""" Gemini SSE/JSON 流解析器 Gemini API 的流式响应格式与 Claude/OpenAI 不同: - 使用 JSON 数组格式 (不是 SSE) - 每个块是一个完整的 JSON 对象 - 响应以 [ 开始，以 ] 结束，块之间用 , 分隔 参考: https://ai.google.dev/api/generate-content#method:-models.streamgeneratecontent """ import json from typing import Any, Dict, List, Optional, Union class GeminiStreamParser: """ Gemini 流解析器 解析 Gemini streamGenerateContent API 的响应流。 Gemini 流式响应特点: - 返回 JSON 数组格式: [{chunk1}, {chunk2}, ...] - 每个 chunk 包含 candidates、usageMetadata 等字段 - finish_reason 可能值: STOP, MAX_TOKENS, SAFETY, RECITATION, OTHER """ # 停止原因 FINISH_REASON_STOP = "STOP" FINISH_REASON_MAX_TOKENS = "MAX_TOKENS" FINISH_REASON_SAFETY = "SAFETY" FINISH_REASON_RECITATION = "RECITATION" FINISH_REASON_OTHER = "OTHER" def __init__(self) -> None: self._buffer = "" self._in_array = False self._brace_depth = 0 def reset(self) -> None: """重置解析器状态""" self._buffer = "" self._in_array = False self._brace_depth = 0 def parse_chunk(self, chunk: Union[bytes, str]) -> List[Dict[str, Any]]: """ 解析流式数据块 Args: chunk: 原始数据（bytes 或 str） Returns: 解析后的事件列表 """ if isinstance(chunk, bytes): text = chunk.decode("utf-8") else: text = chunk events: List[Dict[str, Any]] = [] for char in text: if char == "[" and not self._in_array: self._in_array = True continue if char == "]" and self._in_array and self._brace_depth == 0: # 数组结束 self._in_array = False if self._buffer.strip(): try: obj = json.loads(self._buffer.strip().rstrip(",")) events.append(obj) except json.JSONDecodeError: pass self._buffer = "" continue if self._in_array: if char == "{": self._brace_depth += 1 elif char == "}": self._brace_depth -= 1 self._buffer += char # 当 brace_depth 回到 0 时，说明一个完整的 JSON 对象结束 if self._brace_depth == 0 and self._buffer.strip(): try: obj = json.loads(self._buffer.strip().rstrip(",")) events.append(obj) self._buffer = "" except json.JSONDecodeError: # 可能还不完整，继续累积 pass return events def parse_line(self, line: str) -> Optional[Dict[str, Any]]: """ 解析单行 JSON 数据 Args: line: JSON 数据行 Returns: 解析后的事件字典，如果无法解析返回 None """ if not line or line.strip() in ["[", "]", ","]: return None try: result = json.loads(line.strip().rstrip(",")) if isinstance(result, dict): return result return None except json.JSONDecodeError: return None def is_done_event(self, event: Dict[str, Any]) -> bool: """ 判断是否为结束事件 Args: event: 事件字典 Returns: True 如果是结束事件 """ candidates = event.get("candidates", []) if candidates: for candidate in candidates: finish_reason = candidate.get("finishReason") if finish_reason in ( self.FINISH_REASON_STOP, self.FINISH_REASON_MAX_TOKENS, self.FINISH_REASON_SAFETY, self.FINISH_REASON_RECITATION, self.FINISH_REASON_OTHER, ): return True return False def is_error_event(self, event: Dict[str, Any]) -> bool: """ 判断是否为错误事件 检测多种 Gemini 错误格式: 1. 顶层 error: {"error": {...}} 2. chunks 内嵌套 error: {"chunks": [{"error": {...}}]} 3. candidates 内的错误状态 Args: event: 事件字典 Returns: True 如果是错误事件 """ # 顶层 error if "error" in event: return True # chunks 内嵌套 error (某些 Gemini 响应格式) chunks = event.get("chunks", []) if chunks and isinstance(chunks, list): for chunk in chunks: if isinstance(chunk, dict) and "error" in chunk: return True return False def extract_error_info(self, event: Dict[str, Any]) -> Optional[Dict[str, Any]]: """ 从事件中提取错误信息 Args: event: 事件字典 Returns: 错误信息字典 {"code": int, "message": str, "status": str}，无错误返回 None """ # 顶层 error if "error" in event: error = event["error"] if isinstance(error, dict): return { "code": error.get("code"), "message": error.get("message", str(error)), "status": error.get("status"), } return {"code": None, "message": str(error), "status": None} # chunks 内嵌套 error chunks = event.get("chunks", []) if chunks and isinstance(chunks, list): for chunk in chunks: if isinstance(chunk, dict) and "error" in chunk: error = chunk["error"] if isinstance(error, dict): return { "code": error.get("code"), "message": error.get("message", str(error)), "status": error.get("status"), } return {"code": None, "message": str(error), "status": None} return None def get_finish_reason(self, event: Dict[str, Any]) -> Optional[str]: """ 获取结束原因 Args: event: 事件字典 Returns: 结束原因字符串 """ candidates = event.get("candidates", []) if candidates: reason = candidates[0].get("finishReason") return str(reason) if reason is not None else None return None def extract_text_delta(self, event: Dict[str, Any]) -> Optional[str]: """ 从响应中提取文本内容 Args: event: 事件字典 Returns: 文本内容，如果没有文本返回 None """ candidates = event.get("candidates", []) if not candidates: return None content = candidates[0].get("content", {}) parts = content.get("parts", []) text_parts = [] for part in parts: if "text" in part: text_parts.append(part["text"]) return "".join(text_parts) if text_parts else None def extract_usage(self, event: Dict[str, Any]) -> Optional[Dict[str, int]]: """ 从事件中提取 token 使用量 这是 Gemini token 提取的单一实现源，其他地方都应该调用此方法。 Args: event: 事件字典（包含 usageMetadata） Returns: 使用量字典，如果没有完整的使用量信息返回 None 注意: - 只有当 totalTokenCount 存在时才提取（确保是完整的 usage 数据） - 输出 token = thoughtsTokenCount + candidatesTokenCount """ usage_metadata = event.get("usageMetadata", {}) if not usage_metadata or "totalTokenCount" not in usage_metadata: return None # 输出 token = thoughtsTokenCount + candidatesTokenCount thoughts_tokens = usage_metadata.get("thoughtsTokenCount", 0) candidates_tokens = usage_metadata.get("candidatesTokenCount", 0) output_tokens = thoughts_tokens + candidates_tokens return { "input_tokens": usage_metadata.get("promptTokenCount", 0), "output_tokens": output_tokens, "total_tokens": usage_metadata.get("totalTokenCount", 0), "cached_tokens": usage_metadata.get("cachedContentTokenCount", 0), } def extract_model_version(self, event: Dict[str, Any]) -> Optional[str]: """ 从响应中提取模型版本 Args: event: 事件字典 Returns: 模型版本，如果没有返回 None """ version = event.get("modelVersion") return str(version) if version is not None else None def extract_safety_ratings(self, event: Dict[str, Any]) -> Optional[List[Dict[str, Any]]]: """ 从响应中提取安全评级 Args: event: 事件字典 Returns: 安全评级列表，如果没有返回 None """ candidates = event.get("candidates", []) if not candidates: return None ratings = candidates[0].get("safetyRatings") if isinstance(ratings, list): return ratings return None __all__ = ["GeminiStreamParser"]