feat : display planner next task on front

prompts/base/planner_agent.txt

@@ -81,4 +81,5 @@ Rules:
 - Do not search for tutorial.
 - Make sure json is within ```json tag
 - Coding agent should write the whole code in a single file unless instructed otherwise.
+- Do not use python for NLP analysis of a text, you can review a text with the casual agent
 - One step, one agent.

sources/agents/code_agent.py

@@ -35,7 +35,7 @@ class CoderAgent(Agent):
         info = f"System Info:\n" \
                f"OS: {platform.system()} {platform.release()}\n" \
                f"Python Version: {platform.python_version()}\n" \
-               f"\nYou must save file in work directory: {self.work_dir}"
+               f"\nYou must save file at root directory: {self.work_dir}"
         return f"{prompt}\n\n{info}"
 
     async def process(self, prompt, speech_module) -> str:

sources/agents/planner_agent.py

@@ -224,7 +224,6 @@ class PlannerAgent(Agent):
         self.agents[task['agent'].lower()].show_answer()
         pretty_print(f"Agent {task['agent']} completed task.", color="status")
         self.logger.info(f"Agent {task['agent']} finished working on {task['task']}. Success: {success}")
-        # TODO ajouter feedback / agent et code executer
         agent_answer += "\nAgent succeeded with task." if success else "\nAgent failed with task (Error detected)."
         return agent_answer, success
     
@@ -257,6 +256,7 @@ class PlannerAgent(Agent):
             task_name, task = agents_tasks[i][0], agents_tasks[i][1]
             self.status_message = "Starting agents..."
             pretty_print(f"I will {task_name}.", color="info")
+            self.last_answer = f"I will {task_name.lower()}."
             pretty_print(f"Assigned agent {task['agent']} to {task_name}", color="info")
             if speech_module: speech_module.speak(f"I will {task_name}. I assigned the {task['agent']} agent to the task.")