v0.8.1 fix release

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")

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

@@ -1,6 +1,7 @@
 from langchain_neo4j import Neo4jGraph
 from langchain.docstore.document import Document
 from src.shared.common_fn import load_embedding_model,execute_graph_query
+from src.shared.common_fn import load_embedding_model,execute_graph_query
 import logging
 from typing import List
 import os
@@ -34,6 +35,7 @@ def merge_relationship_between_chunk_and_entites(graph: Neo4jGraph, graph_docume
                     MERGE (c)-[:HAS_ENTITY]->(n)
                 """
         execute_graph_query(graph,unwind_query, params={"batch_data": batch_data})
+        execute_graph_query(graph,unwind_query, params={"batch_data": batch_data})
 
 
 def create_chunk_embeddings(graph, chunkId_chunkDoc_list, file_name):
@@ -60,6 +62,7 @@ def create_chunk_embeddings(graph, chunkId_chunkDoc_list, file_name):
         MERGE (c)-[:PART_OF]->(d)
     """       
     execute_graph_query(graph,query_to_create_embedding, params={"fileName":file_name, "data":data_for_query})
+    execute_graph_query(graph,query_to_create_embedding, params={"fileName":file_name, "data":data_for_query})
 
 def create_relation_between_chunks(graph, file_name, chunks: List[Document])->list:
     logging.info("creating FIRST_CHUNK and NEXT_CHUNK relationships between chunks")
@@ -128,6 +131,7 @@ def create_relation_between_chunks(graph, file_name, chunks: List[Document])->li
         MERGE (c)-[:PART_OF]->(d)
     """
     execute_graph_query(graph,query_to_create_chunk_and_PART_OF_relation, params={"batch_data": batch_data})
+    execute_graph_query(graph,query_to_create_chunk_and_PART_OF_relation, params={"batch_data": batch_data})
 
     query_to_create_FIRST_relation = """ 
         UNWIND $relationships AS relationship
@@ -137,6 +141,7 @@ def create_relation_between_chunks(graph, file_name, chunks: List[Document])->li
                 MERGE (d)-[:FIRST_CHUNK]->(c))
         """
     execute_graph_query(graph,query_to_create_FIRST_relation, params={"f_name": file_name, "relationships": relationships})
+    execute_graph_query(graph,query_to_create_FIRST_relation, params={"f_name": file_name, "relationships": relationships})
 
     query_to_create_NEXT_CHUNK_relation = """ 
         UNWIND $relationships AS relationship
@@ -153,7 +158,7 @@ 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 +173,7 @@ 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"
   }

frontend/src/components/ChatBot/ChatInfoModal.tsx

@@ -81,10 +81,10 @@ const ChatInfoModal: React.FC<chatInfoMessage> = ({
     error?.length
       ? 10
       : mode === chatModeLables['global search+vector+fulltext']
-      ? 7
-      : mode === chatModeLables.graph
-      ? 4
-      : 3
+        ? 7
+        : mode === chatModeLables.graph
+          ? 4
+          : 3
   );
   const [, copy] = useCopyToClipboard();
   const [copiedText, setcopiedText] = useState<boolean>(false);
@@ -97,15 +97,15 @@ const ChatInfoModal: React.FC<chatInfoMessage> = ({
     multiModelMetrics.length > 0 && Object.keys(multiModelMetrics[0]).length > 4
       ? true
       : multiModelMetrics.length > 0 && Object.keys(multiModelMetrics[0]).length <= 4
-      ? false
-      : null
+        ? false
+        : null
   );
   const [isAdditionalMetricsWithSingleMode, setIsAdditionalMetricsWithSingleMode] = useState<boolean | null>(
     metricDetails != undefined && Object.keys(metricDetails).length > 3
       ? true
       : metricDetails != undefined && Object.keys(metricDetails).length <= 3
-      ? false
-      : null
+        ? false
+        : null
   );
   const actions: React.ComponentProps<typeof IconButton<'button'>>[] = useMemo(
     () => [
@@ -320,6 +320,7 @@ const ChatInfoModal: React.FC<chatInfoMessage> = ({
           src={Neo4jRetrievalLogo}
           style={{ width: isTablet ? 80 : 95, height: isTablet ? 80 : 95, marginRight: 10 }}
           loading='lazy'
+          alt='Retrieval-logo'
         />
         <div className='flex! flex-col'>
           <Typography variant='h2'>Retrieval information</Typography>

frontend/src/components/ChatBot/ChatOnlyComponent.tsx

@@ -10,6 +10,7 @@ import { clearChatAPI } from '../../services/QnaAPI';
 import { ChatProps, connectionState, Messages, UserCredentials } from '../../types';
 import { getIsLoading } from '../../utils/Utils';
 import ThemeWrapper from '../../context/ThemeWrapper';
+import { SpotlightProvider } from '@neo4j-ndl/react';
 
 const ChatContent: React.FC<ChatProps> = ({ chatMessages }) => {
   const { clearHistoryData, messages, setMessages, setClearHistoryData, setIsDeleteChatLoading, isDeleteChatLoading } =
@@ -160,11 +161,13 @@ const ChatOnlyComponent: React.FC = () => {
   return (
     <ThemeWrapper>
       <UserCredentialsWrapper>
-        <FileContextProvider>
-          <MessageContextWrapper>
-            <ChatContent chatMessages={chatMessages} />
-          </MessageContextWrapper>
-        </FileContextProvider>
+        <SpotlightProvider>
+          <FileContextProvider>
+            <MessageContextWrapper>
+              <ChatContent chatMessages={chatMessages} />
+            </MessageContextWrapper>
+          </FileContextProvider>
+        </SpotlightProvider>
       </UserCredentialsWrapper>
     </ThemeWrapper>
   );

frontend/src/components/ChatBot/ChunkInfo.tsx

@@ -84,7 +84,7 @@ const ChunkInfo: FC<ChunkProps> = ({ loading, chunks, mode }) => {
                 ) : chunk?.url && chunk?.start_time ? (
                   <>
                     <div className='flex! flex-row justiy-between items-center gap-1'>
-                      <img src={youtubelogo} width={20} height={20} className='mr-2' />
+                      <img src={youtubelogo} width={20} height={20} className='mr-2' alt='youtube-source-logo' />
                       <TextLink
                         href={generateYouTubeLink(chunk?.url, chunk?.start_time)}
                         type={'external'}
@@ -120,7 +120,7 @@ const ChunkInfo: FC<ChunkProps> = ({ loading, chunks, mode }) => {
                 ) : chunk?.url && new URL(chunk.url).host === 'wikipedia.org' ? (
                   <>
                     <div className='flex! flex-row justiy-between items-center gap-1'>
-                      <img src={wikipedialogo} width={20} height={20} className='mr-2' />
+                      <img src={wikipedialogo} width={20} height={20} className='mr-2' alt='wikipedia-source-logo' />
                       <Typography variant='subheading-medium'>{chunk?.fileName}</Typography>
                     </div>
                     {mode !== chatModeLables['global search+vector+fulltext'] &&
@@ -147,7 +147,7 @@ const ChunkInfo: FC<ChunkProps> = ({ loading, chunks, mode }) => {
                 ) : chunk?.url && new URL(chunk.url).host === 'storage.googleapis.com' ? (
                   <>
                     <div className='flex! flex-row justiy-between items-center gap-1'>
-                      <img src={gcslogo} width={20} height={20} className='mr-2' />
+                      <img src={gcslogo} width={20} height={20} className='mr-2' alt='gcs-source-logo' />
                       <Typography variant='subheading-medium'>{chunk?.fileName}</Typography>
                     </div>
                     {mode !== chatModeLables['global search+vector+fulltext'] &&
@@ -172,7 +172,7 @@ const ChunkInfo: FC<ChunkProps> = ({ loading, chunks, mode }) => {
                 ) : chunk?.url && chunk?.url.startsWith('s3://') ? (
                   <>
                     <div className='flex! flex-row  justiy-between items-center gap-1'>
-                      <img src={s3logo} width={20} height={20} className='mr-2' />
+                      <img src={s3logo} width={20} height={20} className='mr-2' alt='s3-source-logo' />
                       <Typography variant='subheading-medium'>{chunk?.fileName}</Typography>
                     </div>
                     {mode !== chatModeLables['global search+vector+fulltext'] &&
@@ -264,6 +264,11 @@ const ChunkInfo: FC<ChunkProps> = ({ loading, chunks, mode }) => {
                     {chunk?.text}
                   </ReactMarkdown>
                 </div>
+                <div className='mt-2 prose prose-sm sm:prose lg:prose-lg xl:prose-xl max-w-none'>
+                  <ReactMarkdown remarkPlugins={[remarkGfm]} rehypePlugins={[rehypeRaw] as any}>
+                    {chunk?.text}
+                  </ReactMarkdown>
+                </div>
               </li>
             ))}
           </ul>