diff --git a/docs/components/vectordbs/config.mdx b/docs/components/vectordbs/config.mdx
index 5daf4048..4ce16fae 100644
--- a/docs/components/vectordbs/config.mdx
+++ b/docs/components/vectordbs/config.mdx
@@ -8,8 +8,9 @@ iconType: "solid"
 
 The `config` is defined as an object with two main keys:
 - `vector_store`: Specifies the vector database provider and its configuration
-  - `provider`: The name of the vector database (e.g., "chroma", "pgvector", "qdrant", "milvus", "azure_ai_search")
-  - `config`: A nested object containing provider-specific settings
+  - `provider`: The name of the vector database (e.g., "chroma", "pgvector", "qdrant", "milvus","azure_ai_search", "vertex_ai_vector_search")
+  - `config`: A nested dictionary containing provider-specific settings
+
 
 ## How to Use Config
 
@@ -86,6 +87,12 @@ Here's a comprehensive list of all parameters that can be used across different
 | `url` | Full URL for the server |
 | `api_key` | API key for the server |
 | `on_disk` | Enable persistent storage |
+| `endpoint_id` | Endpoint ID (vertex_ai_vector_search) |
+| `index_id` | Index ID (vertex_ai_vector_search) |
+| `deployment_index_id` | Deployment index ID (vertex_ai_vector_search) |
+| `project_id` | Project ID (vertex_ai_vector_search) |
+| `project_number` | Project number (vertex_ai_vector_search) |
+| `vector_search_api_endpoint` | Vector search API endpoint (vertex_ai_vector_search) |
 | `connection_string` | PostgreSQL connection string (for Supabase/PGVector) |
 | `index_method` | Vector index method (for Supabase) |
 | `index_measure` | Distance measure for similarity search (for Supabase) |
diff --git a/docs/components/vectordbs/dbs/vertex_ai_vector_search.mdx b/docs/components/vectordbs/dbs/vertex_ai_vector_search.mdx
new file mode 100644
index 00000000..1c303743
--- /dev/null
+++ b/docs/components/vectordbs/dbs/vertex_ai_vector_search.mdx
@@ -0,0 +1,46 @@
+## Google Cloud Vertex AI Vector Search
+
+
+### Usage
+
+To use Google Cloud Vertex AI Vector Search with `mem0`, you need to configure the `vector_store` in your `mem0` config:
+
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["GEMINI_API_KEY"] = = "sk-xx"
+
+config = {
+    "vector_store": {
+        "provider": "vertex_ai_vector_search",
+        "config": {
+            "endpoint_id": "YOUR_ENDPOINT_ID",            # Required: Vector Search endpoint ID
+            "index_id": "YOUR_INDEX_ID",                  # Required: Vector Search index ID 
+            "deployment_index_id": "YOUR_DEPLOYMENT_INDEX_ID",  # Required: Deployment-specific ID
+            "project_id": "YOUR_PROJECT_ID",              # Required: Google Cloud project ID
+            "project_number": "YOUR_PROJECT_NUMBER",      # Required: Google Cloud project number
+            "region": "YOUR_REGION",                      # Optional: Defaults to GOOGLE_CLOUD_REGION
+            "credentials_path": "path/to/credentials.json", # Optional: Defaults to GOOGLE_APPLICATION_CREDENTIALS
+            "vector_search_api_endpoint": "YOUR_API_ENDPOINT" # Required for get operations
+        }
+    }
+}
+m = Memory.from_config(config)
+m.add("Your text here", user_id="user", metadata={"category": "example"})
+```
+
+
+### Required Parameters
+
+| Parameter | Description | Required |
+|-----------|-------------|----------|
+| `endpoint_id` | Vector Search endpoint ID | Yes |
+| `index_id` | Vector Search index ID | Yes |
+| `deployment_index_id` | Deployment-specific index ID | Yes |
+| `project_id` | Google Cloud project ID | Yes |
+| `project_number` | Google Cloud project number | Yes |
+| `vector_search_api_endpoint` | Vector search API endpoint | Yes (for get operations) |
+| `region` | Google Cloud region | No (defaults to GOOGLE_CLOUD_REGION) |
+| `credentials_path` | Path to service account credentials | No (defaults to GOOGLE_APPLICATION_CREDENTIALS) |
diff --git a/mem0/configs/vector_stores/vertex_ai_vector_search.py b/mem0/configs/vector_stores/vertex_ai_vector_search.py
new file mode 100644
index 00000000..9cc1cdbb
--- /dev/null
+++ b/mem0/configs/vector_stores/vertex_ai_vector_search.py
@@ -0,0 +1,29 @@
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class GoogleMatchingEngineConfig(BaseModel):
+    project_id: str = Field(description="Google Cloud project ID")
+    project_number: str = Field(description="Google Cloud project number")
+    region: str = Field(description="Google Cloud region")
+    endpoint_id: str = Field(description="Vertex AI Vector Search endpoint ID")
+    index_id: str = Field(description="Vertex AI Vector Search index ID")
+    deployment_index_id: str = Field(description="Deployment-specific index ID")
+    collection_name: Optional[str] = Field(None, description="Collection name, defaults to index_id")
+    credentials_path: Optional[str] = Field(None, description="Path to service account credentials file")
+    vector_search_api_endpoint: Optional[str] = Field(None, description="Vector search API endpoint")
+
+    model_config = {
+        "extra": "forbid"
+    }
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        if not self.collection_name:
+            self.collection_name = self.index_id
+
+    def model_post_init(self, _context) -> None:
+        """Set collection_name to index_id if not provided"""
+        if self.collection_name is None:
+            self.collection_name = self.index_id
\ No newline at end of file
diff --git a/mem0/memory/main.py b/mem0/memory/main.py
index 6ab3fb64..d3f2d74a 100644
--- a/mem0/memory/main.py
+++ b/mem0/memory/main.py
@@ -641,4 +641,4 @@ class Memory(MemoryBase):
         capture_event("mem0.reset", self)
 
     def chat(self, query):
-        raise NotImplementedError("Chat function not implemented yet.")
+        raise NotImplementedError("Chat function not implemented yet.")
\ No newline at end of file
diff --git a/mem0/utils/factory.py b/mem0/utils/factory.py
index ca2e051e..2e5eb262 100644
--- a/mem0/utils/factory.py
+++ b/mem0/utils/factory.py
@@ -69,6 +69,7 @@ class VectorStoreFactory:
         "azure_ai_search": "mem0.vector_stores.azure_ai_search.AzureAISearch",
         "redis": "mem0.vector_stores.redis.RedisDB",
         "elasticsearch": "mem0.vector_stores.elasticsearch.ElasticsearchDB",
+        "vertex_ai_vector_search": "mem0.vector_stores.vertex_ai_vector_search.GoogleMatchingEngine",
         "opensearch": "mem0.vector_stores.opensearch.OpenSearchDB",
         "supabase": "mem0.vector_stores.supabase.Supabase",
     }
diff --git a/mem0/vector_stores/configs.py b/mem0/vector_stores/configs.py
index 9271fb58..ffa7b5a3 100644
--- a/mem0/vector_stores/configs.py
+++ b/mem0/vector_stores/configs.py
@@ -18,6 +18,7 @@ class VectorStoreConfig(BaseModel):
         "azure_ai_search": "AzureAISearchConfig",
         "redis": "RedisDBConfig",
         "elasticsearch": "ElasticsearchConfig",
+        "vertex_ai_vector_search": "GoogleMatchingEngineConfig",
         "opensearch": "OpenSearchConfig",
         "supabase": "SupabaseConfig",
     }
diff --git a/mem0/vector_stores/vertex_ai_vector_search.py b/mem0/vector_stores/vertex_ai_vector_search.py
new file mode 100644
index 00000000..a7163499
--- /dev/null
+++ b/mem0/vector_stores/vertex_ai_vector_search.py
@@ -0,0 +1,687 @@
+import logging
+import traceback
+import uuid
+from typing import Any, Dict, List, Optional, Tuple
+
+import google.api_core.exceptions
+from google.cloud import aiplatform, aiplatform_v1
+from google.cloud.aiplatform.matching_engine.matching_engine_index_endpoint import (
+    Namespace,
+)
+from google.oauth2 import service_account
+from langchain.schema import Document
+from pydantic import BaseModel
+
+from mem0.configs.vector_stores.vertex_ai_vector_search import (
+    GoogleMatchingEngineConfig,
+)
+from mem0.vector_stores.base import VectorStoreBase
+
+# Configure logging
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger(__name__)
+
+
+class OutputData(BaseModel):
+    id: Optional[str]  # memory id
+    score: Optional[float]  # distance
+    payload: Optional[Dict]  # metadata
+
+
+class GoogleMatchingEngine(VectorStoreBase):
+    def __init__(self, **kwargs):
+        """Initialize Google Matching Engine client."""
+        logger.debug("Initializing Google Matching Engine with kwargs: %s", kwargs)
+        
+        # If collection_name is passed, use it as deployment_index_id if deployment_index_id is not provided
+        if 'collection_name' in kwargs and 'deployment_index_id' not in kwargs:
+            kwargs['deployment_index_id'] = kwargs['collection_name']
+            logger.debug("Using collection_name as deployment_index_id: %s", kwargs['deployment_index_id'])
+        elif 'deployment_index_id' in kwargs and 'collection_name' not in kwargs:
+            kwargs['collection_name'] = kwargs['deployment_index_id']
+            logger.debug("Using deployment_index_id as collection_name: %s", kwargs['collection_name'])
+        
+        try:
+            config = GoogleMatchingEngineConfig(**kwargs)
+            logger.debug("Config created: %s", config.model_dump())
+            logger.debug("Config collection_name: %s", getattr(config, 'collection_name', None))
+        except Exception as e:
+            logger.error("Failed to validate config: %s", str(e))
+            raise
+
+        self.project_id = config.project_id
+        self.project_number = config.project_number
+        self.region = config.region
+        self.endpoint_id = config.endpoint_id
+        self.index_id = config.index_id  # The actual index ID
+        self.deployment_index_id = config.deployment_index_id  # The deployment-specific ID
+        self.collection_name = config.collection_name
+        self.vector_search_api_endpoint = config.vector_search_api_endpoint
+        
+        logger.debug("Using project=%s, location=%s", self.project_id, self.region)
+        
+        # Initialize Vertex AI with credentials if provided
+        init_args = {
+            "project": self.project_id,
+            "location": self.region,
+        }
+        if hasattr(config, 'credentials_path') and config.credentials_path:
+            logger.debug("Using credentials from: %s", config.credentials_path)
+            credentials = service_account.Credentials.from_service_account_file(
+                config.credentials_path
+            )
+            init_args["credentials"] = credentials
+        
+        try:
+            aiplatform.init(**init_args)
+            logger.debug("Vertex AI initialized successfully")
+        except Exception as e:
+            logger.error("Failed to initialize Vertex AI: %s", str(e))
+            raise
+        
+        try:
+            # Format the index path properly using the configured index_id
+            index_path = f"projects/{self.project_number}/locations/{self.region}/indexes/{self.index_id}"
+            logger.debug("Initializing index with path: %s", index_path)
+            self.index = aiplatform.MatchingEngineIndex(index_name=index_path)
+            logger.debug("Index initialized successfully")
+            
+            # Format the endpoint name properly
+            endpoint_name = self.endpoint_id
+            logger.debug("Initializing endpoint with name: %s", endpoint_name)
+            self.index_endpoint = aiplatform.MatchingEngineIndexEndpoint(
+                index_endpoint_name=endpoint_name
+            )
+            logger.debug("Endpoint initialized successfully")
+        except Exception as e:
+            logger.error("Failed to initialize Matching Engine components: %s", str(e))
+            raise ValueError(f"Invalid configuration: {str(e)}")
+
+    def _parse_output(self, data: Dict) -> List[OutputData]:
+        """
+        Parse the output data.
+        Args:
+            data (Dict): Output data.
+        Returns:
+            List[OutputData]: Parsed output data.
+        """
+        results = data.get("nearestNeighbors", {}).get("neighbors", [])
+        output_data = []
+        for result in results:
+            output_data.append(
+                OutputData(
+                    id=result.get("datapoint").get("datapointId"),
+                    score=result.get("distance"),
+                    payload=result.get("datapoint").get("metadata"),
+                )
+            )
+        return output_data
+
+    def _create_restriction(self, key: str, value: Any) -> aiplatform_v1.types.index.IndexDatapoint.Restriction:
+        """Create a restriction object for the Matching Engine index.
+        
+        Args:
+            key: The namespace/key for the restriction
+            value: The value to restrict on
+        
+        Returns:
+            Restriction object for the index
+        """
+        str_value = str(value) if value is not None else ""
+        return aiplatform_v1.types.index.IndexDatapoint.Restriction(
+            namespace=key,
+            allow_list=[str_value]
+        )
+
+    def _create_datapoint(
+        self, 
+        vector_id: str, 
+        vector: List[float], 
+        payload: Optional[Dict] = None
+    ) -> aiplatform_v1.types.index.IndexDatapoint:
+        """Create a datapoint object for the Matching Engine index.
+        
+        Args:
+            vector_id: The ID for the datapoint
+            vector: The vector to store
+            payload: Optional metadata to store with the vector
+        
+        Returns:
+            IndexDatapoint object
+        """
+        restrictions = []
+        if payload:
+            restrictions = [
+                self._create_restriction(key, value) 
+                for key, value in payload.items()
+            ]
+        
+        return aiplatform_v1.types.index.IndexDatapoint(
+            datapoint_id=vector_id,
+            feature_vector=vector,
+            restricts=restrictions
+        )
+
+    def insert(
+        self,
+        vectors: List[list],
+        payloads: Optional[List[Dict]] = None,
+        ids: Optional[List[str]] = None,
+    ) -> None:
+        """Insert vectors into the Matching Engine index.
+        
+        Args:
+            vectors: List of vectors to insert
+            payloads: Optional list of metadata dictionaries
+            ids: Optional list of IDs for the vectors
+            
+        Raises:
+            ValueError: If vectors is empty or lengths don't match
+            GoogleAPIError: If the API call fails
+        """
+        if not vectors:
+            raise ValueError("No vectors provided for insertion")
+        
+        if payloads and len(payloads) != len(vectors):
+            raise ValueError(f"Number of payloads ({len(payloads)}) does not match number of vectors ({len(vectors)})")
+        
+        if ids and len(ids) != len(vectors):
+            raise ValueError(f"Number of ids ({len(ids)}) does not match number of vectors ({len(vectors)})")
+        
+        logger.debug("Starting insert of %d vectors", len(vectors))
+        
+        try:
+            datapoints = [
+                self._create_datapoint(
+                    vector_id=ids[i] if ids else str(uuid.uuid4()),
+                    vector=vector,
+                    payload=payloads[i] if payloads and i < len(payloads) else None
+                )
+                for i, vector in enumerate(vectors)
+            ]
+            
+            logger.debug("Created %d datapoints", len(datapoints))
+            self.index.upsert_datapoints(datapoints=datapoints)
+            logger.debug("Successfully inserted datapoints")
+            
+        except google.api_core.exceptions.GoogleAPIError as e:
+            logger.error("Failed to insert vectors: %s", str(e))
+            raise
+        except Exception as e:
+            logger.error("Unexpected error during insert: %s", str(e))
+            logger.error("Stack trace: %s", traceback.format_exc())
+            raise
+
+
+    def search(self, query: List[float], limit: int = 5, filters: Optional[Dict] = None) -> List[OutputData]:
+        """
+        Search for similar vectors.
+        Args:
+            query (List[float]): Query vector.
+            limit (int, optional): Number of results to return. Defaults to 5.
+            filters (Optional[Dict], optional): Filters to apply to the search. Defaults to None.
+        Returns:
+            List[OutputData]: Search results (unwrapped)
+        """
+        logger.debug("Starting search")
+        logger.debug("Query type: %s, length: %d", type(query), len(query))
+        logger.debug("Limit: %d, Filters: %s", limit, filters)
+        
+        try:
+            filter_namespaces = []
+            if filters:
+                logger.debug("Processing filters")
+                for key, value in filters.items():
+                    logger.debug("Processing filter %s=%s (type=%s)", key, value, type(value))
+                    if isinstance(value, (str, int, float)):
+                        logger.debug("Adding simple filter for %s", key)
+                        filter_namespaces.append(
+                            Namespace(key, [str(value)], [])
+                        )
+                    elif isinstance(value, dict):
+                        logger.debug("Adding complex filter for %s", key)
+                        includes = value.get('include', [])
+                        excludes = value.get('exclude', [])
+                        filter_namespaces.append(
+                            Namespace(key, includes, excludes)
+                        )
+            
+            logger.debug("Final filter_namespaces: %s", filter_namespaces)
+            
+            response = self.index_endpoint.find_neighbors(
+                deployed_index_id=self.deployment_index_id,
+                queries=[query],
+                num_neighbors=limit,
+                filter=filter_namespaces if filter_namespaces else None,
+                return_full_datapoint=True
+            )
+            
+            if not response or len(response) == 0 or len(response[0]) == 0:
+                logger.debug("No results found")
+                return []
+            
+            results = []
+            for neighbor in response[0]:
+                logger.debug("Processing neighbor - id: %s, distance: %s", 
+                            neighbor.id, neighbor.distance)
+                
+                payload = {}
+                if hasattr(neighbor, 'restricts'):
+                    logger.debug("Processing restricts")
+                    for restrict in neighbor.restricts:
+                        if (hasattr(restrict, 'name') and 
+                            hasattr(restrict, 'allow_tokens') and 
+                            restrict.allow_tokens):
+                            logger.debug("Adding %s: %s", restrict.name, restrict.allow_tokens[0])
+                            payload[restrict.name] = restrict.allow_tokens[0]
+                
+                output_data = OutputData(
+                    id=neighbor.id,
+                    score=neighbor.distance,
+                    payload=payload
+                )
+                results.append(output_data)
+            
+            logger.debug("Returning %d results", len(results))
+            return results
+
+        except Exception as e:
+            logger.error("Error occurred: %s", str(e))
+            logger.error("Error type: %s", type(e))
+            logger.error("Stack trace: %s", traceback.format_exc())
+            raise
+
+
+    def delete(self, vector_id: Optional[str] = None, ids: Optional[List[str]] = None) -> bool:
+        """
+        Delete vectors from the Matching Engine index.
+        Args:
+            vector_id (Optional[str]): Single ID to delete (for backward compatibility)
+            ids (Optional[List[str]]): List of IDs of vectors to delete
+        Returns:
+            bool: True if vectors were deleted successfully or already deleted, False if error
