update

app.py

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+import os
+import pinecone
+import streamlit as st
+from langchain.document_loaders import TextLoader 
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.embeddings import OpenAIEmbeddings 
+from langchain.vectorstores import Chroma, Pinecone
+from langchain.chains import ConversationalRetrievalChain, LLMChain, SimpleSequentialChain
+from langchain.memory import ConversationBufferMemory
+from langchain.llms import OpenAI
+from langchain.schema import (AIMessage, HumanMessage, SystemMessage)
+from langchain.chat_models import ChatOpenAI, ChatAnthropic
+from langchain import PromptTemplate
+from dotenv import load_dotenv, find_dotenv
+
+load_dotenv(find_dotenv())
+
+# pinecone.init(api_key=os.getenv("PINECONE_API_KEY"), environment=os.getenv("PINECONE_ENVIRONMENT"))
+
+dataset_path = "./dataset.txt"
+loader = TextLoader(dataset_path)
+comments = loader.load_and_split()
+
+embeddings = OpenAIEmbeddings(model_name="ada")
+vectordb = Chroma.from_documents(comments, embedding=embeddings, persist_directory=".")
+vectordb.persist()
+memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
+
+# Assuming that GPT-4 is used for grammar, structure, and fact-checking
+# and Claude is used for providing tips and encouraging students to do their own research
+grammar_llm = OpenAI(temperature=0.8)
+tips_llm = Claude(temperature=0.8)
+
+grammar_qa = ConversationalRetrievalChain.from_llm(grammar_llm, vectordb.as_retriever(), memory=memory)
+tips_qa = ConversationalRetrievalChain.from_llm(tips_llm, vectordb.as_retriever(), memory=memory)
+
+
+
+st.title('AI Statement Reviewer')
+
+user_input = st.text_area("Enter your personal statement here:")
+
+if st.button('Get feedback'):
+    grammar_result = grammar_qa({"question": user_input})
+    tips_result = tips_qa({"question": user_input})
+    st.write("Grammar and Structure Feedback:")
+    st.write(grammar_result["answer"])
+    st.write("Tips and Recommendations:")
+    st.write(tips_result["answer"])
+
+