9 Commits

11 changed files with 125 additions and 49 deletions
+6
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@@ -66,3 +66,9 @@ class AI(Protocol):
and is not implemented for all AIs. and is not implemented for all AIs.
""" """
raise NotImplementedError raise NotImplementedError
def print(self) -> None:
"""
Print some info about the current AI, like system message.
"""
pass
+12 -6
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@@ -4,25 +4,31 @@ Creates different AI instances, based on the given configuration.
import argparse import argparse
from typing import cast from typing import cast
from .configuration import Config, OpenAIConfig, default_ai_ID from .configuration import Config, AIConfig, OpenAIConfig
from .ai import AI, AIError from .ai import AI, AIError
from .ais.openai import OpenAI from .ais.openai import OpenAI
def create_ai(args: argparse.Namespace, config: Config) -> AI: def create_ai(args: argparse.Namespace, config: Config) -> AI: # noqa: 11
""" """
Creates an AI subclass instance from the given arguments Creates an AI subclass instance from the given arguments
and configuration file. and configuration file. If AI has not been set in the
arguments, it searches for the ID 'default'. If that
is not found, it uses the first AI in the list.
""" """
ai_conf: AIConfig
if args.AI: if args.AI:
try: try:
ai_conf = config.ais[args.AI] ai_conf = config.ais[args.AI]
except KeyError: except KeyError:
raise AIError(f"AI ID '{args.AI}' does not exist in this configuration") raise AIError(f"AI ID '{args.AI}' does not exist in this configuration")
elif default_ai_ID in config.ais: elif 'default' in config.ais:
ai_conf = config.ais[default_ai_ID] ai_conf = config.ais['default']
else: else:
raise AIError("No AI name given and no default exists") try:
ai_conf = next(iter(config.ais.values()))
except StopIteration:
raise AIError("No AI found in this configuration")
if ai_conf.name == 'openai': if ai_conf.name == 'openai':
ai = OpenAI(cast(OpenAIConfig, ai_conf)) ai = OpenAI(cast(OpenAIConfig, ai_conf))
+15 -6
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@@ -43,16 +43,20 @@ class OpenAI(AI):
n=num_answers, n=num_answers,
frequency_penalty=self.config.frequency_penalty, frequency_penalty=self.config.frequency_penalty,
presence_penalty=self.config.presence_penalty) presence_penalty=self.config.presence_penalty)
answers: list[Message] = [] question.answer = Answer(response['choices'][0]['message']['content'])
for choice in response['choices']: # type: ignore question.tags = otags
question.ai = self.ID
question.model = self.config.model
answers: list[Message] = [question]
for choice in response['choices'][1:]: # type: ignore
answers.append(Message(question=question.question, answers.append(Message(question=question.question,
answer=Answer(choice['message']['content']), answer=Answer(choice['message']['content']),
tags=otags, tags=otags,
ai=self.name, ai=self.ID,
model=self.config.model)) model=self.config.model))
return AIResponse(answers, Tokens(response['usage']['prompt'], return AIResponse(answers, Tokens(response['usage']['prompt_tokens'],
response['usage']['completion'], response['usage']['completion_tokens'],
response['usage']['total'])) response['usage']['total_tokens']))
def models(self) -> list[str]: def models(self) -> list[str]:
""" """
@@ -95,3 +99,8 @@ class OpenAI(AI):
def tokens(self, data: Union[Message, Chat]) -> int: def tokens(self, data: Union[Message, Chat]) -> int:
raise NotImplementedError raise NotImplementedError
def print(self) -> None:
print(f"MODEL: {self.config.model}")
print("=== SYSTEM ===")
print(self.config.system)
+4 -1
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@@ -62,7 +62,10 @@ def make_file_path(dir_path: Path,
Create a file_path for the given directory using the Create a file_path for the given directory using the
given file_suffix and ID generator function. given file_suffix and ID generator function.
""" """
return dir_path / f"{next_fid():04d}{file_suffix}" file_path = dir_path / f"{next_fid():04d}{file_suffix}"
while file_path.exists():
file_path = dir_path / f"{next_fid():04d}{file_suffix}"
return file_path
def write_dir(dir_path: Path, def write_dir(dir_path: Path,
+18 -9
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@@ -3,7 +3,7 @@ from pathlib import Path
from itertools import zip_longest from itertools import zip_longest
from ..configuration import Config from ..configuration import Config
from ..chat import ChatDB from ..chat import ChatDB
from ..message import Message, Question, source_code from ..message import Message, MessageFilter, Question, source_code
from ..ai_factory import create_ai from ..ai_factory import create_ai
from ..ai import AI, AIResponse from ..ai import AI, AIResponse
@@ -52,8 +52,12 @@ def question_cmd(args: argparse.Namespace, config: Config) -> None:
""" """
Handler for the 'question' command. Handler for the 'question' command.