+        """
+        logger.debug("Starting delete, vector_id: %s, ids: %s", vector_id, ids)
+        try:
+            # Handle both single vector_id and list of ids
+            if vector_id:
+                datapoint_ids = [vector_id]
+            elif ids:
+                datapoint_ids = ids
+            else:
+                raise ValueError("Either vector_id or ids must be provided")
+
+            logger.debug("Deleting ids: %s", datapoint_ids)
+            try:
+                self.index.remove_datapoints(datapoint_ids=datapoint_ids)
+                logger.debug("Delete completed successfully")
+                return True
+            except google.api_core.exceptions.NotFound:
+                # If the datapoint is already deleted, consider it a success
+                logger.debug("Datapoint already deleted")
+                return True
+            except google.api_core.exceptions.PermissionDenied as e:
+                logger.error("Permission denied: %s", str(e))
+                return False
+            except google.api_core.exceptions.InvalidArgument as e:
+                logger.error("Invalid argument: %s", str(e))
+                return False
+            
+        except Exception as e:
+            logger.error("Error occurred: %s", str(e))
+            logger.error("Error type: %s", type(e))
+            logger.error("Stack trace: %s", traceback.format_exc())
+            return False
+
+
+    def update(
+        self,
+        vector_id: str,
+        vector: Optional[List[float]] = None,
+        payload: Optional[Dict] = None,
+    ) -> bool:
+        """Update a vector and its payload.
+        
+        Args:
+            vector_id: ID of the vector to update
+            vector: Optional new vector values
+            payload: Optional new metadata payload
+            
+        Returns:
+            bool: True if update was successful
+            
+        Raises:
+            ValueError: If neither vector nor payload is provided
+            GoogleAPIError: If the API call fails
+        """
+        logger.debug("Starting update for vector_id: %s", vector_id)
+        
+        if vector is None and payload is None:
+            raise ValueError("Either vector or payload must be provided for update")
+        
+        # First check if the vector exists
+        try:
+            existing = self.get(vector_id)
+            if existing is None:
+                logger.error("Vector ID not found: %s", vector_id)
+                return False
+            
+            datapoint = self._create_datapoint(
+                vector_id=vector_id,
+                vector=vector if vector is not None else [],
+                payload=payload
+            )
+            
+            logger.debug("Upserting datapoint: %s", datapoint)
+            self.index.upsert_datapoints(datapoints=[datapoint])
+            logger.debug("Update completed successfully")
+            return True
+            
+        except google.api_core.exceptions.GoogleAPIError as e:
+            logger.error("API error during update: %s", str(e))
+            return False
+        except Exception as e:
+            logger.error("Unexpected error during update: %s", str(e))
+            logger.error("Stack trace: %s", traceback.format_exc())
+            raise
+
+
+    def get(self, vector_id: str) -> Optional[OutputData]:
+        """
+        Retrieve a vector by ID.
+        Args:
+            vector_id (str): ID of the vector to retrieve.
+        Returns:
+            Optional[OutputData]: Retrieved vector or None if not found.
+        """
+        logger.debug("Starting get for vector_id: %s", vector_id)
+        
+        try:
+            if not self.vector_search_api_endpoint:
+                raise ValueError("vector_search_api_endpoint is required for get operation")
+
+            vector_search_client = aiplatform_v1.MatchServiceClient(
+                client_options={
+                    "api_endpoint": self.vector_search_api_endpoint
+                },
+            )
+            datapoint = aiplatform_v1.IndexDatapoint(
+                datapoint_id=vector_id
+            )
+
+            query = aiplatform_v1.FindNeighborsRequest.Query(
+                datapoint=datapoint,
+                neighbor_count=1
+            )
+            request = aiplatform_v1.FindNeighborsRequest(
+                index_endpoint=f"projects/{self.project_number}/locations/{self.region}/indexEndpoints/{self.endpoint_id}",
+                deployed_index_id=self.deployment_index_id,
+                queries=[query],
+                return_full_datapoint=True,
+            )
+
+            try:
+                response = vector_search_client.find_neighbors(request)
+                logger.debug("Got response")
+                
+                if response and response.nearest_neighbors:
+                    nearest = response.nearest_neighbors[0]
+                    if nearest.neighbors:
+                        neighbor = nearest.neighbors[0]
+                        
+                        payload = {}
+                        if hasattr(neighbor.datapoint, 'restricts'):
+                            for restrict in neighbor.datapoint.restricts:
+                                if restrict.allow_list:
+                                    payload[restrict.namespace] = restrict.allow_list[0]
+                
+                        return OutputData(
+                            id=neighbor.datapoint.datapoint_id,
+                            score=neighbor.distance,
+                            payload=payload
+                        )
+                
+                logger.debug("No results found")
+                return None
+                
+            except google.api_core.exceptions.NotFound:
+                logger.debug("Datapoint not found")
+                return None
+            except google.api_core.exceptions.PermissionDenied as e:
+                logger.error("Permission denied: %s", str(e))
+                return None
+            
+        except Exception as e:
+            logger.error("Error occurred: %s", str(e))
+            logger.error("Error type: %s", type(e))
+            logger.error("Stack trace: %s", traceback.format_exc())
+            raise
+
+
+    def list_cols(self) -> List[str]:
+        """
+        List all collections (indexes).
+        Returns:
+            List[str]: List of collection names.
+        """
+        return [self.deployment_index_id]
+
+
+    def delete_col(self):
+        """
+        Delete a collection (index).
+        Note: This operation is not supported through the API.
+        """
+        logger.warning("Delete collection operation is not supported for Google Matching Engine")
+        pass
+
+
+    def col_info(self) -> Dict:
+        """
+        Get information about a collection (index).
+        Returns:
+            Dict: Collection information.
+        """
+        return {
+            "index_id": self.index_id,
+            "endpoint_id": self.endpoint_id,
+            "project_id": self.project_id,
+            "region": self.region
+        }
+
+
+    def list(self, filters: Optional[Dict] = None, limit: Optional[int] = None) -> List[List[OutputData]]:
+        """List vectors matching the given filters.
+        
+        Args:
+            filters: Optional filters to apply
+            limit: Optional maximum number of results to return
+            
+        Returns:
+            List[List[OutputData]]: List of matching vectors wrapped in an extra array
+            to match the interface
+        """
+        logger.debug("Starting list operation")
+        logger.debug("Filters: %s", filters)
+        logger.debug("Limit: %s", limit)
+        
+        try:
+            # Use a zero vector for the search
+            dimension = 768  # This should be configurable based on the model
+            zero_vector = [0.0] * dimension
+            
+            # Use a large limit if none specified
+            search_limit = limit if limit is not None else 10000
+            
+            results = self.search(
+                query=zero_vector,
+                limit=search_limit,
+                filters=filters
+            )
+            
+            logger.debug("Found %d results", len(results))
+            return [results]  # Wrap in extra array to match interface
+            
+        except Exception as e:
+            logger.error("Error in list operation: %s", str(e))
+            logger.error("Stack trace: %s", traceback.format_exc())
+            raise
+
+
+    def create_col(self, name=None, vector_size=None, distance=None):
+        """
+        Create a new collection. For Google Matching Engine, collections (indexes) 
+        are created through the Google Cloud Console or API separately.
+        This method is a no-op since indexes are pre-created.
+        
+        Args:
+            name: Ignored for Google Matching Engine
+            vector_size: Ignored for Google Matching Engine
+            distance: Ignored for Google Matching Engine
+        """
+        # Google Matching Engine indexes are created through Google Cloud Console
+        # This method is included only to satisfy the abstract base class
+        pass
+
+
+    def add(self, text: str, metadata: Optional[Dict] = None, user_id: Optional[str] = None) -> str:
+        logger.debug("Starting add operation")
+        logger.debug("Text: %s", text)
+        logger.debug("Metadata: %s", metadata)
+        logger.debug("User ID: %s", user_id)
+        
+        try:
+            # Generate a unique ID for this entry
+            vector_id = str(uuid.uuid4())
+            
+            # Create the payload with all necessary fields
+            payload = {
+                "data": text,  # Store the text in the data field
+                "user_id": user_id,
+                **(metadata or {})
+            }
+            
+            # Get the embedding
+            vector = self.embedder.embed_query(text)
+            
+            # Insert using the insert method
+            self.insert(
+                vectors=[vector],
+                payloads=[payload],
+                ids=[vector_id]
+            )
+            
+            return vector_id
+            
+        except Exception as e:
+            logger.error("Error occurred: %s", str(e))
+            raise
+
+
+    def add_texts(
+        self,
+        texts: List[str],
+        metadatas: Optional[List[dict]] = None,
+        ids: Optional[List[str]] = None,
+    ) -> List[str]:
+        """Add texts to the vector store.
+        
+        Args:
+            texts: List of texts to add
+            metadatas: Optional list of metadata dicts
+            ids: Optional list of IDs to use
+            
+        Returns:
+            List[str]: List of IDs of the added texts
+            
+        Raises:
+            ValueError: If texts is empty or lengths don't match
+        """
+        if not texts:
+            raise ValueError("No texts provided")
+        
+        if metadatas and len(metadatas) != len(texts):
+            raise ValueError(f"Number of metadata items ({len(metadatas)}) does not match number of texts ({len(texts)})")
+        
+        if ids and len(ids) != len(texts):
+            raise ValueError(f"Number of ids ({len(ids)}) does not match number of texts ({len(texts)})")
+        
+        logger.debug("Starting add_texts operation")
+        logger.debug("Number of texts: %d", len(texts))
+        logger.debug("Has metadatas: %s", metadatas is not None)
+        logger.debug("Has ids: %s", ids is not None)
+        
+        if ids is None:
+            ids = [str(uuid.uuid4()) for _ in texts]
+        
+        try:
+            # Get embeddings
+            embeddings = self.embedder.embed_documents(texts)
+            
+            # Add to store
+            self.insert(
+                vectors=embeddings,
+                payloads=metadatas if metadatas else [{}] * len(texts),
+                ids=ids
+            )
+            return ids
+            
+        except Exception as e:
+            logger.error("Error in add_texts: %s", str(e))
+            logger.error("Stack trace: %s", traceback.format_exc())
+            raise
+
+    @classmethod
+    def from_texts(
+        cls,
+        texts: List[str],
+        embedding: Any,
+        metadatas: Optional[List[dict]] = None,
+        ids: Optional[List[str]] = None,
+        **kwargs: Any,
+    ) -> "GoogleMatchingEngine":
+        """Create an instance from texts."""
+        logger.debug("Creating instance from texts")
+        store = cls(**kwargs)
+        store.add_texts(texts=texts, metadatas=metadatas, ids=ids)
+        return store
+
+    def similarity_search_with_score(
+        self,
+        query: str,
+        k: int = 5,
+        filter: Optional[Dict] = None,
+    ) -> List[Tuple[Document, float]]:
+        """Return documents most similar to query with scores."""
+        logger.debug("Starting similarity search with score")
+        logger.debug("Query: %s", query)
+        logger.debug("k: %d", k)
+        logger.debug("Filter: %s", filter)
+        
+        embedding = self.embedder.embed_query(query)
+        results = self.search(query=embedding, limit=k, filters=filter)
+        
+        docs_and_scores = [
+            (
+                Document(
+                    page_content=result.payload.get("text", ""),
+                    metadata=result.payload
+                ),
+                result.score
+            )
+            for result in results
+        ]
+        logger.debug("Found %d results", len(docs_and_scores))
+        return docs_and_scores
+
+    def similarity_search(
+        self,
+        query: str,
+        k: int = 5,
+        filter: Optional[Dict] = None,
+    ) -> List[Document]:
+        """Return documents most similar to query."""
+        logger.debug("Starting similarity search")
+        docs_and_scores = self.similarity_search_with_score(query, k, filter)
+        return [doc for doc, _ in docs_and_scores]
+
diff --git a/poetry.lock b/poetry.lock
index 47e82fc9..b12474ce 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand.
 
