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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/cli/src/flux0_cli/main.py
flux0_cli.main.Flux0CLIContext
from flux0_client import Flux0Client class Flux0CLIContext: """Typed context object for Click CLI.""" def __init__(self) -> None: self.client: Flux0Client = Flux0Client()
class Flux0CLIContext: '''Typed context object for Click CLI.''' def __init__(self) -> None: pass
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/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/agents.py
flux0_core.agents.Agent
from typing import List, NewType, Optional, Sequence, TypedDict from dataclasses import dataclass from datetime import datetime @dataclass(frozen=True) class Agent: id: AgentId type: AgentType name: str description: Optional[str] created_at: datetime
@dataclass(frozen=True) class Agent: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/agents.py
flux0_core.agents.AgentStore
from abc import ABC, abstractmethod from typing import List, NewType, Optional, Sequence, TypedDict from datetime import datetime class AgentStore(ABC): @abstractmethod async def create_agent(self, name: str, type: AgentType, description: Optional[str]=None, created_at: Optional[datetime]=None) -> Agent: ... @abstractmethod async def list_agents(self, offset: int=0, limit: int=10, projection: Optional[List[str]]=None) -> Sequence[Agent]: ... @abstractmethod async def read_agent(self, agent_id: AgentId) -> Optional[Agent]: ... @abstractmethod async def update_agent(self, agent_id: AgentId, params: AgentUpdateParams) -> Agent: ... @abstractmethod async def delete_agent(self, agent_id: AgentId) -> bool: ...
class AgentStore(ABC): @abstractmethod async def create_agent(self, name: str, type: AgentType, description: Optional[str]=None, created_at: Optional[datetime]=None) -> Agent: pass @abstractmethod async def list_agents(self, offset: int=0, limit: int=10, projection: Optional[List[str]]=None) -> Sequence[Agent]: pass @abstractmethod async def read_agent(self, agent_id: AgentId) -> Optional[Agent]: pass @abstractmethod async def update_agent(self, agent_id: AgentId, params: AgentUpdateParams) -> Agent: pass @abstractmethod async def delete_agent(self, agent_id: AgentId) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/agents.py
flux0_core.agents.AgentUpdateParams
from typing import List, NewType, Optional, Sequence, TypedDict class AgentUpdateParams(TypedDict, total=False): name: str description: Optional[str]
class AgentUpdateParams(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/async_utils.py
flux0_core.async_utils.RWLock
from contextlib import asynccontextmanager from typing import AsyncContextManager, AsyncIterator import aiorwlock class RWLock: def __init__(self) -> None: """ Initializes a new instance of the ReaderWriterLock class. The constructor creates an underlying `aiorwlock.RWLock` instance and sets up the reader and writer locks. """ _lock = aiorwlock.RWLock() self._reader_lock = _lock.reader self._writer_lock = _lock.writer @property def reader_lock(self) -> AsyncContextManager[None]: """ Provides an asynchronous context manager for acquiring the reader lock. This lock allows multiple readers to access the shared resource simultaneously. Writers are blocked while any reader holds the lock. Returns: AsyncContextManager[None]: An asynchronous context manager for the reader lock. Example: ```python async with lock.reader_lock: # Read from the shared resource ``` """ @asynccontextmanager async def _reader_acm() -> AsyncIterator[None]: async with self._reader_lock: yield return _reader_acm() @property def writer_lock(self) -> AsyncContextManager[None]: """ Provides an asynchronous context manager for acquiring the writer lock. This lock ensures exclusive access to the shared resource for writing. No readers or other writers are allowed while the writer lock is held. Returns: AsyncContextManager[None]: An asynchronous context manager for the writer lock. Example: ```python async with lock.writer_lock: # Write to the shared resource ``` """ @asynccontextmanager async def _writer_acm() -> AsyncIterator[None]: async with self._writer_lock: yield return _writer_acm()
class RWLock: def __init__(self) -> None: ''' Initializes a new instance of the ReaderWriterLock class. The constructor creates an underlying `aiorwlock.RWLock` instance and sets up the reader and writer locks. ''' pass @property def reader_lock(self) -> AsyncContextManager[None]: ''' Provides an asynchronous context manager for acquiring the reader lock. This lock allows multiple readers to access the shared resource simultaneously. Writers are blocked while any reader holds the lock. Returns: AsyncContextManager[None]: An asynchronous context manager for the reader lock. Example: ```python async with lock.reader_lock: # Read from the shared resource ``` ''' pass @asynccontextmanager async def _reader_acm() -> AsyncIterator[None]: pass @property def writer_lock(self) -> AsyncContextManager[None]: ''' Provides an asynchronous context manager for acquiring the writer lock. This lock ensures exclusive access to the shared resource for writing. No readers or other writers are allowed while the writer lock is held. Returns: AsyncContextManager[None]: An asynchronous context manager for the writer lock. Example: ```python async with lock.writer_lock: # Write to the shared resource ``` ''' pass @asynccontextmanager async def _writer_acm() -> AsyncIterator[None]: pass
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/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/background_tasks_service.py
flux0_core.background_tasks_service.BackgroundTaskService
from flux0_core.logging import Logger import traceback from typing import Any, Coroutine, Dict, Optional, Self, TypeAlias import asyncio class BackgroundTaskService: """A service for managing background tasks.""" def __init__(self, logger: Logger) -> None: self._logger: Logger = logger self._last_garbage_collection: float = 0.0 self._garbage_collection_interval: float = 5.0 self._tasks: Dict[str, Task] = {} self._lock = asyncio.Lock() async def __aenter__(self) -> Self: self._collector_task = asyncio.create_task(self._run_collector()) return self async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], tb: Optional[Any]) -> bool: if exc_value: await self.cancel_all(reason='Shutting down due to exception') self._logger.info(f'{type(self).__name__}: Exiting context, cleaning up tasks') await self.collect(force=True) return False async def cancel(self, *, tag: str, reason: str='(not set)') -> None: """ Cancels the task identified by the given tag. """ async with self._lock: task = self._tasks.get(tag) if task and (not task.done()): task.cancel(f'Forced cancellation by {type(self).__name__} [reason: {reason}]') self._logger.info(f"{type(self).__name__}: Cancelled task '{tag}'") await self.collect() async def cancel_all(self, *, reason: str='(not set)') -> None: """ Cancels all running tasks. """ async with self._lock: self._logger.info(f'{type(self).__name__}: Cancelling all remaining tasks ({len(self._tasks)}) [reason: {reason}]') for tag, task in self._tasks.items(): if not task.done(): task.cancel(f'Forced cancellation by {type(self).__name__} [reason: {reason}]') await self.collect() async def start(self, coro: Coroutine[Any, Any, None], /, *, tag: str) -> Task: """ Starts a new background task using the provided coroutine and associates it with the given tag. Raises an exception if a task with the same tag is already running. """ await self.collect() async with self._lock: if tag in self._tasks and (not self._tasks[tag].done()): raise Exception(f"Task '{tag}' is already running; consider calling restart() instead") self._logger.info(f"{type(self).__name__}: Starting task '{tag}'") task: Task = asyncio.create_task(coro) self._tasks[tag] = task return task async def restart(self, coro: Coroutine[Any, Any, None], /, *, tag: str) -> Task: """ Restarts the background task identified by the given tag. If an existing task is running, it will be canceled and awaited before starting a new one. """ await self.collect() async with self._lock: if tag in self._tasks: existing_task = self._tasks[tag] if not existing_task.done(): existing_task.cancel(f"Restarting task '{tag}'") await self._await_task(existing_task) self._logger.info(f"{type(self).__name__}: Restarting task '{tag}'") task: Task = asyncio.create_task(coro) self._tasks[tag] = task return task async def collect(self, *, force: bool=False) -> None: """ Cleans up finished tasks from the internal registry. If 'force' is True, it waits for all tasks to finish before cleanup. """ now: float = asyncio.get_running_loop().time() if not force and now - self._last_garbage_collection < self._garbage_collection_interval: return async with self._lock: new_tasks: Dict[str, Task] = {} for tag, task in self._tasks.items(): if task.done() or force: if not task.done(): self._logger.info(f"{type(self).__name__}: Waiting for task '{tag}' to finish before cleanup") await self._await_task(task) else: new_tasks[tag] = task self._tasks = new_tasks self._last_garbage_collection = now async def _await_task(self, task: Task) -> None: """ Awaits the task and logs exceptions if they occur. """ try: await task except asyncio.CancelledError: pass except Exception as exc: self._logger.warning(f"{type(self).__name__}: Task raised an exception: {''.join(traceback.format_exception_only(type(exc), exc)).strip()}") async def _run_collector(self) -> None: try: while True: await asyncio.sleep(self._garbage_collection_interval) await self.collect() except asyncio.CancelledError: pass
class BackgroundTaskService: '''A service for managing background tasks.''' def __init__(self, logger: Logger) -> None: pass async def __aenter__(self) -> Self: pass async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], tb: Optional[Any]) -> bool: pass async def cancel(self, *, tag: str, reason: str='(not set)') -> None: ''' Cancels the task identified by the given tag. ''' pass async def cancel_all(self, *, reason: str='(not set)') -> None: ''' Cancels all running tasks. ''' pass async def start(self, coro: Coroutine[Any, Any, None], /, *, tag: str) -> Task: ''' Starts a new background task using the provided coroutine and associates it with the given tag. Raises an exception if a task with the same tag is already running. ''' pass async def restart(self, coro: Coroutine[Any, Any, None], /, *, tag: str) -> Task: ''' Restarts the background task identified by the given tag. If an existing task is running, it will be canceled and awaited before starting a new one. ''' pass async def collect(self, *, force: bool=False) -> None: ''' Cleans up finished tasks from the internal registry. If 'force' is True, it waits for all tasks to finish before cleanup. ''' pass async def _await_task(self, task: Task) -> None: ''' Awaits the task and logs exceptions if they occur. ''' pass async def _run_collector(self) -> None: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/contextual_correlator.py
flux0_core.contextual_correlator.ContextualCorrelator
import contextvars from flux0_core.ids import gen_id from contextlib import contextmanager from typing import Iterator class ContextualCorrelator: def __init__(self, delimiter: str='::', default: str='<main>') -> None: self._instance_id: str = gen_id() self._scopes: contextvars.ContextVar[str] = contextvars.ContextVar(f'correlator_{self._instance_id}_scopes', default='') self._delimiter: str = delimiter self._default: str = default @contextmanager def scope(self, scope_id: str) -> Iterator[None]: """ Enter a new correlation scope. Each new scope is appended to the current one using the delimiter. When the context exits, the previous scope is automatically restored. """ current: str = self._scopes.get() new_scope: str = f'{current}{self._delimiter}{scope_id}' if current else scope_id token = self._scopes.set(new_scope) try: yield finally: self._scopes.reset(token) @property def correlation_id(self) -> str: """ Return the current overall correlation string. If no scope is active, returns the default value. """ current: str = self._scopes.get() return current if current else self._default
class ContextualCorrelator: def __init__(self, delimiter: str='::', default: str='<main>') -> None: pass @contextmanager def scope(self, scope_id: str) -> Iterator[None]: ''' Enter a new correlation scope. Each new scope is appended to the current one using the delimiter. When the context exits, the previous scope is automatically restored. ''' pass @property def correlation_id(self) -> str: ''' Return the current overall correlation string. If no scope is active, returns the default value. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/logging.py
flux0_core.logging.ContextualLogger
import structlog import asyncio from flux0_core.contextual_correlator import ContextualCorrelator import time import contextvars from structlog.types import EventDict from structlog.typing import Processor from flux0_core.ids import gen_id from typing import Any, Dict, Iterator, Optional, override import logging from contextlib import contextmanager class ContextualLogger(Logger): """ A structured logger with support for correlation and scopes. Correlation links related logs across systems that are part of the same context (e.g., HTTP Request), while scope provides finer-grained tracking within a process." What is Corrleation? Correlation refers to a unique identifier (correlation ID) that links related logs together across different services. Useful for tracking a request end-to-end across microservices, threads, or async tasks. Typically, a correlation ID remains the same across multiple logs that are part of the same "request" (e.g., HTTP request), "session" or "transaction." Example of Correlation: When a user makes an HTTP request, we generate a correlation ID and attach it to all logs where multiple services handle this request should log with the same correlation ID. { "timestamp": "2025-02-26T10:41:37.917Z", "level": "info", "event": "User login request received", "correlation_id": "request-12345" } What is scope? Scope is more granular and refers to a specific context within a process. Scopes allow to track sub-operations within a correlated request. Each scope is added on top of the existing correlation ID, making logs more informative. Example of Scope: A user logs in (correlation_id: request-12345): { "timestamp": "2025-02-26T10:42:10.917Z", "level": "info", "event": "Querying user data", "correlation_id": "request-12345", "scope": "[UserLogin]" } How Are They Used Together? (1) A user logs in → Generate a correlation ID with correlator.scope("UserLogin"): logger.info("User login request received") log output: { ... "correlation_id": "request-12345", "scope": "[UserLogin]" } (2) Inside the login request, we fetch user details → Add a scope with logger.scope("FetchUser"): logger.info("Fetching user details from DB") log output: { ... "correlation_id": "request-12345", "scope": "[UserLogin][FetchUser]" } (3) Validate credentials → Add a scope with logger.scope("ValidateCredentials"): logger.info("Validating user credentials") log output: { ... "correlation_id": "request-12345", "scope": "[UserLogin][FetchUser][ValidateCredentials]" } """ def __init__(self, correlator: ContextualCorrelator, level: LogLevel=LogLevel.DEBUG, logger_id: str | None=None, renderer: Optional[Processor]=None) -> None: self.correlator = correlator self._instance_id = gen_id() self._scopes: contextvars.ContextVar[str] = contextvars.ContextVar(f'logger_{self._instance_id}_scopes', default='') self.raw_logger = logging.getLogger(logger_id or 'flux0') self.raw_logger.setLevel(level.logging_level()) def add_context_fields(_: 'ContextualLogger', __: str, event_dict: EventDict) -> EventDict: """ Processor to inject correlation_id and scope_id into the structured log. Since structlog does not pass our StructuredLogger instance, we retrieve the values from context. """ event_dict['correlation'] = self.correlator.correlation_id if self._scopes.get(): event_dict['scope'] = self._scopes.get() return event_dict renderer = renderer if renderer is not None else structlog.processors.JSONRenderer() self._logger = structlog.wrap_logger(self.raw_logger, processors=[structlog.processors.TimeStamper(fmt='iso'), structlog.stdlib.add_log_level, structlog.stdlib.filter_by_level, add_context_fields, structlog.stdlib.PositionalArgumentsFormatter(), structlog.processors.StackInfoRenderer(), structlog.processors.format_exc_info, renderer], wrapper_class=structlog.make_filtering_bound_logger(logging.DEBUG)) @override def set_level(self, level: LogLevel) -> None: self.raw_logger.setLevel(level.logging_level()) def debug(self, message: str, *args: Any, **kwargs: Any) -> None: self._logger.debug(self._format_message(message), *args, **kwargs) def info(self, message: str, *args: Any, **kwargs: Any) -> None: self._logger.info(self._format_message(message), *args, **kwargs) def warning(self, message: str, *args: Any, **kwargs: Any) -> None: self._logger.warning(self._format_message(message), *args, **kwargs) def error(self, message: str, *args: Any, **kwargs: Any) -> None: self._logger.error(self._format_message(message), *args, **kwargs) def critical(self, message: str, *args: Any, **kwargs: Any) -> None: self._logger.critical(self._format_message(message), *args, **kwargs) @contextmanager def scope(self, scope_id: str) -> Iterator[None]: """ Extend the logging scope with an additional identifier. """ current_scope = self._scopes.get() new_scope = f'{current_scope}[{scope_id}]' if current_scope else f'[{scope_id}]' token = self._scopes.set(new_scope) try: yield finally: self._scopes.reset(token) @property def current_scope(self) -> str: return self._scopes.get() if self._scopes.get() else '' @contextmanager def operation(self, name: str, props: Optional[Dict[str, Any]]=None) -> Iterator[None]: """ Context manager that logs the beginning and end of an operation, including timing and error handling. """ props = props or {} start_time = time.time() self.info(f'{name} started', **props) try: yield elapsed = time.time() - start_time self.info(f'{name} completed in {elapsed:.3f}s', **props) except asyncio.CancelledError: elapsed = time.time() - start_time self.warning(f'{name} cancelled after {elapsed:.3f}s', **props) raise except Exception: self.error(f'{name} failed', **props) self.error('Exception details', exc_info=True) raise def _format_message(self, message: str) -> str: """ Prepend the current correlation id and scope information to the message. """ correlation = self.correlator.correlation_id return f'[{correlation}]{self.current_scope} {message}'
class ContextualLogger(Logger): ''' A structured logger with support for correlation and scopes. Correlation links related logs across systems that are part of the same context (e.g., HTTP Request), while scope provides finer-grained tracking within a process." What is Corrleation? Correlation refers to a unique identifier (correlation ID) that links related logs together across different services. Useful for tracking a request end-to-end across microservices, threads, or async tasks. Typically, a correlation ID remains the same across multiple logs that are part of the same "request" (e.g., HTTP request), "session" or "transaction." Example of Correlation: When a user makes an HTTP request, we generate a correlation ID and attach it to all logs where multiple services handle this request should log with the same correlation ID. { "timestamp": "2025-02-26T10:41:37.917Z", "level": "info", "event": "User login request received", "correlation_id": "request-12345" } What is scope? Scope is more granular and refers to a specific context within a process. Scopes allow to track sub-operations within a correlated request. Each scope is added on top of the existing correlation ID, making logs more informative. Example of Scope: A user logs in (correlation_id: request-12345): { "timestamp": "2025-02-26T10:42:10.917Z", "level": "info", "event": "Querying user data", "correlation_id": "request-12345", "scope": "[UserLogin]" } How Are They Used Together? (1) A user logs in → Generate a correlation ID with correlator.scope("UserLogin"): logger.info("User login request received") log output: { ... "correlation_id": "request-12345", "scope": "[UserLogin]" } (2) Inside the login request, we fetch user details → Add a scope with logger.scope("FetchUser"): logger.info("Fetching user details from DB") log output: { ... "correlation_id": "request-12345", "scope": "[UserLogin][FetchUser]" } (3) Validate credentials → Add a scope with logger.scope("ValidateCredentials"): logger.info("Validating user credentials") log output: { ... "correlation_id": "request-12345", "scope": "[UserLogin][FetchUser][ValidateCredentials]" } ''' def __init__(self, correlator: ContextualCorrelator, level: LogLevel=LogLevel.DEBUG, logger_id: str | None=None, renderer: Optional[Processor]=None) -> None: pass def add_context_fields(_: 'ContextualLogger', __: str, event_dict: EventDict) -> EventDict: ''' Processor to inject correlation_id and scope_id into the structured log. Since structlog does not pass our StructuredLogger instance, we retrieve the values from context. ''' pass @override def set_level(self, level: LogLevel) -> None: pass def debug(self, message: str, *args: Any, **kwargs: Any) -> None: pass def info(self, message: str, *args: Any, **kwargs: Any) -> None: pass def warning(self, message: str, *args: Any, **kwargs: Any) -> None: pass def error(self, message: str, *args: Any, **kwargs: Any) -> None: pass def critical(self, message: str, *args: Any, **kwargs: Any) -> None: pass @contextmanager def scope(self, scope_id: str) -> Iterator[None]: ''' Extend the logging scope with an additional identifier. ''' pass @property def current_scope(self) -> str: pass @contextmanager def operation(self, name: str, props: Optional[Dict[str, Any]]=None) -> Iterator[None]: ''' Context manager that logs the beginning and end of an operation, including timing and error handling. ''' pass def _format_message(self, message: str) -> str: ''' Prepend the current correlation id and scope information to the message. ''' pass
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/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/logging.py
flux0_core.logging.LogLevel
import logging from enum import IntEnum, auto class LogLevel(IntEnum): DEBUG = auto() INFO = auto() WARNING = auto() ERROR = auto() CRITICAL = auto() def logging_level(self) -> int: return {LogLevel.DEBUG: logging.DEBUG, LogLevel.INFO: logging.INFO, LogLevel.WARNING: logging.WARNING, LogLevel.ERROR: logging.ERROR, LogLevel.CRITICAL: logging.CRITICAL}[self]
class LogLevel(IntEnum): def logging_level(self) -> int: pass
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/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/logging.py
flux0_core.logging.Logger
from contextlib import contextmanager from abc import ABC, abstractmethod from typing import Any, Dict, Iterator, Optional, override class Logger(ABC): """ Logging interface for structured logs with support for scopes and operation measurement. """ @abstractmethod def set_level(self, level: LogLevel) -> None: """Set the logging level.""" ... @abstractmethod def debug(self, message: str, *args: Any, **kwargs: Any) -> None: ... @abstractmethod def info(self, message: str, *args: Any, **kwargs: Any) -> None: ... @abstractmethod def warning(self, message: str, *args: Any, **kwargs: Any) -> None: ... @abstractmethod def error(self, message: str, *args: Any, **kwargs: Any) -> None: ... @abstractmethod def critical(self, message: str, *args: Any, **kwargs: Any) -> None: ... @abstractmethod @contextmanager def scope(self, scope_id: str) -> Iterator[None]: """ Create a new logging scope. Any log issued within this context will include the provided scope id. """ ... @abstractmethod @contextmanager def operation(self, name: str, props: Optional[Dict[str, Any]]=None) -> Iterator[None]: """ Context manager that logs the start and end of an operation. Measures execution time and handles cancellations/exceptions. """ ...
