Comments in schema

This commit is contained in:
Cyber MacGeddon 2024-07-23 20:42:17 +01:00
parent d712b55e89
commit 524fb8b48b

View file

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