 [[package]]
 name = "aiohappyeyeballs"
@@ -6,6 +6,8 @@ version = "2.4.6"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "aiohappyeyeballs-2.4.6-py3-none-any.whl", hash = "sha256:147ec992cf873d74f5062644332c539fcd42956dc69453fe5204195e560517e1"},
     {file = "aiohappyeyeballs-2.4.6.tar.gz", hash = "sha256:9b05052f9042985d32ecbe4b59a77ae19c006a78f1344d7fdad69d28ded3d0b0"},
@@ -13,92 +15,94 @@ files = [
 
 [[package]]
 name = "aiohttp"
-version = "3.11.12"
+version = "3.11.13"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
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+    {file = "aiohttp-3.11.13-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:fa1fb1b61881c8405829c50e9cc5c875bfdbf685edf57a76817dfb50643e4a1a"},
+    {file = "aiohttp-3.11.13-cp39-cp39-musllinux_1_2_armv7l.whl", hash = "sha256:25de43bb3cf83ad83efc8295af7310219af6dbe4c543c2e74988d8e9c8a2a917"},
+    {file = "aiohttp-3.11.13-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:fe7065e2215e4bba63dc00db9ae654c1ba3950a5fff691475a32f511142fcddb"},
+    {file = "aiohttp-3.11.13-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:7836587eef675a17d835ec3d98a8c9acdbeb2c1d72b0556f0edf4e855a25e9c1"},
+    {file = "aiohttp-3.11.13-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:85fa0b18558eb1427090912bd456a01f71edab0872f4e0f9e4285571941e4090"},
+    {file = "aiohttp-3.11.13-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a86dc177eb4c286c19d1823ac296299f59ed8106c9536d2b559f65836e0fb2c6"},
+    {file = "aiohttp-3.11.13-cp39-cp39-win32.whl", hash = "sha256:684eea71ab6e8ade86b9021bb62af4bf0881f6be4e926b6b5455de74e420783a"},
+    {file = "aiohttp-3.11.13-cp39-cp39-win_amd64.whl", hash = "sha256:82c249f2bfa5ecbe4a1a7902c81c0fba52ed9ebd0176ab3047395d02ad96cfcb"},
+    {file = "aiohttp-3.11.13.tar.gz", hash = "sha256:8ce789231404ca8fff7f693cdce398abf6d90fd5dae2b1847477196c243b1fbb"},
 ]
 
