apunkt/trustgraph
1
0
Fork 0
mirror of https://github.com/trustgraph-ai/trustgraph.git synced 2026-07-05 19:32:11 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Comments in schema

Browse source
This commit is contained in:
Cyber MacGeddon 2024-07-23 20:42:17 +01:00
parent d712b55e89
commit 524fb8b48b
1 changed files with 49 additions and 8 deletions
Download patch file Download diff file Expand all files Collapse all files

57
trustgraph/schema.py
View file

@ -15,23 +15,39 @@ class Source(Record):
id = String()
title = String()
############################################################################
# PDF docs etc.
class Document(Record):
source = Source()
data = Bytes()
document_ingest_queue = 'document-load'
text_ingest_queue = 'text-document-load'
############################################################################
# Text documents / text from PDF
class TextDocument(Record):
source = Source()
text = Bytes()
chunk_ingest_queue = 'chunk-load'
text_ingest_queue = 'text-document-load'
############################################################################
# Chunks of text
class Chunk(Record):
source = Source()
chunk = Bytes()
chunk_ingest_queue = 'chunk-load'
############################################################################
# Chunk embeddings are an embeddings associated with a text chunk
class ChunkEmbeddings(Record):
source = Source()
vectors = Array(Array(Double()))
@ -39,11 +55,21 @@ class ChunkEmbeddings(Record):
chunk_embeddings_ingest_queue = 'chunk-embeddings-load'
############################################################################
# Graph embeddings are embeddings associated with a graph entity
class GraphEmbeddings(Record):
source = Source()
vectors = Array(Array(Double()))
entity = Value()
graph_embeddings_store_queue = 'graph-embeddings-store'
############################################################################
# Graph triples
class Triple(Record):
source = Source()
s = Value()
@ -52,11 +78,13 @@ class Triple(Record):
triples_store_queue = 'triples-store'
# chunk_embeddings_store_queue = 'chunk-embeddings-store'
graph_embeddings_store_queue = 'graph-embeddings-store'
############################################################################
text_completion_request_queue = 'text-completion'
text_completion_response_queue = 'text-completion-response'
# chunk_embeddings_store_queue = 'chunk-embeddings-store'
############################################################################
# LLM text completion
class TextCompletionRequest(Record):
prompt = String()
@ -64,12 +92,26 @@ class TextCompletionRequest(Record):
class TextCompletionResponse(Record):
response = String()
text_completion_request_queue = 'text-completion'
text_completion_response_queue = 'text-completion-response'
############################################################################
# Embeddings
class EmbeddingsRequest(Record):
text = String()
class EmbeddingsResponse(Record):
vectors = Array(Array(Double()))
embeddings_request_queue = 'embeddings'
embeddings_response_queue = 'embeddings-response'
############################################################################
# Graph RAG text retrieval
class GraphRagQuery(Record):
query = String()
@ -79,6 +121,5 @@ class GraphRagResponse(Record):
graph_rag_request_queue = 'graph-rag'
graph_rag_response_queue = 'graph-rag-response'
embeddings_request_queue = 'embeddings'
embeddings_response_queue = 'embeddings-response'
############################################################################