I encountered this error while trying to import OpenAIInstructionParser, TaskType. Then, I solved that issue and further checked that the same issue is present in other files too, so solved them. also, pre-commit was throwing FI58 error while merging the new changes to added a parameter in pre-commit config to ignore the particular error.
File ~/.pyenv/versions/3.8.17/lib/python3.8/site-packages/prompt2model/utils/tevatron_utils/init.py:3
1 """Import Tevatron utility functions."""
2 from prompt2model.utils.tevatron_utils.encode import encode_text
----> 3 from prompt2model.utils.tevatron_utils.retrieve import retrieve_objects
5 all = ("encode_text", "retrieve_objects")
File ~/.pyenv/versions/3.8.17/lib/python3.8/site-packages/prompt2model/utils/tevatron_utils/retrieve.py:11
4 import numpy as np
5 from tevatron.faiss_retriever import BaseFaissIPRetriever
8 def retrieve_objects(
9 query_vector: np.ndarray,
10 encoded_datasets_path: str,
---> 11 document_names: list[str],
12 depth: int,
13 ) -> list[tuple[str, float]]:
14 """Return a ranked list of object indices and their scores.
15
16 Args:
(...)
22 Ranked list of object names and their inner product similarity to the query.
23 """
24 assert query_vector.shape[0] == 1, "Only a single query vector is expected."
Description
I encountered this error while trying to import OpenAIInstructionParser, TaskType. Then, I solved that issue and further checked that the same issue is present in other files too, so solved them. also, pre-commit was throwing FI58 error while merging the new changes to added a parameter in pre-commit config to ignore the particular error.
TypeError Traceback (most recent call last) Cell In[1], line 1 ----> 1 from prompt2model.prompt_parser import OpenAIInstructionParser, TaskType 3 prompt_spec = OpenAIInstructionParser(task_type=TaskType.TEXT_GENERATION) 4 prompt_spec.parse_from_prompt(prompt)
File ~/.pyenv/versions/3.8.17/lib/python3.8/site-packages/prompt2model/prompt_parser/init.py:3 1 """Import PromptSpec classes.""" 2 from prompt2model.prompt_parser.base import PromptSpec, TaskType ----> 3 from prompt2model.prompt_parser.instr_parser import OpenAIInstructionParser 4 from prompt2model.prompt_parser.mock import MockPromptSpec 6 all = ( 7 "PromptSpec", 8 "TaskType", 9 "MockPromptSpec", 10 "OpenAIInstructionParser", 11 )
File ~/.pyenv/versions/3.8.17/lib/python3.8/site-packages/prompt2model/prompt_parser/instr_parser.py:15 10 from prompt2model.prompt_parser.base import PromptSpec, TaskType 12 from prompt2model.prompt_parser.instr_parser_prompt import ( # isort: split 13 construct_prompt_for_instruction_parsing, 14 ) ---> 15 from prompt2model.utils import ( 16 OPENAI_ERRORS, 17 ChatGPTAgent, 18 get_formatted_logger, 19 handle_openai_error, 20 ) 22 logger = get_formatted_logger("PromptParser") 24 os.environ["TOKENIZERS_PARALLELISM"] = "false"
File ~/.pyenv/versions/3.8.17/lib/python3.8/site-packages/prompt2model/utils/init.py:10 3 from prompt2model.utils.openai_tools import ( 4 OPENAI_ERRORS, 5 ChatGPTAgent, 6 count_tokens_from_string, 7 handle_openai_error, 8 ) 9 from prompt2model.utils.rng import seed_generator ---> 10 from prompt2model.utils.tevatron_utils import encode_text, retrieve_objects 12 all = ( # noqa: F401 13 "ChatGPTAgent", 14 "encode_text", (...) 20 "get_formatted_logger", 21 )
File ~/.pyenv/versions/3.8.17/lib/python3.8/site-packages/prompt2model/utils/tevatron_utils/init.py:3 1 """Import Tevatron utility functions.""" 2 from prompt2model.utils.tevatron_utils.encode import encode_text ----> 3 from prompt2model.utils.tevatron_utils.retrieve import retrieve_objects 5 all = ("encode_text", "retrieve_objects")
File ~/.pyenv/versions/3.8.17/lib/python3.8/site-packages/prompt2model/utils/tevatron_utils/retrieve.py:11 4 import numpy as np 5 from tevatron.faiss_retriever import BaseFaissIPRetriever 8 def retrieve_objects( 9 query_vector: np.ndarray, 10 encoded_datasets_path: str, ---> 11 document_names: list[str], 12 depth: int, 13 ) -> list[tuple[str, float]]: 14 """Return a ranked list of object indices and their scores. 15 16 Args: (...) 22 Ranked list of object names and their inner product similarity to the query. 23 """ 24 assert query_vector.shape[0] == 1, "Only a single query vector is expected."
TypeError: 'type' object is not subscriptable
References
Below mentioned issue is solved by this PR