mirror of
https://github.com/langgenius/dify.git
synced 2026-05-01 16:08:04 +08:00
feat: new instruction-generate with new LLMGenerator
Signed-off-by: Stream <Stream_2@qq.com>
This commit is contained in:
Stream
@ -1,5 +1,3 @@
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from collections.abc import Sequence
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from flask_restx import Resource, fields, reqparse
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from controllers.console import api, console_ns
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@ -11,13 +9,9 @@ from controllers.console.app.error import (
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)
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from controllers.console.wraps import account_initialization_required, setup_required
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from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
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from core.helper.code_executor.javascript.javascript_code_provider import JavascriptCodeProvider
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from core.helper.code_executor.python3.python3_code_provider import Python3CodeProvider
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from core.llm_generator.llm_generator import LLMGenerator
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from core.model_runtime.errors.invoke import InvokeError
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from extensions.ext_database import db
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from libs.login import current_account_with_tenant, login_required
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from models import App
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from services.workflow_service import WorkflowService
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@ -177,11 +171,29 @@ class InstructionGenerateApi(Resource):
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api.model(
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"InstructionGenerateRequest",
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{
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"flow_id": fields.String(required=True, description="Workflow/Flow ID"),
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"node_id": fields.String(description="Node ID for workflow context"),
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"current": fields.String(description="Current instruction text"),
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"language": fields.String(default="javascript", description="Programming language (javascript/python)"),
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"instruction": fields.String(required=True, description="Instruction for generation"),
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"type": fields.String(
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required=True,
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description="Request type",
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enum=[
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"legacy_prompt_generate",
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"workflow_prompt_generate",
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"workflow_code_generate",
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"workflow_prompt_edit",
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"workflow_code_edit",
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"memory_template_generate",
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"memory_instruction_generate",
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"memory_template_edit",
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"memory_instruction_edit",
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]
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),
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"flow_id": fields.String(description="Workflow/Flow ID"),
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"node_id": fields.String(description="Node ID (optional)"),
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"current": fields.String(description="Current content"),
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"language": fields.String(
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default="javascript",
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description="Programming language (javascript/python)"
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),
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"instruction": fields.String(required=True, description="User instruction"),
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"model_config": fields.Raw(required=True, description="Model configuration"),
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"ideal_output": fields.String(description="Expected ideal output"),
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},
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@ -196,7 +208,8 @@ class InstructionGenerateApi(Resource):
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def post(self):
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parser = (
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reqparse.RequestParser()
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.add_argument("flow_id", type=str, required=True, default="", location="json")
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.add_argument("type", type=str, required=True, nullable=False, location="json")
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.add_argument("flow_id", type=str, required=False, default="", location="json")
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.add_argument("node_id", type=str, required=False, default="", location="json")
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.add_argument("current", type=str, required=False, default="", location="json")
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.add_argument("language", type=str, required=False, default="javascript", location="json")
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@ -206,72 +219,16 @@ class InstructionGenerateApi(Resource):
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)
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args = parser.parse_args()
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_, current_tenant_id = current_account_with_tenant()
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code_template = (
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Python3CodeProvider.get_default_code()
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if args["language"] == "python"
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else (JavascriptCodeProvider.get_default_code())
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if args["language"] == "javascript"
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else ""
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)
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try:
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# Generate from nothing for a workflow node
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if (args["current"] == code_template or args["current"] == "") and args["node_id"] != "":
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app = db.session.query(App).where(App.id == args["flow_id"]).first()
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if not app:
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return {"error": f"app {args['flow_id']} not found"}, 400
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workflow = WorkflowService().get_draft_workflow(app_model=app)
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if not workflow:
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return {"error": f"workflow {args['flow_id']} not found"}, 400
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nodes: Sequence = workflow.graph_dict["nodes"]
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node = [node for node in nodes if node["id"] == args["node_id"]]
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if len(node) == 0:
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return {"error": f"node {args['node_id']} not found"}, 400
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node_type = node[0]["data"]["type"]
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match node_type:
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case "llm":
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return LLMGenerator.generate_rule_config(
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current_tenant_id,
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instruction=args["instruction"],
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model_config=args["model_config"],
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no_variable=True,
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)
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case "agent":
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return LLMGenerator.generate_rule_config(
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current_tenant_id,
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instruction=args["instruction"],
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model_config=args["model_config"],
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no_variable=True,
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)
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case "code":
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return LLMGenerator.generate_code(
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tenant_id=current_tenant_id,
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instruction=args["instruction"],
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model_config=args["model_config"],
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code_language=args["language"],
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)
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case _:
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return {"error": f"invalid node type: {node_type}"}
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if args["node_id"] == "" and args["current"] != "": # For legacy app without a workflow
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return LLMGenerator.instruction_modify_legacy(
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tenant_id=current_tenant_id,
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flow_id=args["flow_id"],
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current=args["current"],
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instruction=args["instruction"],
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model_config=args["model_config"],
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ideal_output=args["ideal_output"],
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)
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if args["node_id"] != "" and args["current"] != "": # For workflow node
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return LLMGenerator.instruction_modify_workflow(
