Python client library for the Portkey API - Control Panel for AI Apps with unified API signature, automated fallbacks, retries, load balancing, semantic caching, virtual keys, and comprehensive observability features.
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Vector database operations for retrieval-augmented generation (RAG) applications with file management and batch processing.
class VectorStores:
def create(self, **kwargs): ...
def list(self, **kwargs): ...
def retrieve(self, **kwargs): ...
def update(self, **kwargs): ...
def delete(self, **kwargs): ...
files: VectorFiles
file_batches: VectorFileBatches
class VectorFiles:
def create(self, **kwargs): ...
def list(self, **kwargs): ...
def retrieve(self, **kwargs): ...
def delete(self, **kwargs): ...
class VectorFileBatches:
def create(self, **kwargs): ...
def list(self, **kwargs): ...
def retrieve(self, **kwargs): ...
def cancel(self, **kwargs): ...from portkey_ai import Portkey
portkey = Portkey(
api_key="PORTKEY_API_KEY",
virtual_key="VIRTUAL_KEY"
)
# Create vector store
vector_store = portkey.beta.vector_stores.create(
name="Knowledge Base"
)
# Add files to vector store
portkey.beta.vector_stores.files.create(
vector_store_id=vector_store.id,
file_id="file-123"
)
# Create file batch
batch = portkey.beta.vector_stores.file_batches.create(
vector_store_id=vector_store.id,
file_ids=["file-123", "file-456"]
)Install with Tessl CLI
npx tessl i tessl/pypi-portkey-aidocs