class Logger(ABC): ''' Logging interface for structured logs with support for scopes and operation measurement. ''' @abstractmethod def set_level(self, level: LogLevel) -> None: '''Set the logging level.''' pass @abstractmethod def debug(self, message: str, *args: Any, **kwargs: Any) -> None: pass @abstractmethod def info(self, message: str, *args: Any, **kwargs: Any) -> None: pass @abstractmethod def warning(self, message: str, *args: Any, **kwargs: Any) -> None: pass @abstractmethod def error(self, message: str, *args: Any, **kwargs: Any) -> None: pass @abstractmethod def critical(self, message: str, *args: Any, **kwargs: Any) -> None: pass @abstractmethod @contextmanager def scope(self, scope_id: str) -> Iterator[None]: ''' Create a new logging scope. Any log issued within this context will include the provided scope id. ''' pass @abstractmethod @contextmanager def operation(self, name: str, props: Optional[Dict[str, Any]]=None) -> Iterator[None]: ''' Context manager that logs the start and end of an operation. Measures execution time and handles cancellations/exceptions. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/logging.py
flux0_core.logging.StdoutLogger
import logging from flux0_core.contextual_correlator import ContextualCorrelator import structlog class StdoutLogger(ContextualLogger): def __init__(self, correlator: ContextualCorrelator, log_level: LogLevel=LogLevel.DEBUG, logger_id: str | None=None, json: bool=True) -> None: super().__init__(correlator, log_level, logger_id, structlog.dev.ConsoleRenderer(colors=True) if not json else None) self.raw_logger.addHandler(logging.StreamHandler())
class StdoutLogger(ContextualLogger): def __init__(self, correlator: ContextualCorrelator, log_level: LogLevel=LogLevel.DEBUG, logger_id: str | None=None, json: bool=True) -> None: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/recordings.py
flux0_core.recordings.RecordedChunkPayload
from flux0_core.sessions import EventId, EventSource, EventType, MessageEventData, SessionId, StatusEventData, ToolEventData from flux0_stream.types import JsonPatchOperation from flux0_core.types import JSONSerializable from typing import Literal, Mapping, NewType, Optional, Sequence, Tuple, TypedDict, Union class RecordedChunkPayload(TypedDict): """Captured JSON Patch 'chunk' as sent to the client.""" correlation_id: str event_id: EventId seq: int patches: list[JsonPatchOperation] metadata: Mapping[str, JSONSerializable]
class RecordedChunkPayload(TypedDict): '''Captured JSON Patch 'chunk' as sent to the client.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/recordings.py
flux0_core.recordings.RecordedEmittedPayload
from flux0_core.types import JSONSerializable from flux0_core.sessions import EventId, EventSource, EventType, MessageEventData, SessionId, StatusEventData, ToolEventData from typing import Literal, Mapping, NewType, Optional, Sequence, Tuple, TypedDict, Union class RecordedEmittedPayload(TypedDict): """Captured non-chunk event (status/message/tool/custom) as sent to the client.""" id: EventId source: EventSource type: EventType correlation_id: str data: Union[MessageEventData, StatusEventData, ToolEventData] metadata: Optional[Mapping[str, JSONSerializable]]
class RecordedEmittedPayload(TypedDict): '''Captured non-chunk event (status/message/tool/custom) as sent to the client.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/recordings.py
flux0_core.recordings.RecordedEvent
from datetime import datetime from dataclasses import dataclass @dataclass(frozen=True) class RecordedEvent: """ One persisted event from a recorded stream. Invariants: • Unique (recording_id, offset) • Header frame: kind == "header" and offset == 0 (exactly one per recording) • All other frames: offset >= 1 • created_at is the backend arrival timestamp used for pacing during replay """ id: RecordedEventId recording_id: RecordingId offset: int kind: RecordedEventKind created_at: datetime payload: RecordedEventPayload
@dataclass(frozen=True) class RecordedEvent: ''' One persisted event from a recorded stream. Invariants: • Unique (recording_id, offset) • Header frame: kind == "header" and offset == 0 (exactly one per recording) • All other frames: offset >= 1 • created_at is the backend arrival timestamp used for pacing during replay ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/recordings.py
flux0_core.recordings.RecordedHeaderPayload
from flux0_core.sessions import EventId, EventSource, EventType, MessageEventData, SessionId, StatusEventData, ToolEventData from typing import Literal, Mapping, NewType, Optional, Sequence, Tuple, TypedDict, Union class RecordedHeaderPayload(TypedDict): """ Sentinel header frame for a recording. Exactly one per recording at offset == 0. """ source_session_id: SessionId
class RecordedHeaderPayload(TypedDict): ''' Sentinel header frame for a recording. Exactly one per recording at offset == 0. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/recordings.py
flux0_core.recordings.RecordingStore
from flux0_core.sessions import EventId, EventSource, EventType, MessageEventData, SessionId, StatusEventData, ToolEventData from abc import ABC, abstractmethod from typing import Literal, Mapping, NewType, Optional, Sequence, Tuple, TypedDict, Union from datetime import datetime class RecordingStore(ABC): """ Minimal store interface for recording + interactive replay. Storage model: - Single normalized collection/table of RecordedEvent documents. - Exactly one header per recording at offset == 0. - All stream frames have offset >= 1. - Offsets are assigned atomically, strictly increasing per recording_id. Concurrency: - Implementations MUST assign offsets with a per-recording atomic counter. DB: - Unique: { recording_id: 1, offset: 1 } - Partial unique (headers): (recording_id) with filter { kind: "header", offset: 0 } - Lookup by session: payload.source_session_id (partial filter { kind: "header" }) - Should support efficient querying by recording_id and offset. """ @abstractmethod async def create_recording(self, source_session_id: SessionId, *, recording_id: Optional[RecordingId]=None, created_at: Optional[datetime]=None) -> RecordedEvent: """ Create the header frame (kind='header', offset=0) for a new recording. Returns: The persisted header event. Must: - Generate a RecordingId if not provided - Enforce: exactly one header per recording with offset == 0 """ @abstractmethod async def append_emitted(self, recording_id: RecordingId, payload: RecordedEmittedPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: """ Append an 'emitted' event (status/message/tool/custom) to the recording. Returns: The persisted emitted event. Must: - Atomically assign the next monotonic offset (>= 1) per recording_id """ @abstractmethod async def append_chunk(self, recording_id: RecordingId, payload: RecordedChunkPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: """ Append a 'chunk' frame (JSON Patch) to the recording. Must: - Same guarantees as append_emitted() """ @abstractmethod async def read_header_by_source_session_id(self, source_session_id: SessionId) -> Optional[RecordedEvent]: """ Fetch the header (offset == 0, kind='header') for the recording whose payload.source_session_id == source_session_id. Returns: - The header RecordedEvent if exactly one exists. - None if not found. Must: - avoid having multiple recordings with the same source_session_id. """ ... @abstractmethod async def read_header_by_recording_id(self, recording_id: RecordingId) -> Optional[RecordedEvent]: """ Fetch the header frame (offset == 0) for a recording. Returns None if not found. """ @abstractmethod async def read_next_turn_range_after_offset(self, recording_id: RecordingId, after_offset: int) -> Optional[TurnRange]: """ Return the next USER-anchored turn that begins strictly AFTER `after_offset`. Semantics: • A turn STARTS at the next 'emitted' frame whose payload.source == 'user'. • A turn ENDS just before the following such user frame. • If there is no following user frame, end_offset_exclusive = None (stream to end). • Header (offset 0) is never part of a turn. Returns: • (start_offset_inclusive, end_offset_exclusive) or None if no subsequent user turn. Notes: • Pass `after_offset=0` for the very first lookup (header is at 0). • If you later want to narrow anchors to only user *messages*, you can implement the predicate as: kind == 'emitted' AND payload.source == 'user' AND payload.type == 'message' For v1, source=='user' is sufficient given your recording policy. """ @abstractmethod async def read_frames_range(self, recording_id: RecordingId, start_offset_inclusive: int, end_offset_exclusive: Optional[int]=None, *, limit: Optional[int]=None) -> Sequence[RecordedEvent]: """ Read frames ordered by offset for [start_offset_inclusive, end_offset_exclusive). If end_offset_exclusive is None, read to the end (respect `limit` if provided). Must: • Return frames sorted by offset ascending. • Exclude the header unless start_offset_inclusive == 0 (normally you'll pass >= 1). • Return <= limit items when 'limit' is provided. """
class RecordingStore(ABC): ''' Minimal store interface for recording + interactive replay. Storage model: - Single normalized collection/table of RecordedEvent documents. - Exactly one header per recording at offset == 0. - All stream frames have offset >= 1. - Offsets are assigned atomically, strictly increasing per recording_id. Concurrency: - Implementations MUST assign offsets with a per-recording atomic counter. DB: - Unique: { recording_id: 1, offset: 1 } - Partial unique (headers): (recording_id) with filter { kind: "header", offset: 0 } - Lookup by session: payload.source_session_id (partial filter { kind: "header" }) - Should support efficient querying by recording_id and offset. ''' @abstractmethod async def create_recording(self, source_session_id: SessionId, *, recording_id: Optional[RecordingId]=None, created_at: Optional[datetime]=None) -> RecordedEvent: ''' Create the header frame (kind='header', offset=0) for a new recording. Returns: The persisted header event. Must: - Generate a RecordingId if not provided - Enforce: exactly one header per recording with offset == 0 ''' pass @abstractmethod async def append_emitted(self, recording_id: RecordingId, payload: RecordedEmittedPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: ''' Append an 'emitted' event (status/message/tool/custom) to the recording. Returns: The persisted emitted event. Must: - Atomically assign the next monotonic offset (>= 1) per recording_id ''' pass @abstractmethod async def append_chunk(self, recording_id: RecordingId, payload: RecordedChunkPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: ''' Append a 'chunk' frame (JSON Patch) to the recording. Must: - Same guarantees as append_emitted() ''' pass @abstractmethod async def read_header_by_source_session_id(self, source_session_id: SessionId) -> Optional[RecordedEvent]: ''' Fetch the header (offset == 0, kind='header') for the recording whose payload.source_session_id == source_session_id. Returns: - The header RecordedEvent if exactly one exists. - None if not found. Must: - avoid having multiple recordings with the same source_session_id. ''' pass @abstractmethod async def read_header_by_recording_id(self, recording_id: RecordingId) -> Optional[RecordedEvent]: ''' Fetch the header frame (offset == 0) for a recording. Returns None if not found. ''' pass @abstractmethod async def read_next_turn_range_after_offset(self, recording_id: RecordingId, after_offset: int) -> Optional[TurnRange]: ''' Return the next USER-anchored turn that begins strictly AFTER `after_offset`. Semantics: • A turn STARTS at the next 'emitted' frame whose payload.source == 'user'. • A turn ENDS just before the following such user frame. • If there is no following user frame, end_offset_exclusive = None (stream to end). • Header (offset 0) is never part of a turn. Returns: • (start_offset_inclusive, end_offset_exclusive) or None if no subsequent user turn. Notes: • Pass `after_offset=0` for the very first lookup (header is at 0). • If you later want to narrow anchors to only user *messages*, you can implement the predicate as: kind == 'emitted' AND payload.source == 'user' AND payload.type == 'message' For v1, source=='user' is sufficient given your recording policy. ''' pass @abstractmethod async def read_frames_range(self, recording_id: RecordingId, start_offset_inclusive: int, end_offset_exclusive: Optional[int]=None, *, limit: Optional[int]=None) -> Sequence[RecordedEvent]: ''' Read frames ordered by offset for [start_offset_inclusive, end_offset_exclusive). If end_offset_exclusive is None, read to the end (respect `limit` if provided). Must: • Return frames sorted by offset ascending. • Exclude the header unless start_offset_inclusive == 0 (normally you'll pass >= 1). • Return <= limit items when 'limit' is provided. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.ContentPart
from flux0_core.types import JSONSerializable from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union class ContentPart(TypedDict): type: Literal['content'] content: JSONSerializable
class ContentPart(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.ControlOptions
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union class ControlOptions(TypedDict, total=False): mode: SessionMode
class ControlOptions(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.Event
from dataclasses import dataclass from flux0_core.types import JSONSerializable from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from datetime import datetime @dataclass(frozen=True) class Event: id: EventId source: EventSource type: EventType offset: int correlation_id: str data: Union[MessageEventData, StatusEventData, ToolEventData] deleted: bool created_at: datetime metadata: Optional[Mapping[str, JSONSerializable]]
@dataclass(frozen=True) class Event: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.MessageEventData
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union class MessageEventData(TypedDict): type: Literal['message'] participant: Participant flagged: NotRequired[bool] tags: NotRequired[list[str]] parts: List[Union[ContentPart, ReasoningPart, ToolCallPart]]
class MessageEventData(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.Participant
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from flux0_core.users import UserId from flux0_core.agents import AgentId class Participant(TypedDict): id: NotRequired[AgentId | UserId | None] name: str
class Participant(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.ReasoningPart
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from flux0_core.types import JSONSerializable class ReasoningPart(TypedDict): type: Literal['reasoning'] reasoning: JSONSerializable
class ReasoningPart(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.Session
from dataclasses import dataclass from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from flux0_core.users import UserId from flux0_core.agents import AgentId from datetime import datetime from flux0_core.types import JSONSerializable @dataclass(frozen=True) class Session: id: SessionId agent_id: AgentId user_id: UserId mode: SessionMode title: Optional[str] consumption_offsets: Mapping[ConsumerId, int] created_at: datetime metadata: Optional[Mapping[str, JSONSerializable]]
@dataclass(frozen=True) class Session: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.SessionStore
from flux0_core.types import JSONSerializable from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from flux0_core.agents import AgentId from datetime import datetime from flux0_core.users import UserId from abc import ABC, abstractmethod class SessionStore(ABC): @abstractmethod async def create_session(self, user_id: UserId, agent_id: AgentId, id: Optional[SessionId]=None, mode: Optional[SessionMode]=None, title: Optional[str]=None, metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Session: ... @abstractmethod async def read_session(self, session_id: SessionId) -> Optional[Session]: ... @abstractmethod async def delete_session(self, session_id: SessionId) -> bool: ... @abstractmethod async def update_session(self, session_id: SessionId, params: SessionUpdateParams) -> Session: ... @abstractmethod async def list_sessions(self, agent_id: Optional[AgentId]=None, user_id: Optional[UserId]=None) -> Sequence[Session]: ... @abstractmethod async def create_event(self, session_id: SessionId, source: EventSource, type: EventType, correlation_id: str, data: Union[MessageEventData, StatusEventData, ToolEventData], metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Event: ... @abstractmethod async def read_event(self, session_id: SessionId, event_id: EventId) -> Optional[Event]: ... @abstractmethod async def delete_event(self, event_id: EventId) -> bool: ... @abstractmethod async def list_events(self, session_id: SessionId, source: Optional[EventSource]=None, correlation_id: Optional[str]=None, types: Sequence[EventType]=[], min_offset: Optional[int]=None, exclude_deleted: bool=True) -> Sequence[Event]: ...
class SessionStore(ABC): @abstractmethod async def create_session(self, user_id: UserId, agent_id: AgentId, id: Optional[SessionId]=None, mode: Optional[SessionMode]=None, title: Optional[str]=None, metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Session: pass @abstractmethod async def read_session(self, session_id: SessionId) -> Optional[Session]: pass @abstractmethod async def delete_session(self, session_id: SessionId) -> bool: pass @abstractmethod async def update_session(self, session_id: SessionId, params: SessionUpdateParams) -> Session: pass @abstractmethod async def list_sessions(self, agent_id: Optional[AgentId]=None, user_id: Optional[UserId]=None) -> Sequence[Session]: pass @abstractmethod async def create_event(self, session_id: SessionId, source: EventSource, type: EventType, correlation_id: str, data: Union[MessageEventData, StatusEventData, ToolEventData], metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Event: pass @abstractmethod async def read_event(self, session_id: SessionId, event_id: EventId) -> Optional[Event]: pass @abstractmethod async def delete_event(self, event_id: EventId) -> bool: pass @abstractmethod async def list_events(self, session_id: SessionId, source: Optional[EventSource]=None, correlation_id: Optional[str]=None, types: Sequence[EventType]=[], min_offset: Optional[int]=None, exclude_deleted: bool=True) -> Sequence[Event]: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.SessionUpdateParams
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from flux0_core.agents import AgentId from flux0_core.types import JSONSerializable from flux0_core.users import UserId class SessionUpdateParams(TypedDict, total=False): user_id: UserId agent_id: AgentId mode: SessionMode title: Optional[str] consumption_offsets: Mapping[ConsumerId, int] metadata: Optional[Mapping[str, JSONSerializable]]
class SessionUpdateParams(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.StatusEventData
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from flux0_core.types import JSONSerializable class StatusEventData(TypedDict): type: Literal['status'] acknowledged_offset: NotRequired[int] status: SessionStatus data: NotRequired[JSONSerializable]
class StatusEventData(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.ToolCall
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union from flux0_core.types import JSONSerializable class ToolCall(TypedDict): tool_call_id: str tool_name: str args: Mapping[str, JSONSerializable] result: NotRequired[ToolResult] error: NotRequired[str]
class ToolCall(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.ToolCallPart
from flux0_core.types import JSONSerializable from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union class ToolCallPart(TypedDict): type: ToolCallPartType tool_call_id: str tool_name: str args: JSONSerializable
class ToolCallPart(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.ToolEventData
from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union class ToolEventData(TypedDict): type: ToolCallResultType tool_calls: list[ToolCall]
class ToolEventData(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/sessions.py
flux0_core.sessions.ToolResult
from flux0_core.types import JSONSerializable from typing import List, Literal, Mapping, NewType, NotRequired, Optional, Sequence, TypeAlias, TypedDict, Union class ToolResult(TypedDict): data: JSONSerializable metadata: Mapping[str, JSONSerializable] control: ControlOptions
class ToolResult(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/users.py
flux0_core.users.User
from dataclasses import dataclass from typing import NewType, Optional, TypedDict from datetime import datetime @dataclass(frozen=True) class User: id: UserId sub: str name: str email: Optional[str] created_at: datetime
@dataclass(frozen=True) class User: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/users.py
flux0_core.users.UserStore
from abc import ABC, abstractmethod from datetime import datetime from typing import NewType, Optional, TypedDict class UserStore(ABC): @abstractmethod async def create_user(self, sub: str, name: str, email: Optional[str]=None, created_at: Optional[datetime]=None) -> User: ... @abstractmethod async def read_user(self, user_id: UserId) -> Optional[User]: ... @abstractmethod async def read_user_by_sub(self, sub: str) -> Optional[User]: ... @abstractmethod async def update_user(self, user_id: UserId, params: UserUpdateParams) -> User: ...
