Update app.py

app.py

@@ -16,6 +16,7 @@ from tavily import TavilyClient
 import requests
 from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file
+from llama_index.core.chat_engine.types import AgentChatResponse
 
 # Initialize models and clients
 MODEL = 'llama3-groq-70b-8192-tool-use-preview'
@@ -48,18 +49,9 @@ def play_voice_output(response):
 # NumPy Code Calculator Tool
 def numpy_code_calculator(query):
     try:
-        llm_response = client.chat.completions.create(
-            model=MODEL,
-            messages=[
-                {"role": "user", "content": f"Write NumPy code to: {query}"}
-            ]
-        )
-        code = llm_response.choices[0].message.content
-        print(f"Generated NumPy code:\n{code}")
-
-        # Execute the code in a safe environment
+        # Assume query is a request for a numpy computation
         local_dict = {"np": np}
-        exec(code, local_dict)
+        exec(query, local_dict)
         result = local_dict.get("result", "No result found")
         return str(result)
     except Exception as e:
@@ -82,8 +74,6 @@ def image_generation(query):
     return "output.jpg"
 
 # Function to handle different input types and choose the right tool
-from llama_index.core.chat_engine.types import AgentChatResponse
-
 def handle_input(user_prompt, image=None, audio=None, websearch=False):
     if audio:
         if isinstance(audio, str):
@@ -115,7 +105,7 @@ def handle_input(user_prompt, image=None, audio=None, websearch=False):
     
     # Extract the content from AgentChatResponse to return as a string
     if isinstance(response, AgentChatResponse):
-        response = response.final_response # Use 'final_response' to access the text response
+        response = response.response
     
     return response
 
@@ -188,4 +178,4 @@ def main_interface(user_prompt, image=None, audio=None, voice_only=False, websea
 
 # Launch the UI
 demo = create_ui()
-demo.launch()
+demo.launch()