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Fix/sys integration issues (#494)

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* Fix integration issues

* Fix query defaults

* Fix tests
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cybermaggedon 2025-09-05 08:38:15 +01:00 • committed by GitHub
parent ed0e02791d
commit 50c37407c5
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6 changed files with 341 additions and 133 deletions
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42
trustgraph-flow/trustgraph/retrieval/nlp_query/service.py
View file

@ -122,7 +122,7 @@ class Processor(FlowProcessor):
logger.info(f"Schema configuration loaded: {len(self.schemas)} schemas")
async def phase1_select_schemas(self, question: str) -> List[str]:
async def phase1_select_schemas(self, question: str, flow) -> List[str]:
"""Phase 1: Use prompt service to select relevant schemas for the question"""
logger.info("Starting Phase 1: Schema selection")
@ -144,20 +144,27 @@ class Processor(FlowProcessor):
}
# Call prompt service for schema selection
# Convert variables to JSON-encoded terms
terms = {k: json.dumps(v) for k, v in variables.items()}
prompt_request = PromptRequest(
template=self.schema_selection_template,
variables=variables
id=self.schema_selection_template,
terms=terms
)
try:
response = await self.client("prompt-request").request(prompt_request)
response = await flow("prompt-request").request(prompt_request)
if response.error is not None:
raise Exception(f"Prompt service error: {response.error}")
# Parse the response to get selected schema names
# Expecting response.text to contain JSON array of schema names
selected_schemas = json.loads(response.text)
# Response could be in either text or object field
response_data = response.text if response.text else response.object
if response_data is None:
raise Exception("Prompt service returned empty response")
# Parse JSON array of schema names
selected_schemas = json.loads(response_data)
logger.info(f"Phase 1 selected schemas: {selected_schemas}")
return selected_schemas
@ -166,7 +173,7 @@ class Processor(FlowProcessor):
logger.error(f"Phase 1 schema selection failed: {e}")
raise
async def phase2_generate_graphql(self, question: str, selected_schemas: List[str]) -> Dict[str, Any]:
async def phase2_generate_graphql(self, question: str, selected_schemas: List[str], flow) -> Dict[str, Any]:
"""Phase 2: Generate GraphQL query using selected schemas"""
logger.info(f"Starting Phase 2: GraphQL generation for schemas: {selected_schemas}")
@ -200,20 +207,27 @@ class Processor(FlowProcessor):
}
# Call prompt service for GraphQL generation
# Convert variables to JSON-encoded terms
terms = {k: json.dumps(v) for k, v in variables.items()}
prompt_request = PromptRequest(
template=self.graphql_generation_template,
variables=variables
id=self.graphql_generation_template,
terms=terms
)
try:
response = await self.client("prompt-request").request(prompt_request)
response = await flow("prompt-request").request(prompt_request)
if response.error is not None:
raise Exception(f"Prompt service error: {response.error}")
# Parse the response to get GraphQL query and variables
# Expecting response.text to contain JSON with "query" and "variables" fields
result = json.loads(response.text)
# Response could be in either text or object field
response_data = response.text if response.text else response.object
if response_data is None:
raise Exception("Prompt service returned empty response")
# Parse JSON with "query" and "variables" fields
result = json.loads(response_data)
logger.info(f"Phase 2 generated GraphQL: {result.get('query', '')[:100]}...")
return result
@ -234,10 +248,10 @@ class Processor(FlowProcessor):
logger.info(f"Handling NLP query request {id}: {request.question[:100]}...")
# Phase 1: Select relevant schemas
selected_schemas = await self.phase1_select_schemas(request.question)
selected_schemas = await self.phase1_select_schemas(request.question, flow)
# Phase 2: Generate GraphQL query
graphql_result = await self.phase2_generate_graphql(request.question, selected_schemas)
graphql_result = await self.phase2_generate_graphql(request.question, selected_schemas, flow)
# Create response
response = QuestionToStructuredQueryResponse(

12
trustgraph-flow/trustgraph/retrieval/structured_query/service.py
View file

@ -87,7 +87,7 @@ class Processor(FlowProcessor):
max_results=100 # Default limit
)
nlp_response = await self.client("nlp-query-request").request(nlp_request)
nlp_response = await flow("nlp-query-request").request(nlp_request)
if nlp_response.error is not None:
raise Exception(f"NLP query service error: {nlp_response.error.message}")
@ -111,17 +111,17 @@ class Processor(FlowProcessor):
else:
variables_as_strings[key] = str(value)
# For now, we'll use default user/collection values
# In a real implementation, these would come from authentication/context
# Use standard TrustGraph user/collection values
# These should eventually come from authentication/context
objects_request = ObjectsQueryRequest(
user="default", # TODO: Get from authentication context
collection="default", # TODO: Get from request context
user="trustgraph", # Standard TrustGraph user
collection="default", # Standard default collection
query=nlp_response.graphql_query,
variables=variables_as_strings,
operation_name=None
)
objects_response = await self.client("objects-query-request").request(objects_request)
objects_response = await flow("objects-query-request").request(objects_request)
if objects_response.error is not None:
raise Exception(f"Objects query service error: {objects_response.error.message}")