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| import logging |
| from abc import ABC |
| from api.db import LLMType |
| from api.db.services.llm_service import LLMBundle |
| from agent.component import GenerateParam, Generate |
| from rag.utils import num_tokens_from_string, encoder |
|
|
|
|
| class RelevantParam(GenerateParam): |
|
|
| """ |
| Define the Relevant component parameters. |
| """ |
| def __init__(self): |
| super().__init__() |
| self.prompt = "" |
| self.yes = "" |
| self.no = "" |
|
|
| def check(self): |
| super().check() |
| self.check_empty(self.yes, "[Relevant] 'Yes'") |
| self.check_empty(self.no, "[Relevant] 'No'") |
|
|
| def get_prompt(self): |
| self.prompt = """ |
| You are a grader assessing relevance of a retrieved document to a user question. |
| It does not need to be a stringent test. The goal is to filter out erroneous retrievals. |
| If the document contains keyword(s) or semantic meaning related to the user question, grade it as relevant. |
| Give a binary score 'yes' or 'no' score to indicate whether the document is relevant to the question. |
| No other words needed except 'yes' or 'no'. |
| """ |
| return self.prompt |
|
|
|
|
| class Relevant(Generate, ABC): |
| component_name = "Relevant" |
|
|
| def _run(self, history, **kwargs): |
| q = "" |
| for r, c in self._canvas.history[::-1]: |
| if r == "user": |
| q = c |
| break |
| ans = self.get_input() |
| ans = " - ".join(ans["content"]) if "content" in ans else "" |
| if not ans: |
| return Relevant.be_output(self._param.no) |
| ans = "Documents: \n" + ans |
| ans = f"Question: {q}\n" + ans |
| chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id) |
|
|
| if num_tokens_from_string(ans) >= chat_mdl.max_length - 4: |
| ans = encoder.decode(encoder.encode(ans)[:chat_mdl.max_length - 4]) |
|
|
| ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": ans}], |
| self._param.gen_conf()) |
|
|
| logging.debug(ans) |
| if ans.lower().find("yes") >= 0: |
| return Relevant.be_output(self._param.yes) |
| if ans.lower().find("no") >= 0: |
| return Relevant.be_output(self._param.no) |
| assert False, f"Relevant component got: {ans}" |
|
|
| def debug(self, **kwargs): |
| return self._run([], **kwargs) |
|
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|
|
