File size: 1,744 Bytes
8360ec7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
from core import register_solver, StandardTaskSolver, FactCheckerState
import asyncio
import nest_asyncio
from factool import Factool
from .ftool_utils.chat_api import OpenAIChat
import yaml
import os
from typing import List
##
#
# Factool Decontextualizer
#
# Notes:
# - This solver is used to extract claims from a response.
# - The response should be a string.
#
##
@register_solver("factool_decontextualizer", "response", "claims")
class FactoolDecontextualizer(StandardTaskSolver):
def __init__(self, args):
super().__init__(args)
self.gpt_model = self.global_config.get("llm_in_use", "gpt-3.5-turbo")
self.gpt = OpenAIChat(self.gpt_model)
self.claim_prompt = yaml.load(
open(
os.path.join(
os.path.dirname(os.path.abspath(__file__)),
"ftool_utils/prompts.yaml",
),
"r",
),
yaml.FullLoader,
)["claim_extraction"]
def __call__(self, state: FactCheckerState, *args, **kwargs):
response = state.get(self.input_name)
claims = self._claim_extraction(responses=[response])[0]
extracted_claims = [claim["claim"] for claim in claims]
state.set(self.output_name, extracted_claims)
return True, state
def _claim_extraction(self, responses):
messages_list = [
[
{"role": "system", "content": self.claim_prompt["system"]},
{
"role": "user",
"content": self.claim_prompt["user"].format(input=response),
},
]
for response in responses
]
return self.gpt.run(messages_list, List)
|