fix(builder): add 0.8 config

kag/common/conf.py

@@ -261,8 +261,12 @@ def init_env(config_file: str = None):
     else:
         msg = "Done init config from local file"
     logger.debug(msg)
-    os.environ[KAGConstants.ENV_KAG_PROJECT_ID] = str(KAG_PROJECT_CONF.project_id)
-    os.environ[KAGConstants.ENV_KAG_PROJECT_HOST_ADDR] = str(KAG_PROJECT_CONF.host_addr)
+    if KAG_PROJECT_CONF.project_id:
+        os.environ[KAGConstants.ENV_KAG_PROJECT_ID] = str(KAG_PROJECT_CONF.project_id)
+    if KAG_PROJECT_CONF.host_addr:
+        os.environ[KAGConstants.ENV_KAG_PROJECT_HOST_ADDR] = str(
+            KAG_PROJECT_CONF.host_addr
+        )
     if len(KAG_CONFIG.all_config) > 0:
         dump_flag = os.getenv(KAGConstants.ENV_KAG_DEBUG_DUMP_CONFIG)
         if dump_flag is not None and dump_flag.strip() == "1":

kag/examples/FinAlibaba/kag_config.yaml

@@ -179,7 +179,7 @@ kag_solver_pipeline:
   executors:
     - *retriever
   generator:
-    type: llm_generator
+    type: llm_index_generator
     llm_client: *chat_llm
     generated_prompt:
       type: default_multi_hop_generator

kag/examples/baike/kag_config.yaml

@@ -74,8 +74,10 @@ graph_api: &graph_api
   type: openspg_graph_api #kag.solver.tools.graph_api.impl.openspg_graph_api.OpenSPGGraphApi
 
 
+
 kg_cs: &kg_cs
   type: kg_cs_open_spg
+  priority: 0
   path_select:
     type: exact_one_hop_select
     graph_api: *graph_api
@@ -87,9 +89,14 @@ kg_cs: &kg_cs
     recognition_threshold: 0.9
     exclude_types:
       - Chunk
+      - AtomicQuery
+      - KnowledgeUnit
+      - Summary
+      - Outline
+      - Doc
 
 kg_fr: &kg_fr
-  type: kg_fr_open_spg
+  type: kg_fr_knowledge_unit
   top_k: 20
   graph_api: *graph_api
   search_api: *search_api
@@ -111,12 +118,18 @@ kg_fr: &kg_fr
     recognition_threshold: 0.8
     exclude_types:
       - Chunk
+      - AtomicQuery
+      - KnowledgeUnit
+      - Summary
+      - Outline
+      - Doc
 
 rc: &rc
   type: rc_open_spg
   vector_chunk_retriever:
-    type: vector_chunk_retriever_legacy
+    type: vector_chunk_retriever
     vectorize_model: *vectorize_model
+    score_threshold: 0.65
     search_api: *search_api
   graph_api: *graph_api
   search_api: *search_api
@@ -135,12 +148,16 @@ kag_hybrid_executor: &kag_hybrid_executor_conf
 
 kag_output_executor: &kag_output_executor_conf
   type: kag_output_executor
+  llm_module: *chat_llm
+
 kag_deduce_executor: &kag_deduce_executor_conf
   type: kag_deduce_executor
+  llm_module: *chat_llm
 
 py_code_based_math_executor: &py_code_based_math_executor_conf
   type: py_code_based_math_executor
-  llm: *openie_llm
+  llm: *chat_llm
+
 
 kag_solver_pipeline:
   type: kag_static_pipeline
@@ -157,7 +174,7 @@ kag_solver_pipeline:
     - *kag_deduce_executor_conf
     - *kag_output_executor_conf
   generator:
-    type: llm_generator
+    type: llm_index_generator
     llm_client: *chat_llm
     generated_prompt:
       type: default_refer_generator_prompt

kag/examples/baike/schema/BaiKe.schema

@@ -1,110 +1,122 @@
 namespace BaiKe
 
+SemanticConcept(语义概念): EntityType
+     properties:
+        desc(内容): Text
+            index: Text
+        isA(上位): SemanticConcept
+
 ArtificialObject(人造物体): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): ArtificialObject
+        officialName(标准名): ArtificialObject
 
 Astronomy(天文学): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Astronomy
+        officialName(标准名): Astronomy
 
