text stringlengths 185 73.3k | repo stringlengths 7 100 | path stringlengths 4 146 | language stringclasses 7
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"""MCP tools for negative keyword shared sets management."""
from server.main import mcp
from server.tools import get_runner, handle_cli_errors
from server.tools.helpers import (
append_pagination,
require_update_fields,
tool_error_dict,
)
@mcp.tool(
name="negativekeywordsharedsets_get",
descript... | axisrow/yandex-direct-mcp-plugin | plugins/yandex-direct/server/tools/negative_keyword_shared_sets.py | .py | 3065e5ca3a2c9c45 | 7.56 | 12 |
"""MCP tools for keyword research."""
from server.main import mcp
from server.tools import ToolError, get_runner, handle_cli_errors
from server.tools.helpers import tool_error_dict
@mcp.tool(
name="keywordsresearch_has_search_volume",
description="Check whether keywords have search volume in given regions. C... | axisrow/yandex-direct-mcp-plugin | plugins/yandex-direct/server/tools/research.py | .py | d28ca02bbe501522 | 7.56 | 12 |
"""MCP tools for retargeting list management."""
from server.main import mcp
from server.tools import get_runner, handle_cli_errors
from server.tools.helpers import (
CliOption,
append_cli_options,
append_pagination,
require_update_fields,
run_single_id_batch,
tool_error_dict,
validate_enum... | axisrow/yandex-direct-mcp-plugin | plugins/yandex-direct/server/tools/retargeting.py | .py | 5fc201189588e199 | 7.56 | 12 |
"""MCP tools for smart ad target management."""
from server.main import mcp
from server.tools import get_runner, handle_cli_errors
from server.tools.helpers import (
CliOption,
append_cli_options,
append_id_filters,
append_pagination,
require_update_fields,
run_set_bids,
run_single_id_batch... | axisrow/yandex-direct-mcp-plugin | plugins/yandex-direct/server/tools/smart_ad_targets.py | .py | 9d1463c26747988b | 7.56 | 12 |
"""Meta-tool: on-demand detailed help for any MCP tool.
To keep the startup context small, every tool exposes only a short one-line
``description``. The full documentation (parameter reference, examples,
constraints) lives in each tool function's docstring and is served lazily
through ``tool_help`` instead of being lo... | axisrow/yandex-direct-mcp-plugin | plugins/yandex-direct/server/tools/tool_help.py | .py | 1a65ddc38a23d2ae | 7.56 | 12 |
"""LRU cache of live application instances."""
from __future__ import annotations
from threading import Lock
from cachetools import TTLCache
from cogbase.core.app import CogBaseApp
def cache_key(account_id: str, namespace_id: str, name: str) -> str:
"""Composite cache key for a live app instance.
An app'... | CogBaseAI/cogbase | api/app_cache.py | .py | 18239bf4a0565ac8 | 7.66 | 20 |
"""FastAPI dependency providers."""
from __future__ import annotations
from dataclasses import dataclass
from typing import Annotated, Any
from fastapi import Depends, Header, HTTPException, Request, status
from api.app_cache import AppCache
from api.auth import InvalidToken, decode_token
from api.system_resources ... | CogBaseAI/cogbase | api/dependencies.py | .py | 3d04270d22419bd4 | 7.66 | 20 |
"""Default-workspace provisioning for a freshly-minted account.
When a brand-new account is minted at signup (the no-invite path), we seed it
with a starter workspace so the user lands on something usable rather than an
empty console: a ``legal-team`` namespace holding a ``contract-analyst``
application built from ``e... | CogBaseAI/cogbase | api/provisioning.py | .py | d5d51990695fc75a | 7.66 | 20 |
"""First-party email/password authentication endpoints.
Signup / login issue an access token (short-lived HS256 JWT) plus a refresh token
(opaque, DB-backed, revocable). Every other route derives its tenant from the
verified access token (see ``api/dependencies.py``), so these endpoints are the
only ones reachable wit... | CogBaseAI/cogbase | api/routers/auth.py | .py | 38268d6b647ce025 | 7.66 | 20 |
"""CRUD endpoints for managing namespaces within an account.
