Update app.py

app.py

@@ -23,8 +23,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, Agent, LocalAgent
 # print(agent.run("Is the following `text` (in Spanish) positive or negative?", text="¡Este es un API muy agradable!"))
 
 # Load tools
-controlnet_transformer = load_tool("huggingface-tools/text-to-image")
-upscaler = load_tool("diffusers/latent-upscaler-tool")
+controlnet_transformer = load_tool("Chris4K/random-character-tool")
+upscaler = load_tool("Chris4K/text-generation-tool")
 
 
 tools = [controlnet_transformer, upscaler]
@@ -55,7 +55,7 @@ class CustomHfAgent(Agent):
             return self._generate_one(prompt)
         elif response.status_code != 200:
             raise ValueError(f"Errors {inputs} {response.status_code}: {response.json()}")
-
+        print(response)
         result = response.json()[0]["generated_text"]
         # Inference API returns the stop sequence
         for stop_seq in stop:
@@ -71,8 +71,8 @@ message = st.text_input("Enter your message:", "")
 
 # Checkboxes for the tools to be used by the agent
 
-        
-tool_checkboxes = [st.checkbox(f"Use {tool}") for tool in tools]
+
+tool_checkboxes = [st.checkbox(f"Use {tool.name} --- {tool.description} ") for tool in tools]
 
 # Submit button
 #submit_button = st.button("Submit")
@@ -94,7 +94,7 @@ def handle_submission():
 
     # Run the agent with the user's message and selected tools
     #response = agent.run(message, tools=selected_tools)
-    response = agent.run(message)
+    response = agent.chat(message)
 
     print(response)
 
@@ -120,7 +120,9 @@ def handle_submission():
     # ...
     
     # Display the agent's response
-    if isinstance(response, Image.Image):
+    if response is None:
+        st.warning("The agent's response is None.")
+    elif isinstance(response, Image.Image):
         # Display the image response
         st.image(response)
     elif "audio" in response: