Fixed Some More Bugs

semantic_router/indices/pinecone.py

@@ -12,7 +12,7 @@ class PineconeIndex(BaseIndex):
     cloud: str = "aws"
     region: str = "us-west-2" 
     pinecone: Any = Field(default=None, exclude=True)
-    vector_id_counter: int = 0
+    vector_id_counter: int = -1
 
     def __init__(self, **data):
         super().__init__(**data) 
@@ -33,15 +33,12 @@ class PineconeIndex(BaseIndex):
             )
         self.index = self.pinecone.Index(self.index_name)
         
-        # Store the index name for potential deletion
-        self.index_name = self.index_name
-
     def add(self, embeds: List[List[float]]):
         # Format embeds as a list of dictionaries for Pinecone's upsert method
         vectors_to_upsert = []
-        for i, vector in enumerate(embeds):
-            # Generate a unique ID for each vector
-            vector_id = f"vec{i+1}"
+        for vector in embeds:
+            self.vector_id_counter += 1  # Increment the counter for each new vector
+            vector_id = str(self.vector_id_counter)  # Convert counter to string ID
 
             # Prepare for upsert
             vectors_to_upsert.append({"id": vector_id, "values": vector})
@@ -52,18 +49,31 @@ class PineconeIndex(BaseIndex):
     def remove(self, ids_to_remove: List[str]):
         self.index.delete(ids=ids_to_remove)
 
+    def remove_all(self):
+        self.index.delete(delete_all=True)
+
     def is_index_populated(self) -> bool:
         stats = self.index.describe_index_stats()
-        return stats["dimension"] > 0 and stats["index_size"] > 0
-
+        return stats["dimension"] > 0 and stats["total_vector_count"] > 0
+    
     def query(self, query_vector: np.ndarray, top_k: int = 5) -> Tuple[np.ndarray, np.ndarray]:
-        results = self.index.query(queries=[query_vector], top_k=top_k)
-        ids = [result["id"] for result in results["matches"]]
+        query_vector_list = query_vector.tolist()
+        results = self.index.query(vector=[query_vector_list], top_k=top_k)
+        ids = [int(result["id"]) for result in results["matches"]]
         scores = [result["score"] for result in results["matches"]]
-        return np.array(ids), np.array(scores)
+        # DEBUGGING: Start.
+        print('#'*50)
+        print('ids')
+        print(ids)
+        print('#'*50)
+        # DEBUGGING: End.
+        # DEBUGGING: Start.
+        print('#'*50)
+        print('scores')
+        print(scores)
+        print('#'*50)
+        # DEBUGGING: End.
+        return np.array(scores), np.array(ids)
 
     def delete_index(self):
-        """
-        Deletes the Pinecone index.
-        """
         pinecone.delete_index(self.index_name)
\ No newline at end of file

semantic_router/layer.py

@@ -188,6 +188,9 @@ class RouteLayer:
             self._add_routes(routes=self.routes)
 
     def check_for_matching_routes(self, top_class: str) -> Optional[Route]:
+        # DEBUGGING: Start.
+        print(f'top_class 2: {top_class}')
+        # DEBUGGING: End.
         matching_routes = [route for route in self.routes if route.name == top_class]
         if not matching_routes:
             logger.error(
@@ -210,8 +213,17 @@ class RouteLayer:
             vector_arr = np.array(vector)
         # get relevant utterances
         results = self._retrieve(xq=vector_arr)
+        # DEBUGGING: Start.
+        print(f'results: {results}')
+        # DEBUGGING: End.
         # decide most relevant routes
         top_class, top_class_scores = self._semantic_classify(results)
+        # DEBUGGING: Start.
+        print(f'top_class 1: {top_class}')
+        # DEBUGGING: End.
+        # DEBUGGING: Start.
+        print(f'top_class_scores: {top_class_scores}')
+        # DEBUGGING: End.
         # TODO do we need this check?
         route = self.check_for_matching_routes(top_class)
         if route is None:
@@ -221,6 +233,24 @@ class RouteLayer:
             if route.score_threshold is not None
             else self.score_threshold
         )
+        # DEBUGGING: Start.
+        print('#'*50)
+        print('Chosen route')
+        print(route)
+        print('#'*50)
+        # DEBUGGING: End.
+        # DEBUGGING: Start.
+        print('#'*50)
+        print('top_class_scores')
+        print(top_class_scores)
+        print('#'*50)
+        # DEBUGGING: End.
+        # DEBUGGING: Start.
+        print('#'*50)
+        print('threshold')
+        print(threshold)
+        print('#'*50)
+        # DEBUGGING: End.
         passed = self._pass_threshold(top_class_scores, threshold)
         if passed:
             if route.function_schema and text is None:
@@ -334,7 +364,17 @@ class RouteLayer:
 
     def _retrieve(self, xq: Any, top_k: int = 5) -> List[dict]:
         """Given a query vector, retrieve the top_k most similar records."""
+        # DEBUGGING: Start.
+        print('#'*50)
+        print('RouteLayer._retrieve - CHECKPOINT 1')
+        print('#'*50)
+        # DEBUGGING: End.
         if self.index.is_index_populated():
+            # DEBUGGING: Start.
+            print('#'*50)
+            print('RouteLayer._retrieve - CHECKPOINT 2')
+            print('#'*50)
+            # DEBUGGING: End.
             # calculate similarity matrix
             scores, idx = self.index.query(xq, top_k)
             # get the utterance categories (route names)