Merge pull request #21 from almutareb/add_gradio_examples

app_gui.py

@@ -18,6 +18,7 @@ if __name__ == "__main__":
     def bot(history):
         # Obtain the response from the 'infer' function using the latest input
         response = infer(history[-1][0], history)
+        print(response)
         history[-1][1] = response['output']
         return history
 
@@ -34,7 +35,7 @@ if __name__ == "__main__":
             )
             return result
         except Exception:
-            raise gr.Error("Model is Overloaded, Please retry later!")
+            raise gr.Warning("Model is Overloaded, please try again in a few minuteslater!")
         
     def vote(data: gr.LikeData):
         if data.liked:
@@ -42,9 +43,14 @@ if __name__ == "__main__":
         else:
             print("You downvoted this response: ")
 
+    def get_examples(input_text: str):
+        tmp_history = [(input_text, None)]
+        response = infer(input_text, tmp_history)
+        return response['output']
+
     # CSS styling for the Gradio interface
     css = """
-    #col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
+    #col-container {max-width: 1200px; margin-left: auto; margin-right: auto;}
     """
 
     # HTML content for the Gradio interface title
@@ -53,27 +59,49 @@ if __name__ == "__main__":
         <p>Hello, I BotTina 2.0, your intelligent AI assistant. I can help you explore Wuerttembergische Versicherungs products.<br />
     </div>
     """
+    head_style = """
+    <style>
+    @media (min-width: 1536px)
+    {
+        .gradio-container {
+            min-width: var(--size-full) !important;
+        }
+    }
+    </style>
+    """
 
     # Building the Gradio interface
-    with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    with gr.Blocks(theme=gr.themes.Soft(), title="InsurePal AI 🤵🏻‍♂️", head=head_style) as demo:
         with gr.Column(elem_id="col-container"):
-            gr.HTML(title)  # Add the HTML title to the interface
+            gr.HTML()  # Add the HTML title to the interface
             chatbot = gr.Chatbot([], elem_id="chatbot",
-                                        label="BotTina 2.0",
+                                        label="InsurePal AI",
                                         bubble_full_width=False,
                                         avatar_images=(None, "https://dacodi-production.s3.amazonaws.com/store/87bc00b6727589462954f2e3ff6f531c.png"),
                                         height=680,)  # Initialize the chatbot component
             chatbot.like(vote, None, None)
-            clear = gr.Button("Clear")  # Add a button to clear the chat
 
             # Create a row for the question input
             with gr.Row():
-                question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ")
+                question = gr.Textbox(label="Question", show_label=False, placeholder="Type your question and hit Enter ", scale=4)
+                send_btn = gr.Button(value="Send", variant="primary", scale=0)
+            with gr.Accordion(label="Beispiele", open=False):
+                #examples
+                examples = gr.Examples([
+                    "Welche Versicherungen brauche ich als Student?", 
+                    "Wie melde ich einen Schaden?",
+                    "Wie kann ich mich als Selbstständiger finanziell absichern?",
+                    "Welche Versicherungen sollte ich für meine Vorsorge abschliessen?"
+                    ], inputs=[question], label="") #, cache_examples="lazy", fn=get_examples, outputs=[chatbot]
+
+            with gr.Row():
+                clear = gr.Button("Clear")  # Add a button to clear the chat
 
         # Define the action when the question is submitted
         question.submit(add_text, [chatbot, question], [chatbot, question], queue=False).then(
-            bot, chatbot, chatbot
-        )
+            bot, chatbot, chatbot)
+        send_btn.click(add_text, [chatbot, question], [chatbot, question], queue=False).then(
+            bot, chatbot, chatbot)
         # Define the action for the clear button
         clear.click(lambda: None, None, chatbot, queue=False)
 

rag_app/agents/react_agent.py

@@ -7,6 +7,10 @@ from langchain.agents.output_parsers import ReActJsonSingleInputOutputParser
 from langchain.tools.render import render_text_description
 import os
 from dotenv import load_dotenv
+# local cache
+from langchain.globals import set_llm_cache
+from langchain.cache import SQLiteCache # sqlite
+#from langchain.cache import InMemoryCache # in memory cache
 from rag_app.structured_tools.structured_tools import (
     google_search, knowledgeBase_search
 )
@@ -22,6 +26,8 @@ GOOGLE_CSE_ID = os.getenv('GOOGLE_CSE_ID')
 GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
 LLM_MODEL = os.getenv('LLM_MODEL')
 
+set_llm_cache(SQLiteCache(database_path=".cache.db"))
+
 # Load the model from the Hugging Face Hub
 llm = HuggingFaceEndpoint(repo_id=LLM_MODEL, 
                           temperature=0.1, 
@@ -65,8 +71,8 @@ agent_executor = AgentExecutor(
     agent=agent, 
     tools=tools, 
     verbose=True,
-    max_iterations=10,       # cap number of iterations
-    #max_execution_time=60,  # timout at 60 sec
+    max_iterations=20,       # cap number of iterations
+    max_execution_time=90,  # timout at 60 sec
     return_intermediate_steps=True,
     handle_parsing_errors=True,
     )