A namespace is an in-account organizational unit: applications, skills, and all
other resources are addressed as ``/namespaces/{namespace}/...``. The account is
the security boundary (the ``X-Account-Id`` header); the namespace is a handle
that is only uniq... | CogBaseAI/cogbase | api/routers/namespaces.py | .py | b70b2ed6bb71bbf7 | 7.66 | 20 |
"""Endpoints for uploading and managing system-wide skills.
Skills are uploaded as a ZIP bundle (SKILL.md + scripts/assets). The bundle bytes
are persisted in the system document store (the shared, multi-node source of
truth) and materialized into a local cache dir for execution. Each skill gets a
stable UUID; applica... | CogBaseAI/cogbase | api/routers/skills.py | .py | e6b148d8d348e682 | 7.66 | 20 |
"""System-level configuration — loaded once at service startup from a YAML file.
The system config defines service-wide defaults for the structured store and
vector store backends. Applications posted to ``POST /applications`` only need
to declare their LLM, embedding, chunker, and pack settings; the store backends
a... | CogBaseAI/cogbase | api/system_config.py | .py | 969cf80b2c0a06a9 | 7.66 | 20 |
"""Shared data primitives used across all layers of CogBase."""
from enum import Enum
from typing import Any
from pydantic import BaseModel, ConfigDict, Field
class TaskStatus(str, Enum):
PENDING = "pending"
RUNNING = "running"
DONE = "done"
FAILED = "failed"
class DocWorkflowStatus(str, Enum):
... | CogBaseAI/cogbase | cogbase/core/models.py | .py | efa4eab3fa4361f4 | 7.66 | 20 |
"""Account profile — the account-scoped company profile document.
The company profile is stable org-wide context a customer supplies once: who they
are, jurisdictions, regulators, risk appetite, house style, role. None of it is
derivable from their documents, and none of it should be re-collected per app — so
it live... | CogBaseAI/cogbase | cogbase/core/profile.py | .py | 116667f38bccc19b | 7.66 | 20 |
"""Abstract contract and built-in implementations for text embedders."""
import abc
import logging
logger = logging.getLogger(__name__)
# Conservative fallback context window (tokens) for a single input text. Most
# hosted embedding models cap one input around 8k tokens (e.g. OpenAI's
# ``text-embedding-3-*`` at 819... | CogBaseAI/cogbase | cogbase/embeddings/base.py | .py | d8520c7a1f151fa5 | 7.66 | 20 |
"""HuggingFace sentence-transformers based implementation of EmbeddingBase."""
import asyncio
import functools
import logging
from typing import cast
from cogbase.embeddings.base import DEFAULT_CONTEXT_WINDOW, EmbeddingBase
logger = logging.getLogger(__name__)
class SentenceTransformersEmbedding(EmbeddingBase):
... | CogBaseAI/cogbase | cogbase/embeddings/huggingface.py | .py | f04928368f9d10a8 | 7.66 | 20 |
"""OpenAI embedding api based implementation of EmbeddingBase.
The provider that provides OpenAI compatible API can use this implementation.
"""
import logging
from typing import Any
from cogbase.embeddings.base import DEFAULT_CONTEXT_WINDOW, EmbeddingBase
logger = logging.getLogger(__name__)
#: Default maximum n... | CogBaseAI/cogbase | cogbase/embeddings/openai.py | .py | b95b8a1c4b2f5ff7 | 7.66 | 20 |
"""Abstract contract for chat-completion LLM backends."""
from __future__ import annotations
import abc
from collections.abc import AsyncGenerator, Awaitable, Callable
from typing import Any, Literal, TypedDict
ReasoningEffort = Literal["minimal", "low", "medium", "high"]
# Conservative fallback context window (tok... | CogBaseAI/cogbase | cogbase/llms/base.py | .py | dc6922148ad4ea46 | 7.66 | 20 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/backup/backup.py | .py | d62d6f7cb1630a68 | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/backup/base.py | .py | d211a06cd5093029 | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/backup/local.py | .py | fe8cc3afa696f3a0 | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/backup/qcow.py | .py | 62dc82d3041df8b3 | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/backup/s3.py | .py | 0610fb5dc9a499ac | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/builder/base.py | .py | 6816b6129bf6ac71 | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/builder/packer.py | .py | a594eb1b59afb982 | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/clients/base_client.py | .py | 5b79a3356065b2c3 | 7.48 | 8 |
# Copyright 2025 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/cmd/base.py | .py | b02f370c67be2e03 | 7.48 | 8 |
# Copyright 2025-2026 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | exordos/exordos | exordos/cmd/compute/common.py | .py | 862bb025dc86f772 | 7.48 | 8 |
# Copyright 2026 Genesis Corporation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | exordos/exordos | exordos/cmd/deploy/commands.py | .py | 4edf9e6040dbc949 | 7.48 | 8 |
#!/usr/bin/env python3
"""
Beast Mode Trading Dashboard 🚀
Real-time performance monitoring for the Unified Advanced Trading System.
