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interactive.py
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180 lines (154 loc) · 5.97 KB
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#!/usr/bin/env python3
"""
text_adventure 交互式 Shell
使用方法:
python interactive.py --model /to/model.litertlm --skill-dir /to/skills
环境变量:
LITEAGENT_MODEL_PATH 默认模型路径
LITEAGENT_SKILL_DIR 默认技能目录
"""
import sys
import os
import ast
import argparse
from text_adventure import text_adventure
def create_interactive_shell(agent):
"""创建交互式对话 Shell"""
print("=" * 60)
print("text_adventure Interactive Shell")
print("=" * 60)
print(f"模型：{agent.model_path}")
if agent._skill_manager:
print(f"可用技能：{', '.join(agent.get_available_skills())}")
else:
print("可用技能：无")
print("提示符：输入 'quit' 或 'exit' 退出，'history' 查看历史")
print("=" * 60)
history = [] # 存储对话历史
BLUE = '\033[94m'
YELLOW = '\033[93m'
END = '\033[0m'
while True:
try:
# 获取用户输入
user_input = input(f"\n{BLUE}您：{END}").strip()
if not user_input:
continue
if user_input.lower() in ('quit', 'exit', 'q'):
print("再见！")
break
if user_input.lower() == 'history':
if not history:
print("暂无历史记录")
else:
print("\n--- 对话历史 ---")
for i, (inp, out) in enumerate(history, 1):
print(f"\n{i}. {BLUE}您：{inp}{END}")
# 显示原始响应或解析后的内容
cleaned = out.strip().rstrip(',')
try:
if cleaned.startswith('[') and cleaned.endswith(']'):
json_data = ast.literal_eval(cleaned)
if isinstance(json_data, list) and len(json_data) > 0:
if isinstance(json_data[0], dict):
answer = json_data[0].get('text', out)
print(f" {YELLOW}助手：{answer}{END}")
continue
except (ValueError, SyntaxError):
pass
# 显示原始响应
print(f" {YELLOW}助手：{out}{END}")
continue
if user_input.lower() == 'clear':
history = []
print("对话历史已清")
continue
# 发送消息
if user_input.startswith('/skill '):
# 查询技能信息
skill_name = user_input[7:].strip()
info = agent.get_skill_info(skill_name)
if info:
print(f"\n技能：{info['name']}")
print(f"描述：{info['description']}")
print(f"指令:\n{info['instructions']}")
else:
print(f"未找到技能：{skill_name}")
continue
if user_input.startswith('/list'):
agent.list_skills()
continue
# 发送消息获取响应
response = agent.chat(user_input)
# 显示响应 - 检查返回格式
if isinstance(response, str):
# 尝试解析可能的 JSON 格式响应
cleaned = response.strip().rstrip(',')
if cleaned.startswith('[') and cleaned.endswith(']'):
# 可能是列表格式的 JSON，尝试解析
try:
json_data = ast.literal_eval(cleaned)
if isinstance(json_data, list) and len(json_data) > 0:
# 提取第一个元素的 text 字段
if isinstance(json_data[0], dict):
answer = json_data[0].get('text', str(response))
else:
answer = str(response)
else:
answer = str(response)
except (ValueError, SyntaxError):
# 不是有效 JSON，直接显示
answer = str(response)
else:
# 不是列表，直接显示
answer = str(response)
else:
answer = str(response)
print(f"助手：{YELLOW}{answer}{END}")
# 保存到历史
history.append((user_input, response))
except EOFError:
print("\n再见！")
break
except KeyboardInterrupt:
print("\n再见！")
break
except Exception as e:
print(f"错误：{e}")
def main():
parser = argparse.ArgumentParser(description="text_adventure 交互式 Shell")
parser.add_argument(
"--model",
type=str,
default=os.environ.get('LITEAGENT_MODEL_PATH', None),
help="LiteRT-LM 模型文件路径 (默认：LITEAGENT_MODEL_PATH 环境变量)"
)
parser.add_argument(
"--skill-dir",
type=str,
default=os.environ.get('LITEAGENT_SKILL_DIR', ''),
help="SKILL.md 目录路径 (默认：LITEAGENT_SKILL_DIR 环境变量)"
)
parser.add_argument(
"--temperature",
type=float,
default=0.7,
help="采样温度 (0.0 最确定，1.0 最随机)"
)
args = parser.parse_args()
# 验证模型路径
if not args.model:
print("❌ 错误：未指定模型路径")
print("请使用 --model 参数或设置 LITEAGENT_MODEL_PATH 环境变量")
sys.exit(1)
# 创建 Agent
agent = text_adventure(
model_path=args.model,
skill_dir=args.skill_dir,
temperature=args.temperature,
max_tokens=32678
)
# 启动交互式 Shell
create_interactive_shell(agent)
if __name__ == "__main__":
main()