 Building(建筑): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Building
+        officialName(标准名): Building
 
 Creature(生物): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Creature
+        officialName(标准名): Creature
 
 Concept(概念): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Concept
+        officialName(标准名): Concept
 
 Date(日期): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Date
+        officialName(标准名): Date
 
 GeographicLocation(地理位置): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): GeographicLocation
+        officialName(标准名): GeographicLocation
 
 Keyword(关键词): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Keyword
+        officialName(标准名): Keyword
 
 Medicine(药物): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
-
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Medicine
+        officialName(标准名): Medicine
 
 NaturalScience(自然科学): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): NaturalScience
+        officialName(标准名): NaturalScience
 
 Organization(组织机构): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Organization
+        officialName(标准名): Organization
 
 Person(人物): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Person
+        officialName(标准名): Person
 
 Transport(运输): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Transport
+        officialName(标准名): Transport
 
 Works(作品): EntityType
      properties:
         desc(描述): Text
             index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
-
-Others(其他): EntityType
-     properties:
-        desc(描述): Text
-            index: TextAndVector
-        semanticType(语义类型): Text
-            index: Text
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Works
+        officialName(标准名): Works
 
 Event(事件): EventType
      properties:
@@ -118,8 +130,10 @@ Event(事件): EventType
         type(事件类型): Text
             index: Text
 
-
-SemanticConcept(语义概念): EntityType
+Others(其他): EntityType
      properties:
-        desc(内容): Text
-          index: Text
+        desc(描述): Text
+            index: TextAndVector
+        semanticType(语义类型): SemanticConcept
+        synonyms(同义词): Others
+        officialName(标准名): Others

kag/examples/csqa/kag_config.yaml

@@ -79,6 +79,7 @@ chain_vectorizer:
 
 kg_cs: &kg_cs
   type: kg_cs_open_spg
+  priority: 0
   path_select:
     type: exact_one_hop_select
     graph_api: *graph_api
@@ -90,6 +91,11 @@ kg_cs: &kg_cs
     recognition_threshold: 0.9
     exclude_types:
       - Chunk
+      - AtomicQuery
+      - KnowledgeUnit
+      - Summary
+      - Outline
+      - Doc
 
 kg_fr: &kg_fr
   type: kg_fr_open_spg
@@ -114,28 +120,24 @@ kg_fr: &kg_fr
     recognition_threshold: 0.8
     exclude_types:
       - Chunk
+      - AtomicQuery
+      - KnowledgeUnit
+      - Summary
+      - Outline
+      - Doc
 
 rc: &rc
   type: rc_open_spg
   vector_chunk_retriever:
-    type: vector_chunk_retriever_legacy
+    type: vector_chunk_retriever
     vectorize_model: *vectorize_model
+    score_threshold: 0.65
     search_api: *search_api
   graph_api: *graph_api
   search_api: *search_api
   vectorize_model: *vectorize_model
   top_k: 20
 
-kag_merger:
-  type: kg_merger
-  top_k: 20
-  llm_module: *chat_llm
-  summary_prompt:
-    type: default_thought_then_answer
-  vectorize_model: *vectorize_model
-  graph_api: *graph_api
-  search_api: *search_api
-
 kag_hybrid_executor: &kag_hybrid_executor_conf
   type: kag_hybrid_retrieval_executor
   retrievers:
@@ -144,19 +146,21 @@ kag_hybrid_executor: &kag_hybrid_executor_conf
     - *rc
   merger:
     type: kag_merger
-  enable_summary: true
+  enable_summary:  true
 
 kag_output_executor: &kag_output_executor_conf
   type: kag_output_executor
+  llm_module: *chat_llm
 
 kag_deduce_executor: &kag_deduce_executor_conf
   type: kag_deduce_executor
-
+  llm_module: *chat_llm
 
 py_code_based_math_executor: &py_code_based_math_executor_conf
   type: py_code_based_math_executor
   llm: *chat_llm
 
+
 kag_solver_pipeline:
   type: kag_static_pipeline
   planner:
@@ -172,7 +176,7 @@ kag_solver_pipeline:
     - *kag_deduce_executor_conf
     - *kag_output_executor_conf
   generator:
-    type: llm_generator
+    type: llm_index_generator
     llm_client: *chat_llm
     generated_prompt:
       type: default_refer_generator_prompt