tcsenpai/agenticSeek
1
0
Fork 0
mirror of https://github.com/tcsenpai/agenticSeek.git synced 2025-06-06 19:15:28 +00:00
Code Issues Packages Projects Releases Wiki Activity

fix : planner not passing info properly between agents

Browse Source
This commit is contained in:
martin legrand 2025-03-26 20:51:31 +01:00
parent 5dd3ffd9ef
commit 1027a2a77b
1 changed files with 7 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

11
sources/agents/planner_agent.py
View File

@ -63,6 +63,8 @@ class PlannerAgent(Agent):
return zip(tasks_names, tasks) return zip(tasks_names, tasks)
def make_prompt(self, task, needed_infos): def make_prompt(self, task, needed_infos):
if needed_infos is None:
needed_infos = "No needed informations."
prompt = f""" prompt = f"""
You are given the following informations: You are given the following informations:
{needed_infos} {needed_infos}
@ -96,20 +98,21 @@ class PlannerAgent(Agent):
agents_tasks = self.parse_agent_tasks(answer) agents_tasks = self.parse_agent_tasks(answer)
if agents_tasks == (None, None): if agents_tasks == (None, None):
return "Failed to parse the tasks", reasoning return "Failed to parse the tasks", reasoning
prev_agent_answer = None
for task_name, task in agents_tasks: for task_name, task in agents_tasks:
pretty_print(f"I will {task_name}.", color="info") pretty_print(f"I will {task_name}.", color="info")
agent_prompt = self.make_prompt(task['task'], task['need']) agent_prompt = self.make_prompt(task['task'], prev_agent_answer)
pretty_print(f"Assigned agent {task['agent']} to {task_name}", color="info") 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.") if speech_module: speech_module.speak(f"I will {task_name}. I assigned the {task['agent']} agent to the task.")
try: try:
self.agents[task['agent'].lower()].process(agent_prompt, speech_module) prev_agent_answer, _ = self.agents[task['agent'].lower()].process(agent_prompt, speech_module)
pretty_print(f"-- Agent answer ---\n\n", color="output") pretty_print(f"-- Agent answer ---\n\n", color="output")
self.agents[task['agent'].lower()].show_answer() self.agents[task['agent'].lower()].show_answer()
pretty_print(f"\n\n", color="output") pretty_print(f"\n\n", color="output")
except Exception as e: except Exception as e:
raise e raise e
self.last_answer = answer self.last_answer = prev_agent_answer
return answer, reasoning return prev_agent_answer, reasoning
if __name__ == "__main__": if __name__ == "__main__":
from llm_provider import Provider from llm_provider import Provider