Features:
- Live portfolio performance across all strategies
- Risk metrics and capital efficiency
- Market making vs directional trading breakdown
- Expected returns and Sharpe ratios
... | anglil/kalshi-ai-trading-bot | beast_mode_dashboard.py | .py | cae041332c07f6bc | 7.48 | 8 |
"""
Deep analysis of all trading activity to identify the dominant loss driver.
Pulls fills, settlements, orders, and positions from Kalshi API.
"""
import asyncio
import json
from datetime import datetime, timedelta
from collections import defaultdict
from src.clients.kalshi_client import KalshiClient
async def main(... | anglil/kalshi-ai-trading-bot | deep_analysis.py | .py | 200ab92b320cfed1 | 7.48 | 8 |
#!/usr/bin/env python3
"""
Beast Mode Trading Dashboard 🚀
Real-time performance monitoring for the Unified Advanced Trading System.
Features:
- Live portfolio performance across all strategies
- Risk metrics and capital efficiency
- Market making vs directional trading breakdown
- Expected returns and Sharpe ratios
... | anglil/kalshi-ai-trading-bot | scripts/beast_mode_dashboard.py | .py | b9abced3ad50cd63 | 7.48 | 8 |
#!/usr/bin/env python3
"""
Cost Monitor - Real-time AI spending tracker for Kalshi Trading System
Usage:
python cost_monitor.py # Show today's costs
python cost_monitor.py --week # Show weekly analysis
python cost_monitor.py --live # Live monitoring mode
"""
import asyncio
import argparse
... | anglil/kalshi-ai-trading-bot | scripts/cost_monitor.py | .py | f0126f2a5d543a73 | 7.48 | 8 |
#!/usr/bin/env python3
"""
Database initialization script for Kalshi AI Trading Bot
Creates the necessary database tables and schema
"""
import asyncio
import sys
from pathlib import Path
# Add src to path for imports
sys.path.append(str(Path(__file__).parent / "src"))
from utils.database import DatabaseManager
as... | anglil/kalshi-ai-trading-bot | scripts/init_database.py | .py | 244ca6c4209ae49b | 7.48 | 8 |
#!/usr/bin/env python3
"""
Beast Mode Installation Script 🚀
This script installs dependencies and validates the Beast Mode trading system.
Usage:
python install_beast_mode.py
"""
import subprocess
import sys
import os
from pathlib import Path
def run_command(command, description):
"""Run a command and hand... | anglil/kalshi-ai-trading-bot | scripts/install_beast_mode.py | .py | 6ac94882317a10bf | 7.48 | 8 |
#!/usr/bin/env python3
"""
Trading Dashboard Launcher
Simple launcher for the comprehensive trading system dashboard.
"""
import subprocess
import sys
import os
from pathlib import Path
def check_requirements():
"""Check if required packages are installed."""
required_packages = [
'streamlit',
... | anglil/kalshi-ai-trading-bot | scripts/launch_dashboard.py | .py | d42fbcf2164d4a14 | 7.48 | 8 |
#!/usr/bin/env python3
"""
Performance System Manager
Comprehensive orchestration system for the automated Kalshi trading performance analyzer.
This is the main entry point for managing the entire performance analysis ecosystem.
