Staging to Main

.github/dependabot.yml

@@ -3,11 +3,11 @@ updates:
   - package-ecosystem: 'npm'
     directory: '/frontend'
     schedule:
-      interval: 'weekly'
+      interval: 'monthly'
     target-branch: 'dev'
 
   - package-ecosystem: 'pip'
     directory: '/backend'
     schedule:
-      interval: 'weekly'
-    target-branch: 'dev'
+      interval: 'monthly'
+    target-branch: 'dev'

backend/requirements.txt

@@ -59,3 +59,5 @@ Secweb==1.11.0
 ragas==0.2.11
 rouge_score==0.1.2
 langchain-neo4j==0.3.0
+pypandoc-binary==1.15
+chardet==5.2.0

backend/score.py

@@ -41,6 +41,27 @@
 CHUNK_DIR = os.path.join(os.path.dirname(__file__), "chunks")
 MERGED_DIR = os.path.join(os.path.dirname(__file__), "merged_files")
 
+def sanitize_filename(filename):
+   """
+   Sanitize the user-provided filename to prevent directory traversal and remove unsafe characters.
+   """
+   # Remove path separators and collapse redundant separators
+   filename = os.path.basename(filename)
+   filename = os.path.normpath(filename)
+   return filename
+
+def validate_file_path(directory, filename):
+   """
+   Construct the full file path and ensure it is within the specified directory.
+   """
+   file_path = os.path.join(directory, filename)
+   abs_directory = os.path.abspath(directory)
+   abs_file_path = os.path.abspath(file_path)
+   # Ensure the file path starts with the intended directory path
+   if not abs_file_path.startswith(abs_directory):
+       raise ValueError("Invalid file path")
+   return abs_file_path
+
 def healthy_condition():
     output = {"healthy": True}
     return output
@@ -217,8 +238,9 @@ async def extract_knowledge_graph_from_file(
         start_time = time.time()
         graph = create_graph_database_connection(uri, userName, password, database)   
         graphDb_data_Access = graphDBdataAccess(graph)
-        merged_file_path = os.path.join(MERGED_DIR,file_name)
         if source_type == 'local file':
+            file_name = sanitize_filename(file_name)
+            merged_file_path = validate_file_path(MERGED_DIR, file_name)
             uri_latency, result = await extract_graph_from_file_local_file(uri, userName, password, database, model, merged_file_path, file_name, allowedNodes, allowedRelationship, token_chunk_size, chunk_overlap, chunks_to_combine, retry_condition, additional_instructions)
 
         elif source_type == 's3 bucket' and source_url:
@@ -278,8 +300,11 @@ async def extract_knowledge_graph_from_file(
         return create_api_response('Success', data=result, file_source= source_type)
     except LLMGraphBuilderException as e:
         error_message = str(e)
+        graph = create_graph_database_connection(uri, userName, password, database)   
+        graphDb_data_Access = graphDBdataAccess(graph)
         graphDb_data_Access.update_exception_db(file_name,error_message, retry_condition)
-        failed_file_process(uri,file_name, merged_file_path, source_type)
+        if source_type == 'local file':
+            failed_file_process(uri,file_name, merged_file_path)
         node_detail = graphDb_data_Access.get_current_status_document_node(file_name)
         # Set the status "Completed" in logging becuase we are treating these error already handled by application as like custom errors.
         json_obj = {'api_name':'extract','message':error_message,'file_created_at':formatted_time(node_detail[0]['created_time']),'error_message':error_message, 'file_name': file_name,'status':'Completed',
@@ -290,8 +315,11 @@ async def extract_knowledge_graph_from_file(
     except Exception as e:
         message=f"Failed To Process File:{file_name} or LLM Unable To Parse Content "
         error_message = str(e)
+        graph = create_graph_database_connection(uri, userName, password, database)   
+        graphDb_data_Access = graphDBdataAccess(graph)
         graphDb_data_Access.update_exception_db(file_name,error_message, retry_condition)
-        failed_file_process(uri,file_name, merged_file_path, source_type)
+        if source_type == 'local file':
+            failed_file_process(uri,file_name, merged_file_path)
         node_detail = graphDb_data_Access.get_current_status_document_node(file_name)
 