class UserStore(ABC): @abstractmethod async def create_user(self, sub: str, name: str, email: Optional[str]=None, created_at: Optional[datetime]=None) -> User: pass @abstractmethod async def read_user(self, user_id: UserId) -> Optional[User]: pass @abstractmethod async def read_user_by_sub(self, sub: str) -> Optional[User]: pass @abstractmethod async def update_user(self, user_id: UserId, params: UserUpdateParams) -> User: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/users.py
flux0_core.users.UserUpdateParams
from typing import NewType, Optional, TypedDict class UserUpdateParams(TypedDict, total=False): name: str
class UserUpdateParams(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/api.py
flux0_nanodb.api.DocumentCollection
from typing import Generic, List, Mapping, Optional, Sequence, Tuple, Type from flux0_nanodb.projection import Projection from flux0_nanodb.types import DeleteResult, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from flux0_nanodb.query import QueryFilter from abc import ABC, abstractmethod class DocumentCollection(ABC, Generic[TDocument]): @abstractmethod async def find(self, filters: Optional[QueryFilter], projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: """ Find all documents that match the optional filters. Optionally apply a projection, pagination, and sorting. - `sort` is a list of tuples where: - The first element is the field name. - The second element is the sorting order (`SortOrder.ASC` for ascending or `SortOrder.DESC` for descending). Sorting is applied after filtering but before pagination. """ pass @abstractmethod async def insert_one(self, document: TDocument) -> InsertOneResult: """ Insert a single document into the collection. """ pass @abstractmethod async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: """ Apply a JSON Patch (RFC 6902) to a single document that matches the provided filters. If upsert is True and no document matches, insert a new document. Parameters: filters (QueryFilter): Query to match a document. patch (List[JSONPatchOperation]): JSON Patch operations in a type-safe structured format. upsert (bool): If True, insert a new document if no match is found. Returns: UpdateOneResult: Metadata about the update operation. """ pass @abstractmethod async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: """ Delete the first document that matches the provided filters. """ pass
class DocumentCollection(ABC, Generic[TDocument]): @abstractmethod async def find(self, filters: Optional[QueryFilter], projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: ''' Find all documents that match the optional filters. Optionally apply a projection, pagination, and sorting. - `sort` is a list of tuples where: - The first element is the field name. - The second element is the sorting order (`SortOrder.ASC` for ascending or `SortOrder.DESC` for descending). Sorting is applied after filtering but before pagination. ''' pass @abstractmethod async def insert_one(self, document: TDocument) -> InsertOneResult: ''' Insert a single document into the collection. ''' pass @abstractmethod async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: ''' Apply a JSON Patch (RFC 6902) to a single document that matches the provided filters. If upsert is True and no document matches, insert a new document. Parameters: filters (QueryFilter): Query to match a document. patch (List[JSONPatchOperation]): JSON Patch operations in a type-safe structured format. upsert (bool): If True, insert a new document if no match is found. Returns: UpdateOneResult: Metadata about the update operation. ''' pass @abstractmethod async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: ''' Delete the first document that matches the provided filters. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/api.py
flux0_nanodb.api.DocumentDatabase
from abc import ABC, abstractmethod from flux0_nanodb.types import DeleteResult, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from typing import Generic, List, Mapping, Optional, Sequence, Tuple, Type class DocumentDatabase(ABC): @abstractmethod async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: """ Create a new collection with the given name and document schema. """ pass @abstractmethod async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: """ Retrieve an existing collection by its name and document schema. """ pass @abstractmethod async def delete_collection(self, name: str) -> None: """ Delete a collection by its name. """ pass
class DocumentDatabase(ABC): @abstractmethod async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: ''' Create a new collection with the given name and document schema. ''' pass @abstractmethod async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: ''' Retrieve an existing collection by its name and document schema. ''' pass @abstractmethod async def delete_collection(self, name: str) -> None: ''' Delete a collection by its name. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/json.py
flux0_nanodb.json.JsonDocumentCollection
from flux0_nanodb.api import DocumentCollection, DocumentDatabase from pathlib import Path from flux0_nanodb.query import QueryFilter, matches_query from flux0_nanodb.projection import Projection, apply_projection from typing import Any, List, Mapping, Optional, Protocol, Sequence, Tuple, Type, cast import jsonpatch import json from flux0_nanodb.types import DeleteResult, DocumentID, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from flux0_core.async_utils import RWLock from flux0_nanodb.common import convert_patch, validate_is_total class JsonDocumentCollection(DocumentCollection[TDocument]): def __init__(self, name: str, schema: Type[TDocument], data_dir: Path) -> None: self._name = name self._schema = schema self._data_dir = data_dir self._file_path = data_dir / f'{name}.json' self._lock = RWLock() self._data_dir.mkdir(parents=True, exist_ok=True) if not self._file_path.exists(): self._save_documents([]) def _load_documents(self) -> List[TDocument]: """Load documents from the JSON file.""" try: with open(self._file_path, 'r', encoding='utf-8') as f: data = json.load(f, object_hook=_json_object_hook) return cast(List[TDocument], data) except (FileNotFoundError, json.JSONDecodeError): return [] def _save_documents(self, documents: List[TDocument]) -> None: """Save documents to the JSON file.""" with open(self._file_path, 'w', encoding='utf-8') as f: json.dump(documents, f, indent=2, ensure_ascii=False, default=_json_default) async def find(self, filters: Optional[QueryFilter]=None, projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: async with self._lock.reader_lock: documents = self._load_documents() docs: Sequence[TDocument] = [] if filters is None: docs = documents else: docs = [doc for doc in documents if matches_query(filters, doc)] if sort is not None: for field, order in reversed(sort): docs.sort(key=lambda doc: cast(Comparable, doc.get(field, None)), reverse=order == SortingOrder.DESC) if projection: docs = [cast(TDocument, apply_projection(doc, projection)) for doc in docs] if offset is not None: if offset < 0: raise ValueError('Offset must be non-negative') docs = docs[offset:] if limit is not None: if limit < 0: raise ValueError('Limit must be non-negative') docs = docs[:limit] return docs async def insert_one(self, document: TDocument) -> InsertOneResult: validate_is_total(document, self._schema) inserted_id: Optional[DocumentID] = document.get('id') if inserted_id is None: raise ValueError("Document is missing an 'id' field") async with self._lock.writer_lock: documents = self._load_documents() documents.append(document) self._save_documents(documents) return InsertOneResult(acknowledged=True, inserted_id=inserted_id) async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: standard_patch = convert_patch(patch) async with self._lock.writer_lock: documents = self._load_documents() for i, doc in enumerate(documents): if matches_query(filters, doc): try: updated_doc = jsonpatch.apply_patch(doc, standard_patch, in_place=False) except jsonpatch.JsonPatchException as e: raise ValueError('Invalid JSON patch') from e documents[i] = cast(TDocument, updated_doc) self._save_documents(documents) return UpdateOneResult(acknowledged=True, matched_count=1, modified_count=1, upserted_id=None) if upsert: try: new_doc = jsonpatch.apply_patch({}, standard_patch, in_place=False) except jsonpatch.JsonPatchException as e: raise ValueError('Invalid JSON patch for upsert') from e if 'id' not in new_doc: raise ValueError("Upserted document is missing an 'id' field") validate_is_total(new_doc, self._schema) documents.append(cast(TDocument, new_doc)) self._save_documents(documents) return UpdateOneResult(acknowledged=True, matched_count=0, modified_count=0, upserted_id=new_doc['id']) return UpdateOneResult(acknowledged=True, matched_count=0, modified_count=0, upserted_id=None) async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: async with self._lock.writer_lock: documents = self._load_documents() for i, doc in enumerate(documents): if matches_query(filters, doc): removed = documents.pop(i) self._save_documents(documents) return DeleteResult(acknowledged=True, deleted_count=1, deleted_document=removed) return DeleteResult(acknowledged=True, deleted_count=0, deleted_document=None)
class JsonDocumentCollection(DocumentCollection[TDocument]): def __init__(self, name: str, schema: Type[TDocument], data_dir: Path) -> None: pass def _load_documents(self) -> List[TDocument]: '''Load documents from the JSON file.''' pass def _save_documents(self, documents: List[TDocument]) -> None: '''Save documents to the JSON file.''' pass async def find(self, filters: Optional[QueryFilter]=None, projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: pass async def insert_one(self, document: TDocument) -> InsertOneResult: pass async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: pass async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/json.py
flux0_nanodb.json.JsonDocumentDatabase
from flux0_core.async_utils import RWLock from pathlib import Path from flux0_nanodb.api import DocumentCollection, DocumentDatabase from flux0_nanodb.types import DeleteResult, DocumentID, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from typing import Any, List, Mapping, Optional, Protocol, Sequence, Tuple, Type, cast class JsonDocumentDatabase(DocumentDatabase): def __init__(self, data_dir: str='./data') -> None: """ Initialize the JSON document database. Args: data_dir: Directory where JSON files will be stored. Defaults to "./data" """ self._data_dir = Path(data_dir) self._collections: dict[str, JsonDocumentCollection[Any]] = {} self._db_lock = RWLock() self._data_dir.mkdir(parents=True, exist_ok=True) async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: async with self._db_lock.writer_lock: if name in self._collections: raise ValueError(f"Collection '{name}' already exists") collection: JsonDocumentCollection[TDocument] = JsonDocumentCollection(name, schema, self._data_dir) self._collections[name] = collection return collection async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: async with self._db_lock.reader_lock: if name in self._collections: return cast(JsonDocumentCollection[TDocument], self._collections[name]) file_path = self._data_dir / f'{name}.json' if not file_path.exists(): raise ValueError(f"Collection '{name}' does not exist") async with self._db_lock.writer_lock: if name in self._collections: return cast(JsonDocumentCollection[TDocument], self._collections[name]) collection: JsonDocumentCollection[TDocument] = JsonDocumentCollection(name, schema, self._data_dir) self._collections[name] = collection return collection async def delete_collection(self, name: str) -> None: async with self._db_lock.writer_lock: file_path = self._data_dir / f'{name}.json' if name in self._collections: del self._collections[name] if file_path.exists(): file_path.unlink() else: raise ValueError(f"Collection '{name}' does not exist")
class JsonDocumentDatabase(DocumentDatabase): def __init__(self, data_dir: str='./data') -> None: ''' Initialize the JSON document database. Args: data_dir: Directory where JSON files will be stored. Defaults to "./data" ''' pass async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: pass async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: pass async def delete_collection(self, name: str) -> None: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/memory.py
flux0_nanodb.memory.Comparable
from typing import Any, List, Mapping, Optional, Protocol, Sequence, Tuple, Type, cast class Comparable(Protocol): def __lt__(self, other: Any) -> bool: ...
class Comparable(Protocol): def __lt__(self, other: Any) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/memory.py
flux0_nanodb.memory.MemoryDocumentCollection
import jsonpatch from flux0_nanodb.types import DeleteResult, DocumentID, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from flux0_core.async_utils import RWLock from flux0_nanodb.api import DocumentCollection, DocumentDatabase from flux0_nanodb.common import convert_patch, validate_is_total from flux0_nanodb.query import QueryFilter, matches_query from flux0_nanodb.projection import Projection, apply_projection from typing import Any, List, Mapping, Optional, Protocol, Sequence, Tuple, Type, cast class MemoryDocumentCollection(DocumentCollection[TDocument]): def __init__(self, name: str, schema: Type[TDocument]) -> None: self._name = name self._schema = schema self._documents: list[TDocument] = [] self._lock = RWLock() async def find(self, filters: Optional[QueryFilter]=None, projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: async with self._lock.reader_lock: docs: Sequence[TDocument] = [] if filters is None: docs = self._documents else: docs = [doc for doc in self._documents if matches_query(filters, doc)] if sort is not None: for field, order in reversed(sort): docs.sort(key=lambda doc: cast(Comparable, doc.get(field, None)), reverse=order == SortingOrder.DESC) if projection: docs = [cast(TDocument, apply_projection(doc, projection)) for doc in docs] if offset is not None: if offset < 0: raise ValueError('Offset must be non-negative') docs = docs[offset:] if limit is not None: if limit < 0: raise ValueError('Limit must be non-negative') docs = docs[:limit] return docs async def insert_one(self, document: TDocument) -> InsertOneResult: async with self._lock.writer_lock: self._documents.append(document) validate_is_total(document, self._schema) inserted_id: Optional[DocumentID] = document.get('id') if inserted_id is None: raise ValueError("Document is missing an 'id' field") return InsertOneResult(acknowledged=True, inserted_id=inserted_id) async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: async with self._lock.writer_lock: standard_patch = convert_patch(patch) for i, doc in enumerate(self._documents): if matches_query(filters, doc): try: updated_doc = jsonpatch.apply_patch(doc, standard_patch, in_place=False) except jsonpatch.JsonPatchException as e: raise ValueError('Invalid JSON patch') from e self._documents[i] = cast(TDocument, updated_doc) return UpdateOneResult(acknowledged=True, matched_count=1, modified_count=1, upserted_id=None) if upsert: try: new_doc = jsonpatch.apply_patch({}, standard_patch, in_place=False) except jsonpatch.JsonPatchException as e: raise ValueError('Invalid JSON patch for upsert') from e if 'id' not in new_doc: raise ValueError("Upserted document is missing an 'id' field") validate_is_total(new_doc, self._schema) self._documents.append(cast(TDocument, new_doc)) return UpdateOneResult(acknowledged=True, matched_count=0, modified_count=0, upserted_id=new_doc['id']) return UpdateOneResult(acknowledged=True, matched_count=0, modified_count=0, upserted_id=None) async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: async with self._lock.writer_lock: for i, doc in enumerate(self._documents): if matches_query(filters, doc): removed = self._documents.pop(i) return DeleteResult(acknowledged=True, deleted_count=1, deleted_document=removed) return DeleteResult(acknowledged=True, deleted_count=0, deleted_document=None)
class MemoryDocumentCollection(DocumentCollection[TDocument]): def __init__(self, name: str, schema: Type[TDocument]) -> None: pass async def find(self, filters: Optional[QueryFilter]=None, projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: pass async def insert_one(self, document: TDocument) -> InsertOneResult: pass async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: pass async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/memory.py
flux0_nanodb.memory.MemoryDocumentDatabase
from flux0_nanodb.api import DocumentCollection, DocumentDatabase from flux0_nanodb.types import DeleteResult, DocumentID, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from typing import Any, List, Mapping, Optional, Protocol, Sequence, Tuple, Type, cast class MemoryDocumentDatabase(DocumentDatabase): def __init__(self) -> None: self._collections: dict[str, MemoryDocumentCollection[Any]] = {} async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: if name in self._collections: raise ValueError(f"Collection '{name}' already exists") collection: MemoryDocumentCollection[TDocument] = MemoryDocumentCollection(name, schema) self._collections[name] = collection return collection async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: collection = self._collections.get(name) if collection is None: raise ValueError(f"Collection '{name}' does not exist") return cast(MemoryDocumentCollection[TDocument], collection) async def delete_collection(self, name: str) -> None: if name in self._collections: del self._collections[name] else: raise ValueError(f"Collection '{name}' does not exist")
class MemoryDocumentDatabase(DocumentDatabase): def __init__(self) -> None: pass async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: pass async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: pass async def delete_collection(self, name: str) -> None: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/mongodb.py
flux0_nanodb.mongodb.MongoDocumentCollection
from flux0_nanodb.api import DocumentCollection, DocumentDatabase from flux0_nanodb.query import And, Comparison, Or, QueryFilter import uuid import jsonpatch from flux0_nanodb.types import DeleteResult, DocumentID, DocumentVersion, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from typing import TYPE_CHECKING, Any, Dict, List, Mapping, Optional, Sequence, Tuple, Type, cast from flux0_nanodb.projection import Projection, apply_projection class MongoDocumentCollection(DocumentCollection[TDocument]): """MongoDB implementation of DocumentCollection using PyMongo async API.""" def __init__(self, collection: Collection[Any], schema: Type[TDocument], ascending_const: Any, descending_const: Any, duplicate_key_error: Any): self.collection = collection self.schema = schema self._ASCENDING = ascending_const self._DESCENDING = descending_const self._DuplicateKeyError = duplicate_key_error def _convert_query_filter_to_mongo(self, query_filter: QueryFilter) -> Dict[str, Any]: """Convert our QueryFilter to MongoDB query format.""" if isinstance(query_filter, Comparison): field = query_filter.path if field == 'id': field = '_id' if query_filter.op == '$eq': return {field: query_filter.value} elif query_filter.op == '$ne': return {field: {'$ne': query_filter.value}} elif query_filter.op == '$gt': return {field: {'$gt': query_filter.value}} elif query_filter.op == '$gte': return {field: {'$gte': query_filter.value}} elif query_filter.op == '$lt': return {field: {'$lt': query_filter.value}} elif query_filter.op == '$lte': return {field: {'$lte': query_filter.value}} elif query_filter.op == '$in': return {field: {'$in': query_filter.value}} else: raise ValueError(f'Unsupported operator: {query_filter.op}') elif isinstance(query_filter, And): return {'$and': [self._convert_query_filter_to_mongo(expr) for expr in query_filter.expressions]} elif isinstance(query_filter, Or): return {'$or': [self._convert_query_filter_to_mongo(expr) for expr in query_filter.expressions]} else: raise ValueError(f'Unsupported query filter type: {type(query_filter)}') def _convert_projection_to_mongo(self, projection: Mapping[str, Projection]) -> Dict[str, int]: """Convert our Projection to MongoDB projection format.""" mongo_projection = {} for field, proj_type in projection.items(): mongo_field = '_id' if field == 'id' else field mongo_projection[mongo_field] = 1 if proj_type == Projection.INCLUDE else 0 return mongo_projection def _convert_sort_to_mongo(self, sort: Sequence[Tuple[str, SortingOrder]]) -> List[Tuple[str, int]]: """Convert our sort specification to MongoDB sort format.""" mongo_sort = [] for field, order in sort: mongo_field = '_id' if field == 'id' else field mongo_order = self._ASCENDING if order == SortingOrder.ASC else self._DESCENDING mongo_sort.append((mongo_field, mongo_order)) return mongo_sort def _convert_from_mongo_doc(self, mongo_doc: Dict[str, Any]) -> TDocument: """Convert MongoDB document to our document format.""" if mongo_doc is None: return None if '_id' in mongo_doc: mongo_doc['id'] = DocumentID(str(mongo_doc['_id'])) del mongo_doc['_id'] return cast(TDocument, mongo_doc) def _convert_to_mongo_doc(self, document: TDocument) -> Dict[str, Any]: """Convert our document format to MongoDB document.""" mongo_doc = dict(document) if 'id' in mongo_doc: mongo_doc['_id'] = mongo_doc['id'] del mongo_doc['id'] return mongo_doc async def find(self, filters: Optional[QueryFilter], projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: """Find all documents that match the optional filters.""" mongo_query = {} if filters: mongo_query = self._convert_query_filter_to_mongo(filters) mongo_projection = None if projection: mongo_projection = self._convert_projection_to_mongo(projection) cursor = self.collection.find(mongo_query, mongo_projection) if sort: mongo_sort = self._convert_sort_to_mongo(sort) cursor = cursor.sort(mongo_sort) if offset: cursor = cursor.skip(offset) if limit: cursor = cursor.limit(limit) results = await cursor.to_list(length=None) documents = [self._convert_from_mongo_doc(doc) for doc in results] if projection: projected_docs = [] for doc in documents: projected_doc = apply_projection(doc, projection) projected_docs.append(cast(TDocument, projected_doc)) return projected_docs return documents async def insert_one(self, document: TDocument) -> InsertOneResult: """Insert a single document into the collection.""" mongo_doc = self._convert_to_mongo_doc(document) if '_id' not in mongo_doc: mongo_doc['_id'] = str(uuid.uuid4()) if 'version' not in mongo_doc: mongo_doc['version'] = DocumentVersion(str(uuid.uuid4())) try: result = await self.collection.insert_one(mongo_doc) return InsertOneResult(acknowledged=result.acknowledged, inserted_id=DocumentID(str(result.inserted_id))) except self._DuplicateKeyError: return InsertOneResult(acknowledged=False, inserted_id=DocumentID(str(mongo_doc['_id']))) async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: """Apply a JSON Patch to a single document that matches the provided filters.""" mongo_query = self._convert_query_filter_to_mongo(filters) existing_doc = await self.collection.find_one(mongo_query) if existing_doc is None and (not upsert): return UpdateOneResult(acknowledged=True, matched_count=0, modified_count=0, upserted_id=None) if existing_doc is None and upsert: new_doc: Dict[str, Any] = {} new_doc['_id'] = str(uuid.uuid4()) new_doc['version'] = DocumentVersion(str(uuid.uuid4())) else: assert existing_doc is not None new_doc = dict(existing_doc) if '_id' in new_doc: new_doc['id'] = str(new_doc['_id']) del new_doc['_id'] patch_obj = jsonpatch.JsonPatch([dict(op) for op in patch]) try: patched_doc = patch_obj.apply(new_doc) except jsonpatch.JsonPatchException as e: raise ValueError(f'Invalid JSON patch: {e}') mongo_doc = dict(patched_doc) if 'id' in mongo_doc: mongo_doc['_id'] = mongo_doc['id'] del mongo_doc['id'] mongo_doc['version'] = DocumentVersion(str(uuid.uuid4())) if existing_doc is None: iresult = await self.collection.insert_one(mongo_doc) return UpdateOneResult(acknowledged=iresult.acknowledged, matched_count=0, modified_count=0, upserted_id=DocumentID(str(iresult.inserted_id))) else: uresult = await self.collection.replace_one(mongo_query, mongo_doc) return UpdateOneResult(acknowledged=uresult.acknowledged, matched_count=uresult.matched_count, modified_count=uresult.modified_count, upserted_id=None) async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: """Delete the first document that matches the provided filters.""" mongo_query = self._convert_query_filter_to_mongo(filters) existing_doc = await self.collection.find_one(mongo_query) deleted_document = None if existing_doc: deleted_document = self._convert_from_mongo_doc(existing_doc) result = await self.collection.delete_one(mongo_query) return DeleteResult(acknowledged=result.acknowledged, deleted_count=result.deleted_count, deleted_document=deleted_document)
