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from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError | |
from request_llms.bridge_all import predict_no_ui_long_connection | |
def get_code_block(reply): | |
import re | |
pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks | |
matches = re.findall(pattern, reply) # find all code blocks in text | |
if len(matches) == 1: | |
return "```" + matches[0] + "```" # code block | |
raise RuntimeError("GPT is not generating proper code.") | |
def is_same_thing(a, b, llm_kwargs): | |
from pydantic import BaseModel, Field | |
class IsSameThing(BaseModel): | |
is_same_thing: bool = Field(description="determine whether two objects are same thing.", default=False) | |
def run_gpt_fn(inputs, sys_prompt, history=[]): | |
return predict_no_ui_long_connection( | |
inputs=inputs, llm_kwargs=llm_kwargs, | |
history=history, sys_prompt=sys_prompt, observe_window=[] | |
) | |
gpt_json_io = GptJsonIO(IsSameThing) | |
inputs_01 = "Identity whether the user input and the target is the same thing: \n target object: {a} \n user input object: {b} \n\n\n".format(a=a, b=b) | |
inputs_01 += "\n\n\n Note that the user may describe the target object with a different language, e.g. cat and 猫 are the same thing." | |
analyze_res_cot_01 = run_gpt_fn(inputs_01, "", []) | |
inputs_02 = inputs_01 + gpt_json_io.format_instructions | |
analyze_res = run_gpt_fn(inputs_02, "", [inputs_01, analyze_res_cot_01]) | |
try: | |
res = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn) | |
return res.is_same_thing | |
except JsonStringError as e: | |
return False |