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tenant_id=current_tenant_id,
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flow_id=args["flow_id"],
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node_id=args["node_id"],
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current=args["current"],
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instruction=args["instruction"],
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model_config=args["model_config"],
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ideal_output=args["ideal_output"],
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workflow_service=WorkflowService(),
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)
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return {"error": "incompatible parameters"}, 400
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# Validate parameters
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is_valid, error_message = self._validate_params(args["type"], args)
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if not is_valid:
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return {"error": error_message}, 400
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# Route based on type
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return self._handle_by_type(args["type"], args, current_tenant_id)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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except QuotaExceededError:
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@ -281,6 +238,131 @@ class InstructionGenerateApi(Resource):
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except InvokeError as e:
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raise CompletionRequestError(e.description)
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def _validate_params(self, request_type: str, args: dict) -> tuple[bool, str]:
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"""
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Validate request parameters
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Returns:
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(is_valid, error_message)
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"""
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# All types require instruction and model_config
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if not args.get("instruction"):
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return False, "instruction is required"
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if not args.get("model_config"):
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return False, "model_config is required"
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# Edit types require flow_id and current
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if request_type.endswith("_edit"):
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if not args.get("flow_id"):
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return False, f"{request_type} requires flow_id"
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if not args.get("current"):
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return False, f"{request_type} requires current content"
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# Code generate requires language
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if request_type == "workflow_code_generate":
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if args.get("language") not in ["python", "javascript"]:
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return False, "language must be 'python' or 'javascript'"
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return True, ""
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def _handle_by_type(self, request_type: str, args: dict, tenant_id: str):
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"""
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Route handling based on type
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"""
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match request_type:
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case "legacy_prompt_generate":
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# Legacy prompt generation doesn't exist, this is actually an edit
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if not args.get("flow_id"):
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return {"error": "legacy_prompt_generate requires flow_id"}, 400
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return LLMGenerator.instruction_modify_legacy(
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tenant_id=tenant_id,
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flow_id=args["flow_id"],
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current=args["current"],
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instruction=args["instruction"],
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model_config=args["model_config"],
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ideal_output=args["ideal_output"],
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)
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case "workflow_prompt_generate":
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return LLMGenerator.generate_rule_config(
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tenant_id,
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instruction=args["instruction"],
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model_config=args["model_config"],
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no_variable=True,
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)
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case "workflow_code_generate":
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return LLMGenerator.generate_code(
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tenant_id=tenant_id,
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instruction=args["instruction"],
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model_config=args["model_config"],
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code_language=args["language"],
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)
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case "workflow_prompt_edit":
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return LLMGenerator.instruction_modify_workflow(
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tenant_id=tenant_id,
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flow_id=args["flow_id"],
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node_id=args["node_id"],
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current=args["current"],
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instruction=args["instruction"],
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model_config=args["model_config"],
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ideal_output=args["ideal_output"],
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workflow_service=WorkflowService(),
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)
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case "workflow_code_edit":
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# Code edit uses the same workflow edit logic
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return LLMGenerator.instruction_modify_workflow(
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tenant_id=tenant_id,
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flow_id=args["flow_id"],
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node_id=args["node_id"],
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current=args["current"],
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instruction=args["instruction"],
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model_config=args["model_config"],
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ideal_output=args["ideal_output"],
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workflow_service=WorkflowService(),
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)
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case "memory_template_generate":
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return LLMGenerator.generate_memory_template(
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tenant_id=tenant_id,
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instruction=args["instruction"],
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model_config=args["model_config"],
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)
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case "memory_instruction_generate":
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return LLMGenerator.generate_memory_instruction(
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tenant_id=tenant_id,
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instruction=args["instruction"],
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model_config=args["model_config"],
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)
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case "memory_template_edit":
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return LLMGenerator.edit_memory_template(
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tenant_id=tenant_id,
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flow_id=args["flow_id"],
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node_id=args.get("node_id") or None,
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current=args["current"],
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instruction=args["instruction"],
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model_config=args["model_config"],
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ideal_output=args["ideal_output"],
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)
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case "memory_instruction_edit":
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return LLMGenerator.edit_memory_instruction(
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tenant_id=tenant_id,
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flow_id=args["flow_id"],
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node_id=args.get("node_id") or None,
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current=args["current"],
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instruction=args["instruction"],
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model_config=args["model_config"],
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ideal_output=args["ideal_output"],
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)
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case _:
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return {"error": f"Invalid request type: {request_type}"}, 400
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@console_ns.route("/instruction-generate/template")
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class InstructionGenerationTemplateApi(Resource):
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