 [package.dependencies]
@@ -120,6 +124,8 @@ version = "1.3.2"
 description = "aiosignal: a list of registered asynchronous callbacks"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "aiosignal-1.3.2-py2.py3-none-any.whl", hash = "sha256:45cde58e409a301715980c2b01d0c28bdde3770d8290b5eb2173759d9acb31a5"},
     {file = "aiosignal-1.3.2.tar.gz", hash = "sha256:a8c255c66fafb1e499c9351d0bf32ff2d8a0321595ebac3b93713656d2436f54"},
@@ -134,6 +140,7 @@ version = "0.7.0"
 description = "Reusable constraint types to use with typing.Annotated"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
@@ -145,6 +152,7 @@ version = "4.8.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
 files = [
     {file = "anyio-4.8.0-py3-none-any.whl", hash = "sha256:b5011f270ab5eb0abf13385f851315585cc37ef330dd88e27ec3d34d651fd47a"},
     {file = "anyio-4.8.0.tar.gz", hash = "sha256:1d9fe889df5212298c0c0723fa20479d1b94883a2df44bd3897aa91083316f7a"},
@@ -167,6 +175,8 @@ version = "4.0.3"
 description = "Timeout context manager for asyncio programs"
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
+markers = "extra == \"graph\" and python_version < \"3.11\""
 files = [
     {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
     {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
@@ -178,6 +188,8 @@ version = "25.1.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "attrs-25.1.0-py3-none-any.whl", hash = "sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a"},
     {file = "attrs-25.1.0.tar.gz", hash = "sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e"},
@@ -197,6 +209,7 @@ version = "2.2.1"
 description = "Function decoration for backoff and retry"
 optional = false
 python-versions = ">=3.7,<4.0"
+groups = ["main"]
 files = [
     {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
     {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
@@ -208,6 +221,7 @@ version = "2025.1.31"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
+groups = ["main"]
 files = [
     {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"},
     {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"},
@@ -219,6 +233,8 @@ version = "1.17.1"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\" and platform_python_implementation == \"PyPy\""
 files = [
     {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
     {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
@@ -298,6 +314,7 @@ version = "3.4.1"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
 files = [
     {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"},
     {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"},
@@ -399,10 +416,12 @@ version = "0.4.6"
 description = "Cross-platform colored terminal text."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
+groups = ["main", "dev", "test"]
 files = [
     {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
+markers = {main = "platform_system == \"Windows\"", dev = "sys_platform == \"win32\"", test = "sys_platform == \"win32\""}
 
