接入dify工作流内容
This commit is contained in:
liuwei
@@ -144,12 +144,12 @@ class DifyChat:
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"query": query,
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"conversation_id": session_id
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}
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# 准备请求数据
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# 准备请求数据
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data = {
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"sys.files": [],
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"user": user_id,
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"inputs": inputs_params,
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"response_mode": "streaming" # 使用流式响应
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"response_mode": "blocking" # 使用阻塞响应模式
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}
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# 添加历史记录
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@@ -171,111 +171,80 @@ class DifyChat:
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self.LOG.info(f"请求数据: {json.dumps(data, ensure_ascii=False)}")
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try:
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# 使用流式请求
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with requests.post(url, headers=headers, json=data, proxies=proxies, stream=True) as response:
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if response.status_code != 200:
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self.LOG.error(f"Dify API请求失败: {response.status_code} {response.text}")
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return f"请求失败，状态码: {response.status_code}"
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# 使用普通请求（非流式）
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response = requests.post(url, headers=headers, json=data, proxies=proxies)
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if response.status_code != 200:
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self.LOG.error(f"Dify API请求失败: {response.status_code} {response.text}")
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return f"请求失败，状态码: {response.status_code}"
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answer = ""
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total_tokens = 0
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# 解析响应
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response_data = response.json()
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self.LOG.info(f"收到Dify API响应: {json.dumps(response_data, ensure_ascii=False)}")
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# 提取回答内容
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answer = ""
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total_tokens = 0
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# 获取输出内容
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outputs = response_data.get("data", {}).get("outputs", {})
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if outputs:
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# 尝试从text字段获取回答
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if "text" in outputs and isinstance(outputs["text"], str):
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answer = outputs["text"]
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# 如果没有text字段，尝试从其他字段获取
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else:
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for key, value in outputs.items():
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if isinstance(value, str) and value.strip():
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answer += value
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elif isinstance(value, dict):
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# 处理嵌套字典的情况
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for sub_key, sub_value in value.items():
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if isinstance(sub_value, str) and sub_value.strip():
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answer += sub_value
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elif isinstance(value, list):
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# 处理列表的情况
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for item in value:
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if isinstance(item, str) and item.strip():
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answer += item
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elif isinstance(item, dict):
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# 处理列表中的字典
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for item_key, item_value in item.items():
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if isinstance(item_value, str) and item_value.strip():
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answer += item_value
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# 获取token使用情况
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total_tokens = response_data.get("data", {}).get("total_tokens", 0)
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# 处理流式响应
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for line in response.iter_lines():
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if not line:
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continue
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# 更新会话历史
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self.conversations[session_id].append({
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"role": "user",
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"content": query
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})
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# 解析事件流数据
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line_text = line.decode('utf-8')
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self.LOG.info(f"收到事件流数据: {line_text}")
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if not line_text.startswith('data: '):
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continue
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self.conversations[session_id].append({
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"role": "assistant",
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"content": answer
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})
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# 提取JSON数据部分
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json_str = line_text[6:] # 去掉 "data: " 前缀
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# 限制会话历史长度
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if len(self.conversations[session_id]) > self.max_history_length * 2:
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self.conversations[session_id] = self.conversations[session_id][-self.max_history_length * 2:]
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try:
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event_data = json.loads(json_str)
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if not event_data:
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continue
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event_type = event_data.get("event")
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if not event_type:
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continue
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# 处理不同类型的事件
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if event_type == "workflow_finished":
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# 工作流完成事件，可以获取总token数
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data_obj = event_data.get("data", {})
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if data_obj:
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total_tokens = data_obj.get("total_tokens", 0)
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# 统计token使用情况
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if total_tokens > 0:
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if user_id in self.token_usage:
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self.token_usage[user_id] += total_tokens
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else:
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self.token_usage[user_id] = total_tokens
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elif event_type == "node_finished":
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# 节点完成事件，可以获取节点输出和token使用情况
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data_obj = event_data.get("data", {})
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if not data_obj:
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continue
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outputs = data_obj.get("outputs", {})
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# 从outputs中提取回答内容
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if outputs and isinstance(outputs, dict):
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for key, value in outputs.items():
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if isinstance(value, str) and value.strip():
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answer += value
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elif isinstance(value, dict):
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# 处理嵌套字典的情况
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for sub_key, sub_value in value.items():
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if isinstance(sub_value, str) and sub_value.strip():
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answer += sub_value
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elif isinstance(value, list):
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# 处理列表的情况
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for item in value:
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if isinstance(item, str) and item.strip():
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answer += item
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elif isinstance(item, dict):
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# 处理列表中的字典
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for item_key, item_value in item.items():
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if isinstance(item_value, str) and item_value.strip():
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answer += item_value
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self.LOG.info(
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f"用户 {user_id} 本次消耗 {total_tokens} tokens，累计 {self.token_usage[user_id]} tokens")
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# 获取token使用情况
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execution_metadata = data_obj.get("execution_metadata", {})
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if "total_tokens" in execution_metadata:
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total_tokens = execution_metadata.get("total_tokens", 0)
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except json.JSONDecodeError:
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self.LOG.error(f"解析事件流数据失败: {line_text}")
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continue
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# 更新会话历史
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self.conversations[session_id].append({
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"role": "user",
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"content": query
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})
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self.conversations[session_id].append({
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"role": "assistant",
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"content": answer
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})
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# 限制会话历史长度
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if len(self.conversations[session_id]) > self.max_history_length * 2:
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self.conversations[session_id] = self.conversations[session_id][-self.max_history_length * 2:]
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# 统计token使用情况
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if total_tokens > 0:
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if user_id in self.token_usage:
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self.token_usage[user_id] += total_tokens
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else:
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self.token_usage[user_id] = total_tokens
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self.LOG.info(
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f"用户 {user_id} 本次消耗 {total_tokens} tokens，累计 {self.token_usage[user_id]} tokens")
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return answer
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return answer
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except Exception as e:
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self.LOG.error(f"处理Dify流式响应时出错: {str(e)}")
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self.LOG.error(f"处理Dify响应时出错: {str(e)}")
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return f"处理响应时出错: {str(e)}"
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def _cleanup_expired_conversations(self) -> None:
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