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- RAG Specialist fully implemented new style

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- Selection Specialist - VA version - fully implemented
- Correction of TRAICIE_ROLE_DEFINITION_SPECIALIST - adaptation to new style
- Removal of 'debug' statements
This commit is contained in:
Josako
2025-07-10 10:39:42 +02:00
parent 509ee95d81
commit 51fd16bcc6
40 changed files with 110 additions and 298 deletions
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7
eveai_chat_workers/specialists/globals/RAG_SPECIALIST/1_0.py
View File

@@ -69,18 +69,12 @@ class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
def execute(self, arguments: SpecialistArguments, formatted_context, citations) -> SpecialistResult:
self.log_tuning("RAG Specialist execution started", {})
current_app.logger.debug(f"Arguments: {arguments.model_dump()}")
current_app.logger.debug(f"Formatted Context: {formatted_context}")
current_app.logger.debug(f"Formatted History: {self._formatted_history}")
current_app.logger.debug(f"Cached Chat Session: {self._cached_session}")
if not self._cached_session.interactions:
specialist_phase = "initial"
else:
specialist_phase = self._cached_session.interactions[-1].specialist_results.get('phase', 'initial')
results = None
current_app.logger.debug(f"Specialist Phase: {specialist_phase}")
match specialist_phase:
case "initial":
@@ -191,7 +185,6 @@ class RAGFlow(EveAICrewAIFlow[RAGFlowState]):
raise e
async def kickoff_async(self, inputs=None):
current_app.logger.debug(f"Async kickoff {self.name}")
self.state.input = RAGSpecialistInput.model_validate(inputs)
result = await super().kickoff_async(inputs)
return self.state

18
eveai_chat_workers/specialists/globals/RAG_SPECIALIST/1_1.py
View File

@@ -1,6 +1,6 @@
import json
from os import wait
from typing import Optional, List
from typing import Optional, List, Dict, Any
from crewai.flow.flow import start, listen, and_
from flask import current_app
@@ -47,6 +47,7 @@ class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
def _config_state_result_relations(self):
self._add_state_result_relation("rag_output")
self._add_state_result_relation("citations")
def _instantiate_specialist(self):
verbose = self.tuning
@@ -69,18 +70,12 @@ class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
def execute(self, arguments: SpecialistArguments, formatted_context, citations) -> SpecialistResult:
self.log_tuning("RAG Specialist execution started", {})
current_app.logger.debug(f"Arguments: {arguments.model_dump()}")
current_app.logger.debug(f"Formatted Context: {formatted_context}")
current_app.logger.debug(f"Formatted History: {self._formatted_history}")
current_app.logger.debug(f"Cached Chat Session: {self._cached_session}")
if not self._cached_session.interactions:
specialist_phase = "initial"
else:
specialist_phase = self._cached_session.interactions[-1].specialist_results.get('phase', 'initial')
results = None
current_app.logger.debug(f"Specialist Phase: {specialist_phase}")
match specialist_phase:
case "initial":
@@ -112,6 +107,8 @@ class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
INSUFFICIENT_INFORMATION_MESSAGE,
arguments.language)
formatted_context, citations = self._retrieve_context(arguments)
if formatted_context:
flow_inputs = {
"language": arguments.language,
@@ -128,16 +125,18 @@ class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
flow_results.rag_output.answer = insufficient_info_message
rag_output = flow_results.rag_output
else:
rag_output = RAGOutput(answer=insufficient_info_message, insufficient_info=True)
self.flow.state.rag_output = rag_output
self.flow.state.citations = citations
self.flow.state.answer = rag_output.answer
self.flow.state.phase = "rag"
results = RAGSpecialistResult.create_for_type(self.type, self.type_version)
return results
class RAGSpecialistInput(BaseModel):
language: Optional[str] = Field(None, alias="language")
@@ -156,6 +155,7 @@ class RAGFlowState(EveAIFlowState):
"""Flow state for RAG specialist that automatically updates from task outputs"""
input: Optional[RAGSpecialistInput] = None
rag_output: Optional[RAGOutput] = None
citations: Optional[List[Dict[str, Any]]] = None
class RAGFlow(EveAICrewAIFlow[RAGFlowState]):
@@ -190,8 +190,6 @@ class RAGFlow(EveAICrewAIFlow[RAGFlowState]):
raise e
async def kickoff_async(self, inputs=None):
current_app.logger.debug(f"Async kickoff {self.name}")
current_app.logger.debug(f"Inputs: {inputs}")
self.state.input = RAGSpecialistInput.model_validate(inputs)
result = await super().kickoff_async(inputs)
return self.state

6
eveai_chat_workers/specialists/globals/SPIN_SPECIALIST/1_0.py
View File

@@ -216,9 +216,7 @@ class SPINFlow(EveAICrewAIFlow[SPINFlowState]):
async def execute_rag(self):
inputs = self.state.input.model_dump()
try:
current_app.logger.debug("In execute_rag")
crew_output = await self.rag_crew.kickoff_async(inputs=inputs)
current_app.logger.debug(f"Crew execution ended with output:\n{crew_output}")
self.specialist_executor.log_tuning("RAG Crew Output", crew_output.model_dump())
output_pydantic = crew_output.pydantic
if not output_pydantic:
@@ -277,11 +275,8 @@ class SPINFlow(EveAICrewAIFlow[SPINFlowState]):
if self.state.spin:
additional_questions = additional_questions + self.state.spin.questions
inputs["additional_questions"] = additional_questions
current_app.logger.debug(f"Prepared Answers: \n{inputs['prepared_answers']}")
current_app.logger.debug(f"Additional Questions: \n{additional_questions}")
try:
crew_output = await self.rag_consolidation_crew.kickoff_async(inputs=inputs)
current_app.logger.debug(f"Consolidation output after crew execution:\n{crew_output}")
self.specialist_executor.log_tuning("RAG Consolidation Crew Output", crew_output.model_dump())
output_pydantic = crew_output.pydantic
if not output_pydantic:
@@ -295,7 +290,6 @@ class SPINFlow(EveAICrewAIFlow[SPINFlowState]):
raise e
async def kickoff_async(self, inputs=None):
current_app.logger.debug(f"Async kickoff {self.name}")
self.state.input = SPINSpecialistInput.model_validate(inputs)
result = await super().kickoff_async(inputs)
return self.state