class MongoDocumentCollection(DocumentCollection[TDocument]): '''MongoDB implementation of DocumentCollection using PyMongo async API.''' def __init__(self, collection: Collection[Any], schema: Type[TDocument], ascending_const: Any, descending_const: Any, duplicate_key_error: Any): pass def _convert_query_filter_to_mongo(self, query_filter: QueryFilter) -> Dict[str, Any]: '''Convert our QueryFilter to MongoDB query format.''' pass def _convert_projection_to_mongo(self, projection: Mapping[str, Projection]) -> Dict[str, int]: '''Convert our Projection to MongoDB projection format.''' pass def _convert_sort_to_mongo(self, sort: Sequence[Tuple[str, SortingOrder]]) -> List[Tuple[str, int]]: '''Convert our sort specification to MongoDB sort format.''' pass def _convert_from_mongo_doc(self, mongo_doc: Dict[str, Any]) -> TDocument: '''Convert MongoDB document to our document format.''' pass def _convert_to_mongo_doc(self, document: TDocument) -> Dict[str, Any]: '''Convert our document format to MongoDB document.''' pass async def find(self, filters: Optional[QueryFilter], projection: Optional[Mapping[str, Projection]]=None, limit: Optional[int]=None, offset: Optional[int]=None, sort: Optional[Sequence[Tuple[str, SortingOrder]]]=None) -> Sequence[TDocument]: '''Find all documents that match the optional filters.''' pass async def insert_one(self, document: TDocument) -> InsertOneResult: '''Insert a single document into the collection.''' pass async def update_one(self, filters: QueryFilter, patch: List[JSONPatchOperation], upsert: bool=False) -> UpdateOneResult: '''Apply a JSON Patch to a single document that matches the provided filters.''' pass async def delete_one(self, filters: QueryFilter) -> DeleteResult[TDocument]: '''Delete the first document that matches the provided filters.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/mongodb.py
flux0_nanodb.mongodb.MongoDocumentDatabase
from flux0_nanodb.types import DeleteResult, DocumentID, DocumentVersion, InsertOneResult, JSONPatchOperation, SortingOrder, TDocument, UpdateOneResult from typing import TYPE_CHECKING, Any, Dict, List, Mapping, Optional, Sequence, Tuple, Type, cast from flux0_nanodb.api import DocumentCollection, DocumentDatabase class MongoDocumentDatabase(DocumentDatabase): """MongoDB implementation of DocumentDatabase using PyMongo async API.""" def __init__(self, client: AsyncMongoClient[Any], database_name: str): self._ASCENDING, self._DESCENDING, _, self._DuplicateKeyError = _import_mongodb_dependencies() self.client = client self.database = client[database_name] async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: """Create a new collection with the given name and document schema.""" collection = self.database[name] return MongoDocumentCollection(collection, schema, self._ASCENDING, self._DESCENDING, self._DuplicateKeyError) async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: """Retrieve an existing collection by its name and document schema.""" collection_names = await self.database.list_collection_names() if name not in collection_names: raise ValueError(f"Collection '{name}' does not exist") collection = self.database[name] return MongoDocumentCollection(collection, schema, self._ASCENDING, self._DESCENDING, self._DuplicateKeyError) async def delete_collection(self, name: str) -> None: """Delete a collection by its name.""" await self.database.drop_collection(name)
class MongoDocumentDatabase(DocumentDatabase): '''MongoDB implementation of DocumentDatabase using PyMongo async API.''' def __init__(self, client: AsyncMongoClient[Any], database_name: str): pass async def create_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: '''Create a new collection with the given name and document schema.''' pass async def get_collection(self, name: str, schema: Type[TDocument]) -> DocumentCollection[TDocument]: '''Retrieve an existing collection by its name and document schema.''' pass async def delete_collection(self, name: str) -> None: '''Delete a collection by its name.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/projection.py
flux0_nanodb.projection.Projection
from enum import Enum class Projection(Enum): INCLUDE = 1 EXCLUDE = 0
class Projection(Enum): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/query.py
flux0_nanodb.query.And
from dataclasses import dataclass from typing import Any, List, Literal, Mapping, Union @dataclass(frozen=True) class And: """ A logical 'AND' of a list of query expressions. """ expressions: List[QueryFilter]
@dataclass(frozen=True) class And: ''' A logical 'AND' of a list of query expressions. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/query.py
flux0_nanodb.query.Comparison
from typing import Any, List, Literal, Mapping, Union from dataclasses import dataclass @dataclass(frozen=True) class Comparison: """ Represents a filter that compares a path to a literal value. For the "$in" operator, `value` should be a list of literal values. """ path: str op: Operator value: Union[LiteralValue, List[LiteralValue]]
@dataclass(frozen=True) class Comparison: ''' Represents a filter that compares a path to a literal value. For the "$in" operator, `value` should be a list of literal values. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/query.py
flux0_nanodb.query.Or
from dataclasses import dataclass from typing import Any, List, Literal, Mapping, Union @dataclass(frozen=True) class Or: """ A logical 'OR' of a list of query expressions. """ expressions: List[QueryFilter]
@dataclass(frozen=True) class Or: ''' A logical 'OR' of a list of query expressions. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.AddOp
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union class AddOp(TypedDict): op: Literal['add'] path: str value: Any
class AddOp(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.BaseDocument
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union class BaseDocument(TypedDict, total=False): id: DocumentID version: DocumentVersion
class BaseDocument(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.CopyOp
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union class CopyOp(TypedDict): op: Literal['copy'] from_: str path: str
class CopyOp(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.DeleteResult
from dataclasses import dataclass from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union @dataclass(frozen=True) class DeleteResult(Generic[TDocument]): acknowledged: bool deleted_count: int deleted_document: Optional[TDocument]
@dataclass(frozen=True) class DeleteResult(Generic[TDocument]): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.InsertOneResult
from dataclasses import dataclass @dataclass(frozen=True) class InsertOneResult: acknowledged: bool inserted_id: DocumentID
@dataclass(frozen=True) class InsertOneResult: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.MoveOp
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union class MoveOp(TypedDict): op: Literal['move'] from_: str path: str
class MoveOp(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.RemoveOp
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union class RemoveOp(TypedDict): op: Literal['remove'] path: str
class RemoveOp(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.ReplaceOp
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union class ReplaceOp(TypedDict): op: Literal['replace'] path: str value: Any
class ReplaceOp(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.SortingOrder
from enum import Enum class SortingOrder(Enum): ASC = True DESC = False
class SortingOrder(Enum): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.TestOp
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union class TestOp(TypedDict): op: Literal['test'] path: str value: Any
class TestOp(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/nanodb/src/flux0_nanodb/types.py
flux0_nanodb.types.UpdateOneResult
from typing import Any, Generic, Literal, NewType, Optional, TypedDict, TypeVar, Union from dataclasses import dataclass @dataclass(frozen=True) class UpdateOneResult: acknowledged: bool matched_count: int modified_count: int upserted_id: Optional[DocumentID]
@dataclass(frozen=True) class UpdateOneResult: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/app.py
flux0_server.app.SPAStaticFiles
import os from fastapi import APIRouter, FastAPI, Request, Response, status from typing import Any, Awaitable, Callable from fastapi.staticfiles import StaticFiles class SPAStaticFiles(StaticFiles): async def get_response(self, path: str, scope: Any) -> Response: assert isinstance(self.directory, str), 'Static directory must be a string' full_path = os.path.join(self.directory, path) if os.path.isfile(full_path): return await super().get_response(path, scope) return await super().get_response('index.html', scope)
class SPAStaticFiles(StaticFiles): async def get_response(self, path: str, scope: Any) -> Response: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/container_factory.py
flux0_server.container_factory.ContainerAgentRunnerFactory
from flux0_core.agent_runners.api import AgentRunner, AgentRunnerFactory from typing import override from lagom import Container from flux0_core.agents import AgentType class ContainerAgentRunnerFactory(AgentRunnerFactory): def __init__(self, container: Container) -> None: self.container = container @override def create_runner(self, agent_type: AgentType) -> AgentRunner: for defi in self.container.defined_types: if not isinstance(defi, type): continue if issubclass(defi, AgentRunner) and getattr(defi, 'agent_type') == agent_type: return self.container[defi] raise ValueError(f'No engine found for agent type {agent_type}') @override def runner_exists(self, agent_type: AgentType) -> bool: for defi in self.container.defined_types: if not isinstance(defi, type): continue if issubclass(defi, AgentRunner) and getattr(defi, 'agent_type') == agent_type: return True return False
class ContainerAgentRunnerFactory(AgentRunnerFactory): def __init__(self, container: Container) -> None: pass @override def create_runner(self, agent_type: AgentType) -> AgentRunner: pass @override def runner_exists(self, agent_type: AgentType) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/main.py
flux0_server.main.StartupError
class StartupError(Exception): def __init__(self, message: str) -> None: super().__init__(message)
class StartupError(Exception): def __init__(self, message: str) -> None: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/replay_agent/replay_agent.py
flux0_server.replay_agent.replay_agent.ReplayAgentRunner
from flux0_core.agent_runners.context import Context from flux0_core.recordings import RecordedChunkPayload, RecordedEmittedPayload, RecordedEvent, RecordingId import uuid from flux0_core.agent_runners.api import AgentRunner, Deps, agent_runner from flux0_stream.types import ChunkEvent from flux0_core.sessions import EventId, Session, SessionUpdateParams, StatusEventData from typing import AsyncIterator, Optional, Required, Sequence, Tuple, TypedDict, cast @agent_runner('replay') class ReplayAgentRunner(AgentRunner): """ Replays recorded frames for a session turn: • Finds the next user-anchored turn after session.metadata.replay.last_streamed_offset • Streams [start, end) as live events via the EventEmitter • Paces by recorded created_at deltas (with clamping, factor = pacing) • Updates last_streamed_offset when done """ async def run(self, context: Context, deps: Deps) -> bool: session = await deps.read_session(context.session_id) if not session: deps.logger.error('ReplayAgentRunner: session not found') return False rmeta = get_replay_meta(session) if not rmeta: deps.logger.error('ReplayAgentRunner: missing replay metadata') return False recording_id = rmeta['recording_id'] if not recording_id: deps.logger.error('ReplayAgentRunner: missing recording_id in session.metadata.replay') await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='completed')) return False pacing = rmeta['pacing'] after = rmeta['last_streamed_offset'] rng: Optional[Tuple[int, Optional[int]]] = await deps._recording_store.read_next_turn_range_after_offset(recording_id=recording_id, after_offset=after) if not rng: deps.logger.info('ReplayAgentRunner: no more turns to replay') await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='completed')) return True start, end = rng frames: Sequence[RecordedEvent] = await deps._recording_store.read_frames_range(recording_id=recording_id, start_offset_inclusive=start, end_offset_exclusive=end) if not frames: deps.logger.warning('ReplayAgentRunner: empty frame range for %s [%s,%s)', recording_id, start, end) return True current_correlation = deps.correlator.correlation_id last_offset_streamed = after async for f in _paced_iter(frames, pacing): last_offset_streamed = f.offset if f.kind == 'chunk': p = cast(RecordedChunkPayload, f.payload) meta = p.get('metadata') or {} ce = ChunkEvent(correlation_id=current_correlation, event_id=p['event_id'], seq=p['seq'], patches=p['patches'], metadata=meta, timestamp=_utc_ts(f.created_at)) await deps.event_emitter.enqueue_event_chunk(ce) elif f.kind == 'emitted': ep = cast(RecordedEmittedPayload, f.payload) etype = ep['type'] if etype == 'status': data = cast(StatusEventData, ep['data']) raw_id = cast(str, ep.get('id', '')) eid = EventId(raw_id) if raw_id else EventId(uuid.uuid4().hex) await deps.event_emitter.enqueue_status_event(correlation_id=current_correlation, data=data, event_id=eid) else: deps.logger.debug('ReplayAgentRunner: skipping emitted type=%s', etype) else: deps.logger.debug('ReplayAgentRunner: skipping kind=%s at offset=%s', f.kind, f.offset) rmeta['last_streamed_offset'] = last_offset_streamed md = getattr(session, 'metadata', {}) or {} md['replay'] = rmeta await deps._session_store.update_session(session.id, SessionUpdateParams(metadata=md)) return True
@agent_runner('replay') class ReplayAgentRunner(AgentRunner): ''' Replays recorded frames for a session turn: • Finds the next user-anchored turn after session.metadata.replay.last_streamed_offset • Streams [start, end) as live events via the EventEmitter • Paces by recorded created_at deltas (with clamping, factor = pacing) • Updates last_streamed_offset when done ''' async def run(self, context: Context, deps: Deps) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/replay_agent/replay_agent.py
flux0_server.replay_agent.replay_agent.ReplayMeta
from typing import AsyncIterator, Optional, Required, Sequence, Tuple, TypedDict, cast from flux0_core.recordings import RecordedChunkPayload, RecordedEmittedPayload, RecordedEvent, RecordingId class ReplayMeta(TypedDict, total=False): recording_id: Required[RecordingId] pacing: Required[float] last_streamed_offset: Required[int]
class ReplayMeta(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/settings.py
flux0_server.settings.EnvType
import enum class EnvType(enum.Enum): PRODUCTION = 'production' DEVELOPMENT = 'development'
class EnvType(enum.Enum): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/settings.py
flux0_server.settings.ParsedStoreConfig
from typing import List, Optional, Union from pydantic import BaseModel, Field, field_validator, model_validator from flux0_core.storage.types import NanoDBStorageType, StorageType class ParsedStoreConfig(BaseModel): type: StorageType mode: Optional[NanoDBStorageType] uri: Optional[str] = None database: Optional[str] = None dir: Optional[str] = None
class ParsedStoreConfig(BaseModel): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/server/src/flux0_server/settings.py
flux0_server.settings.Settings
from flux0_api.auth import AuthType from flux0_core.logging import LogLevel from pydantic_settings import BaseSettings, SettingsConfigDict from typing import List, Optional, Union from pydantic import BaseModel, Field, field_validator, model_validator class Settings(BaseSettings): model_config = SettingsConfigDict(env_file='.env', env_prefix='FLUX0_', enable_decoding=False, extra='allow') env: EnvType = Field(default=EnvType.PRODUCTION) port: int = Field(default=8080) auth_type: AuthType = Field(default_factory=lambda: AuthType.NOOP) log_level: LogLevel = Field(default_factory=lambda: LogLevel.INFO) db_uri: str = Field(default='nanodb://memory') modules: List[str] = Field(default_factory=list) @field_validator('modules', mode='before') @classmethod def decode_modules(cls, v: Union[str, List[str]]) -> List[str]: if isinstance(v, str): return [module.strip() for module in v.split(',') if module.strip()] return v @model_validator(mode='after') def populate_db_config(self) -> 'Settings': self.db = parse_store_uri(self.db_uri) return self
class Settings(BaseSettings): @field_validator('modules', mode='before') @classmethod def decode_modules(cls, v: Union[str, List[str]]) -> List[str]: pass @model_validator(mode='after') def populate_db_config(self) -> 'Settings': pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/frameworks/langchain.py
flux0_stream.frameworks.langchain.RunContext
from typing import AsyncIterator, Dict, Optional, cast class RunContext: def __init__(self, last_known_event_offset: int) -> None: self.data: Dict[str, Dict[str, bool]] = {} self.last_known_event_offset = last_known_event_offset def set_typing_emitted(self, event_id: str, emitted: bool) -> None: """Set the typing_emitted status for a given event_id.""" if event_id not in self.data: self.data[event_id] = {} self.data[event_id]['typing_emitted'] = emitted def get_typing_emitted(self, event_id: str) -> bool: """Retrieve the typing_emitted status for a given event_id.""" return self.data.get(event_id, {}).get('typing_emitted', False) def get_last_known_event_offset(self) -> int: """Get the last known event offset.""" return self.last_known_event_offset def clear(self) -> None: """Clear the entire run context.""" self.data.clear() self.last_known_event_offset = 0
class RunContext: def __init__(self, last_known_event_offset: int) -> None: pass def set_typing_emitted(self, event_id: str, emitted: bool) -> None: '''Set the typing_emitted status for a given event_id.''' pass def get_typing_emitted(self, event_id: str) -> bool: '''Retrieve the typing_emitted status for a given event_id.''' pass def get_last_known_event_offset(self) -> int: '''Get the last known event offset.''' pass def clear(self) -> None: '''Clear the entire run context.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/types.py
flux0_stream.types.AddOperation
from flux0_core.types import JSONSerializable from typing import Literal, Mapping, Optional, TypedDict, Union class AddOperation(TypedDict): op: Literal['add'] path: str value: JSONSerializable
class AddOperation(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/types.py
flux0_stream.types.ChunkEvent
from abc import ABC from dataclasses import dataclass, field from typing import Literal, Mapping, Optional, TypedDict, Union import time from flux0_core.types import JSONSerializable from flux0_core.sessions import EventId, EventSource, EventType, MessageEventData, StatusEventData, ToolEventData @dataclass(frozen=True) class ChunkEvent(ABC): """Represents an incremental update using JSON Patch operations. Attributes: correlation_id (str): Unique identifier for the event stream. event_id (str): Unique identifier for the event. chunk_id (int): The sequence number of the chunk. content (str): The actual content of this chunk. timestamp (float): Time at which the chunk was received. """ correlation_id: str event_id: EventId seq: int patches: list[JsonPatchOperation] metadata: Mapping[str, JSONSerializable] = field(default_factory=dict) timestamp: float = field(default_factory=time.time)
@dataclass(frozen=True) class ChunkEvent(ABC): '''Represents an incremental update using JSON Patch operations. Attributes: correlation_id (str): Unique identifier for the event stream. event_id (str): Unique identifier for the event. chunk_id (int): The sequence number of the chunk. content (str): The actual content of this chunk. timestamp (float): Time at which the chunk was received. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/types.py
flux0_stream.types.EmittedEvent
from dataclasses import dataclass, field from typing import Literal, Mapping, Optional, TypedDict, Union from flux0_core.sessions import EventId, EventSource, EventType, MessageEventData, StatusEventData, ToolEventData from flux0_core.types import JSONSerializable import time @dataclass(frozen=True) class EmittedEvent: """Represents an event emitted by a source. This is the final form of an event after all chunks have been processed and closely related to the `Event` class in core. Attributes: source (EventSource): The source of the event. type (EventType): The type of the event. correlation_id (str): Unique identifier for the event stream. data (Union[MessageEventData, StatusEventData, ToolEventData]): The event data. metadata (Optional[Mapping[str, JSONSerializable]]): Additional metadata. """ id: EventId source: EventSource type: EventType correlation_id: str data: Union[MessageEventData, StatusEventData, ToolEventData] metadata: Optional[Mapping[str, JSONSerializable]] = None timestamp: float = field(default_factory=time.time)
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/types.py
flux0_stream.types.ReplaceOperation
from flux0_core.types import JSONSerializable from typing import Literal, Mapping, Optional, TypedDict, Union class ReplaceOperation(TypedDict): op: Literal['replace'] path: str value: JSONSerializable
class ReplaceOperation(TypedDict): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/examples/langchain_simple/agent.py
langchain_simple.agent.LangChainAgentRunner
