refactor: move the prompt and entities to parser

pull/21565/head
Novice 11 months ago
parent cc19f23230
commit 676b49b5c6

@ -1,12 +1,14 @@
import json
from collections.abc import Generator, Mapping, Sequence
from copy import deepcopy
from enum import StrEnum
from typing import Any, Literal, Optional, cast, overload
import json_repair
from pydantic import TypeAdapter, ValidationError
from core.llm_generator.output_parser.errors import OutputParserError
from core.llm_generator.prompts import STRUCTURED_OUTPUT_PROMPT
from core.model_manager import ModelInstance
from core.model_runtime.callbacks.base_callback import Callback
from core.model_runtime.entities.llm_entities import (
@ -23,8 +25,21 @@ from core.model_runtime.entities.message_entities import (
SystemPromptMessage,
)
from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule
from core.workflow.utils.structured_output.entities import ResponseFormat, SpecialModelType
from core.workflow.utils.structured_output.prompt import STRUCTURED_OUTPUT_PROMPT
class ResponseFormat(StrEnum):
"""Constants for model response formats"""
JSON_SCHEMA = "json_schema" # model's structured output mode. some model like gemini, gpt-4o, support this mode.
JSON = "JSON" # model's json mode. some model like claude support this mode.
JSON_OBJECT = "json_object" # json mode's another alias. some model like deepseek-chat, qwen use this alias.
class SpecialModelType(StrEnum):
"""Constants for identifying model types"""
GEMINI = "gemini"
OLLAMA = "ollama"
@overload

@ -291,3 +291,21 @@ Your task is to convert simple user descriptions into properly formatted JSON Sc
Now, generate a JSON Schema based on my description
""" # noqa: E501
STRUCTURED_OUTPUT_PROMPT = """Youre a helpful AI assistant. You could answer questions and output in JSON format.
constraints:
- You must output in JSON format.
- Do not output boolean value, use string type instead.
- Do not output integer or float value, use number type instead.
eg:
Here is the JSON schema:
{"additionalProperties": false, "properties": {"age": {"type": "number"}, "name": {"type": "string"}}, "required": ["name", "age"], "type": "object"}
Here is the user's question:
My name is John Doe and I am 30 years old.
output:
{"name": "John Doe", "age": 30}
Here is the JSON schema:
{{schema}}
""" # noqa: E501

@ -1,16 +0,0 @@
from enum import StrEnum
class ResponseFormat(StrEnum):
"""Constants for model response formats"""
JSON_SCHEMA = "json_schema" # model's structured output mode. some model like gemini, gpt-4o, support this mode.
JSON = "JSON" # model's json mode. some model like claude support this mode.
JSON_OBJECT = "json_object" # json mode's another alias. some model like deepseek-chat, qwen use this alias.
class SpecialModelType(StrEnum):
"""Constants for identifying model types"""
GEMINI = "gemini"
OLLAMA = "ollama"

@ -1,17 +0,0 @@
STRUCTURED_OUTPUT_PROMPT = """Youre a helpful AI assistant. You could answer questions and output in JSON format.
constraints:
- You must output in JSON format.
- Do not output boolean value, use string type instead.
- Do not output integer or float value, use number type instead.
eg:
Here is the JSON schema:
{"additionalProperties": false, "properties": {"age": {"type": "number"}, "name": {"type": "string"}}, "required": ["name", "age"], "type": "object"}
Here is the user's question:
My name is John Doe and I am 30 years old.
output:
{"name": "John Doe", "age": 30}
Here is the JSON schema:
{{schema}}
""" # noqa: E501
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