fix: GRAPH_COMMUNITY_SUMMARY_ENABLED = False error. (#2086)

eosphoros-ai · Oct 22, 2024 · 6c682be · 6c682be
1 parent d9e2042
commit 6c682be
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Showing 3 changed files with 4 additions and 21 deletions.
diff --git a/dbgpt/rag/index/base.py b/dbgpt/rag/index/base.py
@@ -184,7 +184,6 @@ async def aload_document_with_limit(
             max_threads,
         )
 
-    @abstractmethod
     def similar_search(
         self, text: str, topk: int, filters: Optional[MetadataFilters] = None
     ) -> List[Chunk]:
@@ -197,6 +196,7 @@ def similar_search(
         Return:
             List[Chunk]: The similar documents.
         """
+        return self.similar_search_with_scores(text, topk, 1.0, filters)
 
     async def asimilar_search(
         self,

diff --git a/dbgpt/storage/knowledge_graph/community_summary.py b/dbgpt/storage/knowledge_graph/community_summary.py
@@ -268,20 +268,6 @@ def _load_chunks(
 
         return doc_chunk, chunks
 
-    def similar_search(
-        self, text: str, topk: int, filters: Optional[MetadataFilters] = None
-    ) -> List[Chunk]:
-        """Similar search in index database.
-
-        Args:
-            text(str): The query text.
-            topk(int): The number of similar documents to return.
-            filters(Optional[MetadataFilters]): metadata filters.
-        Return:
-            List[Chunk]: The similar documents.
-        """
-        return []
-
     async def asimilar_search_with_scores(
         self,
         text,

diff --git a/examples/rag/graph_rag_example.py b/examples/rag/graph_rag_example.py
@@ -20,11 +20,9 @@
 )
 
 """GraphRAG example.
-    pre-requirements:
-    * Set LLM config (url/sk) in `.env`.
-    * Install pytest utils: `pip install pytest pytest-asyncio`
-    * Config TuGraph following the format below. 
     ```
+    # Set LLM config (url/sk) in `.env`.
+    # Install pytest utils: `pip install pytest pytest-asyncio`
     GRAPH_STORE_TYPE=TuGraph
     TUGRAPH_HOST=127.0.0.1
     TUGRAPH_PORT=7687
@@ -88,8 +86,7 @@ def __create_community_kg_connector():
 
 async def ask_chunk(chunk: Chunk, question) -> str:
     rag_template = (
-        "Based on the following [Context] {context}, "
-        "answer [Question] {question}."
+        "Based on the following [Context] {context}, " "answer [Question] {question}."
     )
     template = HumanPromptTemplate.from_template(rag_template)
     messages = template.format_messages(context=chunk.content, question=question)