mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-04-29 18:36:22 +02:00
6aa212061d
* Update schema for doc embeddings * Rename embeddings-vectorize to graph-embeddings * Added document-embeddings processor (broken, needs fixing) * Added scripts * Fixed DE queue schema * Add missing DE process * Fix doc RAG processing, put graph-rag and doc-rag in appropriate component files.
144 lines
4 KiB
Python
144 lines
4 KiB
Python
|
|
from . clients.document_embeddings_client import DocumentEmbeddingsClient
|
|
from . clients.triples_query_client import TriplesQueryClient
|
|
from . clients.embeddings_client import EmbeddingsClient
|
|
from . clients.prompt_client import PromptClient
|
|
|
|
from . schema import DocumentEmbeddingsRequest, DocumentEmbeddingsResponse
|
|
from . schema import TriplesQueryRequest, TriplesQueryResponse
|
|
from . schema import prompt_request_queue
|
|
from . schema import prompt_response_queue
|
|
from . schema import embeddings_request_queue
|
|
from . schema import embeddings_response_queue
|
|
from . schema import document_embeddings_request_queue
|
|
from . schema import document_embeddings_response_queue
|
|
|
|
LABEL="http://www.w3.org/2000/01/rdf-schema#label"
|
|
DEFINITION="http://www.w3.org/2004/02/skos/core#definition"
|
|
|
|
class Query:
|
|
|
|
def __init__(self, rag, user, collection, verbose):
|
|
self.rag = rag
|
|
self.user = user
|
|
self.collection = collection
|
|
self.verbose = verbose
|
|
|
|
def get_vector(self, query):
|
|
|
|
if self.verbose:
|
|
print("Compute embeddings...", flush=True)
|
|
|
|
qembeds = self.rag.embeddings.request(query)
|
|
|
|
if self.verbose:
|
|
print("Done.", flush=True)
|
|
|
|
return qembeds
|
|
|
|
def get_docs(self, query):
|
|
|
|
vectors = self.get_vector(query)
|
|
|
|
if self.verbose:
|
|
print("Get entities...", flush=True)
|
|
|
|
docs = self.rag.de_client.request(
|
|
vectors, limit=self.rag.doc_limit
|
|
)
|
|
|
|
if self.verbose:
|
|
print("Docs:", flush=True)
|
|
for doc in docs:
|
|
print(doc, flush=True)
|
|
|
|
return docs
|
|
|
|
class DocumentRag:
|
|
|
|
def __init__(
|
|
self,
|
|
pulsar_host="pulsar://pulsar:6650",
|
|
pr_request_queue=None,
|
|
pr_response_queue=None,
|
|
emb_request_queue=None,
|
|
emb_response_queue=None,
|
|
de_request_queue=None,
|
|
de_response_queue=None,
|
|
verbose=False,
|
|
module="test",
|
|
):
|
|
|
|
self.verbose=verbose
|
|
|
|
if pr_request_queue is None:
|
|
pr_request_queue = prompt_request_queue
|
|
|
|
if pr_response_queue is None:
|
|
pr_response_queue = prompt_response_queue
|
|
|
|
if emb_request_queue is None:
|
|
emb_request_queue = embeddings_request_queue
|
|
|
|
if emb_response_queue is None:
|
|
emb_response_queue = embeddings_response_queue
|
|
|
|
if de_request_queue is None:
|
|
de_request_queue = document_embeddings_request_queue
|
|
|
|
if de_response_queue is None:
|
|
de_response_queue = document_embeddings_response_queue
|
|
|
|
if self.verbose:
|
|
print("Initialising...", flush=True)
|
|
|
|
# FIXME: Configurable
|
|
self.doc_limit = 20
|
|
|
|
self.de_client = DocumentEmbeddingsClient(
|
|
pulsar_host=pulsar_host,
|
|
subscriber=module + "-de",
|
|
input_queue=de_request_queue,
|
|
output_queue=de_response_queue,
|
|
)
|
|
|
|
self.embeddings = EmbeddingsClient(
|
|
pulsar_host=pulsar_host,
|
|
input_queue=emb_request_queue,
|
|
output_queue=emb_response_queue,
|
|
subscriber=module + "-emb",
|
|
)
|
|
|
|
self.lang = PromptClient(
|
|
pulsar_host=pulsar_host,
|
|
input_queue=pr_request_queue,
|
|
output_queue=pr_response_queue,
|
|
subscriber=module + "-de-prompt",
|
|
)
|
|
|
|
if self.verbose:
|
|
print("Initialised", flush=True)
|
|
|
|
def query(self, query, user="trustgraph", collection="default"):
|
|
|
|
if self.verbose:
|
|
print("Construct prompt...", flush=True)
|
|
|
|
q = Query(
|
|
rag=self, user=user, collection=collection, verbose=self.verbose
|
|
)
|
|
|
|
docs = q.get_docs(query)
|
|
|
|
if self.verbose:
|
|
print("Invoke LLM...", flush=True)
|
|
print(docs)
|
|
print(query)
|
|
|
|
resp = self.lang.request_document_prompt(query, docs)
|
|
|
|
if self.verbose:
|
|
print("Done", flush=True)
|
|
|
|
return resp
|
|
|