Create app.py

app.py

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+import gradio as gr
+import os
+
+os.environ["OPENAI_API_KEY"] = "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"
+
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Chroma
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.llms import OpenAI
+from langchain.chains import ConversationalRetrievalChain
+from langchain.document_loaders import DirectoryLoader
+
+
+
+
+txt_loader = DirectoryLoader('.\', glob="**/*.txt")
+pdf_loader = DirectoryLoader('.\', glob="**/*.pdf")
+doc_loader = DirectoryLoader('.\', glob="**/*.docx")
+loaders = [pdf_loader, txt_loader, doc_loader]
+documents = []
+
+for loader in loaders:
+    documents.extend(loader.load())
+    
+print(f"Total # of documents: {len(documents)}")
+
+text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+documents = text_splitter.split_documents(documents)
+
+embeddings = OpenAIEmbeddings()
+vectorstore = Chroma.from_documents(documents, embeddings)
+
+from langchain.memory import ConversationBufferMemory
+memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
+
+qa = ConversationalRetrievalChain.from_llm(OpenAI(temperature=0), vectorstore.as_retriever(), memory=memory)
+
+chat_history = []
+
+def submit_callback(user_message):
+    default_prompt = " Please format your response in the following way: Each statement should be in a newline . "
+    prompt = default_prompt + user_message
+    
+    # Process user input and generate chatbot response
+    response = qa({"question": prompt, "chat_history": chat_history})
+    chat_history.append((prompt, response["answer"]))
+    return response["answer"]
+
+iface = gr.Interface(
+    fn=submit_callback,
+    inputs=gr.inputs.Textbox(lines=2, label="Enter your query"),
+    outputs=gr.outputs.Textbox(label="Chatbot Response"),
+    #outputs=gr.outputs.HTML(label="Chatbot Response"),
+    title="LVE Torpedoes Chatbot",
+    layout="vertical",
+    description="Enter your query to chat with the LVET chatbot",
+    examples=[
+        ["What are the practice times for each age group ?"],
+        ["What are the eligibility criteria for the Mini Torpedoes program?"],
+        ["What is the eligibility to participate in the LVET Swim Team?"],
+        ["How many volunteer hours are required per family during the swim season?"],
+        ["What strokes can swimmers participate in at swim meets?"],
+        ["How are swimmers grouped for practice?"],
+        ["When do evaluations take place for new swimmers?"],
+        ["Who are LVET's Board Members"],
+        ["How can I read swim meet results ?"],
+        ["How can I contact LVET's Board Members?"],
+        ["What is the penalty for not meeting the required volunteer hours?"],
+        ["Volunteer Hours?"],
+        ["Registration info?"],
+        ["How do I sign up for volunteer jobs to fulfill my volunteer hours?"],
+        ["Volunteer jobs that do not require certification or prior experience"],
+        ["What are the responsibilities of an Age Group Coordinator?"],
+        ["How do I commit my swimmer for meets/events?"],
+        ["What age groups and races does the LVET Swim Team participate in?"]
+    ],
+    theme="default"
+    
+)
+iface.launch(share=True)
+while True:
+    pass