fix(solver): add component name (#480)

* add ai search example

* bugfix reporter name

* update version

* fix ci

KAG_VERSION

@@ -1 +1 @@
-0.7.0b2
+0.7.0b2

kag/common/utils.py

@@ -351,6 +351,7 @@ def get_recall_node_label(label_set):
     for l in label_set:
         if l != "Entity":
             return l
+    return "Entity"
 
 
 def node_2_doc(node: dict):

kag/solver/executor/retriever/local_knowledge_base/kag_retriever/kag_component/kag_merger.py

@@ -76,9 +76,7 @@ class KagMerger(FlowComponent):
         top_k,
         llm_module: LLMClient = None,
         summary_prompt: PromptABC = None,
-        vector_chunk_retriever: VectorChunkRetriever = None,
         vectorize_model: VectorizeModelABC = None,
-        search_api: SearchApiABC = None,
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -96,22 +94,6 @@ class KagMerger(FlowComponent):
         )
         self.text_similarity = TextSimilarity(vectorize_model)
 
-        self.search_api = search_api or SearchApiABC.from_config(
-            {"type": "openspg_search_api"}
-        )
-        self.vector_chunk_retriever = vector_chunk_retriever or VectorChunkRetriever(
-            vectorize_model=self.vectorize_model, search_api=self.search_api
-        )
-
-    def recall_query(self, query):
-        sim_scores_start_time = time.time()
-        """Process a single query for similarity scores in parallel."""
-        query_sim_scores = self.vector_chunk_retriever.invoke(query, self.top_k * 20)
-        logger.info(
-            f"`{query}` Similarity scores calculation completed in {time.time() - sim_scores_start_time:.2f} seconds."
-        )
-        return query_sim_scores
-
     def invoke(
         self,
         cur_task: FlowComponentTask,
@@ -157,7 +139,11 @@ class KagMerger(FlowComponent):
                 "FINISH",
                 component_name=self.name,
                 chunk_num=len(limited_merged_chunks),
-                desc="kag_merger_digest",
+                desc=(
+                    "kag_merger_digest"
+                    if len(limited_merged_chunks) > 0
+                    else "kag_merger_digest_failed"
+                ),
             )
         # summary
         formatted_docs = []

kag/solver/executor/retriever/local_knowledge_base/kag_retriever/kag_component/kg_cs/default_kg_cs_retriever.py

@@ -29,7 +29,7 @@ class KgConstrainRetrieverWithOpenSPG(KagLogicalFormComponent):
         **kwargs
     ):
         super().__init__(**kwargs)
-        self.name = "kg_cs"
+        self.name = kwargs.get("name", "kg_cs")
         self.llm = llm or LLMClient.from_config(get_default_chat_llm_config())
         self.path_select = path_select or PathSelect.from_config(
             {"type": "exact_one_hop_select"}

kag/solver/executor/retriever/local_knowledge_base/kag_retriever/kag_component/kg_fr/default_kg_fr_retriever.py

@@ -2,7 +2,7 @@ import logging
 from typing import List, Optional
 
 from kag.common.config import get_default_chat_llm_config
-from kag.interface import LLMClient, Task
+from kag.interface import LLMClient, Task, ToolABC
 from kag.interface.solver.base_model import LogicNode
 from kag.interface.solver.model.one_hop_graph import RetrievedData
 from kag.interface.solver.reporter_abc import ReporterABC
@@ -37,12 +37,12 @@ class KgFreeRetrieverWithOpenSPG(KagLogicalFormComponent):
         path_select: PathSelect = None,
         entity_linking=None,
         llm: LLMClient = None,
-        ppr_chunk_retriever_tool: PprChunkRetriever = None,
+        ppr_chunk_retriever_tool: ToolABC = None,
         top_k=10,
         **kwargs,
     ):
         super().__init__(**kwargs)
-        self.name = "kg_fr"
+        self.name = kwargs.get("name", "kg_fr")
         self.llm = llm or LLMClient.from_config(get_default_chat_llm_config())
         self.path_select = path_select or PathSelect.from_config(
             {"type": "fuzzy_one_hop_select"}
@@ -122,7 +122,7 @@ class KgFreeRetrieverWithOpenSPG(KagLogicalFormComponent):
         )
 
         logger.info(f"`{query}`  Retrieved chunks num: {len(chunks)}")
-        cur_task.logical_node.get_fl_node_result().spo = match_spo
+        cur_task.logical_node.get_fl_node_result().spo = match_spo + selected_rel
         cur_task.logical_node.get_fl_node_result().chunks = chunks
         cur_task.logical_node.get_fl_node_result().sub_question = ppr_sub_query
         if reporter:

kag/solver/executor/retriever/local_knowledge_base/kag_retriever/kag_component/rc/default_rc_retriever.py

@@ -45,7 +45,7 @@ class RCRetrieverOnOpenSPG(KagLogicalFormComponent):
         **kwargs,
     ):
         super().__init__(**kwargs)
-        self.name = "kg_rc"
+        self.name = kwargs.get("name", "kg_rc")
         self.top_k = top_k
         self.vectorize_model = vectorize_model or VectorizeModelABC.from_config(
             KAG_CONFIG.all_config["vectorize_model"]

kag/solver/reporter/open_spg_reporter.py

@@ -143,6 +143,10 @@ class OpenSPGReporter(ReporterABC):
         self.report_sub_segment = {}
         self.thinking_enabled = kwargs.get("thinking_enabled", True)
         self.word_mapping = {
+            "kag_merger_digest_failed": {
+                "zh": "未检索到相关信息。",
+                "en": "No relevant information was found.",
+            },
             "kag_merger_digest": {
                 "zh": "排序文档后，输出{chunk_num}篇文档, 检索信息已足够回答问题。",
                 "en": "{chunk_num} documents were output, sufficient information retrieved to answer the question.",

kag/tools/algorithm_tool/chunk_retriever/ppr_chunk_retriever.py

@@ -369,7 +369,7 @@ class PprChunkRetriever(ToolABC):
                     )
                 )
         return matched_docs, self._convert_relation_datas(
-            chunk_docs=matched_docs, matched_entities=matched_entities[:top_k]
+            chunk_docs=matched_docs[:top_k], matched_entities=matched_entities
         )
 
     def _convert_relation_datas(self, chunk_docs, matched_entities):