Read only demo database

packages/neo4j-semantic-layer/neo4j_semantic_layer/agent.py

@@ -14,7 +14,7 @@ from neo4j_semantic_layer.memory_tool import MemoryTool
 from neo4j_semantic_layer.recommendation_tool import RecommenderTool
 
 llm = ChatOpenAI(temperature=0, model="gpt-4")
-tools = [InformationTool(), RecommenderTool(), MemoryTool()]
+tools = [InformationTool(), RecommenderTool()]# MemoryTool()]
 
 llm_with_tools = llm.bind(functions=[format_tool_to_openai_function(t) for t in tools])
 

packages/neo4j-semantic-layer/neo4j_semantic_layer/utils.py

@@ -41,7 +41,7 @@ def remove_lucene_chars(text: str) -> str:
     return text.strip()
 
 
-def generate_full_text_query(input: str) -> str:
+def generate_full_text_query(input: str, type: str) -> str:
     """
     Generate a full-text search query for a given input string.
 
@@ -51,11 +51,12 @@ def generate_full_text_query(input: str) -> str:
     operator. Useful for mapping movies and people from user questions
     to database values, and allows for some misspelings.
     """
+    property_map = {'movie': 'title', 'person': 'name'}
     full_text_query = ""
     words = [el for el in remove_lucene_chars(input).split() if el]
     for word in words[:-1]:
-        full_text_query += f" {word}~0.8 AND"
-    full_text_query += f" {words[-1]}~0.8"
+        full_text_query += f" {property_map[type]}:{word}~0.8 AND"
+    full_text_query += f" {property_map[type]}:{words[-1]}~0.8"
     return full_text_query.strip()
 
 
@@ -77,8 +78,8 @@ def get_candidates(input: str, type: str, limit: int = 3) -> List[Dict[str, str]
     matching the query, with each candidate being a dictionary containing their name
     (or title) and label (either 'Person' or 'Movie').
     """
-    ft_query = generate_full_text_query(input)
+    ft_query = generate_full_text_query(input, type)
     candidates = graph.query(
-        candidate_query, {"fulltextQuery": ft_query, "index": type, "limit": limit}
+        candidate_query, {"fulltextQuery": ft_query, "index": type + 'Fulltext', "limit": limit}
     )
     return candidates