Features:
- Start/stop automated scheduler
- Run on-demand analysis
- Emergency interven... | anglil/kalshi-ai-trading-bot | scripts/performance_system_manager.py | .py | 5624ceead7961942 | 7.48 | 8 |
#!/usr/bin/env python3
"""
Portfolio Health Check Utility
This script provides a clear view of your portfolio finances:
- Available Cash (for new trades)
- Position Value (current market value of holdings)
- Total Portfolio Value (cash + positions)
- Key utilization metrics
"""
import asyncio
import sys
import os
fro... | anglil/kalshi-ai-trading-bot | scripts/portfolio_health_check.py | .py | 76a555958bc60112 | 7.48 | 8 |
#!/usr/bin/env python3
"""
Complete Dashboard Setup Script
This script:
1. Fixes database schema issues
2. Ensures all tables and columns exist
3. Tests database connectivity
4. Launches the dashboard
Run this to get your dashboard working properly.
"""
import asyncio
import subprocess
import sys
import os
from path... | anglil/kalshi-ai-trading-bot | scripts/run_dashboard_setup.py | .py | b4ad38798975aa6e | 7.48 | 8 |
/**
* Unit tests for the main-process log redaction in electron-log.ts.
*
* The redaction masks credential-looking key=value / key: value pairs in
* console output. Metric keys that merely CONTAIN a keyword
* (first_token_latency_ms, prompt_tokens, ...) must stay untouched.
*/
import { describe, it, expect } fro... | 14790897/MiQi | apps/desktop/src/main/electron-log.test.ts | .ts | 7e020fe982057bcc | 7.02 | 10 |
/**
* Qraft 真实环境集成测试（可选，默认跳过）。
*
* 用法（凭据优先从环境变量读取，client_secret 测试阶段有默认值）：
* QRAFT_LIVE=1 QRAFT_PHONE=<测试账号手机号> QRAFT_PASSWORD=<密码> \
* npx vitest run src/main/qraft/live.integration.test.ts
*
* 走通完整流程：提取公钥 → 平台登录（RSA 加密）→ authorize → doConfirm
* → 取 code → 换 token → userinfo → refresh。断言只检查脱敏摘要，
* 不打印任何... | 14790897/MiQi | apps/desktop/src/main/qraft/live.integration.test.ts | .ts | 2f7bc3e8931ce8b9 | 7.02 | 10 |
#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Model-level coherence + throughput benchmark for PR1 Marlin HIP."""
import argparse
import time
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
pars... | QuixiAI/SlimServe | bench_pr1_model.py | .py | 118726bc54c3dde5 | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Simplified batch specification grammar for attention benchmarks.
Grammar (underscore-separated segments):
Format: (<count>?) q<q_len>(k?) (s<seq_len>(k?))?
- count: Number of identical requests (optiona... | QuixiAI/SlimServe | benchmarks/attention_benchmarks/batch_spec.py | .py | da9af651cacec685 | 7.95 | 7 |
#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Benchmark to measure the performance overhead of VLLM_BATCH_INVARIANT mode.
This benchmark runs the same workload twice:
1. With VLLM_BATCH_INVARIANT=0 (baseline)
2. With VLLM_BATCH_INV... | QuixiAI/SlimServe | benchmarks/benchmark_batch_invariance.py | .py | 2253aad341055774 | 7.45 | 7 |
#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Exact-shape DSV4 throughput benchmark for a local OpenAI completion API."""
from __future__ import annotations
import argparse
import concurrent.futures
import hashlib
import json
impo... | QuixiAI/SlimServe | benchmarks/benchmark_dsv4_exact.py | .py | 8613d0767d313e8f | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Micro benchmark comparing built-in hash(), SHA-256, and xxHash.
This focuses on a single test payload shaped like the prefix-cache hash input:
(32-byte bytes object, 32-int tuple)
Usage:
python bench... | QuixiAI/SlimServe | benchmarks/benchmark_hash.py | .py | 250c9dc9f7ea4699 | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Benchmark hidden state extraction throughput.
Measures two modes:
1. Baseline: bulk inference with max_tokens=1, no extraction.
2. Extract: async hidden state extraction via ExampleHiddenStatesConnector
... | QuixiAI/SlimServe | benchmarks/benchmark_hidden_state_extraction.py | .py | 955d19a109955fe6 | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Offline benchmark to test the long document QA throughput.
Example usage:
# This workload samples 8 different prompts with a default input
# length of 20000 tokens, then replicates each prompt 2 times... | QuixiAI/SlimServe | benchmarks/benchmark_long_document_qa_throughput.py | .py | d91244835135768a | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Benchmark and regression-test pinned (page-locked) CPU memory for vLLM.
