[Improvement] update pinecone client v3 (#1200)

Co-authored-by: Deven Patel <deven298@yahoo.com>

embedchain/vectordb/pinecone.py

@@ -42,7 +42,7 @@ class PineconeDB(BaseVectorDB):
                     "Please make sure the type is right and that you are passing an instance."
                 )
             self.config = config
-        self.client = self._setup_pinecone_index()
+        self._setup_pinecone_index()
         # Call parent init here because embedder is needed
         super().__init__(config=self.config)
 
@@ -57,17 +57,26 @@ class PineconeDB(BaseVectorDB):
         """
         Loads the Pinecone index or creates it if not present.
         """
-        pinecone.init(
-            api_key=os.environ.get("PINECONE_API_KEY"),
-            environment=os.environ.get("PINECONE_ENV"),
-            **self.config.extra_params,
-        )
-        indexes = pinecone.list_indexes()
+        api_key = self.config.api_key or os.environ.get("PINECONE_API_KEY")
+        if not api_key:
+            raise ValueError("Please set the PINECONE_API_KEY environment variable or pass it in config.")
+        self.client = pinecone.Pinecone(api_key=api_key, **self.config.extra_params)
+        indexes = self.client.list_indexes().names()
         if indexes is None or self.config.index_name not in indexes:
-            pinecone.create_index(
-                name=self.config.index_name, metric=self.config.metric, dimension=self.config.vector_dimension
+            if self.config.pod_config:
+                spec = pinecone.PodSpec(**self.config.pod_config)
+            elif self.config.serverless_config:
+                spec = pinecone.ServerlessSpec(**self.config.serverless_config)
+            else:
+                raise ValueError("No pod_config or serverless_config found.")
+
+            self.client.create_index(
+                name=self.config.index_name,
+                metric=self.config.metric,
+                dimension=self.config.vector_dimension,
+                spec=spec,
             )
-        return pinecone.Index(self.config.index_name)
+        self.pinecone_index = self.client.Index(self.config.index_name)
 
     def get(self, ids: Optional[list[str]] = None, where: Optional[dict[str, any]] = None, limit: Optional[int] = None):
         """
@@ -85,7 +94,7 @@ class PineconeDB(BaseVectorDB):
 
         if ids is not None:
             for i in range(0, len(ids), 1000):
-                result = self.client.fetch(ids=ids[i : i + 1000])
+                result = self.pinecone_index.fetch(ids=ids[i : i + 1000])
                 vectors = result.get("vectors")
                 batch_existing_ids = list(vectors.keys())
                 existing_ids.extend(batch_existing_ids)
@@ -125,7 +134,7 @@ class PineconeDB(BaseVectorDB):
             )
 
         for chunk in chunks(docs, self.BATCH_SIZE, desc="Adding chunks in batches"):
-            self.client.upsert(chunk, **kwargs)
+            self.pinecone_index.upsert(chunk, **kwargs)
 
     def query(
         self,
@@ -151,15 +160,19 @@ class PineconeDB(BaseVectorDB):
         """
         query_vector = self.embedder.embedding_fn([input_query])[0]
         query_filter = self._generate_filter(where)
-        data = self.client.query(
-            vector=query_vector, filter=query_filter, top_k=n_results, include_metadata=True, **kwargs
+        data = self.pinecone_index.query(
+            vector=query_vector,
+            filter=query_filter,
+            top_k=n_results,
+            include_metadata=True,
+            **kwargs,
         )
         contexts = []
-        for doc in data["matches"]:
-            metadata = doc["metadata"]
-            context = metadata["text"]
+        for doc in data.get("matches", []):
+            metadata = doc.get("metadata", {})
+            context = metadata.get("text")
             if citations:
-                metadata["score"] = doc["score"]
+                metadata["score"] = doc.get("score")
                 contexts.append(tuple((context, metadata)))
             else:
                 contexts.append(context)
@@ -183,7 +196,8 @@ class PineconeDB(BaseVectorDB):
         :return: number of documents
         :rtype: int
         """
-        return self.client.describe_index_stats()["total_vector_count"]
+        data = self.pinecone_index.describe_index_stats()
+        return data["total_vector_count"]
 
     def _get_or_create_db(self):
         """Called during initialization"""
@@ -194,7 +208,7 @@ class PineconeDB(BaseVectorDB):
         Resets the database. Deletes all embeddings irreversibly.
         """
         # Delete all data from the database
-        pinecone.delete_index(self.config.index_name)
+        self.client.delete_index(self.config.index_name)
         self._setup_pinecone_index()
 
     @staticmethod
@@ -213,7 +227,7 @@ class PineconeDB(BaseVectorDB):
         # Follow `https://docs.pinecone.io/docs/metadata-filtering#deleting-vectors-by-metadata-filter` for more details
         db_filter = self._generate_filter(where)
         try:
-            self.client.delete(filter=db_filter)
+            self.pinecone_index.delete(filter=db_filter)
         except Exception as e:
             print(f"Failed to delete from Pinecone: {e}")
             return