from flux0_stream.frameworks.langchain import RunContext, filter_and_map_events, handle_event from flux0_core.agent_runners.context import Context from flux0_core.sessions import StatusEventData from langchain_core.messages import HumanMessage, SystemMessage from flux0_core.agent_runners.api import AgentRunner, Deps, agent_runner from examples.utils.utils import read_user_input from langchain.chat_models import init_chat_model @agent_runner('langchain_simple') class LangChainAgentRunner(AgentRunner): async def run(self, context: Context, deps: Deps) -> bool: agent = await deps.read_agent(context.agent_id) if not agent: deps.logger.error(f'Agent with ID {context.agent_id} not found') return False user_input = await read_user_input(deps, context) model = init_chat_model('gpt-4.1-nano', model_provider='openai') messages = [SystemMessage('Translate the following from English into Italian'), HumanMessage(user_input)] try: model_events = model.astream_events(messages, stream=True, version='v2') run_ctx: RunContext = RunContext(last_known_event_offset=0) async for e in filter_and_map_events(model_events, deps.logger): await handle_event(agent, deps.correlator.correlation_id, e, deps.event_emitter, deps.logger, run_ctx) except Exception as e: await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='error', data=str(e))) return False finally: await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='completed', acknowledged_offset=0)) return True
@agent_runner('langchain_simple') class LangChainAgentRunner(AgentRunner): async def run(self, context: Context, deps: Deps) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/examples/langgraph_weather/weather_agent.py
langgraph_weather.weather_agent.WeatherAgentRunner
from flux0_core.sessions import StatusEventData from flux0_core.agent_runners.api import AgentRunner, Deps, agent_runner from examples.utils.utils import read_user_input from flux0_core.agent_runners.context import Context from flux0_stream.frameworks.langchain import RunContext, filter_and_map_events, handle_event from langchain_core.runnables.config import RunnableConfig @agent_runner('langgraph_weather') class WeatherAgentRunner(AgentRunner): async def run(self, context: Context, deps: Deps) -> bool: agent = await deps.read_agent(context.agent_id) if not agent: raise ValueError(f'Agent with id {context.agent_id} not found') user_input = await read_user_input(deps, context) if not user_input: raise ValueError('No user input found in session events') deps.logger.info(f'User Input: {user_input} for session {context.session_id} and agent {agent.id}') input = {'messages': [('user', user_input)]} config = RunnableConfig(configurable={'thread_id': context.session_id, 'agent_id': agent.id}) try: model_events = weather_agent.astream_events(input=input, config=config, version='v2') run_ctx: RunContext = RunContext(last_known_event_offset=0) async for e in filter_and_map_events(model_events, deps.logger): await handle_event(agent, deps.correlator.correlation_id, e, deps.event_emitter, deps.logger, run_ctx) return True except Exception as e: await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='error', data=str(e))) return False finally: await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='completed'))
@agent_runner('langgraph_weather') class WeatherAgentRunner(AgentRunner): async def run(self, context: Context, deps: Deps) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/store/memory.py
memory.DocInProgress
from typing import Dict, List, MutableMapping, Optional, Self, TypedDict, Union, cast from flux0_core.types import JSONSerializable class DocInProgress(TypedDict, total=False): metadata: MutableMapping[str, JSONSerializable] content: JSONSerializable
class DocInProgress(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/emitter/memory.py
memory.InMemoryEventEmitterFactory
from flux0_core.sessions import EventId, SessionId, StatusEventData from flux0_stream.emitter.api import EventEmitter, FinalSubscriber, ProcessedSubscriber from flux0_core.agents import AgentId class InMemoryEventEmitterFactory: def __init__(self, event_emitter: EventEmitter) -> None: self._event_emitter = event_emitter async def create_event_emitter(self, emitting_agent_id: AgentId, session_id: SessionId) -> EventEmitter: return self._event_emitter
class InMemoryEventEmitterFactory: def __init__(self, event_emitter: EventEmitter) -> None: pass async def create_event_emitter(self, emitting_agent_id: AgentId, session_id: SessionId) -> EventEmitter: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/emitter/memory.py
memory.MemoryEventEmitter
from flux0_stream.emitter.api import EventEmitter, FinalSubscriber, ProcessedSubscriber from flux0_stream.types import ChunkEvent, EmittedEvent from flux0_stream.store.api import EventStore import asyncio from typing import Dict, List, Optional, Self, Union from flux0_core.sessions import EventId, SessionId, StatusEventData from flux0_core.logging import Logger class MemoryEventEmitter(EventEmitter): """ In-memory implementation of EventEmitter using asyncio.Queue. - Uses a **single** `asyncio.Queue[QueueMessage]` for processing both event chunks and status updates. - Handles **event finalization** when receiving a status event with `"ready"` or `"completed"`. - Supports **subscriber notifications** for both **processed chunks** and **finalized events**. - Implements a **worker loop** that continuously processes queued messages. - Ensures **clean shutdown**, processing remaining messages before stopping. """ def __init__(self, event_store: EventStore, logger: Logger) -> None: """Initializes the event emitter with an event queue and subscriber management.""" self.event_store: EventStore = event_store self.logger: Logger = logger self.queue: asyncio.Queue[QueueMessage] = asyncio.Queue() self.processed_subscribers: Dict[str, List[ProcessedSubscriber]] = {} self.final_subscribers: Dict[str, List[FinalSubscriber]] = {} self._worker_task: asyncio.Task[None] = asyncio.create_task(self._worker_loop()) async def enqueue_status_event(self, correlation_id: str, data: StatusEventData, event_id: Optional[EventId]=None) -> None: """Enqueues a status event for a specific execution (correlation_id).""" await self.queue.put(QueueMessage(correlation_id, event_id, data)) async def enqueue_event_chunk(self, chunk: ChunkEvent) -> None: """Enqueues an event chunk for processing.""" await self.queue.put(QueueMessage(chunk.correlation_id, chunk.event_id, chunk)) def subscribe_processed(self, correlation_id: str, subscriber: ProcessedSubscriber) -> None: """Registers a subscriber to receive event chunks for a specific execution (correlation_id).""" self.processed_subscribers.setdefault(correlation_id, []).append(subscriber) def subscribe_final(self, correlation_id: str, subscriber: FinalSubscriber) -> None: """Registers a subscriber to receive finalized events for a specific execution (correlation_id).""" self.final_subscribers.setdefault(correlation_id, []).append(subscriber) def unsubscribe_processed(self, correlation_id: str, subscriber: ProcessedSubscriber) -> None: """Removes a processed chunk subscriber for a specific execution (correlation_id).""" if correlation_id in self.processed_subscribers: self.processed_subscribers[correlation_id].remove(subscriber) def unsubscribe_final(self, correlation_id: str, subscriber: FinalSubscriber) -> None: """Removes a finalized event subscriber for a specific execution (correlation_id).""" if correlation_id in self.final_subscribers: self.final_subscribers[correlation_id].remove(subscriber) async def _worker_loop(self) -> None: """Background task that processes messages from the queue.""" while True: message: Optional[QueueMessage] = None try: message = await self.queue.get() if isinstance(message.data, ChunkEvent): await self._process_event_chunk(message.correlation_id, message.data) elif isinstance(message.data, dict) and 'status' in message.data: await self._process_status_event(message.correlation_id, message.event_id, message.data) except asyncio.CancelledError: break except Exception as e: self.logger.error(f'Error processing message: {e}', exc_info=True) finally: if message is not None: self.queue.task_done() async def _process_event_chunk(self, correlation_id: str, chunk: ChunkEvent) -> None: """Processes an event chunk and notifies processed subscribers.""" await self.event_store.add_chunk(chunk) if correlation_id in self.processed_subscribers: for subscriber in self.processed_subscribers[correlation_id]: await subscriber(chunk) async def _process_status_event(self, correlation_id: str, event_id: Optional[EventId], data: StatusEventData) -> None: """Processes a status event, finalizing events if required.""" is_final: bool = data['status'] in {'ready'} if is_final: if event_id is None: raise ValueError('Event ID is required for finalization') finalized_event = await self.event_store.finalize_event(correlation_id, event_id) if finalized_event is None: raise ValueError(f'Failed to finalize event for event_id: {event_id}') if correlation_id in self.final_subscribers: for subscriber in self.final_subscribers[correlation_id]: await subscriber(finalized_event) if correlation_id in self.final_subscribers: for subscriber in self.final_subscribers[correlation_id]: await subscriber(EmittedEvent(id=event_id if event_id is not None else EventId(''), correlation_id=correlation_id, source='ai_agent', type='status', data=data)) async def shutdown(self) -> None: """Shuts down the event emitter, ensuring all queued events are processed.""" self.logger.debug('Shutting down EventEmitter, processing remaining messages...') self._worker_task.cancel() try: await self._worker_task except asyncio.CancelledError: pass try: while not self.queue.empty(): self.logger.debug('Processing remaining messages...') message: QueueMessage = self.queue.get_nowait() if isinstance(message.data, ChunkEvent): await self._process_event_chunk(message.correlation_id, message.data) elif isinstance(message.data, dict) and 'status' in message.data: await self._process_status_event(message.correlation_id, message.event_id, message.data) self.queue.task_done() except asyncio.QueueEmpty: pass except Exception as e: self.logger.error(f'Error processing remaining messages: {e}', exc_info=True) self.logger.debug('EventEmitter shutdown complete.') async def __aenter__(self) -> Self: """Allows the event emitter to be used with an async context manager.""" return self async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[object]) -> None: """Ensures the event emitter shuts down properly when used in an async context manager.""" await self.shutdown()
class MemoryEventEmitter(EventEmitter): ''' In-memory implementation of EventEmitter using asyncio.Queue. - Uses a **single** `asyncio.Queue[QueueMessage]` for processing both event chunks and status updates. - Handles **event finalization** when receiving a status event with `"ready"` or `"completed"`. - Supports **subscriber notifications** for both **processed chunks** and **finalized events**. - Implements a **worker loop** that continuously processes queued messages. - Ensures **clean shutdown**, processing remaining messages before stopping. ''' def __init__(self, event_store: EventStore, logger: Logger) -> None: '''Initializes the event emitter with an event queue and subscriber management.''' pass async def enqueue_status_event(self, correlation_id: str, data: StatusEventData, event_id: Optional[EventId]=None) -> None: '''Enqueues a status event for a specific execution (correlation_id).''' pass async def enqueue_event_chunk(self, chunk: ChunkEvent) -> None: '''Enqueues an event chunk for processing.''' pass def subscribe_processed(self, correlation_id: str, subscriber: ProcessedSubscriber) -> None: '''Registers a subscriber to receive event chunks for a specific execution (correlation_id).''' pass def subscribe_final(self, correlation_id: str, subscriber: FinalSubscriber) -> None: '''Registers a subscriber to receive finalized events for a specific execution (correlation_id).''' pass def unsubscribe_processed(self, correlation_id: str, subscriber: ProcessedSubscriber) -> None: '''Removes a processed chunk subscriber for a specific execution (correlation_id).''' pass def unsubscribe_final(self, correlation_id: str, subscriber: FinalSubscriber) -> None: '''Removes a finalized event subscriber for a specific execution (correlation_id).''' pass async def _worker_loop(self) -> None: '''Background task that processes messages from the queue.''' pass async def _process_event_chunk(self, correlation_id: str, chunk: ChunkEvent) -> None: '''Processes an event chunk and notifies processed subscribers.''' pass async def _process_status_event(self, correlation_id: str, event_id: Optional[EventId], data: StatusEventData) -> None: '''Processes a status event, finalizing events if required.''' pass async def shutdown(self) -> None: '''Shuts down the event emitter, ensuring all queued events are processed.''' pass async def __aenter__(self) -> Self: '''Allows the event emitter to be used with an async context manager.''' pass async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[object]) -> None: '''Ensures the event emitter shuts down properly when used in an async context manager.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/store/memory.py
memory.MemoryEventStore
import copy from flux0_stream.store.api import EventStore from flux0_stream.patches import ensure_structure_for_patch from jsonpatch import JsonPatch, apply_patch from typing import Dict, List, MutableMapping, Optional, Self, TypedDict, Union, cast import json from flux0_core.agents import AgentId from flux0_core.types import JSONSerializable from flux0_stream.types import ChunkEvent, EmittedEvent from flux0_core.sessions import ContentPart, EventId, MessageEventData, Participant, ReasoningPart, ToolCall, ToolCallPart, ToolCallPartType, ToolEventData, ToolResult class MemoryEventStore(EventStore): """ In-memory implementation of EventStore. - Applies JSON patches incrementally. - Handles out-of-order chunk arrivals using sequence numbers. - Finalization is instant, as the document is always up-to-date. """ def __init__(self) -> None: self.in_progress_docs: Dict[EventId, DocInProgress] = {} self.chunk_buffer: Dict[EventId, Dict[int, List[JsonPatch]]] = {} self.chunk_index_tracker: Dict[EventId, int] = {} self.finalized_events: Dict[EventId, EmittedEvent] = {} async def __aenter__(self) -> Self: """Allows the event store to be used with an async context manager.""" return self async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[object]) -> None: self.in_progress_docs.clear() self.chunk_buffer.clear() self.chunk_index_tracker.clear() self.finalized_events.clear async def add_chunk(self, chunk: ChunkEvent) -> None: """ Receives a patch chunk and applies it immediately if it's in order. If out of order, stores it in a buffer for later application. """ event_id = chunk.event_id if event_id not in self.in_progress_docs: self.in_progress_docs[event_id] = DocInProgress(metadata={**chunk.metadata}) sequence_number = chunk.seq expected_index = self.chunk_index_tracker.get(event_id, -1) + 1 jpatch_copy = copy.deepcopy(chunk.patches) jpatch = JsonPatch(jpatch_copy) doc_in_progress = self.in_progress_docs[event_id] contains_append = any((op['path'].endswith('/-') for op in jpatch.patch)) if contains_append or sequence_number == expected_index: doc_in_progress = self.in_progress_docs[event_id] for patch in jpatch: content = ensure_structure_for_patch(doc_in_progress.get('content'), patch) content = apply_patch(content, [patch]) if content is None: raise ValueError('Document content is missing') doc_in_progress['content'] = content self.chunk_index_tracker[event_id] = sequence_number self.in_progress_docs[event_id] = doc_in_progress self._apply_buffered_patches(event_id) else: if sequence_number not in self.chunk_buffer[event_id]: self.chunk_buffer[event_id][sequence_number] = [] self.chunk_buffer[event_id][sequence_number].append(jpatch) def _apply_buffered_patches(self, event_id: EventId) -> None: """Applies buffered patches when their missing previous chunks arrive.""" if event_id not in self.chunk_buffer: return while self.chunk_index_tracker[event_id] + 1 in self.chunk_buffer.get(event_id, {}): next_index = self.chunk_index_tracker[event_id] + 1 patches_to_apply = self.chunk_buffer[event_id].pop(next_index) for patch in patches_to_apply: self.in_progress_docs[event_id] = apply_patch(self.in_progress_docs[event_id], patch) self.chunk_index_tracker[event_id] = next_index if not self.chunk_buffer[event_id]: del self.chunk_buffer[event_id] async def finalize_event(self, correlation_id: str, event_id: EventId) -> Optional[EmittedEvent]: """ Finalizes an event by returning the fully built document. Removes it from the in-progress store and marks it as finalized. """ if event_id not in self.in_progress_docs: return None final_data = self.in_progress_docs.pop(event_id) self.chunk_buffer.pop(event_id, None) self.chunk_index_tracker.pop(event_id, None) meta = final_data.get('metadata', {}) content = final_data.get('content') agent_id = AgentId(str(meta.pop('agent_id', ''))) agent_name = str(meta.pop('agent_name')) kind = meta.pop('kind') if 'kind' in meta else None if not content: return None if isinstance(content, str): str_parts: List[Union[ContentPart, ReasoningPart, ToolCallPart]] = [] if kind and kind == 'reasoning': str_parts.append(ReasoningPart(type='reasoning', reasoning=content)) else: str_parts.append(ContentPart(type='content', content=content)) finalized_event = EmittedEvent(correlation_id=correlation_id, id=event_id, source='ai_agent', type='message', data=MessageEventData(type='message', parts=str_parts, participant=Participant(id=agent_id, name=agent_name)), metadata=meta) elif isinstance(content, list): if all((isinstance(item, str) for item in content)): content = ''.join(map(str, content)) list_parts: List[Union[ContentPart, ReasoningPart, ToolCallPart]] = [] if kind and kind == 'reasoning': list_parts.append(ReasoningPart(type='reasoning', reasoning=content)) else: list_parts.append(ContentPart(type='content', content=content)) finalized_event = EmittedEvent(correlation_id=correlation_id, id=event_id, source='ai_agent', type='message', data=MessageEventData(type='message', parts=list_parts, participant=Participant(id=agent_id, name=agent_name)), metadata=meta) elif isinstance(content, dict): if 'tool_calls' in content: tool_call_parts: list[dict[str, JSONSerializable]] = cast(list[dict[str, JSONSerializable]], content['tool_calls']) tcpl: List[Union[ContentPart, ReasoningPart, ToolCallPart]] = [] for tool_call in tool_call_parts: args = tool_call['args'] if isinstance(args, list): args_as_list: list[str] = cast(list[str], args) json_string = ''.join(args_as_list) final_args = json.loads(json_string) elif isinstance(args, dict): final_args = args else: raise ValueError('args is not a list or dict') tool_part = ToolCallPart(type=cast(ToolCallPartType, tool_call['type']), tool_call_id=cast(str, tool_call['tool_call_id']), tool_name=cast(str, tool_call['tool_name']), args=final_args) tcpl.append(tool_part) finalized_event = EmittedEvent(correlation_id=correlation_id, id=event_id, source='ai_agent', type='message', data=MessageEventData(type='message', parts=tcpl, participant=Participant(id=agent_id, name=agent_name))) elif 'tool_call_results' in content: tool_calls: list[dict[str, JSONSerializable]] = cast(list[dict[str, JSONSerializable]], content['tool_call_results']) tcl: list[ToolCall] = [] for tool_call in tool_calls: tc = ToolCall(tool_call_id=cast(str, tool_call['tool_call_id']), tool_name=cast(str, tool_call['tool_name']), args=cast(dict[str, JSONSerializable], tool_call['args']), result=ToolResult(data=tool_call['data']['result'] if isinstance(tool_call['data'], dict) else None, metadata={}, control={'mode': 'auto'})) tcl.append(tc) finalized_event = EmittedEvent(correlation_id=correlation_id, id=event_id, source='ai_agent', type='tool', data=ToolEventData(type='tool_call_result', tool_calls=tcl)) else: parts: List[Union[ContentPart, ReasoningPart, ToolCallPart]] = [] if kind and kind == 'reasoning': parts.append(ReasoningPart(type='reasoning', reasoning=content)) else: parts.append(ContentPart(type='content', content=content)) finalized_event = EmittedEvent(correlation_id=correlation_id, id=event_id, source='ai_agent', type='message', data=MessageEventData(type='message', parts=parts, participant=Participant(id=agent_id, name=agent_name)), metadata=meta) else: raise ValueError('Finalized event is unrecognized') self.finalized_events[event_id] = finalized_event return finalized_event
class MemoryEventStore(EventStore): ''' In-memory implementation of EventStore. - Applies JSON patches incrementally. - Handles out-of-order chunk arrivals using sequence numbers. - Finalization is instant, as the document is always up-to-date. ''' def __init__(self) -> None: pass async def __aenter__(self) -> Self: '''Allows the event store to be used with an async context manager.''' pass async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], traceback: Optional[object]) -> None: pass async def add_chunk(self, chunk: ChunkEvent) -> None: ''' Receives a patch chunk and applies it immediately if it's in order. If out of order, stores it in a buffer for later application. ''' pass def _apply_buffered_patches(self, event_id: EventId) -> None: '''Applies buffered patches when their missing previous chunks arrive.''' pass async def finalize_event(self, correlation_id: str, event_id: EventId) -> Optional[EmittedEvent]: ''' Finalizes an event by returning the fully built document. Removes it from the in-progress store and marks it as finalized. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/stream/src/flux0_stream/emitter/memory.py
memory.QueueMessage
from flux0_core.sessions import EventId, SessionId, StatusEventData from flux0_stream.types import ChunkEvent, EmittedEvent from typing import Dict, List, Optional, Self, Union from dataclasses import dataclass @dataclass class QueueMessage: """Represents a message in the event queue, distinguishing between event chunks and status events.""" correlation_id: str event_id: Optional[EventId] data: Union[ChunkEvent, StatusEventData]
@dataclass class QueueMessage: '''Represents a message in the event queue, distinguishing between event chunks and status events.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/scripts/psr/custom_parser/monorepo_parser.py
monorepo_parser.ConventionalCommitMonorepoParser