         json_obj = {'api_name':'extract','message':message,'file_created_at':formatted_time(node_detail[0]['created_time']),'error_message':error_message, 'file_name': file_name,'status':'Failed',

backend/src/QA_integration.py

@@ -177,7 +177,7 @@ def get_rag_chain(llm, system_template=CHAT_SYSTEM_TEMPLATE):
         logging.error(f"Error creating RAG chain: {e}")
         raise
 
-def format_documents(documents, model):
+def format_documents(documents, model,chat_mode_settings):
     prompt_token_cutoff = 4
     for model_names, value in CHAT_TOKEN_CUT_OFF.items():
         if model in model_names:
@@ -197,9 +197,20 @@ def format_documents(documents, model):
         try:
             source = doc.metadata.get('source', "unknown")
             sources.add(source)
-
-            entities = doc.metadata['entities'] if 'entities'in doc.metadata.keys() else entities
-            global_communities = doc.metadata["communitydetails"] if 'communitydetails'in doc.metadata.keys() else global_communities
+            if 'entities' in doc.metadata:
+                if chat_mode_settings["mode"] == CHAT_ENTITY_VECTOR_MODE:
+                    entity_ids = [entry['entityids'] for entry in doc.metadata['entities'] if 'entityids' in entry]
+                    entities.setdefault('entityids', set()).update(entity_ids)
+                else:
+                    if 'entityids' in doc.metadata['entities']:
+                        entities.setdefault('entityids', set()).update(doc.metadata['entities']['entityids'])
+                    if 'relationshipids' in doc.metadata['entities']:
+                        entities.setdefault('relationshipids', set()).update(doc.metadata['entities']['relationshipids'])
+
+            if 'communitydetails' in doc.metadata:
+                existing_ids = {entry['id'] for entry in global_communities}
+                new_entries = [entry for entry in doc.metadata["communitydetails"] if entry['id'] not in existing_ids]
+                global_communities.extend(new_entries)
 
             formatted_doc = (
                 "Document start\n"
@@ -218,7 +229,7 @@ def process_documents(docs, question, messages, llm, model,chat_mode_settings):
     start_time = time.time()
 
     try:
-        formatted_docs, sources, entitydetails, communities = format_documents(docs, model)
+        formatted_docs, sources, entitydetails, communities = format_documents(docs, model,chat_mode_settings)
 
         rag_chain = get_rag_chain(llm=llm)
 

backend/src/chunkid_entities.py

@@ -190,7 +190,7 @@ def get_entities_from_chunkids(uri, username, password, database ,nodedetails,en
         elif mode == CHAT_ENTITY_VECTOR_MODE:
 
             if "entitydetails" in nodedetails and nodedetails["entitydetails"]:
-                entity_ids = [item["id"] for item in nodedetails["entitydetails"]]
+                entity_ids = [item for item in nodedetails["entitydetails"]["entityids"]]
                 logging.info(f"chunkid_entities module: Starting for entity ids: {entity_ids}")
                 result = process_entityids(driver, entity_ids)
                 if "chunk_data" in result.keys():

backend/src/document_sources/gcs_bucket.py

@@ -1,8 +1,7 @@
 import os
 import logging
 from google.cloud import storage
-from langchain_community.document_loaders import GCSFileLoader, GCSDirectoryLoader
-from langchain_community.document_loaders import PyMuPDFLoader
+from langchain_community.document_loaders import GCSFileLoader
 from langchain_core.documents import Document
 from PyPDF2 import PdfReader
 import io
@@ -42,8 +41,9 @@ def get_gcs_bucket_files_info(gcs_project_id, gcs_bucket_name, gcs_bucket_folder
       logging.exception(f'Exception Stack trace: {error_message}')
       raise LLMGraphBuilderException(error_message)
 
-def load_pdf(file_path):
-    return PyMuPDFLoader(file_path)
+def gcs_loader_func(file_path):
+   loader, _ = load_document_content(file_path)
+   return loader
 
 def get_documents_from_gcs(gcs_project_id, gcs_bucket_name, gcs_bucket_folder, gcs_blob_filename, access_token=None):
   nltk.download('punkt')
@@ -64,7 +64,7 @@ def get_documents_from_gcs(gcs_project_id, gcs_bucket_name, gcs_bucket_folder, g
     blob = bucket.blob(blob_name) 
 
     if blob.exists():
-        loader = GCSFileLoader(project_name=gcs_project_id, bucket=gcs_bucket_name, blob=blob_name, loader_func=load_document_content)
+        loader = GCSFileLoader(project_name=gcs_project_id, bucket=gcs_bucket_name, blob=blob_name, loader_func=gcs_loader_func)
         pages = loader.load() 
     else :
       raise LLMGraphBuilderException('File does not exist, Please re-upload the file and try again.')

backend/src/document_sources/local_file.py

@@ -3,30 +3,61 @@
 from langchain_community.document_loaders import PyMuPDFLoader
 from langchain_community.document_loaders import UnstructuredFileLoader
 from langchain_core.documents import Document
+import chardet
+from langchain_core.document_loaders import BaseLoader
 
+class ListLoader(BaseLoader):
+   """A wrapper to make a list of Documents compatible with BaseLoader."""
+   def __init__(self, documents):
+       self.documents = documents
+   def load(self):
+       return self.documents
+
+def detect_encoding(file_path):
+   """Detects the file encoding to avoid UnicodeDecodeError."""
+   with open(file_path, 'rb') as f:
+       raw_data = f.read(4096)
+       result = chardet.detect(raw_data)
+       return result['encoding'] or "utf-8"
+
 def load_document_content(file_path):
-    if Path(file_path).suffix.lower() == '.pdf':
-        return PyMuPDFLoader(file_path)
+    file_extension = Path(file_path).suffix.lower()
+    encoding_flag = False
+    if file_extension == '.pdf':
+        loader = PyMuPDFLoader(file_path)
+        return loader,encoding_flag
+    elif file_extension == ".txt":
+        encoding = detect_encoding(file_path)
+        logging.info(f"Detected encoding for {file_path}: {encoding}")
+        if encoding.lower() == "utf-8":
+            loader = UnstructuredFileLoader(file_path, mode="elements",autodetect_encoding=True)
+            return loader,encoding_flag
+        else:
+            with open(file_path, encoding=encoding, errors="replace") as f:
+               content = f.read()
+            loader = ListLoader([Document(page_content=content, metadata={"source": file_path})])
+            encoding_flag =  True
+            return loader,encoding_flag
     else:
-        return UnstructuredFileLoader(file_path, mode="elements",autodetect_encoding=True)
+        loader = UnstructuredFileLoader(file_path, mode="elements",autodetect_encoding=True)
+        return loader,encoding_flag
 
 def get_documents_from_file_by_path(file_path,file_name):
     file_path = Path(file_path)
-    if file_path.exists():
-        logging.info(f'file {file_name} processing')        
-        file_extension = file_path.suffix.lower()
-        try:
-            loader = load_document_content(file_path)
-            if file_extension == ".pdf":
-                pages = loader.load()
-            else:
-                unstructured_pages = loader.load()   
-                pages= get_pages_with_page_numbers(unstructured_pages)      
-        except Exception as e:
-            raise Exception('Error while reading the file content or metadata')
-    else:
+    if not file_path.exists():
         logging.info(f'File {file_name} does not exist')
         raise Exception(f'File {file_name} does not exist')
+    logging.info(f'file {file_name} processing')
+    try:
+        loader, encoding_flag = load_document_content(file_path)
+        file_extension = file_path.suffix.lower()
+        if file_extension == ".pdf" or (file_extension == ".txt" and encoding_flag):
+            pages = loader.load()
+        else:
+            unstructured_pages = loader.load()
+            pages = get_pages_with_page_numbers(unstructured_pages)
+    except Exception as e:
+        raise Exception(f'Error while reading the file content or metadata, {e}')
     return file_name, pages , file_extension
 
 def get_pages_with_page_numbers(unstructured_pages):

backend/src/document_sources/web_pages.py

@@ -5,12 +5,6 @@
 def get_documents_from_web_page(source_url:str):
   try:
     pages = WebBaseLoader(source_url, verify_ssl=False).load()
-    try:
-      file_name = pages[0].metadata['title'].strip()
-      if not file_name:
-        file_name = last_url_segment(source_url)      
-    except:
-      file_name = last_url_segment(source_url)
-    return file_name, pages
+    return pages
   except Exception as e:
     raise LLMGraphBuilderException(str(e))

backend/src/document_sources/wikipedia.py

@@ -4,7 +4,7 @@
 
 def get_documents_from_Wikipedia(wiki_query:str, language:str):
   try:
-    pages = WikipediaLoader(query=wiki_query.strip(), lang=language, load_all_available_meta=False).load()
+    pages = WikipediaLoader(query=wiki_query.strip(), lang=language, load_all_available_meta=False,doc_content_chars_max=100000,load_max_docs=1).load()
     file_name = wiki_query.strip()
     logging.info(f"Total Pages from Wikipedia = {len(pages)}") 
     return file_name, pages

backend/src/graphDB_dataAccess.py

@@ -198,10 +198,7 @@ def check_account_access(self, database):
     def check_gds_version(self):
         try:
             gds_procedure_count = """
-            SHOW PROCEDURES
-            YIELD name
-            WHERE name STARTS WITH "gds."
-            RETURN COUNT(*) AS totalGdsProcedures
+            SHOW FUNCTIONS YIELD name WHERE name STARTS WITH 'gds.version' RETURN COUNT(*) AS totalGdsProcedures
             """
             result = self.graph.query(gds_procedure_count)
             total_gds_procedures = result[0]['totalGdsProcedures'] if result else 0
@@ -564,3 +561,12 @@ def get_nodelabels_relationships(self):
         except Exception as e:
             print(f"Error in getting node labels/relationship types from db: {e}")
             return []
+
+    def get_websource_url(self,file_name):
+        logging.info("Checking if same title with different URL exist in db ")
+        query = """
+                MATCH(d:Document {fileName : $file_name}) WHERE d.fileSource = "web-url" 
+                RETURN d.url AS url
+                """
+        param = {"file_name" : file_name}
+        return self.execute_query(query, param)

backend/src/llm.py

@@ -14,6 +14,7 @@
 import boto3
 import google.auth
 from src.shared.constants import ADDITIONAL_INSTRUCTIONS
+import re
 
 def get_llm(model: str):
     """Retrieve the specified language model based on the model name."""
@@ -166,7 +167,8 @@ def get_chunk_id_as_doc_metadata(chunkId_chunkDoc_list):
 async def get_graph_document_list(
     llm, combined_chunk_document_list, allowedNodes, allowedRelationship, additional_instructions=None
 ):
-    futures = []
+    if additional_instructions:
+        additional_instructions = sanitize_additional_instruction(additional_instructions)
     graph_document_list = []
     if "diffbot_api_key" in dir(llm):
         llm_transformer = llm
@@ -210,4 +212,26 @@ async def get_graph_from_llm(model, chunkId_chunkDoc_list, allowedNodes, allowed
     graph_document_list = await get_graph_document_list(
         llm, combined_chunk_document_list, allowedNodes, allowedRelationship, additional_instructions
     )
-    return graph_document_list
+    return graph_document_list
+
+def sanitize_additional_instruction(instruction: str) -> str:
+   """
+   Sanitizes additional instruction by:
+   - Replacing curly braces `{}` with `[]` to prevent variable interpretation.
+   - Removing potential injection patterns like `os.getenv()`, `eval()`, `exec()`.
+   - Stripping problematic special characters.
+   - Normalizing whitespace.
+   Args:
+       instruction (str): Raw additional instruction input.
+   Returns:
+       str: Sanitized instruction safe for LLM processing.
+   """
+   logging.info("Sanitizing additional instructions")
+   instruction = instruction.replace("{", "[").replace("}", "]")  # Convert `{}` to `[]` for safety
+   # Step 2: Block dangerous function calls
+   injection_patterns = [r"os\.getenv\(", r"eval\(", r"exec\(", r"subprocess\.", r"import os", r"import subprocess"]
+   for pattern in injection_patterns:
+       instruction = re.sub(pattern, "[BLOCKED]", instruction, flags=re.IGNORECASE)
+   # Step 4: Normalize spaces
+   instruction = re.sub(r'\s+', ' ', instruction).strip()
+   return instruction

backend/src/main.py

@@ -124,7 +124,12 @@ def create_source_node_graph_web_url(graph, model, source_url, source_type):
       raise LLMGraphBuilderException(message)
     try:
       title = pages[0].metadata['title'].strip()
-      if not title:
+      if title:
+        graphDb_data_Access = graphDBdataAccess(graph)
+        existing_url = graphDb_data_Access.get_websource_url(title)
+        if existing_url != source_url:
+          title = str(title) + "-" + str(last_url_segment(source_url)).strip()
+      else:
         title = last_url_segment(source_url)
       language = pages[0].metadata['language']
     except:
@@ -253,7 +258,7 @@ async def extract_graph_from_file_s3(uri, userName, password, database, model, s
 
 async def extract_graph_from_web_page(uri, userName, password, database, model, source_url, file_name, allowedNodes, allowedRelationship, token_chunk_size, chunk_overlap, chunks_to_combine, retry_condition, additional_instructions):
   if not retry_condition:
-    file_name, pages = get_documents_from_web_page(source_url)
+    pages = get_documents_from_web_page(source_url)
     if pages==None or len(pages)==0:
       raise LLMGraphBuilderException(f'Content is not available for given URL : {file_name}')
     return await processing_source(uri, userName, password, database, model, file_name, pages, allowedNodes, allowedRelationship, token_chunk_size, chunk_overlap, chunks_to_combine, additional_instructions=additional_instructions)
@@ -742,14 +747,13 @@ def set_status_retry(graph, file_name, retry_condition):
     logging.info(obj_source_node)
     graphDb_data_Access.update_source_node(obj_source_node)
 
-def failed_file_process(uri,file_name, merged_file_path, source_type):
+def failed_file_process(uri,file_name, merged_file_path):
   gcs_file_cache = os.environ.get('GCS_FILE_CACHE')
-  if source_type == 'local file':
-    if gcs_file_cache == 'True':
-        folder_name = create_gcs_bucket_folder_name_hashed(uri,file_name)
-        copy_failed_file(BUCKET_UPLOAD, BUCKET_FAILED_FILE, folder_name, file_name)
-        time.sleep(5)
-        delete_file_from_gcs(BUCKET_UPLOAD,folder_name,file_name)
-    else:
-        logging.info(f'Deleted File Path: {merged_file_path} and Deleted File Name : {file_name}')
-        delete_uploaded_local_file(merged_file_path,file_name)
+  if gcs_file_cache == 'True':
+      folder_name = create_gcs_bucket_folder_name_hashed(uri,file_name)
+      copy_failed_file(BUCKET_UPLOAD, BUCKET_FAILED_FILE, folder_name, file_name)
+      time.sleep(5)
+      delete_file_from_gcs(BUCKET_UPLOAD,folder_name,file_name)
+  else:
+      logging.info(f'Deleted File Path: {merged_file_path} and Deleted File Name : {file_name}')
+      delete_uploaded_local_file(merged_file_path,file_name)