 [[package]]
 name = "dataclasses-json"
@@ -410,6 +429,8 @@ version = "0.6.7"
 description = "Easily serialize dataclasses to and from JSON."
 optional = false
 python-versions = "<4.0,>=3.7"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "dataclasses_json-0.6.7-py3-none-any.whl", hash = "sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a"},
     {file = "dataclasses_json-0.6.7.tar.gz", hash = "sha256:b6b3e528266ea45b9535223bc53ca645f5208833c29229e847b3f26a1cc55fc0"},
@@ -425,6 +446,7 @@ version = "1.9.0"
 description = "Distro - an OS platform information API"
 optional = false
 python-versions = ">=3.6"
+groups = ["main"]
 files = [
     {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
     {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
@@ -436,6 +458,8 @@ version = "1.2.2"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
+groups = ["main", "dev", "test"]
+markers = "python_version < \"3.11\""
 files = [
     {file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = "sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b"},
     {file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
@@ -450,6 +474,8 @@ version = "1.5.0"
 description = "A list-like structure which implements collections.abc.MutableSequence"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5b6a66c18b5b9dd261ca98dffcb826a525334b2f29e7caa54e182255c5f6a65a"},
     {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1b3eb7b05ea246510b43a7e53ed1653e55c2121019a97e60cad7efb881a97bb"},
@@ -551,6 +577,8 @@ version = "3.1.1"
 description = "Lightweight in-process concurrent programming"
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
+markers = "(platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\") and python_version < \"3.14\""
 files = [
     {file = "greenlet-3.1.1-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:0bbae94a29c9e5c7e4a2b7f0aae5c17e8e90acbfd3bf6270eeba60c39fce3563"},
     {file = "greenlet-3.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0fde093fb93f35ca72a556cf72c92ea3ebfda3d79fc35bb19fbe685853869a83"},
@@ -637,6 +665,7 @@ version = "1.70.0"
 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "grpcio-1.70.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:95469d1977429f45fe7df441f586521361e235982a0b39e33841549143ae2851"},
     {file = "grpcio-1.70.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:ed9718f17fbdb472e33b869c77a16d0b55e166b100ec57b016dc7de9c8d236bf"},
@@ -704,6 +733,7 @@ version = "1.70.0"
 description = "Protobuf code generator for gRPC"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "grpcio_tools-1.70.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:4d456521290e25b1091975af71604facc5c7db162abdca67e12a0207b8bbacbe"},
     {file = "grpcio_tools-1.70.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:d50080bca84f53f3a05452e06e6251cbb4887f5a1d1321d1989e26d6e0dc398d"},
@@ -773,6 +803,7 @@ version = "0.14.0"
 description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
 files = [
     {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
     {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
@@ -784,6 +815,7 @@ version = "4.2.0"
 description = "Pure-Python HTTP/2 protocol implementation"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
 files = [
     {file = "h2-4.2.0-py3-none-any.whl", hash = "sha256:479a53ad425bb29af087f3458a61d30780bc818e4ebcf01f0b536ba916462ed0"},
     {file = "h2-4.2.0.tar.gz", hash = "sha256:c8a52129695e88b1a0578d8d2cc6842bbd79128ac685463b887ee278126ad01f"},
@@ -799,6 +831,7 @@ version = "4.1.0"
 description = "Pure-Python HPACK header encoding"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
 files = [
     {file = "hpack-4.1.0-py3-none-any.whl", hash = "sha256:157ac792668d995c657d93111f46b4535ed114f0c9c8d672271bbec7eae1b496"},
     {file = "hpack-4.1.0.tar.gz", hash = "sha256:ec5eca154f7056aa06f196a557655c5b009b382873ac8d1e66e79e87535f1dca"},
@@ -810,6 +843,7 @@ version = "1.0.7"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"},
     {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"},
@@ -831,6 +865,7 @@ version = "0.28.1"
 description = "The next generation HTTP client."
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"},
     {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"},
@@ -856,6 +891,8 @@ version = "0.4.0"
 description = "Consume Server-Sent Event (SSE) messages with HTTPX."
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "httpx-sse-0.4.0.tar.gz", hash = "sha256:1e81a3a3070ce322add1d3529ed42eb5f70817f45ed6ec915ab753f961139721"},
     {file = "httpx_sse-0.4.0-py3-none-any.whl", hash = "sha256:f329af6eae57eaa2bdfd962b42524764af68075ea87370a2de920af5341e318f"},
@@ -867,6 +904,7 @@ version = "6.1.0"
 description = "Pure-Python HTTP/2 framing"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
 files = [
     {file = "hyperframe-6.1.0-py3-none-any.whl", hash = "sha256:b03380493a519fce58ea5af42e4a42317bf9bd425596f7a0835ffce80f1a42e5"},
     {file = "hyperframe-6.1.0.tar.gz", hash = "sha256:f630908a00854a7adeabd6382b43923a4c4cd4b821fcb527e6ab9e15382a3b08"},
@@ -878,6 +916,7 @@ version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
+groups = ["main"]
 files = [
     {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"},
     {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"},
@@ -892,6 +931,7 @@ version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
 python-versions = ">=3.7"
+groups = ["dev", "test"]
 files = [
     {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
@@ -903,6 +943,7 @@ version = "5.13.2"
 description = "A Python utility / library to sort Python imports."
 optional = false
 python-versions = ">=3.8.0"
+groups = ["dev"]
 files = [
     {file = "isort-5.13.2-py3-none-any.whl", hash = "sha256:8ca5e72a8d85860d5a3fa69b8745237f2939afe12dbf656afbcb47fe72d947a6"},
     {file = "isort-5.13.2.tar.gz", hash = "sha256:48fdfcb9face5d58a4f6dde2e72a1fb8dcaf8ab26f95ab49fab84c2ddefb0109"},
@@ -917,6 +958,7 @@ version = "0.8.2"
 description = "Fast iterable JSON parser."
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "jiter-0.8.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:ca8577f6a413abe29b079bc30f907894d7eb07a865c4df69475e868d73e71c7b"},
     {file = "jiter-0.8.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b25bd626bde7fb51534190c7e3cb97cee89ee76b76d7585580e22f34f5e3f393"},
@@ -1002,6 +1044,8 @@ version = "1.33"
 description = "Apply JSON-Patches (RFC 6902)"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade"},
     {file = "jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c"},
@@ -1016,6 +1060,8 @@ version = "3.0.0"
 description = "Identify specific nodes in a JSON document (RFC 6901)"
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942"},
     {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
@@ -1027,6 +1073,8 @@ version = "0.3.19"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "langchain-0.3.19-py3-none-any.whl", hash = "sha256:1e16d97db9106640b7de4c69f8f5ed22eeda56b45b9241279e83f111640eff16"},
     {file = "langchain-0.3.19.tar.gz", hash = "sha256:b96f8a445f01d15d522129ffe77cc89c8468dbd65830d153a676de8f6b899e7b"},
@@ -1067,21 +1115,23 @@ xai = ["langchain-xai"]
 
 [[package]]
 name = "langchain-community"
-version = "0.3.17"
+version = "0.3.18"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
-    {file = "langchain_community-0.3.17-py3-none-any.whl", hash = "sha256:13bbd87d681b0df67bafa294321613b13ac524f173c92f11048d40c74e585f0b"},
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 numpy = [
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@@ -1095,13 +1145,15 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.35"
+version = "0.3.40"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
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 [package.dependencies]
@@ -1122,6 +1174,8 @@ version = "0.3.6"
 description = "LangChain text splitting utilities"
 optional = false
 python-versions = "<4.0,>=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
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@@ -1132,18 +1186,21 @@ langchain-core = ">=0.3.34,<1.0.0"
 
 [[package]]
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-version = "0.3.8"
+version = "0.3.11"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.9"
+groups = ["main"]
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 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
 optional = false
 python-versions = ">=3.9"
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 python-versions = "*"
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 python-versions = ">=3.8"
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 description = "Type system extensions for programs checked with the mypy type checker."
 optional = false
 python-versions = ">=3.5"
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+markers = "extra == \"graph\""
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 python-versions = ">=3.7"
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 python-versions = ">=3.9"
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+version = "1.65.2"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -1450,6 +1531,8 @@ version = "3.10.15"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
 optional = false
 python-versions = ">=3.8"
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 python-versions = ">=3.8"
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 ]
+markers = {main = "extra == \"graph\""}
 
 [[package]]
 name = "pluggy"
@@ -1549,6 +1634,7 @@ version = "1.5.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.8"
+groups = ["dev", "test"]
 files = [
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@@ -1564,6 +1650,7 @@ version = "2.10.1"
 description = "Wraps the portalocker recipe for easy usage"
 optional = false
 python-versions = ">=3.8"
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 files = [
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 python-versions = "*"
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 monotonic = ">=1.5"
 python-dateutil = ">2.1"
 requests = ">=2.7,<3.0"
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 python-versions = ">=3.9"
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+]
+
 [[package]]
 name = "pycparser"
 version = "2.22"
 description = "C parser in Python"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\" and platform_python_implementation == \"PyPy\""
 files = [
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@@ -1729,6 +1917,7 @@ version = "2.10.6"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
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@@ -1749,6 +1938,7 @@ version = "2.27.2"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "pydantic_core-2.27.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:2d367ca20b2f14095a8f4fa1210f5a7b78b8a20009ecced6b12818f455b1e9fa"},
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@@ -1857,13 +2047,15 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pydantic-settings"
-version = "2.7.1"
+version = "2.8.1"
 description = "Settings management using Pydantic"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
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+    {file = "pydantic_settings-2.8.1.tar.gz", hash = "sha256:d5c663dfbe9db9d5e1c646b2e161da12f0d734d422ee56f567d0ea2cee4e8585"},
 ]
 
 [package.dependencies]
@@ -1877,13 +2069,14 @@ yaml = ["pyyaml (>=6.0.1)"]
 
 [[package]]
 name = "pytest"
-version = "8.3.4"
+version = "8.3.5"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
+groups = ["dev", "test"]
 files = [
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+    {file = "pytest-8.3.5.tar.gz", hash = "sha256:f4efe70cc14e511565ac476b57c279e12a855b11f48f212af1080ef2263d3845"},
 ]
 
