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