From pipeline > config > UI. Provide example project for promptui - Pipeline to config: `kotaemon.contribs.promptui.config.export_pipeline_to_config`. The config follows schema specified in this document: https://cinnamon-ai.atlassian.net/wiki/spaces/ATM/pages/2748711193/Technical+Detail. Note: this implementation exclude the logs, which will be handled in AUR-408. - Config to UI: `kotaemon.contribs.promptui.build_from_yaml` - Example project is located at `examples/promptui/`
69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
import json
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from pathlib import Path
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from typing import List, Optional, Union
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from ..documents.base import Document
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from .base import BaseDocumentStore
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class InMemoryDocumentStore(BaseDocumentStore):
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"""Simple memory document store that store document in a dictionary"""
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def __init__(self):
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self._store = {}
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def add(
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self,
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docs: Union[Document, List[Document]],
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ids: Optional[Union[List[str], str]] = None,
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exist_ok: bool = False,
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):
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"""Add document into document store
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Args:
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docs: Union[Document, List[Document]],
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ids: Optional[Union[List[str], str]] = None,
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"""
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doc_ids = ids if ids else [doc.doc_id for doc in docs]
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if not isinstance(doc_ids, list):
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doc_ids = [doc_ids]
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if not isinstance(docs, list):
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docs = [docs]
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for doc_id, doc in zip(doc_ids, docs):
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if doc_id in self._store and not exist_ok:
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raise ValueError(f"Document with id {doc_id} already exist")
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self._store[doc_id] = doc
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def get(self, ids: Union[List[str], str]) -> List[Document]:
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"""Get document by id"""
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if not isinstance(ids, list):
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ids = [ids]
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return [self._store[doc_id] for doc_id in ids]
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def get_all(self) -> dict:
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"""Get all documents"""
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return self._store
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def delete(self, ids: Union[List[str], str]):
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"""Delete document by id"""
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if not isinstance(ids, list):
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ids = [ids]
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for doc_id in ids:
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del self._store[doc_id]
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def save(self, path: Union[str, Path]):
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"""Save document to path"""
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store = {key: value.to_dict() for key, value in self._store.items()}
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with open(path, "w") as f:
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json.dump(store, f)
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def load(self, path: Union[str, Path]):
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"""Load document store from path"""
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with open(path) as f:
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store = json.load(f)
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self._store = {key: Document.from_dict(value) for key, value in store.items()}
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