text-generation-webui/extensions/superbooga/chromadb.py
2023-05-13 14:15:40 -03:00

79 lines
2.1 KiB
Python

import logging
import posthog
import torch
from sentence_transformers import SentenceTransformer
import chromadb
from chromadb.config import Settings
logging.info('Intercepting all calls to posthog :)')
posthog.capture = lambda *args, **kwargs: None
class Collecter():
def __init__(self):
pass
def add(self, texts: list[str]):
pass
def get(self, search_strings: list[str], n_results: int) -> list[str]:
pass
def clear(self):
pass
class Embedder():
def __init__(self):
pass
def embed(self, text: str) -> list[torch.Tensor]:
pass
class ChromaCollector(Collecter):
def __init__(self, embedder: Embedder):
super().__init__()
self.chroma_client = chromadb.Client(Settings(anonymized_telemetry=False))
self.embedder = embedder
self.collection = self.chroma_client.create_collection(name="context", embedding_function=embedder.embed)
self.ids = []
def add(self, texts: list[str]):
self.ids = [f"id{i}" for i in range(len(texts))]
self.collection.add(documents=texts, ids=self.ids)
def get(self, search_strings: list[str], n_results: int) -> list[str]:
n_results = min(len(self.ids), n_results)
result = self.collection.query(query_texts=search_strings, n_results=n_results, include=['documents'])['documents'][0]
return result
def get_ids(self, search_strings: list[str], n_results: int) -> list[str]:
n_results = min(len(self.ids), n_results)
result = self.collection.query(query_texts=search_strings, n_results=n_results, include=['documents'])['ids'][0]
return list(map(lambda x: int(x[2:]), result))
def clear(self):
self.collection.delete(ids=self.ids)
class SentenceTransformerEmbedder(Embedder):
def __init__(self) -> None:
self.model = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")
self.embed = self.model.encode
def make_collector():
global embedder
return ChromaCollector(embedder)
def add_chunks_to_collector(chunks, collector):
collector.clear()
collector.add(chunks)
embedder = SentenceTransformerEmbedder()