {
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background-color: #17b794;
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color: white;
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border-radius: 20px;
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padding: 0.5rem 2rem;
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font-weight: 600;
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}
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.stButton button:hover {
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background-color: #148f77;
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}
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div.stSpinner > div {
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border-top-color: #17b794 !important;
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}
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</style>
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""", unsafe_allow_html=True)
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# App Header
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col1, col2, col3 = st.columns([1,6,1])
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with col2:
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st.title("๐งฎ AI Math Problem Solver & Research Assistant")
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st.markdown("""
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<div style='background-color: #ffffff; padding: 1rem; border-radius: 10px; margin-bottom: 2rem;'>
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<p style='color: #666666; margin-bottom: 0;'>
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Powered by Google Gemma 2 AI, this assistant can help you solve math problems,
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provide detailed explanations, and search for additional information.
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</p>
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</div>
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""", unsafe_allow_html=True)
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# API Key Check
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groq_api_key = os.getenv("GROQ_API_KEY")
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if not groq_api_key:
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st.error("โ ๏ธ Please add your Groq API key to continue")
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st.stop()
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# Initialize LLM
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llm = ChatGroq(model="gemma2-9b-it", groq_api_key=groq_api_key)
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# Tool Setup
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wikipedia_wrapper = WikipediaAPIWrapper()
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wikipedia_tool = Tool(
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name="Wikipedia",
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func=wikipedia_wrapper.run,
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description="A tool for searching the Internet to find various information on the topics mentioned"
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)
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def safe_calculator(expression: str) -> str:
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try:
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# Clean and validate the expression
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if any(char in expression for char in ['โซ', 'โ', 'โ']):
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return "I apologize, but I cannot directly solve calculus problems or complex mathematical expressions. I can help explain the steps to solve it though!"
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# Use the math chain
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result = math_chain.run(expression)
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return result
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except Exception as e:
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return f"I encountered an error trying to solve this mathematically. Let me help explain the steps to solve it instead."
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math_chain = LLMMathChain.from_llm(llm=llm,verbose=True,input_key="question",output_key="answer")
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calculator = Tool(
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name="Calculator",
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func=safe_calculator,
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description="A tool for solving basic mathematical expressions. For complex math, it will provide step-by-step explanations"
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)
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prompt = """
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You're a helpful math tutor tasked with solving mathematical questions. For each problem:
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1. First determine if it's a basic arithmetic problem or a more complex mathematical problem
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2. For basic arithmetic, use the calculator tool
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3. For complex math (calculus, integrals, differential equations), explain the solution steps clearly
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4. Always show your work and explain each step
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Question: {question}
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Let me solve this step by step:
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"""
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prompt_template = PromptTemplate(
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input_variables=["question"],
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template=prompt
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)
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chain = LLMChain(llm=llm, prompt=prompt_template)
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reasoning_tool = Tool(
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name="Reasoning tool",
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func=chain.run,
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description="A tool for answering logic-based and reasoning questions."
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)
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# Initialize Agent
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assistant_agent = initialize_agent(
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tools=[wikipedia_tool, calculator, reasoning_tool],
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llm=llm,
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agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
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verbose=False,
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handle_parsing_errors=True
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)
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# Chat History
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if "messages" not in st.session_state:
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st.session_state["messages"] = [
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{"role": "assistant", "content": "๐ Hi! I'm your Math Assistant. I can help you solve math problems and provide detailed explanations."}
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]
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# Display Chat History
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for msg in st.session_state.messages:
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with st.chat_message(msg["role"]):
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st.write(msg["content"])
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# Input Section
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st.markdown("### ๐ Your Question")
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question = st.text_area(
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label="Enter your question:",
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value="I have 5 bananas and 7 grapes. I eat 2 bananas and give away 3 grapes. Then I buy a dozen apples and 2 packs of blueberries. Each pack of blueberries contains 25 berries. How many total pieces of fruit do I have at the end?",
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label_visibility="collapsed",
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height=100
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)
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# Create two columns for button centering
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col1, col2, col3 = st.columns([2,1,2])
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with col2:
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solve_button = st.button("๐ Solve Problem")
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if solve_button:
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if question:
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with st.spinner("๐ค Thinking..."):
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st.session_state.messages.append({"role": "user", "content": question})
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with st.chat_message("user"):
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st.write(question)
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st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False)
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response = assistant_agent.run(st.session_state.messages, callbacks=[st_cb])
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st.session_state.messages.append({"role": "assistant", "content": response})
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st.markdown("### ๐ก Solution:")
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with st.chat_message("assistant"):
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st.success(response)
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else:
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st.warning("โ ๏ธ Please enter your question first!")
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# Footer
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st.markdown("""
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<div style='position: fixed; bottom: 0; left: 0; width: 100%; background-color: #f0f2f6; padding: 1rem; text-align: center;'>
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<p style='color: #666666; margin-bottom: 0;'>
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Made with โค๏ธ using Streamlit and Google Gemma 2
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</p>
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</div>
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""", unsafe_allow_html=True)
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requirements.txt
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Binary file (458 Bytes). View file
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