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gcgj-dify-1.7.0/api/controllers/console/app/generator.py

195 lines
8.8 KiB
Python

import os
from collections.abc import Sequence
from flask_login import current_user
from flask_restful import Resource, reqparse
from opik.rest_api import BadRequestError
from controllers.console import api
from controllers.console.app.error import (
CompletionRequestError,
ProviderModelCurrentlyNotSupportError,
ProviderNotInitializeError,
ProviderQuotaExceededError,
)
from controllers.console.wraps import account_initialization_required, setup_required
from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
from core.llm_generator.llm_generator import LLMGenerator
from core.model_runtime.errors.invoke import InvokeError
from libs.login import login_required
class RuleGenerateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument("instruction", type=str, required=True, nullable=False, location="json")
parser.add_argument("model_config", type=dict, required=True, nullable=False, location="json")
parser.add_argument("no_variable", type=bool, required=True, default=False, location="json")
args = parser.parse_args()
account = current_user
PROMPT_GENERATION_MAX_TOKENS = int(os.getenv("PROMPT_GENERATION_MAX_TOKENS", "512"))
try:
rules = LLMGenerator.generate_rule_config(
tenant_id=account.current_tenant_id,
instruction=args["instruction"],
model_config=args["model_config"],
no_variable=args["no_variable"],
rule_config_max_tokens=PROMPT_GENERATION_MAX_TOKENS,
)
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except InvokeError as e:
raise CompletionRequestError(e.description)
return rules
class RuleCodeGenerateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument("instruction", type=str, required=True, nullable=False, location="json")
parser.add_argument("model_config", type=dict, required=True, nullable=False, location="json")
parser.add_argument("no_variable", type=bool, required=True, default=False, location="json")
parser.add_argument("code_language", type=str, required=False, default="javascript", location="json")
args = parser.parse_args()
account = current_user
CODE_GENERATION_MAX_TOKENS = int(os.getenv("CODE_GENERATION_MAX_TOKENS", "1024"))
try:
code_result = LLMGenerator.generate_code(
tenant_id=account.current_tenant_id,
instruction=args["instruction"],
model_config=args["model_config"],
code_language=args["code_language"],
max_tokens=CODE_GENERATION_MAX_TOKENS,
)
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except InvokeError as e:
raise CompletionRequestError(e.description)
return code_result
class RuleStructuredOutputGenerateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument("instruction", type=str, required=True, nullable=False, location="json")
parser.add_argument("model_config", type=dict, required=True, nullable=False, location="json")
args = parser.parse_args()
account = current_user
try:
structured_output = LLMGenerator.generate_structured_output(
tenant_id=account.current_tenant_id,
instruction=args["instruction"],
model_config=args["model_config"],
)
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except InvokeError as e:
raise CompletionRequestError(e.description)
return structured_output
class InstructionGenerateApi(Resource):
@setup_required
@login_required
@account_initialization_required
def post(self):
parser = reqparse.RequestParser()
parser.add_argument("flow_id", type=str, required=True, default="", location="json")
parser.add_argument("node_id", type=str, required=False, default="", location="json")
parser.add_argument("current", type=str, required=False, default="", location="json")
parser.add_argument("language", type=str, required=False, default="javascript", location="json")
parser.add_argument("instruction", type=str, required=True, nullable=False, location="json")
parser.add_argument("model_config", type=dict, required=True, nullable=False, location="json")
parser.add_argument("ideal_output", type=str, required=False, default="", location="json")
args = parser.parse_args()
try:
if args["current"] == "" and args["node_id"] != "": # Generate from nothing for a workflow node
from models import App, db
from services.workflow_service import WorkflowService
app = db.session.query(App).filter(App.id == args["flow_id"]).first()
workflow = WorkflowService().get_draft_workflow(app_model=app)
nodes:Sequence = workflow.graph_dict["nodes"]
node: dict = [node for node in nodes if node["id"] == args["node_id"]][0]
if not node:
raise BadRequestError(f"node {args['node_id']} not found")
match node_type:=node["data"]["type"]:
case "llm", "agent":
return LLMGenerator.generate_rule_config(
current_user.current_tenant_id,
instruction=args["instruction"],
model_config=args["model_config"],
no_variable=True
)
case "code":
return LLMGenerator.generate_code(
tenant_id=current_user.current_tenant_id,
instruction=args["instruction"],
model_config=args["model_config"],
code_language=args["language"],
)
case _:
raise BadRequestError(f"invalid node type: {node_type}")
if args["node_id"] == "" and args["current"] != "": # For legacy app without a workflow
return LLMGenerator.instruction_modify_legacy(
tenant_id=current_user.current_tenant_id,
flow_id=args["flow_id"],
current=args["current"],
instruction=args["instruction"],
model_config=args["model_config"],
ideal_output=args["ideal_output"],
)
if args["node_id"] != "" and args["current"] != "": # For workflow node
return LLMGenerator.instruction_modify_workflow(
tenant_id=current_user.current_tenant_id,
flow_id=args["flow_id"],
node_id=args["node_id"],
current=args["current"],
instruction=args["instruction"],
model_config=args["model_config"],
ideal_output=args["ideal_output"],
)
raise BadRequestError("incompatible parameters")
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except InvokeError as e:
raise CompletionRequestError(e.description)
api.add_resource(RuleGenerateApi, "/rule-generate")
api.add_resource(RuleCodeGenerateApi, "/rule-code-generate")
api.add_resource(RuleStructuredOutputGenerateApi, "/rule-structured-output-generate")
api.add_resource(InstructionGenerateApi, "/instruction-generate")