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1d0e91d802
* support data: in URL for memory. Add ootb support for pdfs * moved utility to common and updated data_url parsing logic --------- Co-authored-by: Hardik Shah <hjshah@fb.com>
156 lines
4.2 KiB
Python
156 lines
4.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import List, Optional, Protocol
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from llama_models.schema_utils import json_schema_type, webmethod
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from pydantic import BaseModel, Field
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from typing_extensions import Annotated
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from llama_models.llama3.api.datatypes import * # noqa: F403
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@json_schema_type
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class MemoryBankDocument(BaseModel):
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document_id: str
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content: InterleavedTextMedia | URL
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mime_type: str | None = None
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metadata: Dict[str, Any] = Field(default_factory=dict)
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@json_schema_type
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class MemoryBankType(Enum):
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vector = "vector"
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keyvalue = "keyvalue"
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keyword = "keyword"
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graph = "graph"
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class VectorMemoryBankConfig(BaseModel):
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type: Literal[MemoryBankType.vector.value] = MemoryBankType.vector.value
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embedding_model: str
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chunk_size_in_tokens: int
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overlap_size_in_tokens: Optional[int] = None
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class KeyValueMemoryBankConfig(BaseModel):
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type: Literal[MemoryBankType.keyvalue.value] = MemoryBankType.keyvalue.value
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class KeywordMemoryBankConfig(BaseModel):
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type: Literal[MemoryBankType.keyword.value] = MemoryBankType.keyword.value
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class GraphMemoryBankConfig(BaseModel):
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type: Literal[MemoryBankType.graph.value] = MemoryBankType.graph.value
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MemoryBankConfig = Annotated[
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Union[
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VectorMemoryBankConfig,
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KeyValueMemoryBankConfig,
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KeywordMemoryBankConfig,
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GraphMemoryBankConfig,
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],
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Field(discriminator="type"),
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]
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class Chunk(BaseModel):
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content: InterleavedTextMedia
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token_count: int
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document_id: str
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@json_schema_type
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class QueryDocumentsResponse(BaseModel):
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chunks: List[Chunk]
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scores: List[float]
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@json_schema_type
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class QueryAPI(Protocol):
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@webmethod(route="/query_documents")
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def query_documents(
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self,
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query: InterleavedTextMedia,
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params: Optional[Dict[str, Any]] = None,
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) -> QueryDocumentsResponse: ...
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@json_schema_type
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class MemoryBank(BaseModel):
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bank_id: str
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name: str
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config: MemoryBankConfig
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# if there's a pre-existing (reachable-from-distribution) store which supports QueryAPI
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url: Optional[URL] = None
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class Memory(Protocol):
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@webmethod(route="/memory_banks/create")
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async def create_memory_bank(
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self,
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name: str,
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config: MemoryBankConfig,
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url: Optional[URL] = None,
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) -> MemoryBank: ...
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@webmethod(route="/memory_banks/list", method="GET")
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async def list_memory_banks(self) -> List[MemoryBank]: ...
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@webmethod(route="/memory_banks/get", method="GET")
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async def get_memory_bank(self, bank_id: str) -> Optional[MemoryBank]: ...
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@webmethod(route="/memory_banks/drop", method="DELETE")
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async def drop_memory_bank(
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self,
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bank_id: str,
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) -> str: ...
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# this will just block now until documents are inserted, but it should
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# probably return a Job instance which can be polled for completion
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@webmethod(route="/memory_bank/insert")
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async def insert_documents(
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self,
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bank_id: str,
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documents: List[MemoryBankDocument],
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ttl_seconds: Optional[int] = None,
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) -> None: ...
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@webmethod(route="/memory_bank/update")
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async def update_documents(
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self,
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bank_id: str,
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documents: List[MemoryBankDocument],
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) -> None: ...
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@webmethod(route="/memory_bank/query")
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async def query_documents(
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self,
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bank_id: str,
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query: InterleavedTextMedia,
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params: Optional[Dict[str, Any]] = None,
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) -> QueryDocumentsResponse: ...
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@webmethod(route="/memory_bank/documents/get", method="GET")
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async def get_documents(
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self,
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bank_id: str,
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document_ids: List[str],
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) -> List[MemoryBankDocument]: ...
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@webmethod(route="/memory_bank/documents/delete", method="DELETE")
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async def delete_documents(
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self,
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bank_id: str,
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document_ids: List[str],
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) -> None: ...
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