from semantic_release.commit_parser._base import CommitParser, ParserOptions from semantic_release.commit_parser.angular import LONG_TYPE_NAMES from fnmatch import fnmatch from semantic_release.errors import InvalidParserOptions import os from semantic_release.commit_parser.token import ParsedCommit, ParsedMessageResult, ParseError, ParseResult from pathlib import Path from semantic_release.commit_parser.util import breaking_re, parse_paragraphs, sort_numerically from semantic_release.enums import LevelBump from re import compile as regexp from functools import reduce import re class ConventionalCommitMonorepoParser(CommitParser[ParseResult, ConventionalMonorepoParserOptions]): """""" parser_options = ConventionalMonorepoParserOptions def __init__(self, options: ConventionalMonorepoParserOptions | None=None) -> None: super().__init__(options) self.file_selection_filters = [] self.file_ignore_filters = [] for str_path in map(str, self.options.path_filters): str_filter = str_path[1:] if str_path.startswith('!') else str_path filter_list = self.file_ignore_filters if str_path.startswith('!') else self.file_selection_filters filter_list.extend(filter(None, [None if str_path.endswith('*') else f'{str_filter.rstrip(os.sep)}{os.sep}**', None if str_path.endswith(os.sep) else str_filter])) try: commit_type_pattern = regexp('(?P<type>%s)' % str.join('|', self.options.allowed_tags)) except re.error as err: raise InvalidParserOptions(str.join('\n', [f'Invalid options for {self.__class__.__name__}', 'Unable to create regular expression from configured commit-types.', 'Please check the configured commit-types and remove or escape any regular expression characters.'])) from err self.re_parser = regexp(str.join('', ['^' + commit_type_pattern.pattern, '(?:\\(' + self.options.scope_prefix + '(?P<scope>[^\\n]+)\\))?', '(?P<break>!)?:\\s+', '(?P<subject>[^\\n]+)', '(?:\\n\\n(?P<text>.+))?']), flags=re.DOTALL) self.mr_selector = regexp('[\\t ]+\\((?:pull request )?(?P<mr_number>[#!]\\d+)\\)[\\t ]*$') self.issue_selector = regexp(str.join('', ['^(?:clos(?:e|es|ed|ing)|fix(?:es|ed|ing)?|resolv(?:e|es|ed|ing)|implement(?:s|ed|ing)?):', '[\\t ]+(?P<issue_predicate>.+)[\\t ]*$']), flags=re.MULTILINE | re.IGNORECASE) @staticmethod def get_default_options() -> ConventionalMonorepoParserOptions: return ConventionalMonorepoParserOptions() def commit_body_components_separator(self, accumulator: dict[str, list[str]], text: str) -> dict[str, list[str]]: if (match := breaking_re.match(text)): accumulator['breaking_descriptions'].append(match.group(1) or '') return accumulator if (match := self.issue_selector.search(text)): predicate = regexp(',? and | *[,;/& ] *').sub(',', match.group('issue_predicate') or '') has_number = regexp('\\d+') new_issue_refs: set[str] = set(filter(lambda issue_str, validator=has_number: validator.search(issue_str), predicate.split(','))) accumulator['linked_issues'] = sort_numerically(set(accumulator['linked_issues']).union(new_issue_refs)) return accumulator if text not in accumulator['descriptions']: accumulator['descriptions'].append(text) return accumulator def parse_message(self, message: str) -> ParsedMessageResult | None: if not (parsed := self.re_parser.match(message)): return None parsed_break = parsed.group('break') parsed_scope = parsed.group('scope') parsed_subject = parsed.group('subject') parsed_text = parsed.group('text') parsed_type = parsed.group('type') linked_merge_request = '' if (mr_match := self.mr_selector.search(parsed_subject)): linked_merge_request = mr_match.group('mr_number') parsed_subject = self.mr_selector.sub('', parsed_subject).strip() body_components: dict[str, list[str]] = reduce(self.commit_body_components_separator, [parsed_subject, *parse_paragraphs(parsed_text or '')], {'breaking_descriptions': [], 'descriptions': [], 'linked_issues': []}) level_bump = LevelBump.MAJOR if body_components['breaking_descriptions'] or parsed_break else self.options.tag_to_level.get(parsed_type, self.options.default_bump_level) return ParsedMessageResult(bump=level_bump, type=parsed_type, category=LONG_TYPE_NAMES.get(parsed_type, parsed_type), scope=parsed_scope, descriptions=tuple(body_components['descriptions']), breaking_descriptions=tuple(body_components['breaking_descriptions']), linked_issues=tuple(body_components['linked_issues']), linked_merge_request=linked_merge_request) def parse(self, commit: Commit) -> ParseResult: """Attempt to parse the commit message with a regular expression into a ParseResult.""" git_root = Path(commit.repo.working_tree_dir or commit.repo.working_dir).absolute().resolve() relevant_changed_files = [] for rel_git_path in commit.stats.files.keys(): full_path = str(git_root / rel_git_path) for pass_filter in self.file_selection_filters: if (select_file := fnmatch(full_path, pass_filter)): for ignore_filter in self.file_ignore_filters: if fnmatch(full_path, ignore_filter): select_file = False break if select_file: relevant_changed_files.append(rel_git_path) break pmsg_result = self.parse_message(str(commit.message)) if len(relevant_changed_files) == 0: if not pmsg_result: return _logged_parse_error(commit, str.join(' ', [f'Commit {commit.hexsha[:7]} is not scoped with the scope prefix {self.options.scope_prefix}', 'and has no changed files in the path filter(s)', f'relative to the git root {git_root}']) if self.options.scope_prefix and self.options.scope_prefix not in commit.message.split('\n', maxsplit=1)[0] else f'Format Mismatch! Unable to parse commit message: {commit.message!r}') if not self.options.scope_prefix: return _logged_parse_error(commit, str.join(' ', [f'Commit {commit.hexsha[:7]} has no changed files in the path filter(s)', f'relative to the git root {git_root}'])) if not pmsg_result: return _logged_parse_error(commit, f'Commit {commit.hexsha[:7]} scope does not match scope prefix {self.options.scope_prefix}' if self.options.scope_prefix and self.options.scope_prefix not in commit.message.split('\n')[0] else f'Format Mismatch! Unable to parse commit message: {commit.message!r}') logger.debug('commit %s introduces a %s level_bump', commit.hexsha[:8], pmsg_result.bump) return ParsedCommit.from_parsed_message_result(commit, pmsg_result)
class ConventionalCommitMonorepoParser(CommitParser[ParseResult, ConventionalMonorepoParserOptions]): '''''' def __init__(self, options: ConventionalMonorepoParserOptions | None=None) -> None: pass @staticmethod def get_default_options() -> ConventionalMonorepoParserOptions: pass def commit_body_components_separator(self, accumulator: dict[str, list[str]], text: str) -> dict[str, list[str]]: pass def parse_message(self, message: str) -> ParsedMessageResult | None: pass def parse_message(self, message: str) -> ParsedMessageResult | None: '''Attempt to parse the commit message with a regular expression into a ParseResult.''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/scripts/psr/custom_parser/monorepo_parser.py
monorepo_parser.ConventionalMonorepoParserOptions
from pydantic import Field, field_validator from typing_extensions import Annotated from semantic_release.commit_parser._base import CommitParser, ParserOptions from pathlib import Path from typing import TYPE_CHECKING, Any, Iterable, Tuple from semantic_release.enums import LevelBump from itertools import zip_longest from pydantic.dataclasses import dataclass @dataclass class ConventionalMonorepoParserOptions(ParserOptions): """Options dataclass for ConventionalCommitMonorepoParser.""" minor_tags: Tuple[str, ...] = ('feat',) 'Commit-type prefixes that should result in a minor release bump.' patch_tags: Tuple[str, ...] = ('fix', 'perf') 'Commit-type prefixes that should result in a patch release bump.' other_allowed_tags: Tuple[str, ...] = ('build', 'chore', 'ci', 'docs', 'style', 'refactor', 'test') 'Commit-type prefixes that are allowed but do not result in a version bump.' default_bump_level: LevelBump = LevelBump.NO_RELEASE 'The minimum bump level to apply to valid commit message.' path_filters: Annotated[Tuple[Path, ...], Field(validate_default=True)] = (Path('.'),) '\n A set of relative paths to filter commits by. Only commits with file changes that\n match these file paths or its subdirectories will be considered valid commits.\n\n Syntax is similar to .gitignore with file path globs and inverse file match globs\n via `!` prefix. Paths should be relative to the current working directory.\n ' scope_prefix: str = '' '\n A prefix that will be striped from the scope when parsing commit messages.\n\n If set, it will cause unscoped commits to be ignored. Use this in tandem with\n the path_filter option to filter commits by directory and scope.\n ' @field_validator('path_filters', mode='before') @classmethod def convert_strs_to_paths(cls, value: Any) -> Tuple[Path]: values = value if isinstance(value, Iterable) else [value] results = [] for val in values: if isinstance(val, (str, Path)): results.append(Path(val)) continue raise TypeError(f'Invalid type: {type(val)}, expected str or Path.') return tuple(results) @field_validator('path_filters', mode='after') @classmethod def resolve_path(cls, dir_paths: tuple[Path, ...]) -> Tuple[Path, ...]: return tuple([Path(f'!{Path(str_path[1:]).expanduser().absolute().resolve()}') if (str_path := str(path)).startswith('!') else path.expanduser().absolute().resolve() for path in dir_paths]) @property def tag_to_level(self) -> dict[str, LevelBump]: """A mapping of commit tags to the level bump they should result in.""" return self._tag_to_level @property def allowed_tags(self) -> tuple[str, ...]: """ All commit-type prefixes that are allowed. These are used to identify a valid commit message. If a commit message does not start with one of these prefixes, it will not be considered a valid commit message. :return: A tuple of all allowed commit-type prefixes (ordered from most to least significant) """ return tuple(list(self.tag_to_level.keys())[::-1]) def __post_init__(self) -> None: self._tag_to_level: dict[str, LevelBump] = {str(tag): level for tag, level in [*zip_longest(self.other_allowed_tags, (), fillvalue=self.default_bump_level), *zip_longest(self.patch_tags, (), fillvalue=LevelBump.PATCH), *zip_longest(self.minor_tags, (), fillvalue=LevelBump.MINOR)] if '|' not in str(tag)}
@dataclass class ConventionalMonorepoParserOptions(ParserOptions): '''Options dataclass for ConventionalCommitMonorepoParser.''' @field_validator('path_filters', mode='before') @classmethod def convert_strs_to_paths(cls, value: Any) -> Tuple[Path]: pass @field_validator('path_filters', mode='after') @classmethod def resolve_path(cls, dir_paths: tuple[Path, ...]) -> Tuple[Path, ...]: pass @property def tag_to_level(self) -> dict[str, LevelBump]: '''A mapping of commit tags to the level bump they should result in.''' pass @property def allowed_tags(self) -> tuple[str, ...]: ''' All commit-type prefixes that are allowed. These are used to identify a valid commit message. If a commit message does not start with one of these prefixes, it will not be considered a valid commit message. :return: A tuple of all allowed commit-type prefixes (ordered from most to least significant) ''' pass def __post_init__(self) -> None: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory.AgentDocumentStore
from flux0_nanodb import projection from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from flux0_core.ids import gen_id from datetime import datetime, timezone from flux0_nanodb.query import And, Comparison, QueryFilter from flux0_nanodb.api import DocumentCollection, DocumentDatabase from flux0_core.agents import Agent, AgentId, AgentStore, AgentType, AgentUpdateParams class AgentDocumentStore(AgentStore): VERSION = DocumentVersion('0.0.1') def __init__(self, db: DocumentDatabase): self.db = db self._agent_col: DocumentCollection[_AgentDocument] async def __aenter__(self) -> Self: self._agent_col = await self.db.create_collection('agents', _AgentDocument) return self async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize_agent(self, agent: Agent) -> _AgentDocument: return _AgentDocument(id=DocumentID(agent.id), version=self.VERSION, type=agent.type, name=agent.name, description=agent.description, created_at=agent.created_at) def _deserialize_agent(self, doc: _AgentDocument) -> Agent: return Agent(id=AgentId(doc['id']), type=doc['type'], name=doc['name'], description=doc['description'], created_at=doc['created_at']) @override async def create_agent(self, name: str, type: AgentType, description: Optional[str]=None, created_at: Optional[datetime]=None) -> Agent: created_at = created_at or datetime.now(timezone.utc) agent = Agent(id=AgentId(gen_id()), name=name, type=type, description=description, created_at=created_at) await self._agent_col.insert_one(document=self._serialize_agent(agent)) return agent @override async def read_agent(self, agent_id: AgentId) -> Optional[Agent]: result = await self._agent_col.find(Comparison(path='id', op='$eq', value=agent_id)) return self._deserialize_agent(result[0]) if result else None @override async def list_agents(self, offset: int=0, limit: int=10, projection: Optional[List[str]]=None) -> Sequence[Agent]: if offset != 0 or limit != 10: raise NotImplementedError('Pagination is not supported') if projection is not None: raise NotImplementedError('Projection not supported') return [self._deserialize_agent(d) for d in await self._agent_col.find(filters=None)] @override async def update_agent(self, agent_id: AgentId, params: AgentUpdateParams) -> Agent: raise NotImplementedError @override async def delete_agent(self, agent_id: AgentId) -> bool: result = await self._agent_col.delete_one(Comparison(path='id', op='$eq', value=agent_id)) return result.deleted_count > 0
class AgentDocumentStore(AgentStore): def __init__(self, db: DocumentDatabase): pass async def __aenter__(self) -> Self: pass async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize_agent(self, agent: Agent) -> _AgentDocument: pass def _deserialize_agent(self, doc: _AgentDocument) -> Agent: pass @override async def create_agent(self, name: str, type: AgentType, description: Optional[str]=None, created_at: Optional[datetime]=None) -> Agent: pass @override async def read_agent(self, agent_id: AgentId) -> Optional[Agent]: pass @override async def list_agents(self, offset: int=0, limit: int=10, projection: Optional[List[str]]=None) -> Sequence[Agent]: pass @override async def update_agent(self, agent_id: AgentId, params: AgentUpdateParams) -> Agent: pass @override async def delete_agent(self, agent_id: AgentId) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory.RecordingDocumentStore
from flux0_core.sessions import ConsumerId, Event, EventId, EventSource, EventType, MessageEventData, Session, SessionId, SessionMode, SessionStore, SessionUpdateParams, StatusEventData, ToolEventData from flux0_core.recordings import RecordedChunkPayload, RecordedEmittedPayload, RecordedEvent, RecordedEventId, RecordedEventKind, RecordedEventPayload, RecordedHeaderPayload, RecordingId, RecordingStore, TurnRange from flux0_nanodb import projection from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from flux0_core.ids import gen_id from datetime import datetime, timezone from flux0_nanodb.query import And, Comparison, QueryFilter import asyncio from flux0_nanodb.api import DocumentCollection, DocumentDatabase class RecordingDocumentStore(RecordingStore): VERSION = DocumentVersion('0.0.1') def __init__(self, db: DocumentDatabase): self.db = db self._col: DocumentCollection[_RecordedEventDocument] self._locks: dict[RecordingId, asyncio.Lock] = DefaultDict(asyncio.Lock) async def __aenter__(self) -> Self: self._col = await self.db.create_collection('recorded_events', _RecordedEventDocument) return self async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize(self, ev: RecordedEvent) -> _RecordedEventDocument: return _RecordedEventDocument(id=DocumentID(ev.id), recording_id=ev.recording_id, version=self.VERSION, offset=ev.offset, kind=ev.kind, created_at=ev.created_at, payload=ev.payload) def _deserialize(self, doc: _RecordedEventDocument) -> RecordedEvent: return RecordedEvent(id=RecordedEventId(doc['id']), recording_id=RecordingId(doc['recording_id']), offset=doc['offset'], kind=doc['kind'], created_at=doc['created_at'], payload=doc['payload']) async def _next_offset(self, recording_id: RecordingId) -> int: docs = await self._col.find(Comparison(path='recording_id', op='$eq', value=recording_id)) return max((d['offset'] for d in docs)) + 1 if docs else 1 async def _ensure_header_exists(self, recording_id: RecordingId) -> None: header = await self.read_header_by_recording_id(recording_id) if header is None: raise ValueError(f'Recording header not found for {recording_id}') @override async def create_recording(self, source_session_id: SessionId, *, recording_id: Optional[RecordingId]=None, created_at: Optional[datetime]=None) -> RecordedEvent: rid = recording_id or RecordingId(gen_id()) created_at = created_at or datetime.now(timezone.utc) header_payload: RecordedHeaderPayload = {'source_session_id': source_session_id} header = RecordedEvent(id=RecordedEventId(gen_id()), recording_id=rid, offset=0, kind='header', created_at=created_at, payload=header_payload) await self._col.insert_one(self._serialize(header)) return header @override async def append_emitted(self, recording_id: RecordingId, payload: RecordedEmittedPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: await self._ensure_header_exists(recording_id) created_at = created_at or datetime.now(timezone.utc) async with self._locks[recording_id]: offset = await self._next_offset(recording_id) ev = RecordedEvent(id=RecordedEventId(gen_id()), recording_id=recording_id, offset=offset, kind='emitted', created_at=created_at, payload=payload) await self._col.insert_one(self._serialize(ev)) return ev @override async def append_chunk(self, recording_id: RecordingId, payload: RecordedChunkPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: await self._ensure_header_exists(recording_id) created_at = created_at or datetime.now(timezone.utc) offset = await self._next_offset(recording_id) ev = RecordedEvent(id=RecordedEventId(gen_id()), recording_id=recording_id, offset=offset, kind='chunk', created_at=created_at, payload=payload) await self._col.insert_one(self._serialize(ev)) return ev @override async def read_header_by_source_session_id(self, source_session_id: SessionId) -> Optional[RecordedEvent]: result = await self._col.find(And(expressions=[Comparison(path='kind', op='$eq', value='header'), Comparison(path='payload.source_session_id', op='$eq', value=source_session_id), Comparison(path='offset', op='$eq', value=0)])) return self._deserialize(result[0]) if result else None @override async def read_header_by_recording_id(self, recording_id: RecordingId) -> Optional[RecordedEvent]: docs = await self._col.find(And(expressions=[Comparison(path='recording_id', op='$eq', value=recording_id), Comparison(path='offset', op='$eq', value=0), Comparison(path='kind', op='$eq', value='header')])) return self._deserialize(docs[0]) if docs else None @override async def read_next_turn_range_after_offset(self, recording_id: RecordingId, after_offset: int) -> Optional[TurnRange]: """ Return the next user-anchored turn that begins strictly AFTER `after_offset`. A "user anchor" is: kind=='emitted' AND payload.source=='user'. """ start_docs = await self._col.find(And(expressions=[Comparison(path='recording_id', op='$eq', value=recording_id), Comparison(path='kind', op='$eq', value='emitted'), Comparison(path='payload.source', op='$eq', value='user'), Comparison(path='offset', op='$gt', value=after_offset)]), projection={'offset': projection.Projection.INCLUDE}, limit=1, sort=[('offset', SortingOrder.ASC)]) if not start_docs: return None start = start_docs[0]['offset'] next_docs = await self._col.find(And(expressions=[Comparison(path='recording_id', op='$eq', value=recording_id), Comparison(path='kind', op='$eq', value='emitted'), Comparison(path='payload.source', op='$eq', value='user'), Comparison(path='offset', op='$gt', value=start)]), projection={'offset': projection.Projection.INCLUDE}, limit=1, sort=[('offset', SortingOrder.ASC)]) end = next_docs[0]['offset'] if next_docs else None return (start, end) @override async def read_frames_range(self, recording_id: RecordingId, start_offset_inclusive: int, end_offset_exclusive: Optional[int]=None, *, limit: Optional[int]=None) -> Sequence[RecordedEvent]: """ Read frames ordered by offset for [start_offset_inclusive, end_offset_exclusive). If end_offset_exclusive is None, read to the end (respect `limit` if provided). """ filters: list[QueryFilter] = [Comparison(path='recording_id', op='$eq', value=recording_id), Comparison(path='offset', op='$gte', value=start_offset_inclusive)] if end_offset_exclusive is not None: filters.append(Comparison(path='offset', op='$lt', value=end_offset_exclusive)) docs = await self._col.find(And(expressions=filters), limit=limit, sort=[('offset', SortingOrder.ASC)]) return [self._deserialize(d) for d in docs]
class RecordingDocumentStore(RecordingStore): def __init__(self, db: DocumentDatabase): pass async def __aenter__(self) -> Self: pass async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize(self, ev: RecordedEvent) -> _RecordedEventDocument: pass def _deserialize(self, doc: _RecordedEventDocument) -> RecordedEvent: pass async def _next_offset(self, recording_id: RecordingId) -> int: pass async def _ensure_header_exists(self, recording_id: RecordingId) -> None: pass @override async def create_recording(self, source_session_id: SessionId, *, recording_id: Optional[RecordingId]=None, created_at: Optional[datetime]=None) -> RecordedEvent: pass @override async def append_emitted(self, recording_id: RecordingId, payload: RecordedEmittedPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: pass @override async def append_chunk(self, recording_id: RecordingId, payload: RecordedChunkPayload, *, created_at: Optional[datetime]=None) -> RecordedEvent: pass @override async def read_header_by_source_session_id(self, source_session_id: SessionId) -> Optional[RecordedEvent]: pass @override async def read_header_by_recording_id(self, recording_id: RecordingId) -> Optional[RecordedEvent]: pass @override async def read_next_turn_range_after_offset(self, recording_id: RecordingId, after_offset: int) -> Optional[TurnRange]: ''' Return the next user-anchored turn that begins strictly AFTER `after_offset`. A "user anchor" is: kind=='emitted' AND payload.source=='user'. ''' pass @override async def read_frames_range(self, recording_id: RecordingId, start_offset_inclusive: int, end_offset_exclusive: Optional[int]=None, *, limit: Optional[int]=None) -> Sequence[RecordedEvent]: ''' Read frames ordered by offset for [start_offset_inclusive, end_offset_exclusive). If end_offset_exclusive is None, read to the end (respect `limit` if provided). ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory.SessionDocumentStore
