mirror of
https://github.com/Zippland/Snap-Solver.git
synced 2026-02-05 08:21:25 +08:00
重构前端UI和交互逻辑，提升用户体验和代码可维护性
This commit is contained in:
Zylan
@@ -91,39 +91,47 @@ class ClaudeModel(BaseModel):
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if 'delta' in data:
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if 'text' in data['delta']:
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text_chunk = data['delta']['text']
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yield {
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"status": "streaming",
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"content": text_chunk
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}
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response_buffer += text_chunk
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# 只在每累积一定数量的字符后才发送，减少UI跳变
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if len(text_chunk) >= 10 or text_chunk.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "streaming",
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"content": response_buffer
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}
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elif 'thinking' in data['delta']:
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thinking_chunk = data['delta']['thinking']
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thinking_content += thinking_chunk
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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# 只在每累积一定数量的字符后才发送，减少UI跳变
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if len(thinking_chunk) >= 20 or thinking_chunk.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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# 处理新的extended_thinking格式
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elif data.get('type') == 'extended_thinking_delta':
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if 'delta' in data and 'text' in data['delta']:
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thinking_chunk = data['delta']['text']
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thinking_content += thinking_chunk
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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# 只在每累积一定数量的字符后才发送，减少UI跳变
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if len(thinking_chunk) >= 20 or thinking_chunk.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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elif data.get('type') == 'message_stop':
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# 确保发送完整的思考内容
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if thinking_content:
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yield {
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"status": "thinking_complete",
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"content": thinking_content
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}
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# 确保发送完整的响应内容
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yield {
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"status": "completed",
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"content": ""
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"content": response_buffer
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}
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elif data.get('type') == 'error':
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@@ -144,7 +152,7 @@ class ClaudeModel(BaseModel):
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"error": f"Streaming error: {str(e)}"
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}
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def analyze_image(self, image_data, prompt, socket=None, proxies=None):
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def analyze_image(self, image_data, proxies=None):
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yield {"status": "started"}
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api_key = self.api_key
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@@ -157,6 +165,9 @@ class ClaudeModel(BaseModel):
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'content-type': 'application/json'
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}
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# 获取系统提示词，确保包含语言设置
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system_prompt = self.system_prompt
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payload = {
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'model': 'claude-3-7-sonnet-20250219',
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'stream': True,
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@@ -166,7 +177,7 @@ class ClaudeModel(BaseModel):
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'type': 'enabled',
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'budget_tokens': 4096
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},
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'system': "You are a helpful AI assistant that specializes in solving math problems. You should provide step-by-step solutions and explanations for any math problem presented to you. If you're given an image, analyze any mathematical content in it and provide a detailed solution.",
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'system': system_prompt,
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'messages': [{
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'role': 'user',
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'content': [
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@@ -225,36 +236,44 @@ class ClaudeModel(BaseModel):
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if 'delta' in data:
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if 'text' in data['delta']:
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text_chunk = data['delta']['text']
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yield {
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"status": "streaming",
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"content": text_chunk
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}
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response_buffer += text_chunk
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# 只在每累积一定数量的字符后才发送，减少UI跳变
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if len(text_chunk) >= 10 or text_chunk.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "streaming",
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"content": response_buffer
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}
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elif 'thinking' in data['delta']:
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thinking_chunk = data['delta']['thinking']
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thinking_content += thinking_chunk
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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# 只在每累积一定数量的字符后才发送，减少UI跳变
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if len(thinking_chunk) >= 20 or thinking_chunk.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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# 处理新的extended_thinking格式
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elif data.get('type') == 'extended_thinking_delta':
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if 'delta' in data and 'text' in data['delta']:
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thinking_chunk = data['delta']['text']
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thinking_content += thinking_chunk
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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# 只在每累积一定数量的字符后才发送，减少UI跳变
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if len(thinking_chunk) >= 20 or thinking_chunk.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "thinking",
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"content": thinking_content
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}
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elif data.get('type') == 'message_stop':
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# 确保发送完整的思考内容
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if thinking_content:
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yield {
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"status": "thinking_complete",
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"content": thinking_content
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}
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# 确保发送完整的响应内容
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yield {
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"status": "completed",
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"content": response_buffer
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@@ -35,12 +35,10 @@ class GPT4oModel(BaseModel):
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if 'https' in proxies:
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os.environ['https_proxy'] = proxies['https']
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# Create OpenAI client
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client = OpenAI(
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api_key=self.api_key,
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base_url="https://api.openai.com/v1" # Replace with actual GPT-4o API endpoint
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)
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# Initialize OpenAI client
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client = OpenAI(api_key=self.api_key)
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# Prepare messages
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messages = [
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{
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"role": "system",
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@@ -60,39 +58,49 @@ class GPT4oModel(BaseModel):
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max_tokens=4000
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)