""" """
mfilter = MessageFilter(tags_or=args.or_tags if args.or_tags is not None else set(),
tags_and=args.and_tags if args.and_tags is not None else set(),
tags_not=args.exclude_tags if args.exclude_tags is not None else set())
chat = ChatDB.from_dir(cache_path=Path('.'), chat = ChatDB.from_dir(cache_path=Path('.'),
db_path=Path(config.db)) db_path=Path(config.db),
mfilter=mfilter)
# if it's a new question, create and store it immediately # if it's a new question, create and store it immediately
if args.ask or args.create: if args.ask or args.create:
message = create_message(chat, args) message = create_message(chat, args)
@@ -63,23 +67,28 @@ def question_cmd(args: argparse.Namespace, config: Config) -> None:
# create the correct AI instance # create the correct AI instance
ai: AI = create_ai(args, config) ai: AI = create_ai(args, config)
if args.ask: if args.ask:
ai.print()
chat.print(paged=False)
response: AIResponse = ai.request(message, response: AIResponse = ai.request(message,
chat, chat,
args.num_answers, # FIXME args.num_answers, # FIXME
args.output_tags) # FIXME args.output_tags) # FIXME
assert response chat.update_messages([response.messages[0]])
# TODO: chat.add_to_cache(response.messages[1:])
# * add answer to the message above (and create for idx, msg in enumerate(response.messages):
# more messages for any additional answers) print(f"=== ANSWER {idx+1} ===")
pass print(msg.answer)
elif args.repeat: if response.tokens:
print("===============")
print(response.tokens)
elif args.repeat is not None:
lmessage = chat.latest_message() lmessage = chat.latest_message()
assert lmessage assert lmessage
# TODO: repeat either the last question or the # TODO: repeat either the last question or the
# one(s) given in 'args.repeat' (overwrite # one(s) given in 'args.repeat' (overwrite
# existing ones if 'args.overwrite' is True) # existing ones if 'args.overwrite' is True)
pass pass
elif args.process: elif args.process is not None:
# TODO: process either all questions without an # TODO: process either all questions without an
# answer or the one(s) given in 'args.process' # answer or the one(s) given in 'args.process'
pass pass
+19 -6
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@@ -9,7 +9,6 @@ OpenAIConfigInst = TypeVar('OpenAIConfigInst', bound='OpenAIConfig')
supported_ais: list[str] = ['openai'] supported_ais: list[str] = ['openai']
default_ai_ID: str = 'default'
default_config_path = '.config.yaml' default_config_path = '.config.yaml'
@@ -17,6 +16,18 @@ class ConfigError(Exception):
pass pass
def str_presenter(dumper: yaml.Dumper, data: str) -> yaml.ScalarNode:
"""
Changes the YAML dump style to multiline syntax for multiline strings.
"""
if len(data.splitlines()) > 1:
return dumper.represent_scalar('tag:yaml.org,2002:str', data, style='|')
return dumper.represent_scalar('tag:yaml.org,2002:str', data)
yaml.add_representer(str, str_presenter)
@dataclass @dataclass
class AIConfig: class AIConfig:
""" """
@@ -46,15 +57,15 @@ class OpenAIConfig(AIConfig):
# all members have default values, so we can easily create # all members have default values, so we can easily create
# a default configuration # a default configuration
ID: str = 'default' ID: str = 'myopenai'
api_key: str = '0123456789' api_key: str = '0123456789'
system: str = 'You are an assistant'
model: str = 'gpt-3.5-turbo-16k' model: str = 'gpt-3.5-turbo-16k'
temperature: float = 1.0 temperature: float = 1.0
max_tokens: int = 4000 max_tokens: int = 4000
top_p: float = 1.0 top_p: float = 1.0
frequency_penalty: float = 0.0 frequency_penalty: float = 0.0
presence_penalty: float = 0.0 presence_penalty: float = 0.0
system: str = 'You are an assistant'
@classmethod @classmethod
def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst: def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst:
@@ -62,14 +73,14 @@ class OpenAIConfig(AIConfig):
Create OpenAIConfig from a dict. Create OpenAIConfig from a dict.
""" """
res = cls( res = cls(
system=str(source['system']),
api_key=str(source['api_key']), api_key=str(source['api_key']),
model=str(source['model']), model=str(source['model']),
max_tokens=int(source['max_tokens']), max_tokens=int(source['max_tokens']),
temperature=float(source['temperature']), temperature=float(source['temperature']),
top_p=float(source['top_p']), top_p=float(source['top_p']),
frequency_penalty=float(source['frequency_penalty']), frequency_penalty=float(source['frequency_penalty']),
presence_penalty=float(source['presence_penalty']) presence_penalty=float(source['presence_penalty']),
system=str(source['system'])
) )
# overwrite default ID if provided # overwrite default ID if provided
if 'ID' in source: if 'ID' in source:
@@ -148,6 +159,8 @@ class Config:
def as_dict(self) -> dict[str, Any]: def as_dict(self) -> dict[str, Any]:
res = asdict(self) res = asdict(self)
# add the AI name manually (as first element)
# (not done by 'asdict' because it's a class variable)
for ID, conf in res['ais'].items(): for ID, conf in res['ais'].items():
conf.update({'name': self.ais[ID].name}) res['ais'][ID] = {**{'name': self.ais[ID].name}, **conf}
return res return res
+16 -10
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@@ -3,6 +3,8 @@ Module implementing message related functions and classes.
""" """
import pathlib import pathlib
import yaml import yaml
import tempfile
import shutil
from typing import Type, TypeVar, ClassVar, Optional, Any, Union, Final, Literal, Iterable from typing import Type, TypeVar, ClassVar, Optional, Any, Union, Final, Literal, Iterable
from dataclasses import dataclass, asdict, field from dataclasses import dataclass, asdict, field
from .tags import Tag, TagLine, TagError, match_tags, rename_tags from .tags import Tag, TagLine, TagError, match_tags, rename_tags
@@ -312,7 +314,7 @@ class Message():
mfilter.tags_not if mfilter else None) mfilter.tags_not if mfilter else None)
else: else:
message = cls.__from_file_yaml(file_path) message = cls.__from_file_yaml(file_path)
if message and (not mfilter or (mfilter and message.match(mfilter))): if message and (mfilter is None or message.match(mfilter)):
return message return message
else: else:
return None return None
@@ -445,16 +447,18 @@ class Message():
* Answer.txt_header * Answer.txt_header
* Answer * Answer
""" """
with open(file_path, "w") as fd: with tempfile.NamedTemporaryFile(dir=file_path.parent, prefix=file_path.name, mode="w", delete=False) as temp_fd:
temp_file_path = pathlib.Path(temp_fd.name)
if self.tags: if self.tags:
fd.write(f'{TagLine.from_set(self.tags)}\n') temp_fd.write(f'{TagLine.from_set(self.tags)}\n')
if self.ai: if self.ai:
fd.write(f'{AILine.from_ai(self.ai)}\n') temp_fd.write(f'{AILine.from_ai(self.ai)}\n')
if self.model: if self.model:
fd.write(f'{ModelLine.from_model(self.model)}\n') temp_fd.write(f'{ModelLine.from_model(self.model)}\n')
fd.write(f'{Question.txt_header}\n{self.question}\n') temp_fd.write(f'{Question.txt_header}\n{self.question}\n')
if self.answer: if self.answer:
fd.write(f'{Answer.txt_header}\n{self.answer}\n') temp_fd.write(f'{Answer.txt_header}\n{self.answer}\n')
shutil.move(temp_file_path, file_path)
def __to_file_yaml(self, file_path: pathlib.Path) -> None: def __to_file_yaml(self, file_path: pathlib.Path) -> None:
""" """
@@ -466,7 +470,8 @@ class Message():
* Message.ai_yaml_key: str [Optional] * Message.ai_yaml_key: str [Optional]
* Message.model_yaml_key: str [Optional] * Message.model_yaml_key: str [Optional]
""" """
with open(file_path, "w") as fd: with tempfile.NamedTemporaryFile(dir=file_path.parent, prefix=file_path.name, mode="w", delete=False) as temp_fd:
temp_file_path = pathlib.Path(temp_fd.name)
data: YamlDict = {Question.yaml_key: str(self.question)} data: YamlDict = {Question.yaml_key: str(self.question)}
if self.answer: if self.answer:
data[Answer.yaml_key] = str(self.answer) data[Answer.yaml_key] = str(self.answer)
@@ -476,7 +481,8 @@ class Message():
data[self.model_yaml_key] = self.model data[self.model_yaml_key] = self.model
if self.tags: if self.tags:
data[self.tags_yaml_key] = sorted([str(tag) for tag in self.tags]) data[self.tags_yaml_key] = sorted([str(tag) for tag in self.tags])
yaml.dump(data, fd, sort_keys=False) yaml.dump(data, temp_fd, sort_keys=False)
shutil.move(temp_file_path, file_path)
def filter_tags(self, prefix: Optional[str] = None, contain: Optional[str] = None) -> set[Tag]: def filter_tags(self, prefix: Optional[str] = None, contain: Optional[str] = None) -> set[Tag]:
""" """
@@ -508,7 +514,7 @@ class Message():
Return True if all attributes match, else False. Return True if all attributes match, else False.
