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#
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from abc import ABC
from api.db import LLMType
from api.db.services.llm_service import LLMBundle
from agent.component import GenerateParam, Generate
from agent.settings import DEBUG
class CategorizeParam(GenerateParam):
"""
Define the Categorize component parameters.
"""
def __init__(self):
super().__init__()
self.category_description = {}
self.prompt = ""
def check(self):
super().check()
self.check_empty(self.category_description, "[Categorize] Category examples")
for k, v in self.category_description.items():
if not k: raise ValueError(f"[Categorize] Category name can not be empty!")
if not v.get("to"): raise ValueError(f"[Categorize] 'To' of category {k} can not be empty!")
def get_prompt(self):
cate_lines = []
for c, desc in self.category_description.items():
for l in desc.get("examples", "").split("\n"):
if not l: continue
cate_lines.append("Question: {}\tCategory: {}".format(l, c))
descriptions = []
for c, desc in self.category_description.items():
if desc.get("description"):
descriptions.append(
"--------------------\nCategory: {}\nDescription: {}\n".format(c, desc["description"]))
self.prompt = """
You're a text classifier. You need to categorize the user’s questions into {} categories,
namely: {}
Here's description of each category:
{}
You could learn from the following examples:
{}
You could learn from the above examples.
Just mention the category names, no need for any additional words.
""".format(
len(self.category_description.keys()),
"/".join(list(self.category_description.keys())),
"\n".join(descriptions),
"- ".join(cate_lines)
)
return self.prompt
class Categorize(Generate, ABC):
component_name = "Categorize"
def _run(self, history, **kwargs):
input = self.get_input()
input = "Question: " + ("; ".join(input["content"]) if "content" in input else "") + "Category: "
chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": input}],
self._param.gen_conf())
if DEBUG: print(ans, ":::::::::::::::::::::::::::::::::", input)
for c in self._param.category_description.keys():
if ans.lower().find(c.lower()) >= 0:
return Categorize.be_output(self._param.category_description[c]["to"])
return Categorize.be_output(self._param.category_description.items()[-1][1]["to"])
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