aljaz/enclava
1
0
Fork 0
mirror of https://github.com/aljazceru/enclava.git synced 2025-12-18 07:54:29 +01:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'main' into redoing-things

Browse Source
This commit is contained in:
Aljaz
2025-10-02 10:54:36 +02:00
committed by GitHub
parent 8391dd5170 745a72aedb
commit 072c28d67f
79 changed files with 3103 additions and 4700 deletions
Download Patch File Download Diff File Expand all files Collapse all files

82
backend/app/services/llm/service.py
View File

@@ -17,6 +17,7 @@ from .models import (
)
from .config import config_manager, ProviderConfig
from ...core.config import settings
from .resilience import ResilienceManagerFactory
# from .metrics import metrics_collector
from .providers import BaseLLMProvider, PrivateModeProvider
@@ -149,7 +150,6 @@ class LLMService:
if not request.messages:
raise ValidationError("Messages cannot be empty", field="messages")
# Security validation disabled - always allow requests
risk_score = 0.0
# Get provider for model
@@ -159,7 +159,6 @@ class LLMService:
if not provider:
raise ProviderError(f"No available provider for model '{request.model}'", provider=provider_name)
# Security logging disabled
# Execute with resilience
resilience_manager = ResilienceManagerFactory.get_manager(provider_name)
@@ -170,28 +169,15 @@ class LLMService:
provider.create_chat_completion,
request,
retryable_exceptions=(ProviderError, TimeoutError),
non_retryable_exceptions=(SecurityError, ValidationError)
non_retryable_exceptions=(ValidationError,)
)
# Security features disabled
# Security logging disabled
# Record successful request - metrics disabled
total_latency = (time.time() - start_time) * 1000
# metrics_collector.record_request(
# provider=provider_name,
# model=request.model,
# request_type="chat_completion",
# success=True,
# latency_ms=total_latency,
# token_usage=response.usage.model_dump() if response.usage else None,
# security_risk_score=risk_score,
# user_id=request.user_id,
# api_key_id=request.api_key_id
# )
# Security audit logging disabled
return response
@@ -200,19 +186,6 @@ class LLMService:
total_latency = (time.time() - start_time) * 1000
error_code = getattr(e, 'error_code', e.__class__.__name__)
# metrics_collector.record_request(
# provider=provider_name,
# model=request.model,
# request_type="chat_completion",
# success=False,
# latency_ms=total_latency,
# security_risk_score=risk_score,
# error_code=error_code,
# user_id=request.user_id,
# api_key_id=request.api_key_id
# )
# Security audit logging disabled
raise
@@ -223,6 +196,7 @@ class LLMService:
# Security validation disabled - always allow streaming requests
risk_score = 0.0
# Get provider
provider_name = self._get_provider_for_model(request.model)
@@ -239,24 +213,13 @@ class LLMService:
provider.create_chat_completion_stream,
request,
retryable_exceptions=(ProviderError, TimeoutError),
non_retryable_exceptions=(SecurityError, ValidationError)
non_retryable_exceptions=(ValidationError,)
):
yield chunk
except Exception as e:
# Record streaming failure - metrics disabled
error_code = getattr(e, 'error_code', e.__class__.__name__)
# metrics_collector.record_request(
# provider=provider_name,
# model=request.model,
# request_type="chat_completion_stream",
# success=False,
# latency_ms=0,
# security_risk_score=risk_score,
# error_code=error_code,
# user_id=request.user_id,
# api_key_id=request.api_key_id
# )
raise
async def create_embedding(self, request: EmbeddingRequest) -> EmbeddingResponse:
@@ -266,6 +229,7 @@ class LLMService:
# Security validation disabled - always allow embedding requests
risk_score = 0.0
# Get provider
provider_name = self._get_provider_for_model(request.model)
@@ -283,44 +247,20 @@ class LLMService:
provider.create_embedding,
request,
retryable_exceptions=(ProviderError, TimeoutError),
non_retryable_exceptions=(SecurityError, ValidationError)
non_retryable_exceptions=(ValidationError,)
)
# Security features disabled
# Record successful request - metrics disabled
total_latency = (time.time() - start_time) * 1000
# metrics_collector.record_request(
# provider=provider_name,
# model=request.model,
# request_type="embedding",
# success=True,
# latency_ms=total_latency,
# token_usage=response.usage.model_dump() if response.usage else None,
# security_risk_score=risk_score,
# user_id=request.user_id,
# api_key_id=request.api_key_id
# )
return response
except Exception as e:
# Record failed request - metrics disabled
total_latency = (time.time() - start_time) * 1000
error_code = getattr(e, 'error_code', e.__class__.__name__)
# metrics_collector.record_request(
# provider=provider_name,
# model=request.model,
# request_type="embedding",
# success=False,
# latency_ms=total_latency,
# security_risk_score=risk_score,
# error_code=error_code,
# user_id=request.user_id,
# api_key_id=request.api_key_id
# )
error_code = getattr(e, 'error_code', e.__class__.__name__)
raise
async def get_models(self, provider_name: Optional[str] = None) -> List[ModelInfo]: