Dev

backend/Dockerfile

@@ -16,9 +16,10 @@ RUN apt-get update && \
 # Set LD_LIBRARY_PATH
 ENV LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH
 # Copy requirements file and install Python dependencies
-COPY requirements.txt /code/
+COPY requirements.txt constraints.txt /code/
 # --no-cache-dir --upgrade 
-RUN pip install -r requirements.txt 
+RUN pip install --upgrade pip
+RUN pip install -r requirements.txt -c constraints.txt
 # Copy application code
 COPY . /code
 # Set command

backend/constraints.txt

@@ -0,0 +1,4 @@
+-f https://download.pytorch.org/whl/torch_stable.html 
+torch==2.3.1+cpu
+torchvision==0.18.1+cpu
+torchaudio==2.3.1+cpu

backend/score.py

@@ -31,11 +31,10 @@
 from src.ragas_eval import *
 from starlette.types import ASGIApp, Receive, Scope, Send
 from langchain_neo4j import Neo4jGraph
-from src.entities.source_node import sourceNode
 from starlette.middleware.sessions import SessionMiddleware
-from starlette.responses import HTMLResponse, RedirectResponse,JSONResponse
 from starlette.requests import Request
-import secrets
+from dotenv import load_dotenv
+load_dotenv(override=True)
 
 logger = CustomLogger()
 CHUNK_DIR = os.path.join(os.path.dirname(__file__), "chunks")
@@ -342,14 +341,6 @@ async def get_source_list(
     """
     try:
         start = time.time()
-        # if password is not None and password != "null":
-        #     decoded_password = decode_password(password)
-        # else:
-        #     decoded_password = None
-        #     userName = None
-        #     database = None
-        # if " " in uri:
-        #     uri = uri.replace(" ","+")
         result = await asyncio.to_thread(get_source_list_from_graph,uri,userName,password,database)
         end = time.time()
         elapsed_time = end - start

backend/src/graphDB_dataAccess.py

@@ -29,10 +29,10 @@ def update_exception_db(self, file_name, exp_msg, retry_condition=None):
             if retry_condition is not None: 
                 retry_condition = None
                 self.graph.query("""MERGE(d:Document {fileName :$fName}) SET d.status = $status, d.errorMessage = $error_msg, d.retry_condition = $retry_condition""",
-                            {"fName":file_name, "status":job_status, "error_msg":exp_msg, "retry_condition":retry_condition})
+                            {"fName":file_name, "status":job_status, "error_msg":exp_msg, "retry_condition":retry_condition},session_params={"database":self.graph._database})
             else :    
                 self.graph.query("""MERGE(d:Document {fileName :$fName}) SET d.status = $status, d.errorMessage = $error_msg""",
-                            {"fName":file_name, "status":job_status, "error_msg":exp_msg})
+                            {"fName":file_name, "status":job_status, "error_msg":exp_msg},session_params={"database":self.graph._database})
         except Exception as e:
             error_message = str(e)
             logging.error(f"Error in updating document node status as failed: {error_message}")
@@ -66,7 +66,7 @@ def create_source_node(self, obj_source_node:sourceNode):
                             "entityEntityRelCount":obj_source_node.entityEntityRelCount,
                             "communityNodeCount":obj_source_node.communityNodeCount,
                             "communityRelCount":obj_source_node.communityRelCount
-                            })
+                            },session_params={"database":self.graph._database})
         except Exception as e:
             error_message = str(e)
             logging.info(f"error_message = {error_message}")
@@ -118,7 +118,7 @@ def update_source_node(self, obj_source_node:sourceNode):
             logging.info(f'Base Param value 1 : {param}')
             query = "MERGE(d:Document {fileName :$props.fileName}) SET d += $props"
             logging.info("Update source node properties")
-            self.graph.query(query,param)
+            self.graph.query(query,param,session_params={"database":self.graph._database})
         except Exception as e:
             error_message = str(e)
             self.update_exception_db(self,self.file_name,error_message)
@@ -139,15 +139,15 @@ def get_source_list(self):
         """
         logging.info("Get existing files list from graph")
         query = "MATCH(d:Document) WHERE d.fileName IS NOT NULL RETURN d ORDER BY d.updatedAt DESC"
-        result = self.graph.query(query)
+        result = self.graph.query(query,session_params={"database":self.graph._database})
         list_of_json_objects = [entry['d'] for entry in result]
         return list_of_json_objects
 
     def update_KNN_graph(self):
         """
         Update the graph node with SIMILAR relationship where embedding scrore match
         """
-        index = self.graph.query("""show indexes yield * where type = 'VECTOR' and name = 'vector'""")
+        index = self.graph.query("""show indexes yield * where type = 'VECTOR' and name = 'vector'""",session_params={"database":self.graph._database})
         # logging.info(f'show index vector: {index}')
         knn_min_score = os.environ.get('KNN_MIN_SCORE')
         if len(index) > 0:
@@ -158,14 +158,14 @@ def update_KNN_graph(self):
                                     WHERE node <> c and score >= $score MERGE (c)-[rel:SIMILAR]-(node) SET rel.score = score
                                 """,
                                 {"score":float(knn_min_score)}
-                                )
+                                ,session_params={"database":self.graph._database})
         else:
             logging.info("Vector index does not exist, So KNN graph not update")
 
     def check_account_access(self, database):
         try:
             query_dbms_componenet = "call dbms.components() yield edition"
-            result_dbms_componenet = self.graph.query(query_dbms_componenet)
+            result_dbms_componenet = self.graph.query(query_dbms_componenet,session_params={"database":self.graph._database})
 
             if  result_dbms_componenet[0]["edition"] == "enterprise":
                 query = """
@@ -177,7 +177,7 @@ def check_account_access(self, database):
 
                 logging.info(f"Checking access for database: {database}")
 
-                result = self.graph.query(query, params={"database": database})
+                result = self.graph.query(query, params={"database": database},session_params={"database":self.graph._database})
                 read_access_count = result[0]["readAccessCount"] if result else 0
 
                 logging.info(f"Read access count: {read_access_count}")
@@ -202,7 +202,7 @@ def check_gds_version(self):
             gds_procedure_count = """
             SHOW FUNCTIONS YIELD name WHERE name STARTS WITH 'gds.version' RETURN COUNT(*) AS totalGdsProcedures
             """
-            result = self.graph.query(gds_procedure_count)
+            result = self.graph.query(gds_procedure_count,session_params={"database":self.graph._database})
             total_gds_procedures = result[0]['totalGdsProcedures'] if result else 0
 
             if total_gds_procedures > 0:
@@ -231,11 +231,11 @@ def connection_check_and_get_vector_dimensions(self,database):
         db_vector_dimension = self.graph.query("""SHOW INDEXES YIELD *
                                     WHERE type = 'VECTOR' AND name = 'vector'
                                     RETURN options.indexConfig['vector.dimensions'] AS vector_dimensions
-                                """)
+                                """,session_params={"database":self.graph._database})
 
         result_chunks = self.graph.query("""match (c:Chunk) return size(c.embedding) as embeddingSize, count(*) as chunks, 
                                                     count(c.embedding) as hasEmbedding
-                                """)
+                                """,session_params={"database":self.graph._database})
 
         embedding_model = os.getenv('EMBEDDING_MODEL')
         embeddings, application_dimension = load_embedding_model(embedding_model)
@@ -260,7 +260,7 @@ def execute_query(self, query, param=None,max_retries=3, delay=2):
         retries = 0
         while retries < max_retries:
             try:
-                return self.graph.query(query, param)
+                return self.graph.query(query, param,session_params={"database":self.graph._database})
             except TransientError as e:
                 if "DeadlockDetected" in str(e):
                     retries += 1
@@ -473,8 +473,8 @@ def drop_create_vector_index(self, isVectorIndexExist):
         embeddings, dimension = load_embedding_model(embedding_model)
 
         if isVectorIndexExist == 'true':
-            self.graph.query("""drop index vector""")
-        # self.graph.query("""drop index vector""")
+            self.graph.query("""drop index vector""",session_params={"database":self.graph._database})
+
         self.graph.query("""CREATE VECTOR INDEX `vector` if not exists for (c:Chunk) on (c.embedding)
                             OPTIONS {indexConfig: {
                             `vector.dimensions`: $dimensions,
@@ -483,7 +483,7 @@ def drop_create_vector_index(self, isVectorIndexExist):
                         """,
                         {
                             "dimensions" : dimension
-                        }
+                        },session_params={"database":self.graph._database}
                         )
         return "Drop and Re-Create vector index succesfully"
 

backend/src/llm.py

@@ -180,13 +180,16 @@ async def get_graph_document_list(
         else:
             node_properties = ["description"]
             relationship_properties = ["description"]
+        TOOL_SUPPORTED_MODELS = {"qwen3", "deepseek"} 
+        model_name = llm.model_name.lower() 
+        ignore_tool_usage = not any(pattern in model_name for pattern in TOOL_SUPPORTED_MODELS)
         llm_transformer = LLMGraphTransformer(
             llm=llm,
             node_properties=node_properties,
             relationship_properties=relationship_properties,
             allowed_nodes=allowedNodes,
             allowed_relationships=allowedRelationship,
-            ignore_tool_usage=True,
+            ignore_tool_usage=ignore_tool_usage,
             additional_instructions=ADDITIONAL_INSTRUCTIONS+ (additional_instructions if additional_instructions else "")
         )
 

backend/src/main.py

@@ -665,39 +665,40 @@ def upload_file(graph, model, chunk, chunk_number:int, total_chunks:int, origina
   return f"Chunk {chunk_number}/{total_chunks} saved"
 
 def get_labels_and_relationtypes(uri, userName, password, database):
-   excluded_labels = {'Document', 'Chunk', '_Bloom_Perspective_', '__Community__', '__Entity__', 'Session', 'Message'}
-   excluded_relationships = {
-   'PART_OF', 'NEXT_CHUNK', 'HAS_ENTITY', '_Bloom_Perspective_', 'FIRST_CHUNK',
-   'SIMILAR', 'IN_COMMUNITY', 'PARENT_COMMUNITY', 'NEXT', 'LAST_MESSAGE'}
-   driver = get_graphDB_driver(uri, userName, password,database) 
-   with driver.session(database=database) as session:
-       result = session.run("CALL db.schema.visualization() YIELD nodes, relationships RETURN nodes, relationships")
-       if not result:
-         return []
-       record = result.single()
-       nodes = record["nodes"]
-       relationships = record["relationships"]
-       node_map = {}
-       for node in nodes:
-           node_id = node.element_id
-           labels = list(node.labels)
-           if labels:
-               node_map[node_id] = ":".join(labels)
-       triples = []
-       for rel in relationships:
-           start_id = rel.start_node.element_id
-           end_id = rel.end_node.element_id
-           rel_type = rel.type
-           start_label = node_map.get(start_id)
-           end_label = node_map.get(end_id)
-           if start_label and end_label:
-             if (
-                   start_label not in excluded_labels and
-                   end_label not in excluded_labels and
-                   rel_type not in excluded_relationships
-               ):
-                 triples.append(f"{start_label}-{rel_type}->{end_label}")
-       return {"triplets" : list(set(triples))}
+  excluded_labels = {'Document', 'Chunk', '_Bloom_Perspective_', '__Community__', '__Entity__', 'Session', 'Message'}
+  excluded_relationships = {
+       'NEXT_CHUNK', '_Bloom_Perspective_', 'FIRST_CHUNK',
+       'SIMILAR', 'IN_COMMUNITY', 'PARENT_COMMUNITY', 'NEXT', 'LAST_MESSAGE'
+   }
+  driver = get_graphDB_driver(uri, userName, password,database) 
+  triples = set()
+  with driver.session(database=database) as session:
+    result = session.run("""
+           MATCH (n)-[r]->(m)
+           RETURN DISTINCT labels(n) AS fromLabels, type(r) AS relType, labels(m) AS toLabels
+       """)
+    for record in result:
+      from_labels = record["fromLabels"]
+      to_labels = record["toLabels"]
+      rel_type = record["relType"]
+      from_label = next((lbl for lbl in from_labels if lbl not in excluded_labels), None)
+      to_label = next((lbl for lbl in to_labels if lbl not in excluded_labels), None)
+      if not from_label or not to_label:
+          continue
+      if rel_type == 'PART_OF':
+          if from_label == 'Chunk' and to_label == 'Document':
+              continue 
+      elif rel_type == 'HAS_ENTITY':
+          if from_label == 'Chunk':
+              continue 
+      elif (
+          from_label in excluded_labels or
+          to_label in excluded_labels or
+          rel_type in excluded_relationships
+      ):
+          continue
+      triples.add(f"{from_label}-{rel_type}->{to_label}")
+  return {"triplets": list(triples)}
 
 def manually_cancelled_job(graph, filenames, source_types, merged_dir, uri):
 

backend/src/make_relationships.py

@@ -153,7 +153,7 @@ def create_relation_between_chunks(graph, file_name, chunks: List[Document])->li
 def create_chunk_vector_index(graph):
     start_time = time.time()
     try:
-        vector_index_query = "SHOW INDEXES YIELD * WHERE labelsOrTypes = ['Chunk'] and type = 'VECTOR' AND name = 'vector' return options"
+        vector_index_query = "SHOW INDEXES YIELD name, type, labelsOrTypes, properties WHERE name = 'vector' AND type = 'VECTOR' AND 'Chunk' IN labelsOrTypes AND 'embedding' IN properties RETURN name"
         vector_index = execute_graph_query(graph,vector_index_query)
         if not vector_index:
             vector_store = Neo4jVector(embedding=EMBEDDING_FUNCTION,
@@ -168,7 +168,7 @@ def create_chunk_vector_index(graph):
         else:
             logging.info(f"Index already exist,Skipping creation. Time taken: {time.time() - start_time:.2f} seconds")
     except Exception as e:
-        if "EquivalentSchemaRuleAlreadyExists" in str(e):
+        if ("EquivalentSchemaRuleAlreadyExists" in str(e) or "An equivalent index already exists" in str(e)):
             logging.info("Vector index already exists, skipping creation.")
         else:
             raise

frontend/index.html

@@ -1,16 +1,20 @@
 <!doctype html>
 <html lang="en">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <link rel="icon" type="image/png" sizes="32x32" href="/favicons/favicon-32x32.png">
-    <link rel="icon" type="image/png" sizes="194x194" href="/favicons/favicon-194x194.png">
-    <link rel="icon" type="image/png" sizes="16x16" href="/favicons/favicon-16x16.png">
-    <link rel="shortcut icon" href="/favicons/favicon.ico">
-    <title>Neo4j graph builder</title>
-  </head>
-  <body>
-    <div id="root"></div>
-    <script type="module" src="/src/main.tsx"></script>
-  </body>
-</html>
+
+<head>
+  <meta charset="UTF-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <link rel="icon" type="image/png" sizes="32x32" href="/favicons/favicon-32x32.png">
+  <link rel="icon" type="image/png" sizes="194x194" href="/favicons/favicon-194x194.png">
+  <link rel="icon" type="image/png" sizes="16x16" href="/favicons/favicon-16x16.png">
+  <link rel="shortcut icon" href="/favicons/favicon.ico">
+  <title>Neo4j graph builder</title>
+</head>
+
+<body>
+  <div id="root"></div>
+  <script type="module" src="/src/main.tsx"></script>
+
+</body>
+
+</html>

frontend/package.json

@@ -14,17 +14,17 @@
   },
   "dependencies": {
     "@auth0/auth0-react": "^2.2.4",
-    "@emotion/styled": "^11.11.0",
+    "@emotion/styled": "^11.14.0",
     "@mui/material": "^5.15.10",
-    "@mui/styled-engine": "^7.0.1",
+    "@mui/styled-engine": "^7.0.2",
     "@neo4j-devtools/word-color": "^0.0.8",
     "@neo4j-ndl/base": "^3.2.9",
     "@neo4j-ndl/react": "^3.2.18",
     "@neo4j-nvl/base": "^0.3.6",
     "@neo4j-nvl/react": "^0.3.7",
     "@react-oauth/google": "^0.12.1",
     "@tanstack/react-table": "^8.20.5",
-    "@types/uuid": "^9.0.7",
+    "@types/uuid": "^10.0.0",
     "axios": "^1.8.4",
     "clsx": "^2.1.1",
     "eslint-plugin-react": "^7.37.4",
@@ -50,13 +50,13 @@
     "eslint": "^8.45.0",
     "eslint-config-prettier": "^10.1.1",
     "eslint-plugin-react-hooks": "^5.1.0",
-    "eslint-plugin-react-refresh": "^0.4.19",
+    "eslint-plugin-react-refresh": "^0.4.20",
     "husky": "^9.1.7",
     "lint-staged": "^15.5.0",
     "postcss": "^8.5.3",
     "prettier": "^3.5.3",
     "react-dropzone": "^14.3.8",
-    "tailwindcss": "^4.0.7",
+    "tailwindcss": "^4.1.5",
     "typescript": "^5.7.3",
     "vite": "^4.5.3"
   }