Upload 3 files
Browse files- app.py +101 -0
- htmlTemplates.py +44 -0
- requirements.txt +91 -0
app.py
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import streamlit as st
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from dotenv import load_dotenv
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from PyPDF2 import PdfReader
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.embeddings import HuggingFaceInstructEmbeddings
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from langchain.vectorstores import FAISS
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from langchain.memory import ConversationBufferMemory
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from langchain.chains import ConversationalRetrievalChain
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from htmlTemplates import css, bot_template, user_template
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from langchain.llms import HuggingFaceHub
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def get_pdf_text(pdf_docs):
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text = ""
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for pdf in pdf_docs:
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pdf_reader = PdfReader(pdf)
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for page in pdf_reader.pages:
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text += page.extract_text()
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return text
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def get_text_chunks(text):
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text_splitter = CharacterTextSplitter(
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separator="\n", chunk_size=1000, chunk_overlap=200, length_function=len
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)
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chunks = text_splitter.split_text(text)
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return chunks
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def get_vectorstore(text_chunks):
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embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
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vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
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return vectorstore
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def get_conversation_chain(vectorstore):
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llm = HuggingFaceHub(
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repo_id="google/flan-t5-xxl",
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model_kwargs={"temperature": 0.5, "max_length": 512},
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)
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memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
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conversation_chain = ConversationalRetrievalChain.from_llm(
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llm=llm, retriever=vectorstore.as_retriever(), memory=memory
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)
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return conversation_chain
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def handle_userinput(user_question):
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response = st.session_state.conversation({"question": user_question})
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st.session_state.chat_history = response["chat_history"]
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for i, message in enumerate(st.session_state.chat_history):
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if i % 2 == 0:
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st.write(
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user_template.replace("{{MSG}}", message.content),
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unsafe_allow_html=True,
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)
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else:
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st.write(
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bot_template.replace("{{MSG}}", message.content), unsafe_allow_html=True
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)
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def main():
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load_dotenv()
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st.set_page_config(page_title="Chat with multiple PDFs", page_icon=":books:")
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st.write(css, unsafe_allow_html=True)
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if "conversation" not in st.session_state:
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st.session_state.conversation = None
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if "chat_history" not in st.session_state:
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st.session_state.chat_history = None
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st.header("Chat with multiple PDFs :books:")
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user_question = st.text_input("Ask a question about your documents:")
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if user_question:
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handle_userinput(user_question)
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with st.sidebar:
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st.subheader("Your documents")
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pdf_docs = st.file_uploader(
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"Upload your PDFs here and click on 'Process'", accept_multiple_files=True
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)
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if st.button("Process"):
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with st.spinner("Processing"):
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# get pdf text
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raw_text = get_pdf_text(pdf_docs)
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# get the text chunks
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text_chunks = get_text_chunks(raw_text)
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# create vector store
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vectorstore = get_vectorstore(text_chunks)
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# create conversation chain
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st.session_state.conversation = get_conversation_chain(vectorstore)
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if __name__ == "__main__":
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main()
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htmlTemplates.py
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css = """
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<style>
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.chat-message {
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padding: 1.5rem; border-radius: 0.5rem; margin-bottom: 1rem; display: flex
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}
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.chat-message.user {
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background-color: #2b313e
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}
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.chat-message.bot {
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background-color: #475063
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}
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.chat-message .avatar {
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width: 20%;
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}
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.chat-message .avatar img {
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max-width: 78px;
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max-height: 78px;
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border-radius: 50%;
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object-fit: cover;
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}
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.chat-message .message {
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width: 80%;
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padding: 0 1.5rem;
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color: #fff;
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}
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"""
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bot_template = """
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<div class="chat-message bot">
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<div class="avatar">
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<img src="https://i.ibb.co/cN0nmSj/Screenshot-2023-05-28-at-02-37-21.png" style="max-height: 78px; max-width: 78px; border-radius: 50%; object-fit: cover;">
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</div>
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<div class="message">{{MSG}}</div>
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</div>
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"""
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user_template = """
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<div class="chat-message user">
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<div class="avatar">
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<img src="https://i.ibb.co/rdZC7LZ/Photo-logo-1.png">
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</div>
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<div class="message">{{MSG}}</div>
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</div>
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"""
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requirements.txt
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aiohttp==3.9.5
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aiosignal==1.3.1
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altair==5.3.0
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annotated-types==0.6.0
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attrs==23.2.0
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blinker==1.7.0
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cachetools==5.3.3
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certifi==2024.2.2
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charset-normalizer==3.3.2
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click==8.1.7
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colorama==0.4.6
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dataclasses-json==0.6.4
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faiss-cpu==1.8.0
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filelock==3.13.4
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frozenlist==1.4.1
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fsspec==2024.3.1
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gitdb==4.0.11
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GitPython==3.1.43
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greenlet==3.0.3
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huggingface-hub==0.22.2
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idna==3.7
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InstructorEmbedding==1.0.1
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Jinja2==3.1.3
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joblib==1.4.0
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jsonpatch==1.33
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jsonpointer==2.4
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jsonschema==4.21.1
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jsonschema-specifications==2023.12.1
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langchain==0.1.16
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langchain-community==0.0.33
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langchain-core==0.1.44
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langchain-text-splitters==0.0.1
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langsmith==0.1.48
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markdown-it-py==3.0.0
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MarkupSafe==2.1.5
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marshmallow==3.21.1
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mdurl==0.1.2
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mpmath==1.3.0
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multidict==6.0.5
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mypy-extensions==1.0.0
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networkx==3.3
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nltk==3.8.1
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numpy==1.26.4
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orjson==3.10.1
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packaging==23.2
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pandas==2.2.2
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pillow==10.3.0
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protobuf==4.25.3
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pyarrow==15.0.2
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pydantic==2.7.0
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pydantic_core==2.18.1
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pydeck==0.8.1b0
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Pygments==2.17.2
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PyPDF2==3.0.1
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python-dateutil==2.9.0.post0
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python-dotenv==1.0.1
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pytz==2024.1
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PyYAML==6.0.1
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referencing==0.34.0
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regex==2024.4.16
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requests==2.31.0
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rich==13.7.1
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rpds-py==0.18.0
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safetensors==0.4.3
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scikit-learn==1.4.2
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scipy==1.13.0
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sentence-transformers==2.2.2
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sentencepiece==0.2.0
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setuptools==68.2.2
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six==1.16.0
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smmap==5.0.1
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SQLAlchemy==2.0.29
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streamlit==1.33.0
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sympy==1.12
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tenacity==8.2.3
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threadpoolctl==3.4.0
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tokenizers==0.19.1
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toml==0.10.2
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toolz==0.12.1
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torch==2.2.2
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torchvision==0.17.2
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tornado==6.4
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tqdm==4.66.2
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transformers==4.40.0
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typing-inspect==0.9.0
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typing_extensions==4.11.0
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tzdata==2024.1
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urllib3==2.2.1
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watchdog==4.0.0
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wheel==0.41.2
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yarl==1.9.4
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