Spaces:
Sleeping
Sleeping
Sandaruth
commited on
Commit
·
26e663a
1
Parent(s):
12d9740
update
Browse files
app.py
CHANGED
@@ -28,7 +28,7 @@ def chatbot_response(user_input): # Open AI GPT-3 and Google T5
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def main():
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print_colorful_msg("Starting chatbot main function ...", color='blue')
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st.title("
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user_input = st.text_input("Enter your message:")
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if st.button("Send"):
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@@ -45,8 +45,8 @@ def main():
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st.markdown("### Source Documents:")
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if source_documents:
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for doc in source_documents:
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st.write(doc)
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else:
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st.write("No source documents found.")
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def main():
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print_colorful_msg("Starting chatbot main function ...", color='blue')
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st.title("ATrad Chatbot")
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user_input = st.text_input("Enter your message:")
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if st.button("Send"):
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st.markdown("### Source Documents:")
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if source_documents:
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for doc in source_documents:
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pass
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# st.write(doc)
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else:
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st.write("No source documents found.")
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model.py
CHANGED
@@ -4,6 +4,8 @@ from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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# Access the value of OPENAI_API_KEY
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OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
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@@ -12,11 +14,18 @@ os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
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from langchain_openai import ChatOpenAI
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llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0,)
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## Create embeddings and splitter
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from langchain.embeddings import HuggingFaceBgeEmbeddings
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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# Create Embeddings
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model_name = "BAAI/bge-large-en"
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@@ -32,12 +41,18 @@ splitter = RecursiveCharacterTextSplitter(
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chunk_overlap=100,
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)
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from langchain_community.vectorstores import FAISS
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persits_directory="./faiss_Test02_500_C_BGE_large"
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vectorstore= FAISS.load_local(persits_directory, embedding)
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# Define a custom prompt for Unser manual
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from langchain.prompts import PromptTemplate
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@@ -52,7 +67,7 @@ qa_template = ("""
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if context is not enough to answer the question, ask for more information.
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if context is not related to the question, say I dont know.
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each answer
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Question: {question}
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@@ -69,6 +84,8 @@ qa_template2 = ("""
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Question: {question}
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ATrad Ai(QA): Let me think about it...""")
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# Load environment variables from .env file
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load_dotenv()
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# Access the value of OPENAI_API_KEY
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OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
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from langchain_openai import ChatOpenAI
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llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0,)
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## Create embeddings and splitter
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from langchain.embeddings import HuggingFaceBgeEmbeddings
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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# Create Embeddings
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model_name = "BAAI/bge-large-en"
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chunk_overlap=100,
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)
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from langchain_community.vectorstores import FAISS
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persits_directory="./faiss_Test02_500_C_BGE_large"
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vectorstore= FAISS.load_local(persits_directory, embedding)
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# Define a custom prompt for Unser manual
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from langchain.prompts import PromptTemplate
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if context is not enough to answer the question, ask for more information.
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if context is not related to the question, say I dont know.
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each answer Must start with code word ATrad Ai(QA):
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Question: {question}
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Question: {question}
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each answer Must start with code word ATrad Ai(QA):
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ATrad Ai(QA): Let me think about it...""")
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