Update app.py

app.py

@@ -1,4 +1,157 @@
 import streamlit as st
+import json
+from data_module import faq_data, model_options
+import uuid
+from chat_handler import ChatHandler
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+chat = ChatHandler()
+def add_custom_css():
+    st.markdown("""
+        <style>
+            .css-1d391kg { width: 35%; }
+        </style>
+        """, unsafe_allow_html=True)
+def generate_user_id():
+    new_id = chat.generate_id()
+    return new_id
+
+def clear_history(user_id):
+    chat.clear_history(user_id)
+    return 'response'
+
+if 'user_id' not in st.session_state:
+    st.session_state['user_id'] = generate_user_id()
+        
+with open("embeddings_db_model.json", "r") as file:
+    embedding_models = json.load(file)
+embedding_model_names = [model["model"] for model in embedding_models]
+
+agent_types = [
+                'JSON_CHAT_MODEL',
+                'REACT_TEXT'
+              ]
+selected_model = st.sidebar.selectbox("Escolha o Modelo LLM", model_options)
+selected_embedding_model = st.sidebar.selectbox("Escolha o Modelo de Embedding", embedding_model_names)
+selected_embedding_dir = next(item for item in embedding_models if item["model"] == selected_embedding_model)["dir"]
+selected_agent_type = st.sidebar.selectbox("Escolha o Tipo de Agent", agent_types)
+
+
+add_custom_css()    
+with st.sidebar:
+    st.write("## Opções de Controle")
+    if st.button('Limpar Histórico'):
+        # Fazer a requisição para limpar o histórico
+        response = clear_history(st.session_state['user_id'])
+        if response:
+            st.session_state.messages = [{"role": "assistant", "content": "Histórico limpo. Pode começar uma nova conversa."}]
+            st.rerun()
+        else:
+            st.error("Erro ao limpar o histórico")
+with st.container():
+    col1, col2 = st.columns([1, 1])
+    with col1:
+        st.caption("LLM:")
+        st.write(selected_model)
+    with col2:
+        st.caption("Embeddings:")
+        st.write(selected_embedding_model)
+
+st.title("⚖️ ChatBot Direito Tributário")
+st.caption("Direito Tributário da Pessoa Jurídica")
+st.caption("Projeto do Workshop de LLM UFG")      
+
+
+    
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [{"role": "assistant", "content": "Olá como posso ajudar?"}]        
+if "faq_question" not in st.session_state:
+    st.session_state["faq_question"] = None 
+
+# Input de chat do usuário
+for msg in st.session_state.messages:
+    if msg['role'] == 'assistant':
+        img = "server_icon.png"
+    else:
+        img = 'user_icon.png'
+    st.chat_message(msg["role"],avatar=img).write(msg["content"]) 
+
+def process_question(question):
+    st.session_state.messages.append({"role": "user", "content": question})
+    st.chat_message("user", avatar="user_icon.png").write(question)
+
+    with st.chat_message("assistant", avatar="server_icon.png"):
+        with st.spinner("Thinking..."):
+            data = dict(
+                user_id=st.session_state['user_id'],
+                text= question,
+                embedding_model= selected_embedding_model,
+                embedding_dir= selected_embedding_dir,
+                model= selected_model,
+                agent_type=selected_agent_type
+            )
+            
+            msg,intermediary_steps = chat.post_message(message=data)
+            st.write(str(msg))
+            st.session_state.messages.append({"role": "assistant", "content": msg})
+                # Adicionando os passos intermediários
+            #intermediary_steps = response['response']['intermediate_steps']
+            # intermediary_steps = []
+
+            if intermediary_steps:
+                with st.expander("Ver Passos Intermediários"):
+                    if intermediary_steps[0] == 'erro':
+                        st.markdown("## ERROR...\n")
+                    else:    
+                        st.markdown("##  > Entering new AgentExecutor chain...\n")
+                        for index, step in enumerate(intermediary_steps, start=1):
+                            # action = step[0].get('tool', 'Unknown')
+                            action = step[0].tool if hasattr(step[0], 'tool') else 'Unknown'
+                            # action_input = step[0].get('tool_input', 'N/A')
+                            # log = step[0].get('log', 'No log available')
+                            action_input = step[0].tool_input if hasattr(step[0], 'tool_input') else 'N/A'
+                            log = step[0].log if hasattr(step[0], 'log') else 'No log available'
+                            st.markdown(f"**Passo {index}:**")
+                            st.markdown(f"    **Ação:** `{action}`")
+                            st.markdown(f"    **Entrada da Ação:** `{action_input}`")
+                            st.code(log, language='json')
+                            st.markdown("---")
+                        # Adiciona a ação "Final Answer" ao final dos passos
+                        st.markdown("**Ação:** Final Answer")
+                        st.markdown(f"**Entrada da Ação:** `{msg}`")
+                        st.markdown("## > Finished chain.")
+            else:
+                with st.expander("Ver Passos Intermediários"):
+                    st.markdown("#### > Entering new AgentExecutor chain...\n")
+                    st.markdown("**Ação:** Final Answer")
+                    st.markdown(f"**Entrada da Ação:** `{msg}`")
+                    st.markdown("#### > Finished chain...")
+
+def add_faq_question_to_chat(question):
+    st.session_state["faq_question"] = question
+    
+# Barra lateral com perguntas frequentes
+with st.sidebar:
+    st.write("## Perguntas Frequentes")
+    for index, item in enumerate(faq_data, start=1):
+        question_with_number = f"{index}\. {item['question']}"
+        expander = st.expander(question_with_number, expanded=False)
+
+        with expander:
+            st.write(item["answer"])
+            button_key = f"button_{index}"
+            if st.button("Enviar esta pergunta", key=button_key):
+                st.session_state['selected_question'] = item["question"]
+
+if 'selected_question' in st.session_state and st.session_state['selected_question']:
+    add_faq_question_to_chat(st.session_state['selected_question'])
+    del st.session_state['selected_question']
+
+
+
+if st.session_state["faq_question"]:
+    process_question(st.session_state["faq_question"])
+    st.session_state["faq_question"] = None  
+
+    
+if prompt := st.chat_input():
+    process_question(prompt)