"""
反馈业务逻辑模块 - 负责反馈提交和处理的核心业务逻辑
"""
import os
import json
import subprocess
import sys
from typing import Optional
from i18n import i18n
from ui_config import FeedbackResult
class FeedbackLogicManager:
"""反馈业务逻辑管理器"""
def __init__(self, parent_ui):
self.parent_ui = parent_ui
def submit_feedback(self):
"""提交反馈"""
feedback_text = self.parent_ui.feedback_text.toPlainText().strip()
# 处理上传的图片
if hasattr(self.parent_ui, 'uploaded_images') and self.parent_ui.uploaded_images:
feedback_text += self._process_uploaded_images()
# 根据选择的后缀选项追加相应内容
if feedback_text:
feedback_text += self._get_feedback_suffix()
self.parent_ui.feedback_result = FeedbackResult(
logs="".join(self.parent_ui.log_buffer),
interactive_feedback=feedback_text,
)
self.parent_ui.close()
def _process_uploaded_images(self):
"""处理上传的图片"""
# 检查是否启用base64传输
use_base64 = self.parent_ui.config.get("use_base64_transmission", False)
if use_base64:
return self._process_base64_images()
else:
return self._process_path_images()
def _process_base64_images(self):
"""处理base64传输的图片"""
image_info = "\n\n[附件图片 - Base64优化传输]:\n"
for i, img_data in enumerate(self.parent_ui.uploaded_images, 1):
if img_data.get('success'):
image_path = self._get_image_path(img_data)
if image_path:
base64_result = self._generate_optimized_base64(image_path)
if base64_result and base64_result.get('success'):
image_info += f"图片{i}: {base64_result['base64']}\n"
image_info += f"优化信息: 原始{base64_result['original_size']} → 优化{base64_result['optimized_size']}, "
image_info += f"大小{base64_result['file_size_kb']}KB, 压缩比{base64_result['compression_ratio']}\n\n"
else:
# base64生成失败，回退到路径模式
image_info += f"图片{i}路径: {image_path}\n"
image_info += f"图片{i}信息: {img_data.get('original_info', {})}\n"
image_info += f"注意: Base64优化失败，请直接查看路径文件\n\n"
image_info += "[处理指令]: 以上图片已通过优化Base64传输，请分析图片内容并处理用户反馈。\n"
return image_info
def _process_path_images(self):
"""处理路径传输的图片"""
image_info = "\n\n[附件图片 - 请先解析图片内容再处理反馈]:\n"
for i, img_data in enumerate(self.parent_ui.uploaded_images, 1):
if img_data.get('success'):
image_path = self._get_image_path(img_data)
if image_path:
if 'original_path' in img_data:
image_info += f"图片{i}路径: {img_data['original_path']}\n"
elif 'clipboard_path' in img_data:
image_info += f"图片{i}路径(剪贴板): {img_data['clipboard_path']}\n"
elif 'processed_path' in img_data:
image_info += f"图片{i}路径(处理后): {img_data['processed_path']}\n"
image_info += f"图片{i}信息: {img_data.get('original_info', {})}\n\n"
image_info += "[处理指令]: 请先查看并分析上述图片内容，然后结合图片信息处理用户的反馈内容。\n"
return image_info
def _get_image_path(self, img_data):
"""获取图片路径"""
if 'original_path' in img_data:
return img_data['original_path']
elif 'clipboard_path' in img_data:
return img_data['clipboard_path']
elif 'processed_path' in img_data:
return img_data['processed_path']
return None
def _generate_optimized_base64(self, image_path):
"""生成优化的base64"""
try:
from image_handler import ImageHandler
handler = ImageHandler()
# 智能判断图片类型
use_case = 'ui_screenshot' # 默认为UI截图
if 'clipboard' in str(image_path):
use_case = 'ui_screenshot'
# 使用配置中的目标大小
target_size = self.parent_ui.config.get("base64_target_size_kb", 50)
return handler.get_optimized_base64(image_path, target_size)
except Exception as e:
return None
def _get_feedback_suffix(self):
"""获取反馈后缀"""
if self.parent_ui.suffix_radio_force.isChecked():
return i18n.t("suffix_force")
elif self.parent_ui.suffix_radio_smart.isChecked():
return i18n.t("suffix_smart")
# suffix_radio_none 不追加任何内容
return ""
def on_quick_response_clicked(self, response_text: str):
"""处理快捷回复按钮点击事件"""
self.parent_ui.feedback_text.setPlainText(response_text)
# 自动提交反馈（会自动应用后缀选项）
self.submit_feedback()
def run_feedback_ui_process(self) -> Optional[FeedbackResult]:
"""运行反馈UI进程并获取结果"""
from PySide6.QtWidgets import QApplication
from ui_utils import get_dark_mode_palette
app = QApplication.instance() or QApplication()
app.setPalette(get_dark_mode_palette(app))
app.setStyle("Fusion")
result = self.parent_ui.run()
# 在获得结果后调用interactive-feedback-mcp等待用户反馈
if result and result.get("interactive_feedback"):
print("正在调用interactive-feedback-mcp等待您的反馈...")
mcp_result = self._call_interactive_feedback_mcp(
self.parent_ui.project_directory,
"用户反馈已提交，等待进一步指示"
)
# 如果MCP返回了额外的反馈，可以合并到结果中
if mcp_result and mcp_result.get("interactive_feedback"):
original_feedback = result["interactive_feedback"]
additional_feedback = mcp_result["interactive_feedback"]
if additional_feedback.strip(): # 只有在有额外反馈时才合并
result["interactive_feedback"] = f"{original_feedback}\n\n[额外反馈]: {additional_feedback}"
return result
def _call_interactive_feedback_mcp(self, project_directory: str, summary: str):
"""调用interactive-feedback-mcp等待用户反馈"""
try:
# 构建MCP调用命令
mcp_command = [
sys.executable, "-c",
f"""
import json
import sys
try:
# 模拟MCP interactive_feedback调用
print("MCP Interactive Feedback Started")
print(f"Project: {project_directory}")
print(f"Summary: {summary}")
print("等待用户反馈...")
# 这里应该是实际的MCP调用逻辑
# 暂时用输入等待来模拟
user_input = input("请输入反馈（按Enter结束）: ")
result = {{
"logs": "MCP调用完成",
"interactive_feedback": user_input
}}
print(json.dumps(result))
except Exception as e:
print(json.dumps({{"error": str(e)}}))
"""
]
# 执行MCP调用
process = subprocess.Popen(
mcp_command,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True
)
stdout, stderr = process.communicate()
if process.returncode == 0:
try:
result = json.loads(stdout.strip().split('\n')[-1])
return result
except:
return {"logs": stdout, "interactive_feedback": ""}
else:
print(f"MCP调用失败: {stderr}")
return {"logs": stderr, "interactive_feedback": ""}
except Exception as e:
print(f"调用interactive-feedback-mcp时出错: {e}")
return {"logs": str(e), "interactive_feedback": ""}