""" """
mytags = self.tags or set() mytags = self.tags or set()
if (((mfilter.tags_or or mfilter.tags_and or mfilter.tags_not) if (((mfilter.tags_or is not None or mfilter.tags_and is not None or mfilter.tags_not is not None)
and not match_tags(mytags, mfilter.tags_or, mfilter.tags_and, mfilter.tags_not)) # noqa: W503 and not match_tags(mytags, mfilter.tags_or, mfilter.tags_and, mfilter.tags_not)) # noqa: W503
or (mfilter.ai and (not self.ai or mfilter.ai != self.ai)) # noqa: W503 or (mfilter.ai and (not self.ai or mfilter.ai != self.ai)) # noqa: W503
or (mfilter.model and (not self.model or mfilter.model != self.model)) # noqa: W503 or (mfilter.model and (not self.model or mfilter.model != self.model)) # noqa: W503
+2 -2
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@@ -10,7 +10,7 @@ from chatmastermind.ais.openai import OpenAI
class TestCreateAI(unittest.TestCase): class TestCreateAI(unittest.TestCase):
def setUp(self) -> None: def setUp(self) -> None:
self.args = MagicMock(spec=argparse.Namespace) self.args = MagicMock(spec=argparse.Namespace)
self.args.AI = 'default' self.args.AI = 'myopenai'
self.args.model = None self.args.model = None
self.args.max_tokens = None self.args.max_tokens = None
self.args.temperature = None self.args.temperature = None
@@ -18,7 +18,7 @@ class TestCreateAI(unittest.TestCase):
def test_create_ai_from_args(self) -> None: def test_create_ai_from_args(self) -> None:
# Create an AI with the default configuration # Create an AI with the default configuration
config = Config() config = Config()
self.args.AI = 'default' self.args.AI = 'myopenai'
ai = create_ai(self.args, config) ai = create_ai(self.args, config)
self.assertIsInstance(ai, OpenAI) self.assertIsInstance(ai, OpenAI)
+20 -2
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@@ -202,7 +202,25 @@ class TestChatDB(unittest.TestCase):
self.assertEqual(chat_db.messages[1].file_path, self.assertEqual(chat_db.messages[1].file_path,
pathlib.Path(self.db_path.name, '0003.txt')) pathlib.Path(self.db_path.name, '0003.txt'))
def test_chat_db_filter(self) -> None: def test_chat_db_from_dir_filter_tags(self) -> None:
chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name),
pathlib.Path(self.db_path.name),
mfilter=MessageFilter(tags_or={Tag('tag1')}))
self.assertEqual(len(chat_db.messages), 1)
self.assertEqual(chat_db.cache_path, pathlib.Path(self.cache_path.name))
self.assertEqual(chat_db.db_path, pathlib.Path(self.db_path.name))
self.assertEqual(chat_db.messages[0].file_path,
pathlib.Path(self.db_path.name, '0001.txt'))
def test_chat_db_from_dir_filter_tags_empty(self) -> None:
chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name),
pathlib.Path(self.db_path.name),
mfilter=MessageFilter(tags_or=set(),
tags_and=set(),
tags_not=set()))
self.assertEqual(len(chat_db.messages), 0)
def test_chat_db_from_dir_filter_answer(self) -> None:
chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name), chat_db = ChatDB.from_dir(pathlib.Path(self.cache_path.name),
pathlib.Path(self.db_path.name), pathlib.Path(self.db_path.name),
mfilter=MessageFilter(answer_contains='Answer 2')) mfilter=MessageFilter(answer_contains='Answer 2'))
@@ -213,7 +231,7 @@ class TestChatDB(unittest.TestCase):
pathlib.Path(self.db_path.name, '0002.yaml')) pathlib.Path(self.db_path.name, '0002.yaml'))
self.assertEqual(chat_db.messages[0].answer, 'Answer 2') self.assertEqual(chat_db.messages[0].answer, 'Answer 2')
