trustgraph/trustgraph-cli/trustgraph/cli/invoke_document_rag.py

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"""
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Uses the DocumentRAG service to answer a question
"""
import argparse
import os
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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import sys
from trustgraph.api import (
Api,
ExplainabilityClient,
RAGChunk,
ProvenanceEvent,
Question,
Grounding,
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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Exploration,
Synthesis,
)
default_url = os.getenv("TRUSTGRAPH_URL", 'http://localhost:8088/')
default_token = os.getenv("TRUSTGRAPH_TOKEN", None)
default_user = 'trustgraph'
default_collection = 'default'
default_doc_limit = 10
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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def question_explainable(
url, flow_id, question_text, user, collection, doc_limit, token=None, debug=False
):
"""Execute document RAG with explainability - shows provenance events inline."""
api = Api(url=url, token=token)
socket = api.socket()
flow = socket.flow(flow_id)
explain_client = ExplainabilityClient(flow, retry_delay=0.2, max_retries=10)
try:
# Stream DocumentRAG with explainability - process events as they arrive
for item in flow.document_rag_explain(
query=question_text,
user=user,
collection=collection,
doc_limit=doc_limit,
):
if isinstance(item, RAGChunk):
# Print response content
print(item.content, end="", flush=True)
elif isinstance(item, ProvenanceEvent):
# Process provenance event immediately
prov_id = item.explain_id
explain_graph = item.explain_graph or "urn:graph:retrieval"
entity = explain_client.fetch_entity(
prov_id,
graph=explain_graph,
user=user,
collection=collection
)
if entity is None:
if debug:
print(f"\n [warning] Could not fetch entity: {prov_id}", file=sys.stderr)
continue
# Display based on entity type
if isinstance(entity, Question):
print(f"\n [question] {prov_id}", file=sys.stderr)
if entity.query:
print(f" Query: {entity.query}", file=sys.stderr)
if entity.timestamp:
print(f" Time: {entity.timestamp}", file=sys.stderr)
elif isinstance(entity, Grounding):
print(f"\n [grounding] {prov_id}", file=sys.stderr)
if entity.concepts:
for concept in entity.concepts:
print(f" Concept: {concept}", file=sys.stderr)
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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elif isinstance(entity, Exploration):
print(f"\n [exploration] {prov_id}", file=sys.stderr)
if entity.chunk_count:
print(f" Chunks retrieved: {entity.chunk_count}", file=sys.stderr)
elif isinstance(entity, Synthesis):
print(f"\n [synthesis] {prov_id}", file=sys.stderr)
if entity.document:
print(f" Document: {entity.document}", file=sys.stderr)
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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else:
if debug:
print(f"\n [unknown] {prov_id} (type: {entity.entity_type})", file=sys.stderr)
print() # Final newline
finally:
socket.close()
def question(
url, flow_id, question_text, user, collection, doc_limit,
streaming=True, token=None, explainable=False, debug=False
):
# Explainable mode uses the API to capture and process provenance events
if explainable:
question_explainable(
url=url,
flow_id=flow_id,
question_text=question_text,
user=user,
collection=collection,
doc_limit=doc_limit,
token=token,
debug=debug
)
return
# Create API client
api = Api(url=url, token=token)
if streaming:
# Use socket client for streaming
socket = api.socket()
flow = socket.flow(flow_id)
try:
response = flow.document_rag(
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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query=question_text,
user=user,
collection=collection,
doc_limit=doc_limit,
streaming=True
)
# Stream output
for chunk in response:
print(chunk, end="", flush=True)
print() # Final newline
finally:
socket.close()
else:
# Use REST API for non-streaming
flow = api.flow().id(flow_id)
resp = flow.document_rag(
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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query=question_text,
user=user,
collection=collection,
doc_limit=doc_limit,
)
print(resp)
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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def main():
parser = argparse.ArgumentParser(
prog='tg-invoke-document-rag',
description=__doc__,
)
parser.add_argument(
'-u', '--url',
default=default_url,
help=f'API URL (default: {default_url})',
)
parser.add_argument(
'-t', '--token',
default=default_token,
help='Authentication token (default: $TRUSTGRAPH_TOKEN)',
)
parser.add_argument(
'-f', '--flow-id',
default="default",
help=f'Flow ID (default: default)'
)
parser.add_argument(
'-q', '--question',
required=True,
help=f'Question to answer',
)
parser.add_argument(
'-U', '--user',
default=default_user,
help=f'User ID (default: {default_user})'
)
parser.add_argument(
'-C', '--collection',
default=default_collection,
help=f'Collection ID (default: {default_collection})'
)
parser.add_argument(
'-d', '--doc-limit',
type=int,
default=default_doc_limit,
help=f'Document limit (default: {default_doc_limit})'
)
parser.add_argument(
'--no-streaming',
action='store_true',
help='Disable streaming (use non-streaming mode)'
)
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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parser.add_argument(
'-x', '--explainable',
action='store_true',
help='Show provenance events: Question, Exploration, Synthesis (implies streaming)'
)
parser.add_argument(
'--debug',
action='store_true',
help='Show debug output for troubleshooting'
)
args = parser.parse_args()
try:
question(
url=args.url,
flow_id=args.flow_id,
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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question_text=args.question,
user=args.user,
collection=args.collection,
doc_limit=args.doc_limit,
streaming=not args.no_streaming,
token=args.token,
Add unified explainability support and librarian storage for (#693) Add unified explainability support and librarian storage for all retrieval engines Implements consistent explainability/provenance tracking across GraphRAG, DocumentRAG, and Agent retrieval engines. All large content (answers, thoughts, observations) is now stored in librarian rather than as inline literals in the knowledge graph. Explainability API: - New explainability.py module with entity classes (Question, Exploration, Focus, Synthesis, Analysis, Conclusion) and ExplainabilityClient - Quiescence-based eventual consistency handling for trace fetching - Content fetching from librarian with retry logic CLI updates: - tg-invoke-graph-rag -x/--explainable flag returns explain_id - tg-invoke-document-rag -x/--explainable flag returns explain_id - tg-invoke-agent -x/--explainable flag returns explain_id - tg-list-explain-traces uses new explainability API - tg-show-explain-trace handles all three trace types Agent provenance: - Records session, iterations (think/act/observe), and conclusion - Stores thoughts and observations in librarian with document references - New predicates: tg:thoughtDocument, tg:observationDocument DocumentRAG provenance: - Records question, exploration (chunk retrieval), and synthesis - Stores answers in librarian with document references Schema changes: - AgentResponse: added explain_id, explain_graph fields - RetrievalResponse: added explain_id, explain_graph fields - agent_iteration_triples: supports thought_document_id, observation_document_id Update tests.
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explainable=args.explainable,
debug=args.debug,
)
except Exception as e:
print("Exception:", e, flush=True)
if __name__ == "__main__":
main()