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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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from graph.settings import DEBUG |
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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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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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if DEBUG: print(ans, ":::::::::::::::::::::::::::::::::", input) |
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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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