Verifies that enabling pinned memory does not regress throughput or latency
compared to unpinned memory. Each condition runs in an isola... | QuixiAI/SlimServe | benchmarks/benchmark_pin_memory.py | .py | 02c187d8ab6031df | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Benchmark the efficiency of prefix caching.
This script allows you to benchmark the performance of
a model with and without prefix caching using either fixed prompts
or prompts sampled from the ShareGPT datas... | QuixiAI/SlimServe | benchmarks/benchmark_prefix_caching.py | .py | a5dd2a79084885f2 | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Benchmark offline prioritization."""
import argparse
import json
import random
import time
from transformers import AutoTokenizer, PreTrainedTokenizerBase
from vllm.engine.arg_utils import EngineArgs
from vl... | QuixiAI/SlimServe | benchmarks/benchmark_prioritization.py | .py | 089b3ced2857b73c | 7.45 | 7 |
#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Benchmark comparing Triton vs PyTorch sort-based top-k/top-p implementations.
Compares:
- apply_top_k_top_p_triton (Triton binary search)
- apply_top_k_top_p (PyTorch sort-based)
Scena... | QuixiAI/SlimServe | benchmarks/benchmark_topk_topp.py | .py | 93b8663919250379 | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from collections.abc import Callable, Iterable
from dataclasses import dataclass
from itertools import product
import torch
import torch.nn.functional as F
import torch.utils.benchmark as TBenchmark
from torch.u... | QuixiAI/SlimServe | benchmarks/fused_kernels/silu_mul_block_quant_benchmark.py | .py | 8fab7a4a7f446c95 | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import argparse
import torch
from vllm import _custom_ops as ops
from vllm.triton_utils import triton
# DeepSeek V3 dimensions
NOPE_DIM = 512
ROPE_DIM = 64
NUM_HEADS = 128
NUM_TOKENS = [8, 16, 32, 64, 128, 25... | QuixiAI/SlimServe | benchmarks/kernels/bench_concat_mla_q.py | .py | a145888a61e1dd88 | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import argparse
import math
import torch
from vllm import _custom_ops as ops
from vllm.triton_utils import triton
# DeepSeek V3 MLA dimensions
NOPE_DIM = 512
ROPE_DIM = 64
HEAD_DIM = NOPE_DIM + ROPE_DIM # 576 ... | QuixiAI/SlimServe | benchmarks/kernels/bench_cp_gather_fp8.py | .py | a6fccb37a00fa48f | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from dataclasses import dataclass
from enum import Enum
from itertools import product
from typing import Any
import torch
import torch.utils.benchmark as TBenchmark
from torch.utils.benchmark import Measurement ... | QuixiAI/SlimServe | benchmarks/kernels/benchmark_2d_silu_mul_fp8_quant.py | .py | a487150bec47a76a | 7.45 | 7 |
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import os
# Disable DeepGEMM for this benchmark to use CUTLASS
os.environ["VLLM_USE_DEEP_GEMM"] = "0"
import torch
from vllm.benchmarks.lib.utils import default_vllm_config
from vllm.model_executor.kernels.lin... | QuixiAI/SlimServe | benchmarks/kernels/benchmark_block_fp8_gemm.py | .py | f181a7f54df987ca | 7.45 | 7 |
#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Benchmark script for device communicators:
CustomAllreduce (oneshot, twoshot), PyNcclCommunicator,
and SymmMemCommunicator (multimem, two-shot).
for NCCL symmetric memory you need to s... | QuixiAI/SlimServe | benchmarks/kernels/benchmark_device_communicators.py | .py | aef8b6245d7151ac | 7.45 | 7 |
"""Sterling & Vance — the public web presence of the firm that operates Bob's agent.
Both of the identity conventions this lab adopts assume the requesting side has
somewhere on the web that speaks for it, and neither works without one:
/agent.json
A Client ID Metadata Document (draft-ietf-oauth-client-id-met... | nickgamb/uma4agents | clients/agent-operator/server.py | .py | 44e51a0c0d42347c | 7.48 | 8 |
#!/usr/bin/env python3
"""Alice's side of her own authorization server, with no identity provider.