 [package.dependencies]
@@ -1903,6 +2096,7 @@ version = "2.9.0.post0"
 description = "Extensions to the standard Python datetime module"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
+groups = ["main"]
 files = [
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@@ -1917,6 +2111,8 @@ version = "1.0.1"
 description = "Read key-value pairs from a .env file and set them as environment variables"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
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@@ -1931,6 +2127,7 @@ version = "2024.2"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
+groups = ["main"]
 files = [
     {file = "pytz-2024.2-py2.py3-none-any.whl", hash = "sha256:31c7c1817eb7fae7ca4b8c7ee50c72f93aa2dd863de768e1ef4245d426aa0725"},
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@@ -1942,6 +2139,8 @@ version = "308"
 description = "Python for Window Extensions"
 optional = false
 python-versions = "*"
+groups = ["main"]
+markers = "platform_system == \"Windows\""
 files = [
     {file = "pywin32-308-cp310-cp310-win32.whl", hash = "sha256:796ff4426437896550d2981b9c2ac0ffd75238ad9ea2d3bfa67a1abd546d262e"},
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@@ -1969,6 +2168,8 @@ version = "6.0.2"
 description = "YAML parser and emitter for Python"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
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@@ -2025,36 +2226,13 @@ files = [
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 ]
 
-[[package]]
-name = "qdrant-client"
-version = "1.12.1"
-description = "Client library for the Qdrant vector search engine"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.dependencies]
-grpcio = ">=1.41.0"
-grpcio-tools = ">=1.41.0"
-httpx = {version = ">=0.20.0", extras = ["http2"]}
-numpy = {version = ">=1.26", markers = "python_version >= \"3.12\""}
-portalocker = ">=2.7.0,<3.0.0"
-pydantic = ">=1.10.8"
-urllib3 = ">=1.26.14,<3"
-
-[package.extras]
-fastembed = ["fastembed (==0.3.6)"]
-fastembed-gpu = ["fastembed-gpu (==0.3.6)"]
-
 [[package]]
 name = "qdrant-client"
 version = "1.13.2"
 description = "Client library for the Qdrant vector search engine"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
 files = [
     {file = "qdrant_client-1.13.2-py3-none-any.whl", hash = "sha256:db97e759bd3f8d483a383984ba4c2a158eef56f2188d83df7771591d43de2201"},
     {file = "qdrant_client-1.13.2.tar.gz", hash = "sha256:c8cce87ce67b006f49430a050a35c85b78e3b896c0c756dafc13bdeca543ec13"},
@@ -2068,6 +2246,7 @@ numpy = [
     {version = ">=1.21", markers = "python_version >= \"3.10\" and python_version < \"3.12\""},
     {version = ">=1.21,<2.1.0", markers = "python_version < \"3.10\""},
     {version = ">=1.26", markers = "python_version >= \"3.12\" and python_version < \"3.13\""},
+    {version = ">=2.1.0", markers = "python_version >= \"3.13\""},
 ]
 portalocker = ">=2.7.0,<3.0.0"
 pydantic = ">=1.10.8"
@@ -2083,6 +2262,8 @@ version = "0.2.2"
 description = "Various BM25 algorithms for document ranking"
 optional = false
 python-versions = "*"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "rank_bm25-0.2.2-py3-none-any.whl", hash = "sha256:7bd4a95571adadfc271746fa146a4bcfd89c0cf731e49c3d1ad863290adbe8ae"},
     {file = "rank_bm25-0.2.2.tar.gz", hash = "sha256:096ccef76f8188563419aaf384a02f0ea459503fdf77901378d4fd9d87e5e51d"},
@@ -2100,6 +2281,7 @@ version = "2.32.3"
 description = "Python HTTP for Humans."
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
     {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
@@ -2121,6 +2303,8 @@ version = "1.0.0"
 description = "A utility belt for advanced users of python-requests"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6"},
     {file = "requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06"},
@@ -2135,6 +2319,7 @@ version = "0.6.9"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
+groups = ["dev"]
 files = [
     {file = "ruff-0.6.9-py3-none-linux_armv6l.whl", hash = "sha256:064df58d84ccc0ac0fcd63bc3090b251d90e2a372558c0f057c3f75ed73e1ccd"},
     {file = "ruff-0.6.9-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:140d4b5c9f5fc7a7b074908a78ab8d384dd7f6510402267bc76c37195c02a7ec"},
@@ -2158,13 +2343,14 @@ files = [
 
 [[package]]
 name = "setuptools"
-version = "75.8.0"
+version = "75.8.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
 files = [
-    {file = "setuptools-75.8.0-py3-none-any.whl", hash = "sha256:e3982f444617239225d675215d51f6ba05f845d4eec313da4418fdbb56fb27e3"},
-    {file = "setuptools-75.8.0.tar.gz", hash = "sha256:c5afc8f407c626b8313a86e10311dd3f661c6cd9c09d4bf8c15c0e11f9f2b0e6"},
+    {file = "setuptools-75.8.2-py3-none-any.whl", hash = "sha256:558e47c15f1811c1fa7adbd0096669bf76c1d3f433f58324df69f3f5ecac4e8f"},
+    {file = "setuptools-75.8.2.tar.gz", hash = "sha256:4880473a969e5f23f2a2be3646b2dfd84af9028716d398e46192f84bc36900d2"},
 ]
 
 [package.extras]
@@ -2182,6 +2368,7 @@ version = "1.17.0"
 description = "Python 2 and 3 compatibility utilities"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
+groups = ["main"]
 files = [
     {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"},
     {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"},
@@ -2193,6 +2380,7 @@ version = "1.3.1"
 description = "Sniff out which async library your code is running under"
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
 files = [
     {file = "sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2"},
     {file = "sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc"},
@@ -2204,6 +2392,7 @@ version = "2.0.38"
 description = "Database Abstraction Library"
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
 files = [
     {file = "SQLAlchemy-2.0.38-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5e1d9e429028ce04f187a9f522818386c8b076723cdbe9345708384f49ebcec6"},
     {file = "SQLAlchemy-2.0.38-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b87a90f14c68c925817423b0424381f0e16d80fc9a1a1046ef202ab25b19a444"},
@@ -2299,6 +2488,8 @@ version = "9.0.0"
 description = "Retry code until it succeeds"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539"},
     {file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"},
@@ -2314,6 +2505,8 @@ version = "2.2.1"
 description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
+groups = ["dev", "test"]
+markers = "python_version < \"3.11\""
 files = [
     {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
     {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
@@ -2355,6 +2548,7 @@ version = "4.67.1"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
+groups = ["main"]
 files = [
     {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"},
     {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"},
@@ -2376,6 +2570,7 @@ version = "4.12.2"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
 files = [
     {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
     {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
@@ -2387,6 +2582,8 @@ version = "0.9.0"
 description = "Runtime inspection utilities for typing module."
 optional = false
 python-versions = "*"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "typing_inspect-0.9.0-py3-none-any.whl", hash = "sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f"},
     {file = "typing_inspect-0.9.0.tar.gz", hash = "sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78"},
@@ -2402,6 +2599,7 @@ version = "2.3.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
 files = [
     {file = "urllib3-2.3.0-py3-none-any.whl", hash = "sha256:1cee9ad369867bfdbbb48b7dd50374c0967a0bb7710050facf0dd6911440e3df"},
     {file = "urllib3-2.3.0.tar.gz", hash = "sha256:f8c5449b3cf0861679ce7e0503c7b44b5ec981bec0d1d3795a07f1ba96f0204d"},
@@ -2419,6 +2617,8 @@ version = "1.18.3"
 description = "Yet another URL library"
 optional = false
 python-versions = ">=3.9"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34"},
     {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7"},
@@ -2515,6 +2715,8 @@ version = "0.23.0"
 description = "Zstandard bindings for Python"
 optional = false
 python-versions = ">=3.8"
+groups = ["main"]
+markers = "extra == \"graph\""
 files = [
     {file = "zstandard-0.23.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bf0a05b6059c0528477fba9054d09179beb63744355cab9f38059548fedd46a9"},
     {file = "zstandard-0.23.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fc9ca1c9718cb3b06634c7c8dec57d24e9438b2aa9a0f02b8bb36bf478538880"},
@@ -2625,6 +2827,6 @@ cffi = ["cffi (>=1.11)"]
 graph = ["langchain-community", "neo4j", "rank-bm25"]
 
