新增difyapi 的Chat 请求运行器

pkg/provider/runnermgr.py

@@ -4,7 +4,7 @@ from . import runner
 from ..core import app
 
 from .runners import localagent
-
+from .runners import difypai
 
 class RunnerManager:
 

pkg/provider/runners/difyapi.py

@@ -0,0 +1,205 @@
+from __future__ import annotations
+
+import json
+import typing
+import aiohttp
+
+from .. import runner
+from ...core import app, entities as core_entities
+from .. import entities as llm_entities
+
+api_url = "请求地址/v1"
+api_key = "请求key"
+user_name = "dify-plugin"
+# 需要在dify的自定义字段中另外设置context和system_prompt
+headers = {
+    "Authorization": f"Bearer {api_key}",
+    "Content-Type": "application/json"
+}
+
+
+def get_content_text(content):
+    if isinstance(content, list):
+        return " ".join(str(element) if element.image_url is None else " " for element in content)
+    elif isinstance(content, str):
+        return content
+    else:
+        return ""
+
+
+@runner.runner_class("difyapi")
+class DifyAgentRunner(runner.RequestRunner):
+    """Dify API 对话请求器
+    """
+
+    async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
+        """运行请求"""
+        await query.use_model.requester.preprocess(query)
+
+        # 构建系统提示词
+        prompt_messages = query.prompt.messages.copy()
+        system_prompt = "\n".join(
+            f"{msg.role}: {get_content_text(msg.content)}" for msg in prompt_messages if msg.content
+        )
+
+        # 构建上下文
+        previous_messages = query.messages.copy()
+        user_message = [query.user_message]
+
+        # 检查 user_message 中的 image_url
+        image_urls = [element.image_url.url for element in query.user_message.content if element.type == 'image_url' and element.image_url is not None]
+
+        if len(image_urls) > 10:
+            raise ValueError("仅可包含最多10张图片")
+
+        data = {}
+        if image_urls:
+            data["files"] = [
+                {
+                    "type": "image",
+                    "transfer_method": "remote_url",
+                    "url": url
+                } for url in image_urls
+            ]
+        else:
+            data["files"] = []
+
+        # 继续处理其他逻辑
+        all_messages = previous_messages + user_message
+
+        context = "\n".join(
+            f"{msg.role}: {get_content_text(msg.content)}" for msg in all_messages if msg.content
+        )
+
+        # 构建请求数据
+        data.update({
+            "inputs": {
+                "context": context,
+                "system_prompt": system_prompt,
+                "files": data["files"]
+            },
+            "query": get_content_text(query.user_message.content),
+            "response_mode": "blocking",
+            "conversation_id": "",
+            "user": user_name
+            
+        })
+
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.post(api_url + "/chat-messages", headers=headers, json=data) as response:
+                    response_data = await response.json()
+                    response.raise_for_status()
+
+                    # 处理响应数据
+                    content_elements = [llm_entities.ContentElement.from_text(response_data.get("answer", ""))]
+
+                    msg = llm_entities.Message(
+                        role="assistant",
+                        content=content_elements
+                    )
+                    yield msg
+            except aiohttp.ClientResponseError as http_err:
+                if response.status == 404:
+                    error_message = "对话不存在"
+                elif response.status == 400:
+                    error_code = response_data.get("code")
+                    if error_code == "invalid_param":
+                        error_message = "传入参数异常"
+                    elif error_code == "app_unavailable":
+                        error_message = "App 配置不可用"
+                    elif error_code == "provider_not_initialize":
+                        error_message = "无可用模型凭据配置"
+                    elif error_code == "provider_quota_exceeded":
+                        error_message = "模型调用额度不足"
+                    elif error_code == "model_currently_not_support":
+                        error_message = "当前模型不可用"
+                    elif error_code == "completion_request_error":
+                        error_message = "文本生成失败"
+                elif response.status == 500:
+                    error_message = "服务内部异常"
+                else:
+                    error_message = f"HTTP error occurred: {http_err}"
+                raise ValueError(error_message)
+            except Exception as err:
+                raise ValueError(f"An error occurred: {err}")
+
+
+@runner.runner_class("local-agent")
+class LocalAgentRunner(runner.RequestRunner):
+    """本地Agent请求运行器
+    """
+
+    async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
+        """运行请求
+        """
+        await query.use_model.requester.preprocess(query)
+
+        pending_tool_calls = []
+
+        req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
+
+        # 首次请求
+        try:
+            msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
+            if "answer" not in msg.content:
+                raise ValueError("请求失败：返回内容不含answer")
+        except Exception as e:
+            err_msg = llm_entities.Message(
+                role="system", content=f"请求失败：{e}"
+            )
+            yield err_msg
+            return
+
+        yield msg
+
+        pending_tool_calls = msg.tool_calls
+
+        req_messages.append(msg)
+
+        # 持续请求，只要还有待处理的工具调用就继续处理调用
+        while pending_tool_calls:
+            for tool_call in pending_tool_calls:
+                try:
+                    func = tool_call.function
+                    
+                    parameters = json.loads(func.arguments)
+
+                    func_ret = await self.ap.tool_mgr.execute_func_call(
+                        query, func.name, parameters
+                    )
+
+                    msg = llm_entities.Message(
+                        role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
+                    )
+
+                    yield msg
+
+                    req_messages.append(msg)
+                except Exception as e:
+                    # 工具调用出错，添加一个报错信息到 req_messages
+                    err_msg = llm_entities.Message(
+                        role="tool", content=f"err: {e}", tool_call_id=tool_call.id
+                    )
+
+                    yield err_msg
+
+                    req_messages.append(err_msg)
+
+            # 处理完所有调用，再次请求
+            try:
+                msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
+                if "answer" not in msg.content:
+                    raise ValueError("请求失败：返回内容不含answer")
+            except Exception as e:
+                err_msg = llm_entities.Message(
+                    role="system", content=f"请求失败：{e}"
+                )
+                yield err_msg
+                return
+
+            yield msg
+
+            pending_tool_calls = msg.tool_calls
+
+            req_messages.append(msg)