openai client

Author: handong

KAG_VERSION

@@ -1 +1 @@
-0.8.0.20250623
+0.8.0.20250616.18

kag/common/llm/openai_client.py

@@ -23,6 +23,7 @@
 logging.getLogger("openai").setLevel(logging.ERROR)
 logging.getLogger("httpx").setLevel(logging.ERROR)
 logger = logging.getLogger(__name__)
+import json
 
 AzureADTokenProvider = Callable[[], str]
 
@@ -148,6 +149,15 @@ def __call__(self, prompt: str = "", image_url: str = None, **kwargs):
             rsp = response.choices[0].message.content
             tool_calls = response.choices[0].message.tool_calls
             usages.append(response.usage)
+            if self.model in ["corpus_tianchang_qwen2_5_72b_instruct"]:
+                # 特殊模型格式处理
+                message_content = response.choices[0].message.content
+                data_dict = json.loads(message_content)
+                rsp = data_dict["choices"][0]["message"]["content"]
+                tool_calls = data_dict["choices"][0]["message"]["tool_calls"]
+            else:
+                rsp = response.choices[0].message.content
+                tool_calls = response.choices[0].message.tool_calls
         else:
             rsp = ""
             tool_calls = None  # TODO: Handle tool calls in stream mode
@@ -234,6 +244,15 @@ async def acall(self, prompt: str = "", image_url: str = None, **kwargs):
             rsp = response.choices[0].message.content
             tool_calls = response.choices[0].message.tool_calls
             usages.append(response.usage)
+            if self.model in ["corpus_tianchang_qwen2_5_72b_instruct"]:
+                # 特殊模型格式处理
+                message_content = response.choices[0].message.content
+                data_dict = json.loads(message_content)
+                rsp = data_dict["choices"][0]["message"]["content"]
+                tool_calls = data_dict["choices"][0]["message"]["tool_calls"]
+            else:
+                rsp = response.choices[0].message.content
+                tool_calls = response.choices[0].message.tool_calls
         else:
             rsp = ""
             tool_calls = None

kag/solver/executor/deduce/kag_output_executor.py

@@ -95,6 +95,8 @@ def invoke(self, query: str, task: Any, context: Context, **kwargs):
             dep_context = []
             for p in task.parents:
                 dep_context.append(p.get_task_context())
+            if not dep_context:
+                logger.warning(f"no dep context the query is:{query}")
             result = self.llm_module.invoke(
                 {"question": query, "context": dep_context},
                 self.summary_prompt,

kag/solver/pipeline/kag_static_pipeline.py

@@ -124,8 +124,10 @@ async def ainvoke(self, query, **kwargs):
         finished = False
         while True:
             context: Context = Context()
-            tasks = await self.planning(query, context, **kwargs)
-
+            tasks,think_response = await self.planning(query, context, **kwargs)
+            if not tasks:
+                answer = await self.generator.ainvoke(query+"\n"+think_response, context, **kwargs)
+                return answer
             for task in tasks:
                 context.add_task(task)