Merge branch 'feat/queue-based-graph-engine' into feat/rag-2

api/core/llm_generator/llm_generator.py

@@ -129,7 +129,7 @@ class LLMGenerator:
         return questions
 
     @classmethod
-    def generate_rule_config(cls, tenant_id: str, instruction: str, model_config: dict, no_variable: bool) -> dict:
+    def generate_rule_config(cls, tenant_id: str, instruction: str, model_config: dict, no_variable: bool):
         output_parser = RuleConfigGeneratorOutputParser()
 
         error = ""
@@ -264,9 +264,7 @@ class LLMGenerator:
         return rule_config
 
     @classmethod
-    def generate_code(
-        cls, tenant_id: str, instruction: str, model_config: dict, code_language: str = "javascript"
-    ) -> dict:
+    def generate_code(cls, tenant_id: str, instruction: str, model_config: dict, code_language: str = "javascript"):
         if code_language == "python":
             prompt_template = PromptTemplateParser(PYTHON_CODE_GENERATOR_PROMPT_TEMPLATE)
         else:
@@ -375,7 +373,7 @@ class LLMGenerator:
     @staticmethod
     def instruction_modify_legacy(
         tenant_id: str, flow_id: str, current: str, instruction: str, model_config: dict, ideal_output: str | None
-    ) -> dict:
+    ):
         last_run: Message | None = (
             db.session.query(Message).where(Message.app_id == flow_id).order_by(Message.created_at.desc()).first()
         )
@@ -415,7 +413,7 @@ class LLMGenerator:
         instruction: str,
         model_config: dict,
         ideal_output: str | None,
-    ) -> dict:
+    ):
         from services.workflow_service import WorkflowService
 
         session = db.session()
@@ -455,7 +453,7 @@ class LLMGenerator:
                 return []
             parsed: Sequence[AgentLogEvent] = json.loads(raw_agent_log)
 
-            def dict_of_event(event: AgentLogEvent) -> dict:
+            def dict_of_event(event: AgentLogEvent):
                 return {
                     "status": event.status,
                     "error": event.error,
@@ -493,7 +491,7 @@ class LLMGenerator:
         instruction: str,
         node_type: str,
         ideal_output: str | None,
-    ) -> dict:
+    ):
         LAST_RUN = "{{#last_run#}}"
         CURRENT = "{{#current#}}"
         ERROR_MESSAGE = "{{#error_message#}}"

api/core/llm_generator/output_parser/rule_config_generator.py

@@ -1,5 +1,3 @@
-from typing import Any
-
 from core.llm_generator.output_parser.errors import OutputParserError
 from core.llm_generator.prompts import (
     RULE_CONFIG_PARAMETER_GENERATE_TEMPLATE,
@@ -17,7 +15,7 @@ class RuleConfigGeneratorOutputParser:
             RULE_CONFIG_STATEMENT_GENERATE_TEMPLATE,
         )
 
-    def parse(self, text: str) -> Any:
+    def parse(self, text: str):
         try:
             expected_keys = ["prompt", "variables", "opening_statement"]
             parsed = parse_and_check_json_markdown(text, expected_keys)

api/core/llm_generator/output_parser/structured_output.py

@@ -210,7 +210,7 @@ def _handle_native_json_schema(
     structured_output_schema: Mapping,
     model_parameters: dict,
     rules: list[ParameterRule],
-) -> dict:
+):
     """
     Handle structured output for models with native JSON schema support.
 
@@ -232,7 +232,7 @@ def _handle_native_json_schema(
     return model_parameters
 
 
-def _set_response_format(model_parameters: dict, rules: list) -> None:
+def _set_response_format(model_parameters: dict, rules: list):
     """
     Set the appropriate response format parameter based on model rules.
 
@@ -306,7 +306,7 @@ def _parse_structured_output(result_text: str) -> Mapping[str, Any]:
     return structured_output
 
 
-def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema: Mapping) -> dict:
+def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema: Mapping):
     """
     Prepare JSON schema based on model requirements.
 
@@ -334,7 +334,7 @@ def _prepare_schema_for_model(provider: str, model_schema: AIModelEntity, schema
         return {"schema": processed_schema, "name": "llm_response"}
 
 
-def remove_additional_properties(schema: dict) -> None:
+def remove_additional_properties(schema: dict):
     """
     Remove additionalProperties fields from JSON schema.
     Used for models like Gemini that don't support this property.
@@ -357,7 +357,7 @@ def remove_additional_properties(schema: dict) -> None:
                     remove_additional_properties(item)
 
 
-def convert_boolean_to_string(schema: dict) -> None:
+def convert_boolean_to_string(schema: dict):
     """
     Convert boolean type specifications to string in JSON schema.
 

api/core/llm_generator/output_parser/suggested_questions_after_answer.py

@@ -1,6 +1,5 @@
 import json
 import re
-from typing import Any
 
 from core.llm_generator.prompts import SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT
 
@@ -9,7 +8,7 @@ class SuggestedQuestionsAfterAnswerOutputParser:
     def get_format_instructions(self) -> str:
         return SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT
 
-    def parse(self, text: str) -> Any:
+    def parse(self, text: str):
         action_match = re.search(r"\[.*?\]", text.strip(), re.DOTALL)
         if action_match is not None:
             json_obj = json.loads(action_match.group(0).strip())