process_message只保留find、get工具
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朱潮
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@ -144,7 +144,15 @@ def process_messages(messages: List[Dict], language: Optional[str] = None) -> Li
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这是 get_content_from_messages 的逆运算，将包含 [TOOL_RESPONSE] 的消息重新组装回
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msg['role'] == 'function' 和 msg.get('function_call') 的格式。
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Args:
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messages: 消息列表
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language: 可选的语言参数
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include_function_name: 需要包含的function_name关键词列表，默认包含['find', 'get']
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"""
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# 设置默认的排除function_name列表
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include_function_name = ['find', 'get']
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processed_messages = []
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# 收集所有ASSISTANT消息的索引
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@ -173,38 +181,36 @@ def process_messages(messages: List[Dict], language: Optional[str] = None) -> Li
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continue
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# 不往后传输 历史工具调用的文字
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if current_tag == "ANSWER":
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filtered_content += f"[ANSWER]\n{text}\n"
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# if current_tag == "TOOL_RESPONSE":
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# if is_recent_message:
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# # 最近10条ASSISTANT消息：保留完整TOOL_RESPONSE信息（使用简略模式）
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# if len(text) <= 500:
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# filtered_content += f"[TOOL_RESPONSE]\n{text}\n"
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# else:
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# # 截取前中后3段内容，每段250字
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# first_part = text[:250]
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# middle_start = len(text) // 2 - 125
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# middle_part = text[middle_start:middle_start + 250]
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# last_part = text[-250:]
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if current_tag == "TOOL_RESPONSE":
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if is_recent_message:
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# 最近10条ASSISTANT消息：保留完整TOOL_RESPONSE信息（使用简略模式）
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if len(text) <= 1000:
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filtered_content += f"[TOOL_RESPONSE] {text}\n"
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else:
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# 截取前中后3段内容，每段250字
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first_part = text[:250]
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middle_start = len(text) // 2 - 125
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middle_part = text[middle_start:middle_start + 250]
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last_part = text[-250:]
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# # 计算省略的字数
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# omitted_count = len(text) - 750
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# omitted_text = f"...此处省略{omitted_count}字..."
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# 计算省略的字数
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omitted_count = len(text) - 750
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omitted_text = f"...此处省略{omitted_count}字..."
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# # 拼接内容
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# truncated_text = f"{first_part}\n{omitted_text}\n{middle_part}\n{omitted_text}\n{last_part}"
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# filtered_content += f"[TOOL_RESPONSE]\n{truncated_text}\n"
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# # 10条以上的消息：不保留TOOL_RESPONSE数据（完全跳过）
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# elif current_tag == "TOOL_CALL":
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# if is_recent_message:
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# # 最近10条ASSISTANT消息：保留TOOL_CALL信息
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# filtered_content += f"[TOOL_CALL]\n{text}\n"
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# # 10条以上的消息：不保留TOOL_CALL数据（完全跳过）
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# elif current_tag == "ANSWER":
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# # 所有ASSISTANT消息都保留ANSWER数据
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# filtered_content += f"[ANSWER]\n{text}\n"
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# elif current_tag != "THINK" and current_tag != "PREAMBLE":
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# filtered_content += text + "\n"
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# 拼接内容
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truncated_text = f"{first_part}\n{omitted_text}\n{middle_part}\n{omitted_text}\n{last_part}"
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filtered_content += f"[TOOL_RESPONSE] {truncated_text}\n"
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# 10条以上的消息：不保留TOOL_RESPONSE数据（完全跳过）
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elif current_tag == "TOOL_CALL":
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if is_recent_message:
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# 最近10条ASSISTANT消息：保留TOOL_CALL信息
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filtered_content += f"[TOOL_CALL] {text}\n"
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# 10条以上的消息：不保留TOOL_CALL数据（完全跳过）
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elif current_tag == "ANSWER":
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# 所有ASSISTANT消息都保留ANSWER数据
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filtered_content += f"[ANSWER] {text}\n"
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elif current_tag != "THINK" and current_tag != "PREAMBLE":
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filtered_content += text + "\n"
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else: # 标签
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current_tag = parts[i]
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@ -237,48 +243,61 @@ def process_messages(messages: List[Dict], language: Optional[str] = None) -> Li
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if not text:
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continue
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# 不往后传输 历史工具调用的文字
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if current_tag == "ANSWER":
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if current_tag == "TOOL_RESPONSE":
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# 解析 TOOL_RESPONSE 格式：[TOOL_RESPONSE] function_name\ncontent
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lines = text.split('\n', 1)
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function_name = lines[0].strip() if lines else ""
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response_content = lines[1].strip() if len(lines) > 1 else ""
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# 过滤掉包含指定关键词的function_name
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should_include = False
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if function_name:
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for exclude_name in include_function_name:
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if exclude_name in function_name:
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should_include = True
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break
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if should_include:
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final_messages.append({
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"role": FUNCTION,
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"name": function_name,
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"content": response_content
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})
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elif current_tag == "TOOL_CALL":
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# 解析 TOOL_CALL 格式：[TOOL_CALL] function_name\narguments
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lines = text.split('\n', 1)
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function_name = lines[0].strip() if lines else ""
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arguments = lines[1].strip() if len(lines) > 1 else ""
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# 过滤掉包含指定关键词的function_name
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should_include = False
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if function_name:
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for exclude_name in include_function_name:
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if exclude_name in function_name:
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should_include = True
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break
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if should_include:
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final_messages.append({
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"role": ASSISTANT,
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"content": "",
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"function_call": {
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"name": function_name,
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"arguments": arguments
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}
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})
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elif current_tag != "THINK" and current_tag != "PREAMBLE":
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final_messages.append({
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"role": ASSISTANT,
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"content": text
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})
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# if current_tag == "TOOL_RESPONSE":
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# # 解析 TOOL_RESPONSE 格式：[TOOL_RESPONSE] function_name\ncontent
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# lines = text.split('\n', 1)
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# function_name = lines[0].strip() if lines else ""
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# response_content = lines[1].strip() if len(lines) > 1 else ""
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# final_messages.append({
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# "role": FUNCTION,
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# "name": function_name,
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# "content": response_content
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# })
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# elif current_tag == "TOOL_CALL":
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# # 解析 TOOL_CALL 格式：[TOOL_CALL] function_name\narguments
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# lines = text.split('\n', 1)
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# function_name = lines[0].strip() if lines else ""
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# arguments = lines[1].strip() if len(lines) > 1 else ""
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# final_messages.append({
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# "role": ASSISTANT,
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# "content": "",
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# "function_call": {
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# "name": function_name,
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# "arguments": arguments
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# }
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# })
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# elif current_tag != "THINK" and current_tag != "PREAMBLE":
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# final_messages.append({
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# "role": ASSISTANT,
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# "content": text
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# })
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else: # 标签
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current_tag = parts[i]
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else:
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# 非 assistant 消息或不包含 [TOOL_RESPONSE] 的消息直接添加
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final_messages.append(msg)
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print(final_messages)
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return final_messages
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