 [metadata]
-lock-version = "2.0"
+lock-version = "2.1"
 python-versions = ">=3.9,<4.0"
-content-hash = "6dba8e3091ed9a081a2035313e674206e2bee10072cb5c0ce6fb407686ce5156"
+content-hash = "3d2febfdf2d1318fc91fce5640e2f9cfb3bf964cc23a797e4f01df81dc7175da"
diff --git a/pyproject.toml b/pyproject.toml
index b2ffb55d..4c041b76 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,6 +25,7 @@ sqlalchemy = "^2.0.31"
 langchain-community = "^0.3.1"
 neo4j = "^5.23.1"
 rank-bm25 = "^0.2.2"
+psycopg2-binary = "^2.9.10"
 
 [tool.poetry.extras]
 graph = ["langchain-community", "neo4j", "rank-bm25"]
diff --git a/tests/vector_stores/test_vertex_ai_vector_search.py b/tests/vector_stores/test_vertex_ai_vector_search.py
new file mode 100644
index 00000000..36233d20
--- /dev/null
+++ b/tests/vector_stores/test_vertex_ai_vector_search.py
@@ -0,0 +1,139 @@
+from unittest.mock import Mock, patch
+
+import pytest
+from google.api_core import exceptions
+from google.cloud.aiplatform.matching_engine.matching_engine_index_endpoint import (
+    Namespace,
+)
+
+from mem0.configs.vector_stores.vertex_ai_vector_search import (
+    GoogleMatchingEngineConfig,
+)
+from mem0.vector_stores.vertex_ai_vector_search import GoogleMatchingEngine
+
+
+@pytest.fixture
+def mock_vertex_ai():
+    with patch('google.cloud.aiplatform.MatchingEngineIndex') as mock_index, \
+         patch('google.cloud.aiplatform.MatchingEngineIndexEndpoint') as mock_endpoint, \
+         patch('google.cloud.aiplatform.init') as mock_init:
+        mock_index_instance = Mock()
+        mock_endpoint_instance = Mock()
+        yield {
+            'index': mock_index_instance,
+            'endpoint': mock_endpoint_instance,
+            'init': mock_init,
+            'index_class': mock_index,
+            'endpoint_class': mock_endpoint
+        }
+
+@pytest.fixture
+def config():
+    return GoogleMatchingEngineConfig(
+        project_id='test-project',
+        project_number='123456789',
+        region='us-central1',
+        endpoint_id='test-endpoint',
+        index_id='test-index',
+        deployment_index_id='test-deployment',
+        collection_name='test-collection',
+        vector_search_api_endpoint='test.vertexai.goog'
+    )
+
+@pytest.fixture
+def vector_store(config, mock_vertex_ai):
+    mock_vertex_ai['index_class'].return_value = mock_vertex_ai['index']
+    mock_vertex_ai['endpoint_class'].return_value = mock_vertex_ai['endpoint']
+    return GoogleMatchingEngine(**config.model_dump())
+
+def test_initialization(vector_store, mock_vertex_ai, config):
+    """Test proper initialization of GoogleMatchingEngine"""
+    mock_vertex_ai['init'].assert_called_once_with(
+        project=config.project_id,
+        location=config.region
+    )
+
+    expected_index_path = f"projects/{config.project_number}/locations/{config.region}/indexes/{config.index_id}"
+    mock_vertex_ai['index_class'].assert_called_once_with(index_name=expected_index_path)
+
+def test_insert_vectors(vector_store, mock_vertex_ai):
+    """Test inserting vectors with payloads"""
+    vectors = [[0.1, 0.2, 0.3]]
+    payloads = [{"name": "test", "user_id": "user1"}]
+    ids = ["test-id"]
+
+    vector_store.insert(vectors=vectors, payloads=payloads, ids=ids)
+
+    mock_vertex_ai['index'].upsert_datapoints.assert_called_once()
+    call_args = mock_vertex_ai['index'].upsert_datapoints.call_args[1]
+    assert len(call_args['datapoints']) == 1
+    datapoint_str = str(call_args['datapoints'][0])
+    assert "test-id" in datapoint_str
+    assert "0.1" in datapoint_str and "0.2" in datapoint_str and "0.3" in datapoint_str
+
+def test_search_vectors(vector_store, mock_vertex_ai):
+    """Test searching vectors with filters"""
+    query = [0.1, 0.2, 0.3]
+    filters = {"user_id": "test_user"}
+
+    mock_datapoint = Mock()
+    mock_datapoint.datapoint_id = "test-id"
+    mock_datapoint.feature_vector = query
+
+    mock_restrict = Mock()
+    mock_restrict.namespace = "user_id"
+    mock_restrict.allow_list = ["test_user"]
+    mock_restrict.name = "user_id"
+    mock_restrict.allow_tokens = ["test_user"]
+    
+    mock_datapoint.restricts = [mock_restrict]
+
+    mock_neighbor = Mock()
+    mock_neighbor.id = "test-id"
+    mock_neighbor.distance = 0.1
+    mock_neighbor.datapoint = mock_datapoint
+    mock_neighbor.restricts = [mock_restrict]
+
+    mock_vertex_ai['endpoint'].find_neighbors.return_value = [[mock_neighbor]]
+
+    results = vector_store.search(query=query, filters=filters, limit=1)
+
+    mock_vertex_ai['endpoint'].find_neighbors.assert_called_once_with(
+        deployed_index_id=vector_store.deployment_index_id,
+        queries=[query],
+        num_neighbors=1,
+        filter=[Namespace("user_id", ["test_user"], [])],
+        return_full_datapoint=True
+    )
+
+    assert len(results) == 1
+    assert results[0].id == "test-id"
+    assert results[0].score == 0.1
+    assert results[0].payload == {"user_id": "test_user"}
+
+def test_delete(vector_store, mock_vertex_ai):
+    """Test deleting vectors"""
+    vector_id = "test-id"
+
+    remove_mock = Mock()
+
+    with patch.object(GoogleMatchingEngine, 'delete', wraps=vector_store.delete) as delete_spy:
+        with patch.object(vector_store.index, 'remove_datapoints', remove_mock):
+            vector_store.delete(ids=[vector_id])
+
+            delete_spy.assert_called_once_with(ids=[vector_id])
+            remove_mock.assert_called_once_with(datapoint_ids=[vector_id])
+
+def test_error_handling(vector_store, mock_vertex_ai):
+    """Test error handling during operations"""
+    mock_vertex_ai['index'].upsert_datapoints.side_effect = exceptions.InvalidArgument("Invalid request")
+
+    with pytest.raises(Exception) as exc_info:
+        vector_store.insert(
+            vectors=[[0.1, 0.2, 0.3]],
+            payloads=[{"name": "test"}],
+            ids=["test-id"]
+        )
+
+    assert isinstance(exc_info.value, exceptions.InvalidArgument)
+    assert "Invalid request" in str(exc_info.value)