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Embeddings API scores (#671)

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- Put scores in all responses
- Remove unused 'middle' vector layer. Vector of texts -> vector of (vector embedding)
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cybermaggedon 2026-03-09 10:53:44 +00:00 • committed by GitHub
parent 4fa7cc7d7c
commit f2ae0e8623
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65 changed files with 1339 additions and 1292 deletions
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55
trustgraph-base/trustgraph/messaging/translators/embeddings_query.py
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@ -10,18 +10,18 @@ from .primitives import ValueTranslator
class DocumentEmbeddingsRequestTranslator(MessageTranslator):
"""Translator for DocumentEmbeddingsRequest schema objects"""
def to_pulsar(self, data: Dict[str, Any]) -> DocumentEmbeddingsRequest:
return DocumentEmbeddingsRequest(
vectors=data["vectors"],
vector=data["vector"],
limit=int(data.get("limit", 10)),
user=data.get("user", "trustgraph"),
collection=data.get("collection", "default")
)
def from_pulsar(self, obj: DocumentEmbeddingsRequest) -> Dict[str, Any]:
return {
"vectors": obj.vectors,
"vector": obj.vector,
"limit": obj.limit,
"user": obj.user,
"collection": obj.collection
@ -30,18 +30,24 @@ class DocumentEmbeddingsRequestTranslator(MessageTranslator):
class DocumentEmbeddingsResponseTranslator(MessageTranslator):
"""Translator for DocumentEmbeddingsResponse schema objects"""
def to_pulsar(self, data: Dict[str, Any]) -> DocumentEmbeddingsResponse:
raise NotImplementedError("Response translation to Pulsar not typically needed")
def from_pulsar(self, obj: DocumentEmbeddingsResponse) -> Dict[str, Any]:
result = {}
if obj.chunk_ids is not None:
result["chunk_ids"] = list(obj.chunk_ids)
if obj.chunks is not None:
result["chunks"] = [
{
"chunk_id": chunk.chunk_id,
"score": chunk.score
}
for chunk in obj.chunks
]
return result
def from_response_with_completion(self, obj: DocumentEmbeddingsResponse) -> Tuple[Dict[str, Any], bool]:
"""Returns (response_dict, is_final)"""
return self.from_pulsar(obj), True
@ -49,18 +55,18 @@ class DocumentEmbeddingsResponseTranslator(MessageTranslator):
class GraphEmbeddingsRequestTranslator(MessageTranslator):
"""Translator for GraphEmbeddingsRequest schema objects"""
def to_pulsar(self, data: Dict[str, Any]) -> GraphEmbeddingsRequest:
return GraphEmbeddingsRequest(
vectors=data["vectors"],
vector=data["vector"],
limit=int(data.get("limit", 10)),
user=data.get("user", "trustgraph"),
collection=data.get("collection", "default")
)
def from_pulsar(self, obj: GraphEmbeddingsRequest) -> Dict[str, Any]:
return {
"vectors": obj.vectors,
"vector": obj.vector,
"limit": obj.limit,
"user": obj.user,
"collection": obj.collection
@ -69,24 +75,27 @@ class GraphEmbeddingsRequestTranslator(MessageTranslator):
class GraphEmbeddingsResponseTranslator(MessageTranslator):
"""Translator for GraphEmbeddingsResponse schema objects"""
def __init__(self):
self.value_translator = ValueTranslator()
def to_pulsar(self, data: Dict[str, Any]) -> GraphEmbeddingsResponse:
raise NotImplementedError("Response translation to Pulsar not typically needed")
def from_pulsar(self, obj: GraphEmbeddingsResponse) -> Dict[str, Any]:
result = {}
if obj.entities is not None:
result["entities"] = [
self.value_translator.from_pulsar(entity)
for entity in obj.entities
{
"entity": self.value_translator.from_pulsar(match.entity),
"score": match.score
}
for match in obj.entities
]
return result
def from_response_with_completion(self, obj: GraphEmbeddingsResponse) -> Tuple[Dict[str, Any], bool]:
"""Returns (response_dict, is_final)"""
return self.from_pulsar(obj), True
@ -97,7 +106,7 @@ class RowEmbeddingsRequestTranslator(MessageTranslator):
def to_pulsar(self, data: Dict[str, Any]) -> RowEmbeddingsRequest:
return RowEmbeddingsRequest(
vectors=data["vectors"],
vector=data["vector"],
limit=int(data.get("limit", 10)),
user=data.get("user", "trustgraph"),
collection=data.get("collection", "default"),
@ -107,7 +116,7 @@ class RowEmbeddingsRequestTranslator(MessageTranslator):
def from_pulsar(self, obj: RowEmbeddingsRequest) -> Dict[str, Any]:
result = {
"vectors": obj.vectors,
"vector": obj.vector,
"limit": obj.limit,
"user": obj.user,
"collection": obj.collection,