app.py

import os
import gradio as gr
from langchain.text_splitter import CharacterTextSplitter
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores import FAISS
from langchain.chains import ConversationalRetrievalChain
from langchain_community.llms import HuggingFaceHub
from langchain_community.document_loaders import PyPDFLoader

# Load PDF
loader = PyPDFLoader("chimera.pdf")
documents = loader.load()

# Split documents
text_splitter = CharacterTextSplitter(chunk_size=800, chunk_overlap=100)
texts = text_splitter.split_documents(documents)

# Embeddings
embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
db = FAISS.from_documents(texts, embeddings)

retriever = db.as_retriever(search_kwargs={"k": 3})

# Hugging Face Hub LLM
hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
if hf_token is None:
    raise ValueError("HUGGINGFACEHUB_API_TOKEN not set in Space Secrets!")

llm = HuggingFaceHub(
    repo_id="google/flan-t5-base",
    model_kwargs={"temperature": 0},
    huggingfacehub_api_token=hf_token
)

qa = ConversationalRetrievalChain.from_llm(
    llm,
    retriever=retriever
)

chat_history = []

def respond(message, history):
    history = history[-6:]
    result = qa({"question": message, "chat_history": history})
    history.append((message, result["answer"]))
    return history, history

with gr.Blocks() as demo:
    with gr.Column():
        warning_text = gr.HTML(
            "<div style='background-color:black;color:white;padding:20px;'>⚠ WARNING: Investigative Simulation ⚠<br>Are you ready?</div>"
        )
        enter_btn = gr.Button("Enter the Case")
        exit_btn = gr.Button("Exit")
        chatbot = gr.Chatbot(visible=False)
        user_input = gr.Textbox(placeholder="Type here...", visible=False)
        submit_btn = gr.Button("Send", visible=False)

    def enter_case():
        return (
            gr.update(visible=True),
            gr.update(visible=True),
            gr.update(visible=True),
            gr.update(value=""),
            gr.update(visible=False),
            gr.update(visible=False)
        )

    def exit_case():
        return (
            gr.update(value="Session ended."),
            gr.update(visible=False),
            gr.update(visible=False),
            gr.update(visible=False),
            gr.update(visible=False),
            gr.update(visible=False)
        )

    enter_btn.click(enter_case, inputs=None, outputs=[chatbot, user_input, submit_btn, warning_text, enter_btn, exit_btn])
    exit_btn.click(exit_case, inputs=None, outputs=[warning_text, chatbot, user_input, submit_btn, enter_btn, exit_btn])
    submit_btn.click(respond, inputs=[user_input, chatbot], outputs=[chatbot, chatbot])

if __name__ == "__main__":
    demo.launch(share=True, enable_queue=True)