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IamVicky111
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Upload 2 files
Browse files- app.py +168 -0
- requirements.txt +7 -0
app.py
ADDED
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# Import necessary libraries
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import streamlit as st
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from langchain.chat_models import ChatOpenAI
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# from langchain import ConversationChain, LLMChain, PromptTemplate
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from langchain.memory import ConversationBufferWindowMemory
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from langchain.text_splitter import CharacterTextSplitter
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from langchain.vectorstores import Chroma
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from langchain.embeddings import OpenAIEmbeddings
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from langchain.chains import RetrievalQA
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from PyPDF2 import PdfReader
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from typing_extensions import Concatenate
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from langchain.chains import LLMChain
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from langchain_community.llms import OpenAI
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from langchain_core.prompts import PromptTemplate
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import os
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# Initialize session states
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if "past" not in st.session_state:
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st.session_state["past"] = []
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if "generated" not in st.session_state:
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st.session_state["generated"] = []
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if "input" not in st.session_state:
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st.session_state["input"] = ""
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if "bot_details" not in st.session_state:
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st.session_state["bot_details"] = ""
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if "bot_name" not in st.session_state:
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st.session_state["bot_name"] = ""
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if "raw_text" not in st.session_state:
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st.session_state["raw_text"] = ""
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if "is_created" not in st.session_state:
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st.session_state["is_created"] = False
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if "vectorstore" not in st.session_state:
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st.session_state["vectorstore"] = None
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if "file" not in st.session_state:
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st.session_state["file"] = None
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template = """As a highly intelligent and powerful chatbot, your personality is shaped by the following description:
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{description}
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Your designated name is {name}. Initiate the conversation with a warm greeting only when the user asks something for the first time. Subsequent interactions can skip the greeting.
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Your generated responses should be comprehensive, utilizing pointers when necessary for an enhanced user experience. Provide detailed answers, and if the user's input isn't related to personality, respond politely with an apology, encouraging them to ask questions related to your established personality. Keep your responses concise and accurate, seeking additional information from the user when required.
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Incorporate the provided context and any relevant information from the chat history into your responses. If the user's input is related to the context or question, articulate your answer accordingly.
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{context}
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{chat_history}
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Human: {input}
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Assistant:"""
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st.set_page_config(page_title=' 🤖ChatGPT with Memory🧠', layout='wide')
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prompt = PromptTemplate(
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input_variables=["name", "description",
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"context", "input", "chat_history"],
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template=template
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)
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chatgpt_chain = LLMChain(
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llm=OpenAI(model_name='gpt-3.5-turbo-16k', temperature=0.7,
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api_key=os.environ.get('OPEN_API_KEY')),
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prompt=prompt,
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verbose="true",
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memory=ConversationBufferWindowMemory(
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memory_key="chat_history", input_key="input", k=5),
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)
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def genrate_result():
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if len(st.session_state["input"]) > 0:
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db = st.session_state["vectorstore"]
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result = db.similarity_search(st.session_state["input"])
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inputs = {"input": st.session_state["input"],
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"description": st.session_state["bot_details"],
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"name": st.session_state["bot_name"],
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"context": result[0].page_content
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}
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output = chatgpt_chain.run(inputs)
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st.session_state.past.append(st.session_state["input"])
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st.session_state.generated.append(output)
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st.session_state["input"] = ""
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# function to delete the chatbot
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def delete_bot():
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"""
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Clears session state and starts a new chat.
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"""
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st.session_state["generated"] = []
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st.session_state["past"] = []
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st.session_state["input"] = ""
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st.session_state["bot_details"] = ""
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st.session_state["bot_name"] = ""
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st.session_state["raw_text"] = ""
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st.session_state["is_created"] = False
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st.session_state["vectorstore"] = None
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st.session_state["is_file_uploded"] = False
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# set up the stram lit user inputs in slider bar
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with st.sidebar:
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with st.form("my_form"):
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name = st.text_input('Name', key='name',
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type="default", placeholder='Bot Name')
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details = st.text_area(
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"Enter Description", placeholder='Bot Description', key='description', height=100)
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file = st.file_uploader('Document', type='pdf')
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submitted = st.form_submit_button("Create Bot")
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if submitted:
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if file and name and details:
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st.session_state["bot_details"] = details
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st.session_state["bot_name"] = name
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loader = PdfReader(file)
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for i, page in enumerate(loader.pages):
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content = page.extract_text()
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if content:
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temp = st.session_state["raw_text"]
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st.session_state["raw_text"] = temp+content
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text_splitter = CharacterTextSplitter(
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separator='\n', chunk_size=600, chunk_overlap=150, length_function=len)
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texts = text_splitter.split_text(
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st.session_state["raw_text"])
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st.session_state["vectorstore"] = Chroma().from_texts(texts, embedding=OpenAIEmbeddings(
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openai_api_key=os.environ.get('OPEN_API_KEY')))
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st.session_state["is_created"] = True
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else:
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st.warning(
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'Name ,Description and File are required to create chatbot', icon="⚠️")
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if st.session_state["is_created"] == True:
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st.button('Delete Bot', on_click=delete_bot)
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# Set up the Streamlit app layout
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st.title("🤖 Personality Chatbot 🧠")
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st.subheader(" Powered by Coffeebeans")
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hide_default_format = """
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<style>
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#MainMenu {visibility: hidden; }
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footer {visibility: hidden;}
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[data-testid="stVerticalBlock"] > [style*="flex-direction: column;"] > [data-testid="stVerticalBlock"] {
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# overflow: auto;
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# max-height: 300px;
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}
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</style>
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"""
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st.markdown(hide_default_format, unsafe_allow_html=True)
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if st.session_state["is_created"] == True:
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st.text_input("You: ", st.session_state["input"], key="input",
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placeholder="Your AI assistant here! Ask me anything ...",
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on_change=genrate_result(),
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label_visibility='hidden')
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with st.container():
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for i in range(len(st.session_state['generated'])-1, -1, -1):
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st.success(st.session_state["generated"][i], icon="🤖")
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st.info(st.session_state["past"][i], icon="🧐")
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requirements.txt
ADDED
@@ -0,0 +1,7 @@
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|
|
|
1 |
+
streamlit
|
2 |
+
langchain
|
3 |
+
openai==0.28
|
4 |
+
chromadb
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5 |
+
tiktoken
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6 |
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PyPDF2
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7 |
+
typing-extensions
|