Removing unnecessary files

requirements.txt

@@ -4,7 +4,7 @@ bs4
 lxml
 fastapi
 loguru
-chromadb
+chromadb==0.3.26
 langchain
 sentence_transformers
 sse_starlette

server.py

@@ -1,154 +0,0 @@
-import chromadb
-from chromadb.config import Settings, System
-import time,json
-from pydantic import BaseModel
-from typing import List, Dict, Any, Generator, Optional, cast, Callable
-from chromadb.api.types import (
-    Documents,
-    Embeddings,
-    EmbeddingFunction,
-    IDs,
-    Include,
-    Metadatas,
-    Where,
-    WhereDocument,
-    GetResult,
-    QueryResult,
-    CollectionMetadata,
-)
-from chromadb.errors import (
-    ChromaError,
-    InvalidUUIDError,
-    InvalidDimensionException,
-)
-from chromadb.server.fastapi.types import (
-    AddEmbedding,
-    DeleteEmbedding,
-    GetEmbedding,
-    QueryEmbedding,
-    RawSql,  # Results,
-    CreateCollection,
-    UpdateCollection,
-    UpdateEmbedding,
-)
-from chromadb.api import API
-from chromadb.config import System
-import chromadb.utils.embedding_functions as ef
-import pandas as pd
-import requests
-import json
-from typing import Sequence
-from chromadb.api.models.Collection import Collection
-import chromadb.errors as errors
-from uuid import UUID
-from chromadb.telemetry import Telemetry
-from overrides import override
-
-
-class client():
-    def __init__(self):
-        self.db = chromadb.Client(Settings(
-            chroma_db_impl="duckdb+parquet",
-            persist_directory="./index/chroma" # Optional, defaults to .chromadb/ in the current directory
-        ))
-
-    def heartbeat(self):
-        return {"nanosecond heartbeat":int(time.time_ns())}
-
-    def list_collections(self):
-        return self.db.list_collections()
-    
-    def create_collection(
-        self,
-        name: str,
-        metadata: Optional[CollectionMetadata] = None,
-        embedding_function: Optional[EmbeddingFunction] = ef.DefaultEmbeddingFunction(),
-        get_or_create: bool = False,
-    ) -> Collection:
-        col=self.db.create_collection(name,metadata=metadata,embedding_function=embedding_function,get_or_create=get_or_create)
-        print(col)
-        return col
-    
-    def get_collection(
-        self,
-        name: str,
-        embedding_function: Optional[EmbeddingFunction] = ef.DefaultEmbeddingFunction()
-    ) -> Collection:
-        col=self.db.get_collection(name,embedding_function=embedding_function)
-        print(col)
-        return col
-
-    def reset(self):
-        return self.db.reset()
-
-    def version(self):
-        return self.db.get_version()
-
-    def persist(self):
-        return self.db.persist()
-
-    def raw_sql(self,raw_sql: RawSql):
-        return self.db.raw_sql(raw_sql.raw_sql) 
-    
-    def add(self,ids: IDs,
-        collection_id: UUID,
-        embeddings: Embeddings,
-        metadatas: Optional[Metadatas] = None,
-        documents: Optional[Documents] = None,
-        increment_index: bool = True,
-    ) -> bool:
-        return self.db._add(collection_id=collection_id,embeddings=embeddings,
-            metadatas=metadatas,documents=documents,
-            ids=ids,increment_index=increment_index)
-    
-    def update( self, collection_id: UUID, ids: IDs,
-        embeddings: Optional[Embeddings] = None,
-        metadatas: Optional[Metadatas] = None,
-        documents: Optional[Documents] = None,
-    ) -> bool:
-        return self.db._update(ids=ids, collection_id=collection_id, embeddings=embeddings, documents=documents, metadatas=metadatas)
-    
-    def upsert( self, collection_id: UUID, ids: IDs,
-        embeddings: Embeddings,
-        metadatas: Optional[Metadatas] = None,
-        documents: Optional[Documents] = None,
-        increment_index: bool = True,
-    ) -> bool:
-        return self.db._upsert(collection_id=collection_id,embeddings=embeddings,metadatas=metadatas,documents=documents,ids=ids,increment_index=increment_index)
-    
-    def get( self, collection_id: UUID, ids: Optional[IDs] = None, where: Optional[Where] = {},
-        sort: Optional[str] = None, limit: Optional[int] = None, offset: Optional[int] = None,
-        page: Optional[int] = None, page_size: Optional[int] = None,
-        where_document: Optional[WhereDocument] = {},
-        include: Include = ["embeddings", "metadatas", "documents"],
-    ) -> GetResult:
-        return self.db._get(collection_id=collection_id, ids=ids, where=where,
-            where_document=where_document, sort=sort, limit=limit,
-            offset=offset, include=include)
-    def delete( self, collection_id: UUID, ids: Optional[IDs],
-        where: Optional[Where] = {}, where_document: Optional[WhereDocument] = {},
-    ) -> IDs:
-        return self.db._delete(where=where, ids=ids, collection_id=collection_id, where_document=where_document)
-
-    def count(self, collection_id: UUID) -> int:
-        return self.db._count(collection_id)
-    
-    def get_nearest_neighbors( self, collection_id: UUID, query_embeddings: Embeddings,
-        n_results: int = 10, where: Where = {}, where_document: WhereDocument = {},
-        include: Include = ["embeddings", "metadatas", "documents", "distances"],
-    ) -> QueryResult:
-        return self.db._query(collection_id=collection_id, where=where,  where_document=where_document, 
-              query_embeddings=query_embeddings, n_results=n_results, include=include)
-    
-    def create_index(self, collection_name: str) -> bool:
-        return self.db.create_index(collection_name)
-    
-    def modify( self, id: UUID, new_name: Optional[str] = None,
-        new_metadata: Optional[CollectionMetadata] = None,
-    ) -> None:
-        """This is for updating the collection"""
-        return self.db._modify(id=id, new_name=new_name, new_metadata=new_metadata)
-    
-    def delete_collection( self, name: str,) -> None:
-        return self.db.delete_collection(name)
-

