Planner agent structure

This commit is contained in:
martin legrand 2025-03-09 13:50:06 +01:00
parent 2c08509d1b
commit 0dbcf29701
3 changed files with 63 additions and 1 deletions

22
prompts/planner_agent.txt Normal file
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You are a planner agent.
Your goal is to divide and conquer the task using the following agents:
- Coder: An expert coder agent.
- File: An expert agent for finding files.
- Web: An expert agent for web search.
Agents are other AI that obey your instructions.
You will be given a task and you will need to divide it into smaller tasks and assign them to the agents.
Here is an example:
User: Make a cool game to illustrate the current relation between USA and europe
You:
Sure, here is the plan:
```plan
Web(name="web1"): Search for the current relation between USA and europe
Coder(name="coder1", need="web1"): Make a game to illustrate the current relation between USA and europe
```

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@ -3,5 +3,6 @@ from .agent import Agent
from .code_agent import CoderAgent
from .casual_agent import CasualAgent
from .file_agent import FileAgent
from .planner_agent import PlannerAgent
__all__ = ["Agent", "CoderAgent", "CasualAgent", "FileAgent"]
__all__ = ["Agent", "CoderAgent", "CasualAgent", "FileAgent", "PlannerAgent"]

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from sources.utility import pretty_print
from sources.agents.agent import Agent, CoderAgent, FileAgent
class PlannerAgent(Agent):
def __init__(self, model, name, prompt_path, provider):
"""
The planner agent is a special agent that divides and conquers the task.
"""
super().__init__(model, name, prompt_path, provider)
self.tools = {
}
self.agents = {
"coder": CoderAgent(model, name, prompt_path, provider),
"file": FileAgent(model, name, prompt_path, provider)
}
self.role = "planning"
def process(self, prompt, speech_module) -> str:
complete = False
exec_success = False
self.memory.push('user', prompt)
self.wait_message(speech_module)
while not complete:
if exec_success:
complete = True
pretty_print("Thinking...", color="status")
answer, reasoning = self.llm_request()
exec_success, _ = self.execute_modules(answer)
answer = self.remove_blocks(answer)
self.last_answer = answer
return answer, reasoning
if __name__ == "__main__":
from llm_provider import Provider
server_provider = Provider("server", "deepseek-r1:14b", "192.168.1.100:5000")
agent = PlannerAgent("deepseek-r1:14b", "jarvis", "prompts/planner_agent.txt", server_provider)
ans = agent.process("Make a cool game to illustrate the current relation between USA and europe")