llama-stack/llama_stack/apis/memory/memory.py
Ashwin Bharambe 9487ad8294
API Updates (#73)
* API Keys passed from Client instead of distro configuration

* delete distribution registry

* Rename the "package" word away

* Introduce a "Router" layer for providers

Some providers need to be factorized and considered as thin routing
layers on top of other providers. Consider two examples:

- The inference API should be a routing layer over inference providers,
  routed using the "model" key
- The memory banks API is another instance where various memory bank
  types will be provided by independent providers (e.g., a vector store
  is served by Chroma while a keyvalue memory can be served by Redis or
  PGVector)

This commit introduces a generalized routing layer for this purpose.

* update `apis_to_serve`

* llama_toolchain -> llama_stack

* Codemod from llama_toolchain -> llama_stack

- added providers/registry
- cleaned up api/ subdirectories and moved impls away
- restructured api/api.py
- from llama_stack.apis.<api> import foo should work now
- update imports to do llama_stack.apis.<api>
- update many other imports
- added __init__, fixed some registry imports
- updated registry imports
- create_agentic_system -> create_agent
- AgenticSystem -> Agent

* Moved some stuff out of common/; re-generated OpenAPI spec

* llama-toolchain -> llama-stack (hyphens)

* add control plane API

* add redis adapter + sqlite provider

* move core -> distribution

* Some more toolchain -> stack changes

* small naming shenanigans

* Removing custom tool and agent utilities and moving them client side

* Move control plane to distribution server for now

* Remove control plane from API list

* no codeshield dependency randomly plzzzzz

* Add "fire" as a dependency

* add back event loggers

* stack configure fixes

* use brave instead of bing in the example client

* add init file so it gets packaged

* add init files so it gets packaged

* Update MANIFEST

* bug fix

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Xi Yan <xiyan@meta.com>
Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
2024-09-17 19:51:35 -07:00

156 lines
4.2 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import List, Optional, Protocol
from llama_models.schema_utils import json_schema_type, webmethod
from pydantic import BaseModel, Field
from typing_extensions import Annotated
from llama_models.llama3.api.datatypes import * # noqa: F403
@json_schema_type
class MemoryBankDocument(BaseModel):
document_id: str
content: InterleavedTextMedia | URL
mime_type: str | None = None
metadata: Dict[str, Any] = Field(default_factory=dict)
@json_schema_type
class MemoryBankType(Enum):
vector = "vector"
keyvalue = "keyvalue"
keyword = "keyword"
graph = "graph"
class VectorMemoryBankConfig(BaseModel):
type: Literal[MemoryBankType.vector.value] = MemoryBankType.vector.value
embedding_model: str
chunk_size_in_tokens: int
overlap_size_in_tokens: Optional[int] = None
class KeyValueMemoryBankConfig(BaseModel):
type: Literal[MemoryBankType.keyvalue.value] = MemoryBankType.keyvalue.value
class KeywordMemoryBankConfig(BaseModel):
type: Literal[MemoryBankType.keyword.value] = MemoryBankType.keyword.value
class GraphMemoryBankConfig(BaseModel):
type: Literal[MemoryBankType.graph.value] = MemoryBankType.graph.value
MemoryBankConfig = Annotated[
Union[
VectorMemoryBankConfig,
KeyValueMemoryBankConfig,
KeywordMemoryBankConfig,
GraphMemoryBankConfig,
],
Field(discriminator="type"),
]
class Chunk(BaseModel):
content: InterleavedTextMedia
token_count: int
document_id: str
@json_schema_type
class QueryDocumentsResponse(BaseModel):
chunks: List[Chunk]
scores: List[float]
@json_schema_type
class QueryAPI(Protocol):
@webmethod(route="/query_documents")
def query_documents(
self,
query: InterleavedTextMedia,
params: Optional[Dict[str, Any]] = None,
) -> QueryDocumentsResponse: ...
@json_schema_type
class MemoryBank(BaseModel):
bank_id: str
name: str
config: MemoryBankConfig
# if there's a pre-existing (reachable-from-distribution) store which supports QueryAPI
url: Optional[URL] = None
class Memory(Protocol):
@webmethod(route="/memory_banks/create")
async def create_memory_bank(
self,
name: str,
config: MemoryBankConfig,
url: Optional[URL] = None,
) -> MemoryBank: ...
@webmethod(route="/memory_banks/list", method="GET")
async def list_memory_banks(self) -> List[MemoryBank]: ...
@webmethod(route="/memory_banks/get", method="GET")
async def get_memory_bank(self, bank_id: str) -> Optional[MemoryBank]: ...
@webmethod(route="/memory_banks/drop", method="DELETE")
async def drop_memory_bank(
self,
bank_id: str,
) -> str: ...
# this will just block now until documents are inserted, but it should
# probably return a Job instance which can be polled for completion
@webmethod(route="/memory_bank/insert")
async def insert_documents(
self,
bank_id: str,
documents: List[MemoryBankDocument],
ttl_seconds: Optional[int] = None,
) -> None: ...
@webmethod(route="/memory_bank/update")
async def update_documents(
self,
bank_id: str,
documents: List[MemoryBankDocument],
) -> None: ...
@webmethod(route="/memory_bank/query")
async def query_documents(
self,
bank_id: str,
query: InterleavedTextMedia,
params: Optional[Dict[str, Any]] = None,
) -> QueryDocumentsResponse: ...
@webmethod(route="/memory_bank/documents/get", method="GET")
async def get_documents(
self,
bank_id: str,
document_ids: List[str],
) -> List[MemoryBankDocument]: ...
@webmethod(route="/memory_bank/documents/delete", method="DELETE")
async def delete_documents(
self,
bank_id: str,
document_ids: List[str],
) -> None: ...