She holds an Ed25519 key. Every owner-API request is signed with it under
RFC 9421 — the same message-signature profile agents use to prove possession
of a grant, pointed the other way. The authority verifies one public ... | nickgamb/uma4agents | clients/owner-cli/owner.py | .py | 86e6880d4c3224f4 | 7.48 | 8 |
"""What does agentgateway actually hand an external authorization service?
The enforcement core (lib/uma4a_pep.py) decides from request *facts*: the
tool being called, the signature headers, the authorization header, the
authority. Under the file-driven gateway those facts arrive because of three
settings in gateway/a... | nickgamb/uma4agents | k8s/verify/extauth/recorder.py | .py | db884d9414eb9686 | 7.48 | 8 |
"""The personal-AI binding against the real stack.
Against the reference architecture — her identity provider, her replicated
authority, the gateway, the vault and her portal all present and unchanged —
because that is the deployment the binding has to work in to mean anything.
The only difference from the portal's p... | nickgamb/uma4agents | kwaai/check.py | .py | c80236b9c1265426 | 7.48 | 8 |
"""A personal AI, reduced to the four things the ability needs from one.
pAI-OS would be the host here. This stands in for it so the binding is
runnable and reviewable today, and so the call with Kwaai is about mapping
four named requirements onto their actual mechanism rather than starting from
a blank page.
What it... | nickgamb/uma4agents | kwaai/host_demo.py | .py | 1745eb0620c88d28 | 7.48 | 8 |
"""uma4a_enroll — enroll a requesting agent with its AAuth agent server.
The identified half of the AAuth identity model: the agent holds a persisted
*stable* key (its long-term identity) and a per-session *ephemeral* key. It
registers with its principal's agent server by POSTing its stable public key
in a request sig... | nickgamb/uma4agents | lib/uma4a_enroll.py | .py | 4f1e520ce2311c1b | 7.48 | 8 |
"""Minimal RFC 9421 HTTP message signatures for the uma4agents lab.
One implementation shared by the agent-shim (signing) and uma-pep
(verification), so the two ends cannot drift. Profile:
covered components: "@method" "@authority" "@path" "authorization"
params: created, keyid, alg="ed25519"
Covering the `autho... | nickgamb/uma4agents | lib/uma4a_http_sig.py | .py | a023caa544f952db | 7.48 | 8 |
"""What a resource server publishes about itself, in one implementation.
Discovery has two audiences and three documents:
RFC 9728 metadata public, structural — the tools, the scopes, which
authorization servers speak for this resource, and
the key its metadata... | nickgamb/uma4agents | lib/uma4a_publish.py | .py | 407e024f0d7cbc2b | 7.48 | 8 |
"""alice-vault-mcp — Alice's brokerage vault as an MCP server.
Fixture data through a real protocol path: positions, transaction history,
and a pretend trade-execution endpoint, served over MCP streamable-http.
Whether this server handles its own authorization, or something in front of it
does, is a deployment choice... | nickgamb/uma4agents | mcp/alice-vault/server.py | .py | 4a97409783fe8432 | 7.48 | 8 |
"""The same UMA enforcement, hosted inside the resource instead of ahead of it.
An MCP SDK 2.x `Extension` that carries the FedAuthz obligations in-process:
`intercept_tool_call` is a short-circuiting hook at exactly the boundary the
gateway deployment protects from outside, and it reaches its verdicts by
calling the ... | nickgamb/uma4agents | mcp/alice-vault/uma_extension.py | .py | 1893cb88489d25c7 | 7.48 | 8 |
"""Shared per-forward-pass metadata produced by framework adapters.
Carved out as part of the unified-adaptor refactor (Phase 1). Every
``BackendAdapter.build_step_context`` returns one of these objects; the
driver feeds it to ``RingTransport.set_step_context`` and
``RingTransport.pre_push_all_metas``.
