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4093e53 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | import streamlit as st
from langchain_groq import ChatGroq
from langchain.chains import LLMMathChain, LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.utilities import WikipediaAPIWrapper
from langchain.agents.agent_types import AgentType
from langchain.agents import Tool, initialize_agent
from langchain.callbacks import StreamlitCallbackHandler
## Set upi the Stramlit app
st.set_page_config(page_title="Text To MAth Problem Solver And Data Search Assistant",page_icon="🧮")
st.title("Text To Math Problem Solver Using Google Gemma 2")
groq_api_key=st.sidebar.text_input(label="Groq API Key",type="password")
if not groq_api_key:
st.info("Please add your Groq API key to continue")
st.stop()
llm=ChatGroq(model="Gemma2-9b-It",groq_api_key=groq_api_key)
## Initializing the tools
wikipedia_wrapper=WikipediaAPIWrapper()
wikipedia_tool=Tool(
name="Wikipedia",
func=wikipedia_wrapper.run,
description="A tool for searching the Internet to find the vatious information on the topics mentioned"
)
## Initializa the MAth tool
math_chain=LLMMathChain.from_llm(llm=llm)
calculator=Tool(
name="Calculator",
func=math_chain.run,
description="A tools for answering math related questions. Only input mathematical expression need to bed provided"
)
prompt="""
Your a agent tasked for solving users mathemtical question. Logically arrive at the solution and provide a detailed explanation
and display it point wise for the question below
Question:{question}
Answer:
"""
prompt_template=PromptTemplate(
input_variables=["question"],
template=prompt
)
## Combine all the tools into chain
chain=LLMChain(llm=llm,prompt=prompt_template)
reasoning_tool=Tool(
name="Reasoning tool",
func=chain.run,
description="A tool for answering logic-based and reasoning questions."
)
## initialize the agents
assistant_agent=initialize_agent(
tools=[wikipedia_tool,calculator,reasoning_tool],
llm=llm,
agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
verbose=False,
handle_parsing_errors=True
)
if "messages" not in st.session_state:
st.session_state["messages"]=[
{"role":"assistant","content":"Hi, I'm a Math chatbot who can answer all your maths questions"}
]
for msg in st.session_state.messages:
st.chat_message(msg["role"]).write(msg['content'])
## LEts start the interaction
question=st.text_area("Enter your question:","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?")
if st.button("find my answer"):
if question:
with st.spinner("Generate response.."):
st.session_state.messages.append({"role":"user","content":question})
st.chat_message("user").write(question)
st_cb=StreamlitCallbackHandler(st.container(),expand_new_thoughts=False)
response=assistant_agent.run(st.session_state.messages,callbacks=[st_cb])
st.session_state.messages.append({'role':'assistant',"content":response})
st.write('### Response:')
st.success(response)
else:
st.warning("Please enter the question")
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