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增加对Agent应用的支持 fixed #5

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LzSkyline 2025-04-10 19:18:05 +08:00
parent 75598b34f9
commit d374400d80
3 changed files with 75 additions and 1 deletions
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1
README.md
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@ -13,6 +13,7 @@ OpenDify 是一个将 Dify API 转换为 OpenAI API 格式的代理服务器。
- 智能动态延迟控制，提供流畅的输出体验
- 支持多种会话记忆模式，包括零宽字符模式和history_message模式
- 支持多个模型配置
- 支持Dify Agent应用，处理高级工具调用（如生成图片等）
- 兼容标准的 OpenAI API 客户端
- 自动获取 Dify 应用信息

1
README_EN.md
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@ -13,6 +13,7 @@ OpenDify is a proxy server that transforms the Dify API into OpenAI API format.
- Intelligent dynamic delay control for smooth output experience
- Multiple conversation memory modes, including zero-width character mode and history_message mode
- Support for multiple model configurations
- Support for Dify Agent applications with advanced tool calls (like image generation)
- Compatible with standard OpenAI API clients
- Automatic fetching of Dify application information

74
main.py
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@ -179,7 +179,22 @@ def transform_dify_to_openai(dify_response, model="claude-3-5-sonnet-v2", stream
"""将Dify格式的响应转换为OpenAI格式"""
if not stream:
answer = dify_response.get("answer", "")
# 首先获取回答内容，支持不同的响应模式
answer = ""
mode = dify_response.get("mode", "")
# 普通聊天模式
if "answer" in dify_response:
answer = dify_response.get("answer", "")
# 如果是Agent模式，需要从agent_thoughts中提取回答
elif "agent_thoughts" in dify_response:
# Agent模式下通常最后一个thought包含最终答案
agent_thoughts = dify_response.get("agent_thoughts", [])
if agent_thoughts:
for thought in agent_thoughts:
if thought.get("thought"):
answer = thought.get("thought", "")
# 只在零宽字符会话记忆模式时处理conversation_id
if CONVERSATION_MEMORY_MODE == 2:
@ -524,6 +539,63 @@ def chat_completions():
# 立即继续处理下一个请求
continue
# 处理Agent模式的消息事件
elif dify_chunk.get("event") == "agent_message" and "answer" in dify_chunk:
current_answer = dify_chunk["answer"]
if not current_answer:
continue
message_id = dify_chunk.get("message_id", "")
if not generate.message_id:
generate.message_id = message_id
# 将当前批次的字符添加到输出缓冲区
for char in current_answer:
output_buffer.append((char, generate.message_id))
# 根据缓冲区大小动态调整输出速度
while output_buffer:
char, msg_id = output_buffer.pop(0)
yield send_char(char, msg_id)
# 根据剩余缓冲区大小计算延迟
delay = calculate_delay(len(output_buffer))
time.sleep(delay)
# 立即继续处理下一个请求
continue
# 处理Agent的思考过程，记录日志但不输出给用户
elif dify_chunk.get("event") == "agent_thought":
thought_id = dify_chunk.get("id", "")
thought = dify_chunk.get("thought", "")
tool = dify_chunk.get("tool", "")
tool_input = dify_chunk.get("tool_input", "")
observation = dify_chunk.get("observation", "")
logger.info(f"[Agent Thought] ID: {thought_id}, Tool: {tool}")
if thought:
logger.info(f"[Agent Thought] Thought: {thought}")
if tool_input:
logger.info(f"[Agent Thought] Tool Input: {tool_input}")
if observation:
logger.info(f"[Agent Thought] Observation: {observation}")
# 获取message_id以关联思考和最终输出
message_id = dify_chunk.get("message_id", "")
if not generate.message_id and message_id:
generate.message_id = message_id
continue
# 处理消息中的文件(如图片)，记录日志但不直接输出给用户
elif dify_chunk.get("event") == "message_file":
file_id = dify_chunk.get("id", "")
file_type = dify_chunk.get("type", "")
file_url = dify_chunk.get("url", "")
logger.info(f"[Message File] ID: {file_id}, Type: {file_type}, URL: {file_url}")
continue
elif dify_chunk.get("event") == "message_end":
# 快速输出剩余内容
while output_buffer: