Update src/core/PineconeManager.py

src/core/PineconeManager.py

@@ -1,6 +1,6 @@
 import time
 import logging
-from pinecone import Pinecone, ServerlessSpec, PodSpec
+from pinecone import Pinecone, ServerlessSpec
 from langchain_pinecone import PineconeVectorStore
 
 logger = logging.getLogger(__name__)
@@ -9,8 +9,6 @@ class PineconeManager:
     def __init__(self, api_key: str):
         if not api_key:
             raise ValueError("Pinecone API Key is missing.")
-        
-        # Initialize the client
         self.pc = Pinecone(api_key=api_key)
         
     def list_indexes(self):
@@ -21,25 +19,14 @@ class PineconeManager:
             logger.error(f"Error listing indexes: {e}")
             return []
 
-    def get_index_stats(self, index_name: str):
-        """Returns stats like total vector count and dimension."""
-        try:
-            idx = self.pc.Index(index_name)
-            return idx.describe_index_stats()
-        except Exception as e:
-            logger.error(f"Error fetching stats for {index_name}: {e}")
-            return None
-
     def check_dimension_compatibility(self, index_name: str, target_dim: int = 384) -> bool:
         """
-        SAFETY MECHANISM: Ensures the Index dimension matches the Model dimension.
+        SAFETY MECHANISM: Ensures the Index dimension matches the Model.
         all-MiniLM-L6-v2 output is 384.
         """
         try:
-            # We have to get the description from the list API, not the index object
             idx_info = self.pc.describe_index(index_name)
             idx_dim = int(idx_info.dimension)
-            
             if idx_dim != target_dim:
                 logger.warning(f"Dimension Mismatch! Index: {idx_dim}, Model: {target_dim}")
                 return False
@@ -49,56 +36,38 @@ class PineconeManager:
             return False
 
     def create_index(self, index_name: str, dimension: int = 384, metric: str = "cosine"):
-        """
-        Creates a new Serverless Index (cheapest/easiest option).
-        Includes a wait loop to ensure it's ready.
-        """
+        """Creates a new Serverless Index with a wait loop."""
         existing = self.list_indexes()
         if index_name in existing:
-            logger.info(f"Index {index_name} already exists.")
             return True, "Index already exists."
 
         try:
-            # Create Serverless Index (AWS/US-EAST-1 is usually the default free region)
             self.pc.create_index(
                 name=index_name,
                 dimension=dimension,
                 metric=metric,
                 spec=ServerlessSpec(cloud="aws", region="us-east-1") 
             )
-            
             # Wait for initialization
-            logger.info("Waiting for index to initialize...")
             while not self.pc.describe_index(index_name).status['ready']:
                 time.sleep(1)
-            
             return True, f"Index {index_name} created successfully."
         except Exception as e:
-            logger.error(f"Failed to create index: {e}")
             return False, str(e)
 
     def get_vectorstore(self, index_name: str, embedding_function, namespace: str):
-        """
-        Returns the LangChain VectorStore object for RAG operations.
-        """
+        """Returns the LangChain VectorStore object."""
         return PineconeVectorStore(
             index_name=index_name,
             embedding=embedding_function,
             namespace=namespace
         )
         
-    def delete_file_from_index(self, index_name: str, filename: str, namespace: str):
-        """
-        Deletes all vectors associated with a specific file source.
-        """
+    def delete_file(self, index_name: str, filename: str, namespace: str):
+        """Deletes vectors for a specific file."""
         try:
             index = self.pc.Index(index_name)
-            # Pinecone delete by metadata filter
-            index.delete(
-                filter={"source": filename},
-                namespace=namespace
-            )
+            index.delete(filter={"source": filename}, namespace=namespace)
             return True, f"Deleted vectors for {filename}"
         except Exception as e:
-            logger.error(f"Delete failed: {e}")
             return False, str(e)