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LLAMA3 model.rar

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ed712b2e370f6f2cec1ee2bd35e046b076d7cb771adf1f9c40e94dca90996291
+size 99508396

constants.py

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+openai_key='sk-proj-bqOf8lKa9hnV1KmGXedaT3BlbkFJwM8oiBEkmwEoYR7yxl63'

main.py

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+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from langchain_community.llms import Ollama
+import os
+
+import streamlit as st
+
+from dotenv import load_dotenv
+load_dotenv()
+
+os.environ["OPENAI_API_KEY"]=os.getenv("OPENAI_API_KEY", "not found")
+#langmith Tracking
+os.environ["LANGCHAIN_TRACING_V2"]="true"   
+os.environ["LANGCHAIN_API_KEY"]=os.getenv("LANGCHAIN_API_KEY", "not found")
+
+#Prompt Template
+
+prompt = ChatPromptTemplate.from_messages(
+    [
+        ("system", "You are a world class helpful assistant.Please respond to the user."),
+        ("user","Question:{question}")
+    ]
+)
+
+#streamlit framework
+
+st.title('LLAMA3 using Langchain :sunglasses:') 
+st.subheader("I am developed by :blue[Kartavya.] How can i assist you:question  :")
+input_text = st.text_input("")
+
+#OLLAMA LLAma3
+
+llm = Ollama(model="llama3")
+output_parser = StrOutputParser()
+chain = prompt|llm|output_parser
+
+if st.button("Enter"):
+    st.write(chain.invoke({"question":input_text}))
+
+

requirements.txt

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+openai
+langchain
+streamlit
+langchain_openai
+langchain_community
+ollama
+python-dotenv