from flux0_core.sessions import ConsumerId, Event, EventId, EventSource, EventType, MessageEventData, Session, SessionId, SessionMode, SessionStore, SessionUpdateParams, StatusEventData, ToolEventData from fastapi import HTTPException from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from flux0_core.ids import gen_id from datetime import datetime, timezone from flux0_core.users import User, UserId, UserStore, UserUpdateParams from flux0_nanodb.query import And, Comparison, QueryFilter from flux0_core.types import JSONSerializable import asyncio from flux0_nanodb.api import DocumentCollection, DocumentDatabase from flux0_core.agents import Agent, AgentId, AgentStore, AgentType, AgentUpdateParams class SessionDocumentStore(SessionStore): VERSION = DocumentVersion('0.0.1') def __init__(self, db: DocumentDatabase): self.db = db self._session_col: DocumentCollection[_SessionDocument] self._event_col: DocumentCollection[_EventDocument] async def __aenter__(self) -> Self: self._session_col = await self.db.create_collection('sessions', _SessionDocument) self._event_col = await self.db.create_collection('session_events', _EventDocument) return self async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize_session(self, session: Session) -> _SessionDocument: return _SessionDocument(id=DocumentID(session.id), version=self.VERSION, agent_id=session.agent_id, user_id=session.user_id, mode=session.mode, title=session.title, consumption_offsets=session.consumption_offsets, created_at=session.created_at, metadata=session.metadata) def _deserialize_session(self, doc: _SessionDocument) -> Session: return Session(id=SessionId(doc['id']), agent_id=doc['agent_id'], user_id=doc['user_id'], mode=doc['mode'], title=doc.get('title'), consumption_offsets=doc['consumption_offsets'], created_at=doc['created_at'], metadata=doc.get('metadata', None)) def _serialize_event(self, session_id: SessionId, event: Event) -> _EventDocument: return _EventDocument(id=DocumentID(event.id), version=self.VERSION, session_id=session_id, source=event.source, type=event.type, offset=event.offset, correlation_id=event.correlation_id, data=event.data, deleted=event.deleted, created_at=event.created_at, metadata=event.metadata) def _deserialize_event(self, doc: _EventDocument) -> Event: return Event(id=EventId(doc['id']), source=doc['source'], type=doc['type'], offset=doc['offset'], correlation_id=doc['correlation_id'], data=doc['data'], deleted=doc['deleted'], created_at=doc['created_at'], metadata=doc.get('metadata')) @override async def create_session(self, user_id: UserId, agent_id: AgentId, id: Optional[SessionId]=None, mode: Optional[SessionMode]=None, title: Optional[str]=None, metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Session: if id: existing = await self.read_session(id) if existing: raise HTTPException(status_code=409, detail=f'Session with id {id} already exists') created_at = created_at or datetime.now(timezone.utc) consumption_offsets: dict[ConsumerId, int] = {'client': 0} session = Session(id=id or SessionId(gen_id()), user_id=user_id, agent_id=agent_id, mode=mode or 'auto', title=title, consumption_offsets=consumption_offsets, created_at=created_at, metadata=metadata) await self._session_col.insert_one(document=self._serialize_session(session)) return session @override async def read_session(self, session_id: SessionId) -> Optional[Session]: result = await self._session_col.find(Comparison(path='id', op='$eq', value=session_id)) return self._deserialize_session(result[0]) if result else None @override async def delete_session(self, session_id: SessionId) -> bool: events = await self.list_events(session_id) futures = [asyncio.ensure_future(self._event_col.delete_one(Comparison(path='id', op='$eq', value=e.id))) for e in events] await asyncio.gather(*futures, return_exceptions=False) result = await self._session_col.delete_one(Comparison(path='id', op='$eq', value=session_id)) return result.deleted_count > 0 @override async def update_session(self, session_id: SessionId, params: SessionUpdateParams) -> Session: update_data = {k: v for k, v in params.items() if v is not None} patch: List[JSONPatchOperation] = [{'op': 'replace', 'path': f'/{k}', 'value': v} for k, v in update_data.items()] await self._session_col.update_one(Comparison(path='id', op='$eq', value=session_id), patch) updated = await self.read_session(session_id) if not updated: raise ValueError(f'Session not found: {session_id}') return updated @override async def list_sessions(self, agent_id: Optional[AgentId]=None, user_id: Optional[UserId]=None) -> Sequence[Session]: expressions: List[QueryFilter] = [] if agent_id is not None: expressions.append(Comparison(path='agent_id', op='$eq', value=str(agent_id))) if user_id is not None: expressions.append(Comparison(path='user_id', op='$eq', value=str(user_id))) query_filter: Optional[QueryFilter] = None if expressions: query_filter = And(expressions=expressions) return [self._deserialize_session(d) for d in await self._session_col.find(query_filter)] @override async def create_event(self, session_id: SessionId, source: EventSource, type: EventType, correlation_id: str, data: Union[MessageEventData, StatusEventData, ToolEventData], metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Event: session = await self.read_session(session_id) if session is None: raise ValueError(f'Session not found: {session_id}') events = await self.list_events(session_id) offset = len(list(events)) created_at = created_at or datetime.now(timezone.utc) event = Event(id=EventId(gen_id()), source=source, type=type, offset=offset, correlation_id=correlation_id, data=data, metadata=metadata, deleted=False, created_at=created_at) await self._event_col.insert_one(document=self._serialize_event(session_id, event)) return event @override async def read_event(self, session_id: SessionId, event_id: EventId) -> Optional[Event]: result = await self._event_col.find(And(expressions=[Comparison(path='id', op='$eq', value=event_id), Comparison(path='session_id', op='$eq', value=session_id)])) return self._deserialize_event(result[0]) if result else None @override async def delete_event(self, event_id: EventId) -> bool: result = await self._event_col.delete_one(Comparison(path='id', op='$eq', value=event_id)) return result.deleted_count > 0 @override async def list_events(self, session_id: SessionId, source: Optional[EventSource]=None, correlation_id: Optional[str]=None, types: Sequence[EventType]=[], min_offset: Optional[int]=None, exclude_deleted: bool=True) -> Sequence[Event]: expressions: List[QueryFilter] = [Comparison(path='session_id', op='$eq', value=session_id)] if source is not None: expressions.append(Comparison(path='source', op='$eq', value=source)) if correlation_id is not None: expressions.append(Comparison(path='correlation_id', op='$eq', value=correlation_id)) if types: expressions.append(Comparison(path='type', op='$in', value=list(types))) if min_offset is not None: expressions.append(Comparison(path='offset', op='$gte', value=min_offset)) if exclude_deleted: expressions.append(Comparison(path='deleted', op='$eq', value=False)) query_filter: Optional[QueryFilter] = None if expressions: query_filter = And(expressions=expressions) return [self._deserialize_event(d) for d in await self._event_col.find(query_filter)]
class SessionDocumentStore(SessionStore): def __init__(self, db: DocumentDatabase): pass async def __aenter__(self) -> Self: pass async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize_session(self, session: Session) -> _SessionDocument: pass def _deserialize_session(self, doc: _SessionDocument) -> Session: pass def _serialize_event(self, session_id: SessionId, event: Event) -> _EventDocument: pass def _deserialize_event(self, doc: _EventDocument) -> Event: pass @override async def create_session(self, user_id: UserId, agent_id: AgentId, id: Optional[SessionId]=None, mode: Optional[SessionMode]=None, title: Optional[str]=None, metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Session: pass @override async def read_session(self, session_id: SessionId) -> Optional[Session]: pass @override async def delete_session(self, session_id: SessionId) -> bool: pass @override async def update_session(self, session_id: SessionId, params: SessionUpdateParams) -> Session: pass @override async def list_sessions(self, agent_id: Optional[AgentId]=None, user_id: Optional[UserId]=None) -> Sequence[Session]: pass @override async def create_event(self, session_id: SessionId, source: EventSource, type: EventType, correlation_id: str, data: Union[MessageEventData, StatusEventData, ToolEventData], metadata: Optional[Mapping[str, JSONSerializable]]=None, created_at: Optional[datetime]=None) -> Event: pass @override async def read_event(self, session_id: SessionId, event_id: EventId) -> Optional[Event]: pass @override async def delete_event(self, event_id: EventId) -> bool: pass @override async def list_events(self, session_id: SessionId, source: Optional[EventSource]=None, correlation_id: Optional[str]=None, types: Sequence[EventType]=[], min_offset: Optional[int]=None, exclude_deleted: bool=True) -> Sequence[Event]: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory.UserDocumentStore
from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from flux0_core.ids import gen_id from datetime import datetime, timezone from flux0_core.users import User, UserId, UserStore, UserUpdateParams from flux0_nanodb.query import And, Comparison, QueryFilter from flux0_nanodb.api import DocumentCollection, DocumentDatabase class UserDocumentStore(UserStore): VERSION = DocumentVersion('0.0.1') def __init__(self, db: DocumentDatabase): self.db = db self._user_col: DocumentCollection[_UserDocument] async def __aenter__(self) -> Self: self._user_col = await self.db.create_collection('users', _UserDocument) return self async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize_user(self, user: User) -> _UserDocument: return _UserDocument(id=DocumentID(user.id), version=self.VERSION, sub=user.sub, name=user.name, email=user.email, created_at=user.created_at) def _deserialize_user(self, doc: _UserDocument) -> User: return User(id=UserId(doc['id']), sub=doc['sub'], name=doc['name'], email=doc.get('email'), created_at=doc['created_at']) @override async def create_user(self, sub: str, name: str, email: Optional[str]=None, created_at: Optional[datetime]=None) -> User: created_at = created_at or datetime.now(timezone.utc) user = User(id=UserId(gen_id()), sub=sub, name=name, email=email, created_at=created_at) await self._user_col.insert_one(document=self._serialize_user(user)) return user @override async def read_user(self, user_id: UserId) -> Optional[User]: result = await self._user_col.find(Comparison(path='id', op='$eq', value=user_id)) return self._deserialize_user(result[0]) if result else None @override async def read_user_by_sub(self, sub: str) -> Optional[User]: result = await self._user_col.find(Comparison(path='sub', op='$eq', value=sub)) return self._deserialize_user(result[0]) if result else None @override async def update_user(self, user_id: UserId, params: UserUpdateParams) -> User: raise NotImplementedError
class UserDocumentStore(UserStore): def __init__(self, db: DocumentDatabase): pass async def __aenter__(self) -> Self: pass async def __aexit__(self, exc_type: Optional[type[BaseException]], exc_value: Optional[BaseException], exec_tb: Optional[object]) -> None: pass def _serialize_user(self, user: User) -> _UserDocument: pass def _deserialize_user(self, doc: _UserDocument) -> User: pass @override async def create_user(self, sub: str, name: str, email: Optional[str]=None, created_at: Optional[datetime]=None) -> User: pass @override async def read_user(self, user_id: UserId) -> Optional[User]: pass @override async def read_user_by_sub(self, sub: str) -> Optional[User]: pass @override async def update_user(self, user_id: UserId, params: UserUpdateParams) -> User: pass
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327,883
flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory._AgentDocument
from flux0_core.agents import Agent, AgentId, AgentStore, AgentType, AgentUpdateParams from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from datetime import datetime, timezone from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override class _AgentDocument(TypedDict, total=False): id: DocumentID version: DocumentVersion type: AgentType name: str description: Optional[str] created_at: datetime
class _AgentDocument(TypedDict, total=False): pass
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327,884
flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory._EventDocument
from flux0_core.sessions import ConsumerId, Event, EventId, EventSource, EventType, MessageEventData, Session, SessionId, SessionMode, SessionStore, SessionUpdateParams, StatusEventData, ToolEventData from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from datetime import datetime, timezone from dataclasses import dataclass from flux0_core.types import JSONSerializable @dataclass(frozen=True) class _EventDocument(TypedDict, total=False): id: DocumentID version: DocumentVersion session_id: SessionId source: EventSource type: EventType offset: int correlation_id: str data: Union[MessageEventData, StatusEventData, ToolEventData] deleted: bool created_at: datetime metadata: Optional[Mapping[str, JSONSerializable]]
@dataclass(frozen=True) class _EventDocument(TypedDict, total=False): pass
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327,885
flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory._RecordedEventDocument
from flux0_core.recordings import RecordedChunkPayload, RecordedEmittedPayload, RecordedEvent, RecordedEventId, RecordedEventKind, RecordedEventPayload, RecordedHeaderPayload, RecordingId, RecordingStore, TurnRange from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from datetime import datetime, timezone from dataclasses import dataclass @dataclass(frozen=True) class _RecordedEventDocument(TypedDict, total=False): id: DocumentID version: DocumentVersion recording_id: Required[RecordingId] offset: Required[int] kind: Required[RecordedEventKind] created_at: Required[datetime] payload: Required[RecordedEventPayload]
@dataclass(frozen=True) class _RecordedEventDocument(TypedDict, total=False): pass
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327,886
flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory._SessionDocument
from flux0_core.sessions import ConsumerId, Event, EventId, EventSource, EventType, MessageEventData, Session, SessionId, SessionMode, SessionStore, SessionUpdateParams, StatusEventData, ToolEventData from flux0_core.types import JSONSerializable from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from flux0_core.users import User, UserId, UserStore, UserUpdateParams from datetime import datetime, timezone from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from flux0_core.agents import Agent, AgentId, AgentStore, AgentType, AgentUpdateParams class _SessionDocument(TypedDict, total=False): id: DocumentID version: DocumentVersion agent_id: AgentId user_id: UserId mode: SessionMode title: Optional[str] consumption_offsets: Mapping[ConsumerId, int] created_at: datetime metadata: Optional[Mapping[str, JSONSerializable]]
class _SessionDocument(TypedDict, total=False): pass
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327,887
flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/nanodb_memory.py
nanodb_memory._UserDocument
from flux0_nanodb.types import DocumentID, DocumentVersion, JSONPatchOperation, SortingOrder from typing import DefaultDict, List, Mapping, Optional, Required, Self, Sequence, TypedDict, Union, override from datetime import datetime, timezone class _UserDocument(TypedDict, total=False): id: DocumentID version: DocumentVersion sub: str name: str email: Optional[str] created_at: datetime
class _UserDocument(TypedDict, total=False): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/examples/openai_simple/agent.py
openai_simple.agent.OpenAIChatAgentRunner
import uuid from flux0_core.agent_runners.api import AgentRunner, Deps, agent_runner from flux0_core.sessions import EventId, MessageEventData, StatusEventData from typing import cast from openai.types.chat import ChatCompletionSystemMessageParam, ChatCompletionUserMessageParam from openai import AsyncOpenAI import time from flux0_stream.types import ChunkEvent, JsonPatchOperation import asyncio from flux0_core.agent_runners.context import Context @agent_runner('openai_simple') class OpenAIChatAgentRunner(AgentRunner): def __init__(self) -> None: self.client: AsyncOpenAI = AsyncOpenAI() async def run(self, context: Context, deps: Deps) -> bool: agent = await deps.read_agent(context.agent_id) if not agent: raise ValueError(f'Agent {context.agent_id} not found') events = await deps.list_session_events(context.session_id) last_event = events[-1] if last_event.type != 'message': return False user_event_data = cast(MessageEventData, last_event.data) user_input = next((part['content'] for part in user_event_data['parts'] if part['type'] == 'content'), None) if not user_input: raise ValueError('No user input content found') event_id = EventId(uuid.uuid4().hex) seq = 0 try: await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='processing', data={'detail': 'Thinking...'})) await asyncio.sleep(0.5) await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='typing')) messages: list[ChatCompletionSystemMessageParam | ChatCompletionUserMessageParam] = [ChatCompletionSystemMessageParam(role='system', content='Be concise.'), ChatCompletionUserMessageParam(role='user', content=str(user_input))] stream = await self.client.chat.completions.create(model='gpt-4o', stream=True, messages=messages) async for chunk in stream: delta = chunk.choices[0].delta.content if delta: patch: JsonPatchOperation = {'op': 'add', 'path': '/-', 'value': delta} chunk_event = ChunkEvent(correlation_id=deps.correlator.correlation_id, seq=seq, event_id=event_id, patches=[patch], metadata={'agent_id': agent.id, 'agent_name': agent.name}, timestamp=time.time()) await deps.event_emitter.enqueue_event_chunk(chunk_event) seq += 1 await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, event_id=event_id, data=StatusEventData(type='status', status='ready')) return True except Exception as e: await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='error', data=str(e))) return False finally: await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='completed', acknowledged_offset=0))
@agent_runner('openai_simple') class OpenAIChatAgentRunner(AgentRunner): def __init__(self) -> None: pass async def run(self, context: Context, deps: Deps) -> bool: pass
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327,889
flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/cli/src/flux0_cli/utils/output.py
output.OutputFormatter
from typing import Optional, Sequence, Union from rich.table import Table from rich.console import Console import json from jsonpath_ng import parse import click from pydantic import BaseModel class OutputFormatter: @staticmethod def format(data: Union[BaseModel, Sequence[BaseModel]], output_format: str='table', jsonpath_expr: Optional[str]=None) -> str: """ Format one or more Pydantic models using the specified output format. """ models = [data] if isinstance(data, BaseModel) else data data_dicts = [model.model_dump() for model in models] if output_format == 'json': return json.dumps(data_dicts[0] if isinstance(data, BaseModel) else data_dicts, default=str, indent=2) elif output_format == 'table': if not data_dicts: return '' console = Console() table = Table(show_header=True, header_style='bold') headers = list(data_dicts[0].keys()) for header in headers: table.add_column(header) for d in data_dicts: table.add_row(*(str(d.get(header, '')) for header in headers)) console.print(table) return '' elif output_format == 'jsonpath': if jsonpath_expr is None: jsonpath_expr = '$' expr = parse(jsonpath_expr) matches = [match.value for d in data_dicts for match in expr.find(d)] if not matches: return json.dumps(None) elif len(matches) == 1: return json.dumps(matches[0], default=str, indent=2) else: return json.dumps(matches, default=str, indent=2) else: raise click.ClickException(f'Unknown output format: {output_format}')
class OutputFormatter: @staticmethod def format(data: Union[BaseModel, Sequence[BaseModel]], output_format: str='table', jsonpath_expr: Optional[str]=None) -> str: ''' Format one or more Pydantic models using the specified output format. ''' pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/examples/static/static_agent.py
static.static_agent.StaticAgentRunner
import asyncio from flux0_stream.types import ChunkEvent from flux0_core.sessions import EventId, StatusEventData import uuid from examples.utils.utils import read_user_input, send_processing_event import time from flux0_core.agent_runners.context import Context from flux0_core.agent_runners.api import AgentRunner, Deps, agent_runner @agent_runner('static_agent') class StaticAgentRunner(AgentRunner): async def run(self, context: Context, deps: Deps) -> bool: agent = await deps.read_agent(context.agent_id) if not agent: raise ValueError(f'Agent with id {context.agent_id} not found') user_input = await read_user_input(deps, context) if not user_input: raise ValueError('No user input found in session events') deps.logger.info(f'User Input: {user_input} for session {context.session_id} and agent {agent.id}') await asyncio.sleep(2) await send_processing_event(deps, 'Thinking...') await asyncio.sleep(2) await send_processing_event(deps, 'Reasoning...') event_id = EventId(uuid.uuid4().hex) tool_call = ChunkEvent(correlation_id=deps.correlator.correlation_id, seq=0, event_id=event_id, patches=[{'op': 'add', 'path': '/tool_calls/0', 'value': {'type': 'tool_call', 'tool_call_id': 'id1234', 'tool_name': 'get_weather', 'args': {'city': 'tel aviv'}}}], timestamp=time.time(), metadata={'agent_id': agent.id, 'agent_name': agent.name}) await deps.event_emitter.enqueue_event_chunk(tool_call) await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='ready'), event_id=event_id) await asyncio.sleep(1) event_id = EventId(uuid.uuid4().hex) tool_call_result = ChunkEvent(correlation_id=deps.correlator.correlation_id, seq=0, event_id=event_id, patches=[{'op': 'add', 'path': '/tool_call_results/0', 'value': {'tool_call_id': 'id1234', 'tool_name': 'get_weather', 'data': {'result': "It's always sunny in Israel!"}, 'args': {'city': 'tel aviv'}}}], timestamp=time.time(), metadata={'agent_id': agent.id, 'agent_name': agent.name}) await deps.event_emitter.enqueue_event_chunk(tool_call_result) await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='ready'), event_id=event_id) await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='typing')) event_id = EventId(uuid.uuid4().hex) cec = ChunkEvent(correlation_id=deps.correlator.correlation_id, seq=0, event_id=event_id, patches=[{'op': 'add', 'path': '/-', 'value': f'Hey there! I received your input: {user_input}'}], metadata={'agent_id': agent.id, 'agent_name': agent.name}, timestamp=time.time()) print(f'Sending response: {cec}') await deps.event_emitter.enqueue_event_chunk(cec) await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='ready'), event_id=event_id) await deps.event_emitter.enqueue_status_event(correlation_id=deps.correlator.correlation_id, data=StatusEventData(type='status', status='completed')) return True
@agent_runner('static_agent') class StaticAgentRunner(AgentRunner): async def run(self, context: Context, deps: Deps) -> bool: pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/types.py
types.NanoDBStorageType
from enum import Enum class NanoDBStorageType(Enum): MEMORY = 'nanodb_memory' JSON = 'nanodb_json'
class NanoDBStorageType(Enum): pass
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327,892
flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/packages/core/src/flux0_core/storage/types.py
types.StorageType
from enum import Enum class StorageType(Enum): NANODB = 'nanodb' MONGODB = 'mongodb'
class StorageType(Enum): pass
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flux0-ai/flux0
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/flux0-ai_flux0/scripts/utils.py
utils.Package
from dataclasses import dataclass from pathlib import Path from typing import Callable, List, NoReturn, Optional import subprocess import sys @dataclass(frozen=True) class Package: name: str path: Path def run_command(self, command: str, env: Optional[dict[str, str]]=None) -> int: """ Execute a shell command in the package's directory. Returns the exit code. """ print(f'⏳ Running: {command} (in {self.path})') result = subprocess.run(command, shell=True, cwd=self.path, capture_output=True, text=True, env=env) if result.stdout: print(result.stdout) if result.returncode != 0: print(result.stderr, file=sys.stderr) return result.returncode
@dataclass(frozen=True) class Package: def run_command(self, command: str, env: Optional[dict[str, str]]=None) -> int: ''' Execute a shell command in the package's directory. Returns the exit code. ''' pass
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Euro-BioImaging/EuBI-Bridge
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/Euro-BioImaging_EuBI-Bridge/eubi_bridge/base/data_manager.py
Euro-BioImaging_EuBI-Bridge.eubi_bridge.base.data_manager.ArrayManager