types.py

@@ -1,82 +0,0 @@
-from pydantic import BaseModel
-from typing import Any, Dict, List, Optional
-#from chromadb.api.types import (
-#    CollectionMetadata,
-#    Include,
-#)
-from typing import Union, Literal
-
-#TODO:Update version-Step1::This file is a copy from chromadb/server/fastapi/types.py
-# Copy CollectionMetadata and Include from chromadb.api.types and comment that import
-# Additionally import Union and Literal from typing for "Include to work"
-CollectionMetadata = Dict[Any, Any]
-
-Include = List[
-    Union[
-        Literal["documents"],
-        Literal["embeddings"],
-        Literal["metadatas"],
-        Literal["distances"],
-    ]
-]
-
-
-class AddEmbedding(BaseModel):  # type: ignore
-    # Pydantic doesn't handle Union types cleanly like Embeddings which has
-    # Union[int, float] so we use Any here to ensure data is parsed
-    # to its original type.
-    embeddings: Optional[List[Any]] = None
-    metadatas: Optional[List[Dict[Any, Any]]] = None
-    documents: Optional[List[str]] = None
-    ids: List[str]
-    increment_index: bool = True
-
-
-class UpdateEmbedding(BaseModel):  # type: ignore
-    embeddings: Optional[List[Any]] = None
-    metadatas: Optional[List[Dict[Any, Any]]] = None
-    documents: Optional[List[str]] = None
-    ids: List[str]
-    increment_index: bool = True
-
-
-class QueryEmbedding(BaseModel):  # type: ignore
-    # TODO: Pydantic doesn't bode well with recursive types so we use generic Dicts
-    # for Where and WhereDocument. This is not ideal, but it works for now since
-    # there is a lot of downstream validation.
-    where: Optional[Dict[Any, Any]] = {}
-    where_document: Optional[Dict[Any, Any]] = {}
-    query_embeddings: List[Any]
-    n_results: int = 10
-    include: Include = ["metadatas", "documents", "distances"]
-
-
-class GetEmbedding(BaseModel):  # type: ignore
-    ids: Optional[List[str]] = None
-    where: Optional[Dict[Any, Any]] = None
-    where_document: Optional[Dict[Any, Any]] = None
-    sort: Optional[str] = None
-    limit: Optional[int] = None
-    offset: Optional[int] = None
-    include: Include = ["metadatas", "documents"]
-
-
-class RawSql(BaseModel):  # type: ignore
-    raw_sql: str
-
-
-class DeleteEmbedding(BaseModel):  # type: ignore
-    ids: Optional[List[str]] = None
-    where: Optional[Dict[Any, Any]] = None
-    where_document: Optional[Dict[Any, Any]] = None
-
-
-class CreateCollection(BaseModel):  # type: ignore
-    name: str
-    metadata: Optional[CollectionMetadata] = None
-    get_or_create: bool = False
-
-
-class UpdateCollection(BaseModel):  # type: ignore
-    new_name: Optional[str] = None
-    new_metadata: Optional[CollectionMetadata] = None