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# 使用累积缓冲区
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response_buffer = ""
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for chunk in response:
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if hasattr(chunk.choices[0].delta, 'content'):
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content = chunk.choices[0].delta.content
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if content:
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yield {
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"status": "streaming",
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"content": content
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}
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# 累积内容
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response_buffer += content
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# 只在累积一定数量的字符或遇到句子结束标记时才发送
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if len(content) >= 10 or content.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "streaming",
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"content": response_buffer
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}
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# 确保发送最终完整内容
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if response_buffer:
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yield {
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"status": "streaming",
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"content": response_buffer
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}
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# Send completion status
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yield {
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"status": "completed",
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"content": ""
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"content": response_buffer
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}
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finally:
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# Restore original environment state
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for key, value in original_env.items():
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if value is None:
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os.environ.pop(key, None)
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if key in os.environ:
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del os.environ[key]
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else:
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os.environ[key] = value
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except Exception as e:
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error_msg = str(e)
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if "invalid_api_key" in error_msg.lower():
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error_msg = "Invalid API key provided"
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elif "rate_limit" in error_msg.lower():
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error_msg = "Rate limit exceeded. Please try again later."
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yield {
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"status": "error",
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"error": f"GPT-4o API error: {error_msg}"
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"error": str(e)
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}
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def analyze_image(self, image_data: str, proxies: dict = None) -> Generator[dict, None, None]:
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@@ -115,12 +123,10 @@ class GPT4oModel(BaseModel):
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if 'https' in proxies:
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os.environ['https_proxy'] = proxies['https']
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# Create OpenAI client
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client = OpenAI(
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api_key=self.api_key,
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base_url="https://api.openai.com/v1" # Replace with actual GPT-4o API endpoint
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)
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# Initialize OpenAI client
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client = OpenAI(api_key=self.api_key)
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# Prepare messages with image
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messages = [
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{
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"role": "system",
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@@ -132,13 +138,12 @@ class GPT4oModel(BaseModel):
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{
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"type": "image_url",
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"image_url": {
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"url": image_data if image_data.startswith('data:') else f"data:image/png;base64,{image_data}",
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"detail": "high"
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"url": f"data:image/jpeg;base64,{image_data}"
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}
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},
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{
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"type": "text",
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"text": "Please analyze this question and provide a detailed solution. If you see multiple questions, focus on solving them one at a time."
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"text": "Please analyze this image and provide a detailed solution."
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}
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]
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}
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@@ -152,37 +157,47 @@ class GPT4oModel(BaseModel):
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max_tokens=4000
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)
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# 使用累积缓冲区
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response_buffer = ""
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for chunk in response:
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if hasattr(chunk.choices[0].delta, 'content'):
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content = chunk.choices[0].delta.content
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if content:
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yield {
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"status": "streaming",
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"content": content
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}
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# 累积内容
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response_buffer += content
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# 只在累积一定数量的字符或遇到句子结束标记时才发送
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if len(content) >= 10 or content.endswith(('.', '!', '?', '。', '！', '？', '\n')):
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yield {
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"status": "streaming",
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"content": response_buffer
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}
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# 确保发送最终完整内容
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if response_buffer:
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yield {
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"status": "streaming",
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"content": response_buffer
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}
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# Send completion status
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yield {
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"status": "completed",
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"content": ""
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"content": response_buffer
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}
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finally:
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# Restore original environment state
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for key, value in original_env.items():
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if value is None:
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os.environ.pop(key, None)
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if key in os.environ:
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del os.environ[key]
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else:
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os.environ[key] = value
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except Exception as e:
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error_msg = str(e)
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if "invalid_api_key" in error_msg.lower():
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error_msg = "Invalid API key provided"
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elif "rate_limit" in error_msg.lower():
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error_msg = "Rate limit exceeded. Please try again later."
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yield {
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"status": "error",
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"error": f"GPT-4o API error: {error_msg}"
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"error": str(e)
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}
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