def test_chat_db_from_messges(self) -> None: def test_chat_db_from_messages(self) -> None:
chat_db = ChatDB.from_messages(pathlib.Path(self.cache_path.name), chat_db = ChatDB.from_messages(pathlib.Path(self.cache_path.name),
pathlib.Path(self.db_path.name), pathlib.Path(self.db_path.name),
messages=[self.message1, self.message2, messages=[self.message1, self.message2,
+7 -7
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@@ -59,7 +59,7 @@ class TestConfig(unittest.TestCase):
source_dict = { source_dict = {
'db': './test_db/', 'db': './test_db/',
'ais': { 'ais': {
'default': { 'myopenai': {
'name': 'openai', 'name': 'openai',
'system': 'Custom system', 'system': 'Custom system',
'api_key': '9876543210', 'api_key': '9876543210',
@@ -75,10 +75,10 @@ class TestConfig(unittest.TestCase):
config = Config.from_dict(source_dict) config = Config.from_dict(source_dict)
self.assertEqual(config.db, './test_db/') self.assertEqual(config.db, './test_db/')
self.assertEqual(len(config.ais), 1) self.assertEqual(len(config.ais), 1)
self.assertEqual(config.ais['default'].name, 'openai') self.assertEqual(config.ais['myopenai'].name, 'openai')
self.assertEqual(cast(OpenAIConfig, config.ais['default']).system, 'Custom system') self.assertEqual(cast(OpenAIConfig, config.ais['myopenai']).system, 'Custom system')
# check that 'ID' has been added # check that 'ID' has been added
self.assertEqual(config.ais['default'].ID, 'default') self.assertEqual(config.ais['myopenai'].ID, 'myopenai')
def test_create_default_should_create_default_config(self) -> None: def test_create_default_should_create_default_config(self) -> None:
Config.create_default(Path(self.test_file.name)) Config.create_default(Path(self.test_file.name))
@@ -117,8 +117,8 @@ class TestConfig(unittest.TestCase):
config = Config( config = Config(
db='./test_db/', db='./test_db/',
ais={ ais={
'default': OpenAIConfig( 'myopenai': OpenAIConfig(
ID='default', ID='myopenai',
system='Custom system', system='Custom system',
api_key='9876543210', api_key='9876543210',
model='custom_model', model='custom_model',
@@ -135,7 +135,7 @@ class TestConfig(unittest.TestCase):
saved_config = yaml.load(f, Loader=yaml.FullLoader) saved_config = yaml.load(f, Loader=yaml.FullLoader)
self.assertEqual(saved_config['db'], './test_db/') self.assertEqual(saved_config['db'], './test_db/')
self.assertEqual(len(saved_config['ais']), 1) self.assertEqual(len(saved_config['ais']), 1)
self.assertEqual(saved_config['ais']['default']['system'], 'Custom system') self.assertEqual(saved_config['ais']['myopenai']['system'], 'Custom system')
def test_from_file_error_unknown_ai(self) -> None: def test_from_file_error_unknown_ai(self) -> None:
source_dict = { source_dict = {
+6
View File
@@ -300,6 +300,12 @@ This is a question.
MessageFilter(tags_or={Tag('tag1')})) MessageFilter(tags_or={Tag('tag1')}))
self.assertIsNone(message) self.assertIsNone(message)
def test_from_file_txt_empty_tags_dont_match(self) -> None:
message = Message.from_file(self.file_path_min,
MessageFilter(tags_or=set(),
tags_and=set()))
self.assertIsNone(message)
def test_from_file_txt_no_tags_match_tags_not(self) -> None: def test_from_file_txt_no_tags_match_tags_not(self) -> None:
message = Message.from_file(self.file_path_min, message = Message.from_file(self.file_path_min,
MessageFilter(tags_not={Tag('tag1')})) MessageFilter(tags_not={Tag('tag1')}))