File size: 2,971 Bytes
3f6526a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | import os
from pathlib import Path
from openhands.sdk import LLM, Agent, Conversation, Tool
from openhands.tools.file_editor import FileEditorTool
from openhands.tools.task_tracker import TaskTrackerTool
from openhands.tools.terminal import TerminalTool
# ============================================================================
# 基础示例 - 使用默认 system prompt
# ============================================================================
def basic_example():
"""使用默认的 system prompt"""
llm = LLM(
model=os.getenv("LLM_MODEL", "vertex_ai/gemini-2.5-flash"),
api_key=os.getenv("LLM_API_KEY"),
base_url=os.getenv("LLM_BASE_URL", None),
)
agent = Agent(
llm=llm,
tools=[
Tool(name=TerminalTool.name),
Tool(name=FileEditorTool.name),
Tool(name=TaskTrackerTool.name),
],
)
cwd = os.getcwd()
conversation = Conversation(agent=agent, workspace=cwd)
conversation.send_message("Write 3 facts about the current project into FACTS.txt.")
conversation.run()
print("All done!")
# ============================================================================
# 自定义示例 - 使用自定义的代码演化 prompt
# ============================================================================
def custom_evolution_example():
"""使用专门为代码演化任务定制的 system prompt"""
llm = LLM(
model=os.getenv("LLM_MODEL", "vertex_ai/gemini-2.5-flash"),
api_key=os.getenv("LLM_API_KEY"),
base_url=os.getenv("LLM_BASE_URL", None),
)
# 使用自定义的演化 prompt 模板
custom_prompt_path = Path(__file__).parent / "custom_evolution_prompt.j2"
agent = Agent(
llm=llm,
tools=[
Tool(name=TerminalTool.name),
Tool(name=FileEditorTool.name),
Tool(name=TaskTrackerTool.name),
],
# 指定自定义 prompt 文件
system_prompt_filename=str(custom_prompt_path),
# 传递额外的上下文变量到 prompt 模板
system_prompt_kwargs={
"custom_instructions": (
"Focus on evolutionary improvements. "
"Prioritize algorithmic efficiency and code clarity."
),
"project_name": "ShinkaEvolve",
"task_type": "Code Evolution",
"project_context": "Evolutionary framework for optimizing scientific code",
"task_description": "Analyze and improve the initial implementation",
},
)
cwd = os.getcwd()
conversation = Conversation(agent=agent, workspace=cwd)
conversation.send_message(
"Analyze the project structure and write 3 insights about "
"potential code evolution strategies into FACTS.txt."
)
conversation.run()
print("Evolution analysis complete!")
if __name__ == "__main__":
# 运行基础示例
# basic_example()
# 或者运行自定义演化示例
custom_evolution_example() |