Update app.py

app.py

@@ -8,6 +8,8 @@ from skyfield.api import load, Topos, load_file
 from skyfield import almanac
 from tools.final_answer import FinalAnswerTool
 from Gradio_UI import GradioUI
+from langchain.memory import SimpleMemory
+from gradio import Interface
 import os
 import base64
 
@@ -282,6 +284,18 @@ def get_current_time_raw(timezone: str) -> str:
     except Exception as e:
         return f"Error: {str(e)}"
 
+# Memory initialization
+memory = SimpleMemory(
+    memory={
+        "location_provided": False,
+        "plant": None,
+        "root_crop": None,
+        "location_cautions": "",
+        "answer": "",
+        "last_question": None
+    }
+)
+
 # Model configuration
 final_answer = FinalAnswerTool()
 model = HfApiModel(
@@ -298,11 +312,38 @@ image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_co
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
 
+# Prompt template
+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}
+
+      User's input: {input}
+
+      Instructions:
+      1. If responding to a clarification question (last_question is not None), interpret the input as the answer to that question and update the state accordingly.
+      2. Otherwise, process the user's request as follows:
+         - Check if a plant name is provided and recognized. If not, ask "Please specify the plant you are interested in." If recognized, determine if it’s a root crop or above-ground plant (e.g., known plants: potato=root, tomato=above-ground). If unrecognized, ask "Is this plant a root crop? (yes/no)".
+         - Check if a location is provided. If yes, set location_provided to true. If the location is not on Earth (e.g., "Moon", "Mars"), set location_cautions to "Salute you explorer! Moon indices are Earth-specific due to gravitational and tidal influences. For other planets, develop indices based on local celestial cycles." and use it as the final answer. If on Earth, ask "Is this location suitable for outdoor planting? (yes/no)" to determine suitability.
+         - Determine if the request is about planting or pruning. For planting, ensure plant is defined (ask if not), then calculate the fertility index using get_moon_info. For pruning, calculate the pruning index.
+         - If location_cautions is not empty, append it to the answer.
+      3. When asking a question, format your response as:
+         "Action: Ask user\nQuestion: [your question]"
+      4. When all information is gathered, calculate the answer and call FinalAnswerTool.
+    """
+}
+
+
 # Initialize agent with all tools
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, get_moon_info, get_current_time_in_timezone, get_current_time_raw, image_generation_tool],
-    max_steps=6,
+    tools=[final_answer, get_moon_info, get_current_time_in_timezone, get_current_time_raw],
+    max_steps=10,
     verbosity_level=1,
     prompt_templates=prompt_templates
 #    execution_env=E2BSandbox(  
@@ -317,8 +358,60 @@ agent = CodeAgent(
 #    max_code_iterations=100, # Prevent infinite loops
 )
 
+# Conversation handler
+def conversation_handler(user_input, history):
+    global memory, agent
+    if memory["last_question"] is not None:
+        if memory["last_question"] == "plant":
+            memory["plant"] = user_input
+            known_plants = {"potato": True, "tomato": False}
+            if user_input in known_plants:
+                memory["root_crop"] = known_plants[user_input]
+            else:
+                memory["last_question"] = "root_crop"
+                return "Action: Ask user\nQuestion: Is this plant a root crop? (yes/no)"
+        elif memory["last_question"] == "root_crop":
+            memory["root_crop"] = user_input.lower() in ["yes", "y"]
+            memory["last_question"] = None
+        elif memory["last_question"] == "location_suitability":
+            if user_input.lower() in ["no", "n"]:
+                memory["location_cautions"] = "Ensure required conditions for the plant (e.g., indoor) before relying on the fertility indices."
+            else:
+                memory["location_cautions"] = ""
+            memory["last_question"] = None
+
+    output = agent.run(user_input)
+    if "Action: Ask user" in output:
+        question = output.split("Question: ")[1].strip()
+        if "plant" in question.lower():
+            memory["last_question"] = "plant"
+        elif "root crop" in question.lower():
+            memory["last_question"] = "root_crop"
+        elif "suitable for outdoor" in question.lower():
+            memory["last_question"] = "location_suitability"
+            memory["location_provided"] = True
+        return question
+    else:
+        if "Salute you explorer!" in output:
+            memory["location_cautions"] = output
+            memory["answer"] = output
+        elif memory["location_cautions"]:
+            memory["answer"] = output + " " + memory["location_cautions"]
+        else:
+            memory["answer"] = output
+        return output
+
+# Gradio interface
+interface = Interface(
+    fn=conversation_handler,
+    inputs="text",
+    outputs="text",
+    title="Garden Magus",
+    description="Ask about planting or pruning based on moon indices."
+)
+
 if __name__ == "__main__":
-    GradioUI(agent).launch()
+    interface.launch()
 
 # Change to your username and repo name
 # agent.push_to_hub('sergeyo7/Garden_Magus')