Update app.py

app.py

@@ -24,6 +24,61 @@ from Virtualization import visualize_data
 
 
 
+bot_template = '''
+<div style="display: flex; align-items: center; margin-bottom: 10px; background-color: #B22222; padding: 10px; border-radius: 10px; border: 1px solid #7A0000;">
+    <div style="flex-shrink: 0; margin-right: 10px;">
+        <img src="https://raw.githubusercontent.com/AalaaAyman24/Test/main/chatbot.png" 
+             style="max-height: 50px; max-width: 50px; object-fit: cover;">
+    </div>
+    <div style="background-color: #B22222; color: white; padding: 10px; border-radius: 10px; max-width: 75%; word-wrap: break-word; overflow-wrap: break-word;">
+        {msg}
+    </div>
+</div>
+'''
+
+
+user_template = '''
+<div style="display: flex; align-items: center; margin-bottom: 10px; justify-content: flex-end;">
+    <div style="flex-shrink: 0; margin-left: 10px;">
+        <img src="https://raw.githubusercontent.com/AalaaAyman24/Test/main/question.png"
+             style="max-height: 50px; max-width: 50px; border-radius: 50%; object-fit: cover;">
+    </div>    
+    <div style="background-color: #757882; color: white; padding: 10px; border-radius: 10px; max-width: 75%; word-wrap: break-word; overflow-wrap: break-word;">
+        {msg}
+    </div>
+</div>
+'''
+
+button_style = """
+<style>
+    .small-button {
+        display: inline-block;
+        padding: 5px 10px;
+        font-size: 12px;
+        color: white;
+        background-color: #007bff;
+        border: none;
+        border-radius: 5px;
+        cursor: pointer;
+        margin-right: 5px;
+    }
+    .small-button:hover {
+        background-color: #0056b3;
+    }
+    .chat-box {
+        position: fixed;
+        bottom: 20px;
+        width: 100%;
+        left: 0;
+        padding: 20px;
+        background-color: #f1f1f1;
+        border-radius: 10px;
+        box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    }
+</style>
+"""
+
+
 # Helper Functions
 def create_documents(df):
     """Converts a DataFrame into a list of Document objects."""
@@ -106,33 +161,73 @@ def preview_data():
 
 
 api="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21"
+
 def rag_chatbot():
     st.title("RAG Chatbot")
+    st.markdown(button_style, unsafe_allow_html=True)
 
     # Check if data is uploaded
     if "data" in st.session_state and isinstance(st.session_state["data"], pd.DataFrame):
         df = st.session_state["data"]
 
         # Convert data to documents
-        st.write("Processing the dataset...")
         documents = create_documents(df)
 
         # Load models
-        st.write("Loading models...")
         embedding_model = load_embedding_model()
         llm_model = load_llm(api_key=api[:-2])
-
-        # Create retriever using Chroma
-         # FAISS.from_documents(documents, embedding)
         retriever = FAISS.from_documents(documents, embedding=embedding_model).as_retriever()
 
-        # Ask a question
-        question = st.text_input("Ask a question about your dataset:")
-        if question:
-            response = ask_question(question, retriever, llm_model)
-            st.write(f"Answer: {response}")
+        # Chat Interface
+        if "chat_history" not in st.session_state:
+            st.session_state["chat_history"] = []
+
+        question = st.text_area("Ask a question about your dataset:", key="question_input")
+        if st.button("Send", key="send_button"):
+            if question.strip():
+                # Append user message
+                st.session_state["chat_history"].append({"role": "user", "content": question})
+
+                # Generate response
+                response = ask_question(question, retriever, llm_model)
+                st.session_state["chat_history"].append({"role": "bot", "content": response})
+
+        # Render chat history
+        for message in st.session_state["chat_history"]:
+            if message["role"] == "user":
+                st.markdown(user_template.format(msg=message["content"]), unsafe_allow_html=True)
+            else:
+                st.markdown(bot_template.format(msg=message["content"]), unsafe_allow_html=True)
     else:
         st.warning("Please upload a dataset to proceed.")
+        
+# def rag_chatbot():
+#     st.title("RAG Chatbot")
+
+#     # Check if data is uploaded
+#     if "data" in st.session_state and isinstance(st.session_state["data"], pd.DataFrame):
+#         df = st.session_state["data"]
+
+#         # Convert data to documents
+#         st.write("Processing the dataset...")
+#         documents = create_documents(df)
+
+#         # Load models
+#         st.write("Loading models...")
+#         embedding_model = load_embedding_model()
+#         llm_model = load_llm(api_key=api[:-2])
+
+#         # Create retriever using Chroma
+#          # FAISS.from_documents(documents, embedding)
+#         retriever = FAISS.from_documents(documents, embedding=embedding_model).as_retriever()
+
+#         # Ask a question
+#         question = st.text_input("Ask a question about your dataset:")
+#         if question:
+#             response = ask_question(question, retriever, llm_model)
+#             st.write(f"Answer: {response}")
+#     else:
+#         st.warning("Please upload a dataset to proceed.")
 
 def main():
     st.sidebar.title("Navigation")