alpha-nerd-nomyo
d80b29e4f2
- Renamed Feedback class to follow PascalCase convention - Fixed candidate enumeration start index from 0 to 1 - Simplified candidate content access by removing .message.content - Updated CONFIG_PATH environment variable name to CONFIG_PATH_ARG - Bumped version from 0.5 to 0.6 - Removed unnecessary return statement and trailing newline
48 lines
No EOL
1.4 KiB
Python
48 lines
No EOL
1.4 KiB
Python
from pydantic import BaseModel
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class Feedback(BaseModel):
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query_id: int
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content: str
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def moe(query: str, query_id: int, response: str) -> str:
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moe_prompt = f"""
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User query: {query}
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query_id: {query_id}
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The following is an assistant response to the original user query. Analyse the response, then criticize the it by discussing both strengths and weaknesses. Do not add additional commentary.
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<assistant_response>
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{response}
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</assistant_response>
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Respond in the format:
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original_response
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---
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Response Analysis:
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your analysis
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"""
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return moe_prompt
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def moe_select_candidate(query: str, candidates: list[str]) -> str:
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if not candidates:
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raise ValueError("No candidates supplied")
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candidate_sections = ""
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for i, cand in enumerate(candidates[:3], start=1):
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candidate_sections += f"""
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<candidate_{i}>
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{cand}
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</candidate_{i}>
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"""
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# Strict instruction: "Respond **only** with the final answer."
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select_prompt = f"""
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From the following responses for the user query: {query}
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{candidate_sections}
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Choose the best candidate and output the final answer in the language of the query.
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**Do NOT** mention candidate numbers, strengths, weaknesses, or any other commentary.
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Just give the final answer—nothing else.
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"""
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return select_prompt.strip() |