| """Researcher Agent — gathers information and analyzes topics. |
| |
| Handles steps that involve research, analysis, or information gathering. |
| Uses the LLM to generate insights and summaries. |
| """ |
|
|
| from __future__ import annotations |
|
|
| import logging |
| from typing import Any |
|
|
| from .agent_base import BaseAgent |
| from ..memory.goal_memory import Goal |
|
|
| logger = logging.getLogger(__name__) |
|
|
|
|
| class ResearcherAgent(BaseAgent): |
| """Researches topics and gathers information for goal steps.""" |
|
|
| def __init__(self, goal_memory, persistent_memory=None, generate_fn=None): |
| super().__init__( |
| name="researcher", |
| role="Researcher", |
| description="Gathers information, analyzes topics, and generates insights", |
| goal_memory=goal_memory, |
| persistent_memory=persistent_memory, |
| generate_fn=generate_fn, |
| poll_interval_s=3.0, |
| ) |
|
|
| def _can_handle(self, goal: Goal) -> bool: |
| """Researcher handles goals related to research/analysis.""" |
| keywords = ["research", "analyze", "investigate", "study", "learn", "understand", |
| "explore", "gather", "find", "search", "compare", "evaluate"] |
| text = (goal.title + " " + goal.description).lower() |
| return any(kw in text for kw in keywords) |
|
|
| def process_goal(self, goal: Goal) -> dict[str, Any]: |
| """Execute a research step.""" |
| if goal.current_step >= len(goal.steps): |
| return {"success": True, "output": "No more steps"} |
|
|
| step = goal.steps[goal.current_step] |
| prompt = ( |
| f"You are a research agent. Execute this step:\n" |
| f"Goal: {goal.title}\n" |
| f"Step: {step['title']}\n" |
| f"Description: {step['description']}\n" |
| f"Research and provide a concise summary of findings.\n" |
| ) |
|
|
| response = self._generate(prompt) |
|
|
| |
| if self.persistent_memory and response: |
| self.persistent_memory.add_episodic( |
| "research", f"Research for '{goal.title}': {response[:200]}", |
| importance=0.7, tags=["research", goal.title[:20]] |
| ) |
|
|
| return {"success": True, "output": response[:200]} |
|
|
