Update app.py

app.py

@@ -130,7 +130,7 @@ def get_moon_info(date_time: str) -> dict:
         # Calculate Moon's ecliptic longitude
         astrometric = earth.at(t).observe(moon)
         ecliptic_lat, ecliptic_lon, distance = astrometric.ecliptic_latlon()
-        lon_thr = ecliptic_lon.degrees % 360
+        lon_deg = ecliptic_lon.degrees % 360
 
         # Calculate the phase angle using almanac.moon_phase
         phase = almanac.moon_phase(planets, t)
@@ -238,12 +238,12 @@ memory = SimpleMemory(
 prompt_templates = {
     "main_prompt": """
       Current state:
-      - location_provided: {memory.location_provided}
-      - plant: {memory.plant}
-      - root_crop: {memory.root_crop}
-      - location_cautions: {memory.location_cautions}
-      - answer: {memory.answer}
-      - last_question: {memory.last_question}
+      - location_provided: {memory[location_provided]}
+      - plant: {memory[plant]}
+      - root_crop: {memory[root_crop]}
+      - location_cautions: {memory[location_cautions]}
+      - answer: {memory[answer]}
+      - last_question: {memory[last_question]}
 
       User's input: {input}
 
@@ -270,14 +270,13 @@ model = HfApiModel(
 )
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
-# Initialize the agent
+# Initialize the agent without the 'memory' parameter
 agent = CodeAgent(
     model=model,
     tools=[final_answer, get_moon_info, get_current_time_in_timezone, get_current_time_raw, image_generation_tool],
     max_steps=10,
     verbosity_level=1,
     prompt_templates=prompt_templates,
-    memory=memory
 )
 
 # Conversation handler for multi-turn interactions
@@ -302,7 +301,15 @@ def conversation_handler(user_input, history):
                 memory["location_cautions"] = ""
             memory["last_question"] = None
 
-    output = agent.run(user_input)
+    # Update the prompt with current memory state
+    current_prompt = prompt_templates["main_prompt"].format(
+        memory=memory.memory,  # Pass the memory dictionary directly
+        input=user_input
+    )
+    
+    # Run the agent with the updated prompt
+    output = agent.run(current_prompt)
+    
     if "Action: Ask user" in output:
         question = output.split("Question: ")[1].strip()
         if "plant" in question.lower():