from dask import array as da import os from eubi_bridge.utils.convenience import sensitive_glob, is_zarr_group, is_zarr_array, take_filepaths, autocompute_chunk_shape from pathlib import Path from typing import Union from eubi_bridge.ngff.defaults import unit_map, scale_map, default_axes import zarr import zarr import os class ArrayManager: essential_omexml_fields = {'physical_size_x', 'physical_size_x_unit', 'physical_size_y', 'physical_size_y_unit', 'physical_size_z', 'physical_size_z_unit', 'time_increment', 'time_increment_unit', 'size_x', 'size_y', 'size_z', 'size_t', 'size_c'} def __init__(self, path: Union[str, Path]=None, series: int=None, metadata_reader='bfio', **kwargs): self.path = path self.series = series if series is not None: assert isinstance(self.series, (int, str)), f'The series parameter must be either an integer or string. Selection of multiple series from the same image is currently not supported.' if self.series is None: self.series = 0 self._seriesattrs = '' else: self._seriesattrs = self.series self._meta_reader = metadata_reader self.omemeta = None if not path is None: if is_zarr_group(path): self.img = NGFFImageMeta(self.path) else: self.img = PFFImageMeta(self.path, self.series, self._meta_reader) self.axes = self.img.get_axes() self.array = None self.pyr = self.img.pyr self._channels = None self.set_arraydata() def fill_default_meta(self): if self.array is None: raise Exception(f'Array is missing. An array needs to be assigned.') new_scaledict = {} new_unitdict = {} values = list(self.scaledict.values()) if not None in values: return for ax, value in self.scaledict.items(): if value is None: if (ax == 'z' or ax == 'y') and self.scaledict['x'] is not None: new_scaledict[ax] = self.scaledict['x'] new_unitdict[ax] = self.unitdict['x'] else: new_scaledict[ax] = scale_map[ax] new_unitdict[ax] = unit_map[ax] else: if ax in self.scaledict.keys(): new_scaledict[ax] = self.scaledict[ax] if ax in self.unitdict.keys(): new_unitdict[ax] = self.unitdict[ax] new_units = [new_unitdict[ax] for ax in self.axes if ax in new_unitdict] new_scales = [new_scaledict[ax] for ax in self.axes if ax in new_scaledict] self.set_arraydata(self.array, self.axes, new_units, new_scales) return self def get_pixel_size_basemap(self, t=1, z=1, y=1, x=1, **kwargs): return {'pixel_size_t': t, 'pixel_size_z': z, 'pixel_size_y': y, 'pixel_size_x': x} def get_unit_basemap(self, t='second', z='micrometer', y='micrometer', x='micrometer', **kwargs): return {'unit_t': t, 'unit_z': z, 'unit_y': y, 'unit_x': x} def update_meta(self, new_scaledict={}, new_unitdict={}): scaledict = self.img.get_scaledict() for key, val in new_scaledict.items(): if key in scaledict.keys() and val is not None: scaledict[key] = val if 'c' in scaledict: scales = [scaledict[ax] for ax in self.axes] else: scales = [scaledict[ax] for ax in self.caxes] unitdict = self.img.get_unitdict() for key, val in new_unitdict.items(): if key in unitdict.keys() and val is not None: unitdict[key] = val if 'c' in unitdict: units = [expand_units(unitdict[ax]) for ax in self.axes] else: units = [expand_units(unitdict[ax]) for ax in self.caxes] self.set_arraydata(array=self.array, axes=self.axes, units=units, scales=scales) def _ensure_correct_channels(self): if self.array is None: return if self.channels is None: return shapedict = dict(zip(list(self.axes), self.array.shape)) csize = shapedict['c'] channelsize = len(self.channels) if channelsize > csize: self._channels = [channel for channel in self.channels if channel['label'] is not None] def fix_bad_channels(self): chn = ChannelIterator() for i, channel in enumerate(self.channels): if channel['label'] is None: channel = chn.__next__() self.channels[i] = channel def set_arraydata(self, array=None, axes=None, units=None, scales=None, **kwargs): axes = axes or self.img.get_axes() units = units or self.img.get_units() scales = scales or self.img.get_scales() self.axes = axes if array is not None: self.array = array self.ndim = self.array.ndim assert len(self.axes) == self.ndim self.caxes = ''.join([ax for ax in axes if ax != 'c']) if self.array is not None: self.chunkdict = dict(zip(list(self.axes), self.array.chunksize)) self.shapedict = dict(zip(list(self.axes), self.array.shape)) if 'c' in self.shapedict: self._ensure_correct_channels() if len(units) == len(self.axes): self.unitdict = dict(zip(list(self.axes), units)) elif len(units) == len(self.caxes): self.unitdict = dict(zip(list(self.caxes), units)) else: raise Exception(f'Unit length is invalid.') if len(scales) == len(self.axes): self.scaledict = dict(zip(list(self.axes), scales)) elif len(scales) == len(self.caxes): self.scaledict = dict(zip(list(self.caxes), scales)) self.scaledict['c'] = 1 else: raise Exception(f'Scale length is invalid') @property def scales(self): if self.scaledict.__len__() < len(self.axes): return [self.scaledict[ax] for ax in self.caxes] elif self.scaledict.__len__() == len(self.axes): return [self.scaledict[ax] for ax in self.axes] else: raise ValueError @property def units(self): if self.unitdict.__len__() < len(self.axes): return [self.unitdict[ax] for ax in self.caxes] elif self.unitdict.__len__() == len(self.axes): return [self.unitdict[ax] for ax in self.axes] else: raise ValueError @property def channels(self): if self._channels is not None: return self._channels return self.img.get_channels() @property def chunks(self): return [self.chunkdict[ax] for ax in self.axes] def sync_pyramid(self, create_omexml_if_not_exists=False): """ Synchronizes the scale and unit metadata with the Pyramid (if a Pyramid exists). The scale metadata is recalculated for all layers based on the shape of each layer. Also updates the ome-xml metadata to the pyramid. :return: """ if self.pyr is None: raise Exception(f'No pyramid exists.') self.pyr.update_scales(**self.scaledict) self.pyr.update_units(**self.unitdict) if self.omemeta is None: self.omemeta = create_ome_xml(image_shape=self.pyr.base_array.shape, axis_order=self.pyr.axes, pixel_size_x=self.pyr.meta.scaledict.get('0', {}).get('x'), pixel_size_y=self.pyr.meta.scaledict.get('0', {}).get('y'), pixel_size_z=self.pyr.meta.scaledict.get('0', {}).get('z'), pixel_size_t=self.pyr.meta.scaledict.get('0', {}).get('t'), unit_x=self.pyr.meta.unit_dict.get('x'), unit_y=self.pyr.meta.unit_dict.get('y'), unit_z=self.pyr.meta.unit_dict.get('z'), unit_t=self.pyr.meta.unit_dict.get('t'), dtype=str(self.pyr.base_array.dtype), image_name=self.pyr.meta.multiscales.get('name', 'Default image'), channel_names=[channel['label'] for channel in self.channels]) if 'OME' in list(self.pyr.gr.keys()) or create_omexml_if_not_exists: self.save_omexml(self.pyr.gr.store.root, overwrite=True) self.pyr.meta.save_changes() def create_omemeta(self): self.fill_default_meta() pixel_size_basemap = self.get_pixel_size_basemap(**self.scaledict) unit_basemap = self.get_unit_basemap(**self.unitdict) self.omemeta = create_ome_xml(image_shape=self.array.shape, axis_order=self.axes, **pixel_size_basemap, **unit_basemap, dtype=str(self.array.dtype), channel_names=[channel['label'] for channel in self.channels]) self.pixels = self.omemeta.images[0].pixels missing_fields = self.essential_omexml_fields - self.pixels.model_fields_set self.pixels.model_fields_set.update(missing_fields) self.omemeta.images[0].pixels = self.pixels return self def save_omexml(self, base_path: str, overwrite=False): assert self.omemeta is not None, f'No ome-xml exists.' gr = zarr.group(base_path) gr.create_group('OME', overwrite=overwrite) path = os.path.join(gr.store.root, 'OME/METADATA.ome.xml') with open(path, 'w', encoding='utf-8') as f: f.write(self.omemeta.to_xml()) if gr.info._zarr_format == 2: gr['OME'].attrs['series'] = [self._seriesattrs] else: gr['OME'].attrs['ome'] = dict(version='0.5', series=[str(self._seriesattrs)]) def squeeze(self): singlet_axes = [ax for ax, size in self.shapedict.items() if size == 1] newaxes = ''.join((ax for ax in self.axes if ax not in singlet_axes)) newunits, newscales = ([], []) assert self.scaledict.__len__() - self.unitdict.__len__() <= 1 for ax in self.axes: if ax not in singlet_axes: if ax in self.unitdict.keys(): newunits.append(self.unitdict[ax]) if ax in self.scaledict.keys(): newscales.append(self.scaledict[ax]) newarray = da.squeeze(self.array) self.set_arraydata(newarray, newaxes, newunits, newscales) def transpose(self, newaxes): newaxes = ''.join((ax for ax in newaxes if ax in self.axes)) new_ids = [self.axes.index(ax) for ax in newaxes] newunits, newscales = ([], []) assert self.scaledict.__len__() - self.unitdict.__len__() <= 1 for ax in newaxes: if ax in self.unitdict: newunits.append(self.unitdict[ax]) if ax in self.scaledict.keys(): newscales.append(self.scaledict[ax]) newarray = self.array.transpose(*new_ids) self.set_arraydata(newarray, newaxes, newunits, newscales) def crop(self, trange=None, crange=None, zrange=None, yrange=None, xrange=None): slicedict = {'t': slice(*trange) if trange is not None else slice(None), 'c': slice(*crange) if crange is not None else slice(None), 'z': slice(*zrange) if zrange is not None else slice(None), 'y': slice(*yrange) if yrange is not None else slice(None), 'x': slice(*xrange) if xrange is not None else slice(None)} slicedict = {ax: r for ax, r in slicedict.items() if ax in self.axes} slices = tuple([slicedict[ax] for ax in self.axes]) array = self.array[slices] self.set_arraydata(array, self.axes, self.units, self.scales) def to_cupy(self): try: import cupy except: raise Exception('Cupy not installed but required for this operation.') array = self.array.map_blocks(cupy.asarray) self.set_arraydata(array, self.axes, self.units, self.scales) def split(self): pass def get_autocomputed_chunks(self, dtype=None): array_shape = self.array.shape dtype = dtype or self.array.dtype axes = self.axes chunk_shape = autocompute_chunk_shape(array_shape=array_shape, axes=axes, dtype=dtype) return chunk_shape
class ArrayManager: def __init__(self, path: Union[str, Path]=None, series: int=None, metadata_reader='bfio', **kwargs): pass def fill_default_meta(self): pass def get_pixel_size_basemap(self, t=1, z=1, y=1, x=1, **kwargs): pass def get_unit_basemap(self, t='second', z='micrometer', y='micrometer', x='micrometer', **kwargs): pass def update_meta(self, new_scaledict={}, new_unitdict={}): pass def _ensure_correct_channels(self): pass def fix_bad_channels(self): pass def set_arraydata(self, array=None, axes=None, units=None, scales=None, **kwargs): pass @property def scales(self): pass @property def units(self): pass @property def channels(self): pass @property def chunks(self): pass def sync_pyramid(self, create_omexml_if_not_exists=False): ''' Synchronizes the scale and unit metadata with the Pyramid (if a Pyramid exists). The scale metadata is recalculated for all layers based on the shape of each layer. Also updates the ome-xml metadata to the pyramid. :return: ''' pass def create_omemeta(self): pass def save_omexml(self, base_path: str, overwrite=False): pass def squeeze(self): pass def transpose(self, newaxes): pass def crop(self, trange=None, crange=None, zrange=None, yrange=None, xrange=None): pass def to_cupy(self): pass def split(self): pass def get_autocomputed_chunks(self, dtype=None): pass
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Euro-BioImaging/EuBI-Bridge
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/Euro-BioImaging_EuBI-Bridge/eubi_bridge/base/data_manager.py
Euro-BioImaging_EuBI-Bridge.eubi_bridge.base.data_manager.BatchManager
class BatchManager: def __init__(self, managers): self.managers = managers def _collect_scaledict(self, **kwargs): """ Retrieves pixel sizes for image dimensions. Args: **kwargs: Pixel sizes for time, channel, z, y, and x dimensions. Returns: list: Pixel sizes. """ t = kwargs.get('time_scale', None) c = kwargs.get('channel_scale', None) y = kwargs.get('y_scale', None) x = kwargs.get('x_scale', None) z = kwargs.get('z_scale', None) fulldict = dict(zip('tczyx', [t, c, z, y, x])) final = {key: val for key, val in fulldict.items() if val is not None} return final def _collect_unitdict(self, **kwargs): """ Retrieves unit specifications for image dimensions. Args: **kwargs: Unit values for time, channel, z, y, and x dimensions. Returns: list: Unit values. """ t = kwargs.get('time_unit', None) c = kwargs.get('channel_unit', None) y = kwargs.get('y_unit', None) x = kwargs.get('x_unit', None) z = kwargs.get('z_unit', None) fulldict = dict(zip('tczyx', [t, c, z, y, x])) final = {key: val for key, val in fulldict.items() if val is not None} return final def _collect_chunks(self, **kwargs): """ Retrieves chunk specifications for image dimensions. Args: **kwargs: Chunk sizes for time, channel, z, y, and x dimensions. Returns: list: Chunk shape. """ t = kwargs.get('time_chunk', None) c = kwargs.get('channel_chunk', None) y = kwargs.get('y_chunk', None) x = kwargs.get('x_chunk', None) z = kwargs.get('z_chunk', None) fulldict = dict(zip('tczyx', [t, c, z, y, x])) final = {key: val for key, val in fulldict.items() if val is not None} return final def fill_default_meta(self): for key, manager in self.managers.items(): manager.fill_default_meta() def squeeze(self): for key, manager in self.managers.items(): manager.squeeze() def to_cupy(self): for key, manager in self.managers.items(): manager.to_cupy() def crop(self, time_range=None, channel_range=None, z_range=None, y_range=None, x_range=None, **kwargs): if any([item is not None for item in (time_range, channel_range, z_range, y_range, x_range)]): for key, manager in self.managers.items(): manager.crop(time_range, channel_range, z_range, y_range, x_range) def transpose(self, newaxes): for key, manager in self.managers.items(): manager.transpose(newaxes) def sync_pyramids(self): pass
class BatchManager: def __init__(self, managers): pass def _collect_scaledict(self, **kwargs): ''' Retrieves pixel sizes for image dimensions. Args: **kwargs: Pixel sizes for time, channel, z, y, and x dimensions. Returns: list: Pixel sizes. ''' pass def _collect_unitdict(self, **kwargs): ''' Retrieves unit specifications for image dimensions. Args: **kwargs: Unit values for time, channel, z, y, and x dimensions. Returns: list: Unit values. ''' pass def _collect_chunks(self, **kwargs): ''' Retrieves chunk specifications for image dimensions. Args: **kwargs: Chunk sizes for time, channel, z, y, and x dimensions. Returns: list: Chunk shape. ''' pass def fill_default_meta(self): pass def squeeze(self): pass def to_cupy(self): pass def crop(self, time_range=None, channel_range=None, z_range=None, y_range=None, x_range=None, **kwargs): pass def transpose(self, newaxes): pass def sync_pyramids(self): pass
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Euro-BioImaging/EuBI-Bridge
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/Euro-BioImaging_EuBI-Bridge/eubi_bridge/base/data_manager.py
Euro-BioImaging_EuBI-Bridge.eubi_bridge.base.data_manager.ChannelIterator
class ChannelIterator: """ Iterator for generating and managing channel colors. This class provides a way to iterate through a sequence of channel colors, generating new colors in a visually distinct sequence when needed. """ DEFAULT_COLORS = ['FF0000', '00FF00', '0000FF', 'FF00FF', '00FFFF', 'FFFF00', 'FFFFFF'] def __init__(self, num_channels=0): """ Initialize the channel iterator. Args: num_channels: Initial number of channels to pre-generate """ self._channels = [] self._current_index = 0 self._generate_channels(num_channels) def _generate_channels(self, count): """Generate the specified number of unique channel colors.""" for i in range(len(self._channels), count): if i < len(self.DEFAULT_COLORS): color = self.DEFAULT_COLORS[i] else: hue = int(i * 137.5 % 360) r, g, b = self._hsv_to_rgb(hue / 360.0, 1.0, 1.0) color = f'{int(r * 255):02X}{int(g * 255):02X}{int(b * 255):02X}' self._channels.append({'label': f'Channel {i + 1}', 'color': color}) @staticmethod def _hsv_to_rgb(h, s, v): """Convert HSV color space to RGB color space.""" h = h * 6.0 i = int(h) f = h - i p = v * (1.0 - s) q = v * (1.0 - s * f) t = v * (1.0 - s * (1.0 - f)) if i == 0: return (v, t, p) elif i == 1: return (q, v, p) elif i == 2: return (p, v, t) elif i == 3: return (p, q, v) elif i == 4: return (t, p, v) else: return (v, p, q) def __iter__(self): """Return the iterator object itself.""" self._current_index = 0 return self def __next__(self): """Return the next channel color.""" if self._current_index >= len(self._channels): self._generate_channels(len(self._channels) + 1) if self._current_index < len(self._channels): result = self._channels[self._current_index] self._current_index += 1 return result raise StopIteration def get_channel(self, index): """ Get channel color by index. Args: index: Index of the channel to retrieve Returns: dict: Channel information with 'label' and 'color' keys """ if index >= len(self._channels): self._generate_channels(index + 1) return self._channels[index] def __len__(self): """Return the number of generated channels.""" return len(self._channels)
class ChannelIterator: ''' Iterator for generating and managing channel colors. This class provides a way to iterate through a sequence of channel colors, generating new colors in a visually distinct sequence when needed. ''' def __init__(self, num_channels=0): ''' Initialize the channel iterator. Args: num_channels: Initial number of channels to pre-generate ''' pass def _generate_channels(self, count): '''Generate the specified number of unique channel colors.''' pass @staticmethod def _hsv_to_rgb(h, s, v): '''Convert HSV color space to RGB color space.''' pass def __iter__(self): '''Return the iterator object itself.''' pass def __next__(self): '''Return the next channel color.''' pass def get_channel(self, index): ''' Get channel color by index. Args: index: Index of the channel to retrieve Returns: dict: Channel information with 'label' and 'color' keys ''' pass def __len__(self): '''Return the number of generated channels.''' pass
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Euro-BioImaging/EuBI-Bridge
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/Euro-BioImaging_EuBI-Bridge/eubi_bridge/base/data_manager.py
Euro-BioImaging_EuBI-Bridge.eubi_bridge.base.data_manager.NGFFImageMeta
from eubi_bridge.utils.convenience import sensitive_glob, is_zarr_group, is_zarr_array, take_filepaths, autocompute_chunk_shape from eubi_bridge.ngff.multiscales import Pyramid class NGFFImageMeta: def __init__(self, path): if is_zarr_group(path): self.pyr = Pyramid().from_ngff(path) meta = self.pyr.meta self._meta = meta self._base_path = self._meta.resolution_paths[0] else: raise Exception(f'The given path does not contain an NGFF group.') def get_axes(self): return self._meta.axis_order def get_scales(self): return self._meta.get_scale(self._base_path) def get_scaledict(self): return self._meta.get_scaledict(self._base_path) def get_units(self): return self._meta.unit_list def get_unitdict(self): return self._meta.unit_dict def get_channels(self): if not hasattr(self._meta, 'channels'): return None return self._meta.channels
class NGFFImageMeta: def __init__(self, path): pass def get_axes(self): pass def get_scales(self): pass def get_scaledict(self): pass def get_units(self): pass def get_unitdict(self): pass def get_channels(self): pass
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Euro-BioImaging/EuBI-Bridge
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/Euro-BioImaging_EuBI-Bridge/eubi_bridge/base/data_manager.py
Euro-BioImaging_EuBI-Bridge.eubi_bridge.base.data_manager.PFFImageMeta
from eubi_bridge.base.readers import read_metadata_via_bioio_bioformats, read_metadata_via_extension, read_metadata_via_bfio from ome_types.model import OME, Image, Pixels, Channel class PFFImageMeta: essential_omexml_fields = {'physical_size_x', 'physical_size_x_unit', 'physical_size_y', 'physical_size_y_unit', 'physical_size_z', 'physical_size_z_unit', 'time_increment', 'time_increment_unit', 'size_x', 'size_y', 'size_z', 'size_t', 'size_c'} def __init__(self, path, series, meta_reader='bioio'): if path.endswith('ome') or path.endswith('xml'): from ome_types import OME omemeta = OME().from_xml(path) elif meta_reader == 'bioio': try: omemeta = read_metadata_via_extension(path, series=series) except: omemeta = read_metadata_via_bioio_bioformats(path, series=series) elif meta_reader == 'bfio': try: omemeta = read_metadata_via_bfio(path) except: omemeta = read_metadata_via_bioio_bioformats(path, series=series) else: raise ValueError(f'Unsupported metadata reader: {meta_reader}') if series is None: series = 0 images = [omemeta.images[series]] omemeta.images = images self.omemeta = omemeta self.pixels = self.omemeta.images[0].pixels missing_fields = self.essential_omexml_fields - self.pixels.model_fields_set self.pixels.model_fields_set.update(missing_fields) self.omemeta.images[0].pixels = self.pixels self.pyr = None def get_axes(self): return 'tczyx' def get_scaledict(self): return {'t': self.pixels.time_increment, 'z': self.pixels.physical_size_z, 'y': self.pixels.physical_size_y, 'x': self.pixels.physical_size_x} def get_scales(self): scaledict = self.get_scaledict() caxes = [ax for ax in self.get_axes() if ax != 'c'] return [scaledict[ax] for ax in caxes] def get_unitdict(self): return {'t': self.pixels.time_increment_unit.name.lower(), 'z': self.pixels.physical_size_z_unit.name.lower(), 'y': self.pixels.physical_size_y_unit.name.lower(), 'x': self.pixels.physical_size_x_unit.name.lower()} def get_units(self): unitdict = self.get_unitdict() caxes = [ax for ax in self.get_axes() if ax != 'c'] return [unitdict[ax] for ax in caxes] def get_channels(self): if not hasattr(self.pixels, 'channels'): return None if len(self.pixels.channels) == 0: return None if len(self.pixels.channels) < self.pixels.size_c: chn = ChannelIterator(num_channels=self.pixels.size_c) channels = chn._channels elif len(self.pixels.channels) == self.pixels.size_c: channels = [] for _, channel in enumerate(self.pixels.channels): color = channel.color.as_hex().upper() color = expand_hex_shorthand(color) name = channel.name channels.append(dict(label=name, color=color)) return channels
class PFFImageMeta: def __init__(self, path, series, meta_reader='bioio'): pass def get_axes(self): pass def get_scaledict(self): pass def get_scales(self): pass def get_unitdict(self): pass def get_units(self): pass def get_channels(self): pass
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Euro-BioImaging/EuBI-Bridge
/Users/umroot/Documents/PhD_works/PhD-Core-Contents/Class-level-dataset-curation/unseen_data/git_repos_for_analysis/Euro-BioImaging_EuBI-Bridge/eubi_bridge/base/scale.py
Euro-BioImaging_EuBI-Bridge.eubi_bridge.base.scale.DownscaleManager
import dataclasses import numpy as np @dataclasses.dataclass class DownscaleManager: base_shape: (list, tuple) scale_factor: (list, tuple) n_layers: (list, tuple) scale: (list, tuple) = None def __post_init__(self): ndim = len(self.base_shape) assert len(self.scale_factor) == ndim @property def _scale_ids(self): return np.arange(self.n_layers).reshape(-1, 1) @property def _theoretical_scale_factors(self): return np.power(self.scale_factor, self._scale_ids) @property def output_shapes(self): shapes = np.floor_divide(self.base_shape, self._theoretical_scale_factors) shapes[shapes == 0] = 1 return shapes @property def scale_factors(self): return np.true_divide(self.output_shapes[0], self.output_shapes) @property def scales(self): return np.multiply(self.scale, self.scale_factors)
@dataclasses.dataclass class DownscaleManager: def __post_init__(self): pass @property def _scale_ids(self): pass @property def _theoretical_scale_factors(self): pass @property def output_shapes(self): pass @property def scale_factors(self): pass @property def scales(self): pass
13
0
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3
0
1
0
0
0
0
0
6
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6
31
6
25
15
13
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20
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1
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6