Fix query filter in azure ai search (#2171)

mem0/vector_stores/azure_ai_search.py

@@ -76,6 +76,9 @@ class AzureAISearch(VectorStoreBase):
 
         fields = [
             SimpleField(name="id", type=SearchFieldDataType.String, key=True),
+            SimpleField(name="user_id", type=SearchFieldDataType.String, filterable=True),
+            SimpleField(name="run_id", type=SearchFieldDataType.String, filterable=True),
+            SimpleField(name="agent_id", type=SearchFieldDataType.String, filterable=True),
             SearchField(
                 name="vector",
                 type=vector_type,
@@ -96,6 +99,14 @@ class AzureAISearch(VectorStoreBase):
         index = SearchIndex(name=self.index_name, fields=fields, vector_search=vector_search)
         self.index_client.create_or_update_index(index)
 
+    def _generate_document(self, vector, payload, id):
+        document = {"id": id, "vector": vector, "payload": json.dumps(payload)}
+        # Extract additional fields if they exist
+        for field in ["user_id", "run_id", "agent_id"]:
+            if field in payload:
+                document[field] = payload[field]
+        return document
+
     def insert(self, vectors, payloads=None, ids=None):
         """Insert vectors into the index.
 
@@ -105,12 +116,26 @@ class AzureAISearch(VectorStoreBase):
             ids (List[str], optional): List of IDs corresponding to vectors.
         """
         logger.info(f"Inserting {len(vectors)} vectors into index {self.index_name}")
+
         documents = [
-            {"id": id, "vector": vector, "payload": json.dumps(payload)}
+            self._generate_document(vector, payload, id)
             for id, vector, payload in zip(ids, vectors, payloads)
         ]
         self.search_client.upload_documents(documents)
 
+    def _build_filter_expression(self, filters):
+        filter_conditions = []
+        for key, value in filters.items():
+            # If the value is a string, add quotes
+            if isinstance(value, str):
+                condition = f"{key} eq '{value}'"
+            else:
+                condition = f"{key} eq {value}"
+            filter_conditions.append(condition)
+        # Use 'and' to join multiple conditions
+        filter_expression = ' and '.join(filter_conditions)
+        return filter_expression
+
     def search(self, query, limit=5, filters=None):
         """Search for similar vectors.
 
@@ -122,17 +147,23 @@ class AzureAISearch(VectorStoreBase):
         Returns:
             list: Search results.
         """
+        # Build filter expression
+        filter_expression = None
+        if filters:
+            filter_expression = self._build_filter_expression(filters)
 
-        vector_query = VectorizedQuery(vector=query, k_nearest_neighbors=limit, fields="vector")
+        vector_query = VectorizedQuery(
-        search_results = self.search_client.search(vector_queries=[vector_query], top=limit)
+            vector=query, k_nearest_neighbors=limit, fields="vector"
+        )
+        search_results = self.search_client.search(
+            vector_queries=[vector_query],
+            filter=filter_expression,
+            top=limit
+        )
 
         results = []
         for result in search_results:
             payload = json.loads(result["payload"])
-            if filters:
-                for key, value in filters.items():
-                    if key not in payload or payload[key] != value:
-                        continue
             results.append(OutputData(id=result["id"], score=result["@search.score"], payload=payload))
         return results
 
@@ -143,6 +174,7 @@ class AzureAISearch(VectorStoreBase):
             vector_id (str): ID of the vector to delete.
         """
         self.search_client.delete_documents(documents=[{"id": vector_id}])
+        logger.info(f"Deleted document with ID '{vector_id}' from index '{self.index_name}'.")
 
     def update(self, vector_id, vector=None, payload=None):
         """Update a vector and its payload.
@@ -156,7 +188,10 @@ class AzureAISearch(VectorStoreBase):
         if vector:
             document["vector"] = vector
         if payload:
-            document["payload"] = json.dumps(payload)
+            json_payload = json.dumps(payload)
+            document["payload"] = json_payload
+            for field in ["user_id", "run_id", "agent_id"]:
+                document[field] = payload.get(field)
         self.search_client.merge_or_upload_documents(documents=[document])
 
     def get(self, vector_id) -> OutputData:
@@ -206,17 +241,18 @@ class AzureAISearch(VectorStoreBase):
         Returns:
             List[OutputData]: List of vectors.
         """
-        search_results = self.search_client.search(search_text="*", top=limit)
+        filter_expression = None
+        if filters:
+            filter_expression = self._build_filter_expression(filters)
+
+        search_results = self.search_client.search(
+            search_text="*",
+            filter=filter_expression,
+            top=limit
+        )
         results = []
         for result in search_results:
             payload = json.loads(result["payload"])
-            include_result = True
-            if filters:
-                for key, value in filters.items():
-                    if (key not in payload) or (payload[key] != filters[key]):
-                        include_result = False
-                        break
-            if include_result:
             results.append(OutputData(id=result["id"], score=result["@search.score"], payload=payload))
 
         return [results]