feat(bridge): spg server bridge supports config check and run solver (#…

…287)

* x

* x (#280)

* bridge add solver

* x

* feat(bridge): spg server bridge (#283)

* x

* bridge add solver

* x

* add invoke

* llm client catch error

kag/bridge/spg_server_bridge.py

@@ -16,7 +16,6 @@
 
 
 def init_kag_config(project_id: str, host_addr: str):
-
     os.environ[KAGConstants.ENV_KAG_PROJECT_ID] = project_id
     os.environ[KAGConstants.ENV_KAG_PROJECT_HOST_ADDR] = host_addr
     init_env()
@@ -47,3 +46,34 @@ def run_component(self, component_name, component_config, input_data):
         if hasattr(instance.input_types, "from_dict"):
             input_data = instance.input_types.from_dict(input_data)
         return [x.to_dict() for x in instance.invoke(input_data, write_ckpt=False)]
+
+    def run_llm_config_check(self, llm_config):
+        from kag.common.llm.llm_config_checker import LLMConfigChecker
+
+        return LLMConfigChecker().check(llm_config)
+
+    def run_vectorizer_config_check(self, vec_config):
+        from kag.common.vectorize_model.vectorize_model_config_checker import (
+            VectorizeModelConfigChecker,
+        )
+
+        return VectorizeModelConfigChecker().check(vec_config)
+
+    def run_solver(
+        self,
+        project_id,
+        task_id,
+        query,
+        func_name="invoke",
+        is_report=True,
+        host_addr="http://127.0.0.1:8887",
+    ):
+        from kag.solver.main_solver import SolverMain
+
+        return getattr(SolverMain(), func_name)(
+            project_id=project_id,
+            task_id=task_id,
+            query=query,
+            is_report=is_report,
+            host_addr=host_addr,
+        )

kag/interface/common/llm_client.py

@@ -77,7 +77,7 @@ def invoke(
         variables: Dict[str, Any],
         prompt_op: PromptABC,
         with_json_parse: bool = True,
-        with_except: bool = True,
+        with_except: bool = False,
     ):
         """
         Call the model and process the result.
@@ -109,10 +109,10 @@ def invoke(
         except Exception as e:
             import traceback
 
-            logger.error(f"Error {e} during invocation: {traceback.format_exc()}")
+            logger.debug(f"Error {e} during invocation: {traceback.format_exc()}")
             if with_except:
                 raise RuntimeError(
-                    f"LLM invoke exception, info: {e}\nllm input: {input}\nllm output: {response}"
+                    f"LLM invoke exception, info: {e}\nllm input: \n{prompt}\nllm output: \n{response}"
                 )
         return result