kaizenkodo/ChatMastermind
2
0
Fork 0
Code Issues 2 Pull Requests Packages Projects Releases Wiki Activity

message: fixed Answer header for TXT format

Browse Source
This commit is contained in:
juk0de 2023-09-02 10:00:08 +02:00 committed by Oleksandr Kozachuk
parent aba3eb783d
commit d35de86c67
1 changed files with 9 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
chatmastermind/message.py
View File

@ -96,7 +96,7 @@ class AILine(str):
def __new__(cls: Type[AILineInst], string: str) -> AILineInst:
if not string.startswith(cls.prefix):
raise TagError(f"AILine '{string}' is missing prefix '{cls.prefix}'")
raise MessageError(f"AILine '{string}' is missing prefix '{cls.prefix}'")
instance = super().__new__(cls, string)
return instance
@ -116,7 +116,7 @@ class ModelLine(str):
def __new__(cls: Type[ModelLineInst], string: str) -> ModelLineInst:
if not string.startswith(cls.prefix):
raise TagError(f"ModelLine '{string}' is missing prefix '{cls.prefix}'")
raise MessageError(f"ModelLine '{string}' is missing prefix '{cls.prefix}'")
instance = super().__new__(cls, string)
return instance
@ -133,7 +133,7 @@ class Answer(str):
A single answer with a defined header.
"""
tokens: int = 0 # tokens used by this answer
txt_header: ClassVar[str] = '=== ANSWER ==='
txt_header: ClassVar[str] = '==== ANSWER ===='
yaml_key: ClassVar[str] = 'answer'
def __new__(cls: Type[AnswerInst], string: str) -> AnswerInst:
@ -355,17 +355,20 @@ class Message():
try:
pos = fd.tell()
ai = AILine(fd.readline()).ai()
except TagError:
except MessageError:
fd.seek(pos)
# ModelLine (Optional)
try:
pos = fd.tell()
model = ModelLine(fd.readline()).model()
except TagError:
except MessageError:
fd.seek(pos)
# Question and Answer
text = fd.read().strip().split('\n')
try:
question_idx = text.index(Question.txt_header) + 1
except ValueError:
raise MessageError(f"Question header '{Question.txt_header}' not found in '{file_path}'")
try:
answer_idx = text.index(Answer.txt_header)
question = Question.from_list(text[question_idx:answer_idx])