Create app.py

app.py

@@ -0,0 +1,38 @@
+import streamlit as st #deployment
+from langchain.chains.llm import LLMChain #individual chain
+from langchain.chains.sequential import SequentialChain #combine chains
+from langchain_groq import ChatGroq # llm model
+from langchain.prompts import PromptTemplate #prompt for query
+
+st.title('LEADER DATABASE') #title
+leader_name=st.text_input('Enter The Famous leader_name from India.')
+
+sub=st.button('SUBMIT')
+
+LLM_model=ChatGroq(temperature=0.6,
+                   groq_api_key='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')
+
+prompt1=PromptTemplate(input=['A'],
+                       template='tell me about {A} in 20 words.') 
+
+chain1=LLMChain(llm=LLM_model,prompt=prompt1,output_key='person')
+
+prompt2=PromptTemplate(input=['person'],
+                       template='what is date of birth of this {person}.')
+
+chain2=LLMChain(llm=LLM_model,prompt=prompt2,output_key='dob')  
+
+prompt3=PromptTemplate(input=['dob'],
+                       template='mention how many time win elections {dob}.') 
+
+chain3=LLMChain(llm=LLM_model,prompt=prompt3,output_key='election win')
+
+
+#combine all the chains in sequence
+parent=SequentialChain(chains=[chain1,chain2,chain3],
+                       input_variables=['A'],
+                       output_variables=['person','dob','election win']
+                       )
+
+if sub:
+    st.write(parent({'A':leader_name}))