在本教學中，我們將使用 ClientAI 和 Ollama 來建構一個人工智慧驅動的任務規劃器。我們的計劃者會將目標分解為可操作的任務，創建現實的時間表並管理資源 - 所有這些都在您自己的機器上運行。
我們的任務規劃器將能夠：
有關 ClientAI 的文檔，請參閱此處；有關 Github Repo，請參閱此處。
首先，為您的專案建立一個新目錄：
mkdir local_task_planner cd local_task_planner
在 Ollama 支援下安裝 ClientAI：
pip install clientai[ollama]
確保您的系統上安裝了 Ollama。您可以從 Ollama 的網站取得。
建立我們的主要 Python 檔案：
touch task_planner.py
讓我們從核心導入開始：
from datetime import datetime, timedelta from typing import Dict, List import logging from clientai import ClientAI from clientai.agent import create_agent, tool from clientai.ollama import OllamaManager logger = logging.getLogger(__name__)
每個組件都扮演著至關重要的角色：
首先，讓我們建立用於管理 AI 互動的 TaskPlanner 類別：
class TaskPlanner:
"""A local task planning system using Ollama."""
def __init__(self):
"""Initialize the task planner with Ollama."""
self.manager = OllamaManager()
self.client = None
self.planner = None
def start(self):
"""Start the Ollama server and initialize the client."""
self.manager.start()
self.client = ClientAI("ollama", host="http://localhost:11434")
self.planner = create_agent(
client=self.client,
role="task planner",
system_prompt="""You are a practical task planner. Break down goals into
specific, actionable tasks with realistic time estimates and resource needs.
Use the tools provided to validate timelines and format plans properly.""",
model="llama3",
step="think",
tools=[validate_timeline, format_plan],
tool_confidence=0.8,
stream=True,
)
這個課程是我們的基礎。它管理 Ollama 伺服器生命週期，建立和配置我們的 AI 用戶端，並設定具有特定功能的規劃代理程式。
現在讓我們建構人工智慧將使用的工具。首先，時間軸驗證器：
@tool(name="validate_timeline")
def validate_timeline(tasks: Dict[str, int]) -> Dict[str, dict]:
"""
Validate time estimates and create a realistic timeline.
Args:
tasks: Dictionary of task names and estimated hours
Returns:
Dictionary with start dates and deadlines
"""
try:
current_date = datetime.now()
timeline = {}
accumulated_hours = 0
for task, hours in tasks.items():
try:
hours_int = int(float(str(hours)))
if hours_int <= 0:
logger.warning(f"Skipping task {task}: Invalid hours value {hours}")
continue
days_needed = hours_int / 6
start_date = current_date + timedelta(hours=accumulated_hours)
end_date = start_date + timedelta(days=days_needed)
timeline[task] = {
"start": start_date.strftime("%Y-%m-%d"),
"end": end_date.strftime("%Y-%m-%d"),
"hours": hours_int,
}
accumulated_hours += hours_int
except (ValueError, TypeError) as e:
logger.warning(f"Skipping task {task}: Invalid hours value {hours} - {e}")
continue
return timeline
except Exception as e:
logger.error(f"Error validating timeline: {str(e)}")
return {}
此驗證器將時間估計轉換為工作日，優雅地處理無效輸入，建立現實的順序調度並提供詳細的偵錯日誌記錄。
接下來，讓我們建立計劃格式化程式：
@tool(name="format_plan")
def format_plan(
tasks: List[str],
timeline: Dict[str, dict],
resources: List[str]
) -> str:
"""
Format the plan in a clear, structured way.
Args:
tasks: List of tasks
timeline: Timeline from validate_timeline
resources: List of required resources
Returns:
Formatted plan as a string
"""
try:
plan = "== Project Plan ==\n\n"
plan += "Tasks and Timeline:\n"
for i, task in enumerate(tasks, 1):
if task in timeline:
t = timeline[task]
plan += f"\n{i}. {task}\n"
plan += f" Start: {t['start']}\n"
plan += f" End: {t['end']}\n"
plan += f" Estimated Hours: {t['hours']}\n"
plan += "\nRequired Resources:\n"
for resource in resources:
plan += f"- {resource}\n"
return plan
except Exception as e:
logger.error(f"Error formatting plan: {str(e)}")
return "Error: Unable to format plan"
在這裡，我們希望透過正確的任務編號和有組織的時間軸來創建一致、可讀的輸出。
讓我們為我們的計劃者創建一個用戶友好的介面：
def get_plan(self, goal: str) -> str:
"""
Generate a plan for the given goal.
Args:
goal: The goal to plan for
Returns:
A formatted plan string
"""
if not self.planner:
raise RuntimeError("Planner not initialized. Call start() first.")
return self.planner.run(goal)
def main():
planner = TaskPlanner()
try:
print("Task Planner (Local AI)")
print("Enter your goal, and I'll create a practical, timeline-based plan.")
print("Type 'quit' to exit.")
planner.start()
while True:
print("\n" + "=" * 50 + "\n")
goal = input("Enter your goal: ")
if goal.lower() == "quit":
break
try:
plan = planner.get_plan(goal)
print("\nYour Plan:\n")
for chunk in plan:
print(chunk, end="", flush=True)
except Exception as e:
print(f"Error: {str(e)}")
finally:
planner.stop()
if __name__ == "__main__":
main()
我們的介面提供：
以下是執行計劃程式時您將看到的內容：
Task Planner (Local AI) Enter your goal, and I'll create a practical, timeline-based plan. Type 'quit' to exit. ================================================== Enter your goal: Create a personal portfolio website Your Plan: == Project Plan == Tasks and Timeline: 1. Requirements Analysis and Planning Start: 2024-12-08 End: 2024-12-09 Estimated Hours: 6 2. Design and Wireframing Start: 2024-12-09 End: 2024-12-11 Estimated Hours: 12 3. Content Creation Start: 2024-12-11 End: 2024-12-12 Estimated Hours: 8 4. Development Start: 2024-12-12 End: 2024-12-15 Estimated Hours: 20 Required Resources: - Design software (e.g., Figma) - Text editor or IDE - Web hosting service - Version control system
為您自己的任務規劃器考慮這些增強功能：
要了解有關 ClientAI 的更多信息，請訪問文件。
如果您對本教學有任何疑問或想分享您對任務規劃程式的改進，請隨時聯絡：
以上是使用 ClientAI 和 Ollama 建構本地 AI 任務規劃器的詳細內容。更多資訊請關注PHP中文網其他相關文章！
