Create app.py

app.py

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+# app.py
+
+import os
+from langchain.vectorstores import FAISS
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.chains import RetrievalQA
+from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+from langchain_community.llms import GPT4All
+from langchain.memory import ConversationBufferMemory
+import gradio as gr
+
+# Load embeddings and FAISS vector store
+def load_vectorstore():
+    model_name = "sentence-transformers/all-MiniLM-L6-v2"
+    embeddings = HuggingFaceEmbeddings(model_name=model_name)
+    db = FAISS.load_local("vectorstore", embeddings, allow_dangerous_deserialization=True)
+    return db
+
+db = load_vectorstore()
+
+# Initialize GPT4All model
+local_path = "./models/ggml-gpt4all-j.bin"  # Or any supported GPT4All model
+
+callbacks = [StreamingStdOutCallbackHandler()]
+llm = GPT4All(
+    model=local_path,
+    callbacks=callbacks,
+    verbose=True,
+)
+
+# Create Retrieval QA Chain
+qa_chain = RetrievalQA.from_chain_type(
+    llm=llm,
+    chain_type="stuff",
+    retriever=db.as_retriever(k=2),
+    return_source_documents=True
+)
+
+# Define chat function
+def chat(message, chat_history):
+    result = qa_chain({"query": message})
+    response = result["result"]
+    sources = result.get("source_documents", [])
+
+    if sources:
+        source_info = "\n\nSources:\n" + "\n".join([f"- {doc.metadata}" for doc in sources])
+        response += source_info
+
+    return response
+
+# Gradio Chat Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 🤖 My Offline RAG Chatbot (No API Key Needed)")
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(label="💬 Your Message")
+    clear = gr.Button("🗑️ Clear Chat")
+
+    state = gr.State([])
+
+    def respond(message, chat_history):
+        bot_response = chat(message, chat_history)
+        chat_history.append((message, bot_response))
+        return "", chat_history
+
+    msg.submit(respond, [msg, state], [msg, chatbot])
+    clear.click(lambda: ([], None), None, [chatbot, state])
+
+if __name__ == "__main__":
+    demo.launch()