Today this is... | ProjectDMX/DMI | src/dmi/adapters/types.py | .py | 7da94743a868dedd | 7.66 | 20 |
"""Configuration helpers for DMI capture scheduling."""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Literal
@dataclass
class CaptureSchedule:
"""Schedule for step-level and request-level capture."""
step_stride: int = 1
step_offset: int = 0
warmup_... | ProjectDMX/DMI | src/dmi/config.py | .py | 062aced8dcf98c1d | 7.66 | 20 |
"""Hook-to-native-producer dispatch and hook installation."""
from __future__ import annotations
from collections.abc import Sequence
from typing import Optional
import torch
from .specs import HookSpec
def dispatch_producer(
ring_payload: torch.Tensor,
tensor: torch.Tensor,
strip_tensor: Optional[tor... | ProjectDMX/DMI | src/dmi/hooks/dispatch.py | .py | 338fc735fb7e97d8 | 7.66 | 20 |
"""CLI entry point for the hermes-agent ACP adapter.
Loads environment variables from ``~/.hermes/.env``, configures logging
to write to stderr (so stdout is reserved for ACP JSON-RPC transport),
and starts the ACP agent server.
Usage::
python -m acp_adapter.entry
# or
hermes acp
# or
hermes-acp
... | cyborg-garden/hermes-agent-mt | acp_adapter/entry.py | .py | f8c0a430671643e7 | 7.54 | 11 |
class SSLConfigurationError(Exception):
"""Raised when SSL/TLS certificate bundle configuration fails."""
pass
class EmptyStreamError(RuntimeError):
"""Raised when a provider closes a stream without yielding a response."""
pass
class MoAPresetNotFoundError(ValueError):
"""Raised when a persiste... | cyborg-garden/hermes-agent-mt | agent/errors.py | .py | 237581ac4180cffe | 7.04 | 11 |
"""Helpers for translating OpenAI-style tool schemas to Gemini's schema subset."""
from __future__ import annotations
from typing import Any, Dict
# Gemini's ``FunctionDeclaration.parameters`` field accepts the ``Schema``
# object, which is only a subset of OpenAPI 3.0 / JSON Schema. Strip fields
# outside that sub... | cyborg-garden/hermes-agent-mt | agent/gemini_schema.py | .py | b995fce2570ffe0f | 7.54 | 11 |
from __future__ import annotations
import hashlib
import json
import re
from pathlib import Path
from typing import Any
QUEUE_CONTRACT_VERSION = "queue.v2"
MAX_ID_LENGTH = 240
MAX_CAPABILITY_LENGTH = 80
# Queue identifiers become single filesystem path components. Keep the portable
# contract intentionally narrower... | philngt/afc-runtime | wo_runtime/core/validation.py | .py | 4b3786cf2e0a6a6a | 7.42 | 6 |
#!/usr/bin/env python
"""Emit a launch plan from runtime/fleet.json for `scripts/run.sh up`.
Groups roles by their assigned runtime. Headless (supervisor-capable) runtimes get one
supervisor covering all their roles; interactive runtimes get one AGENT line per replica.
Output (TAB-separated), one directive per line:
... | philngt/afc-runtime | wo_runtime/runtime/fleet_plan.py | .py | 761b2632338ea62d | 7.42 | 6 |
#!/usr/bin/env python
"""Generic runtime-adapter wiring self-test (no model calls, no network).
For every runtime descriptor in runtime/runtimes/ (or --runtime NAME), verifies:
1. descriptor shape (name, bin, kinds; supervisor => exec block);
2. interactive resolve.py emits BIN + role_env + ARGs (binary stubbed);
... | philngt/afc-runtime | wo_runtime/runtime/selftest.py | .py | 4db76c2557e86306 | 7.92 | 6 |
"""File-level CSV read/write helpers.
Row-level (`from_csv_row`) and dict flattening (`to_records`) are the building
blocks; these wrap them for whole files, so a CSV on disk becomes a list of
normalized events, and events or bars go back out to a tidy CSV. Standard
library only.
"""
from __future__ import annotations... | Harvestgroup360/market-data-normalizer | src/mdnorm/csvio.py | .py | b7aea829eef2f8ca | 7.42 | 6 |
"""NDJSON (JSON Lines) read/write helpers.
CSV is fine for tabular hand-offs, but modern data stacks — log shippers,
object stores, streaming loaders — speak newline-delimited JSON. These
helpers mirror :mod:`mdnorm.csvio`: events and bars go out as one JSON
object per line, and event files come back as normalized
:cl... | Harvestgroup360/market-data-normalizer | src/mdnorm/jsonl.py | .py | ea45d876e59ccee8 | 7.42 | 6 |
"""Labels, and splitting a time series without letting the answer leak.
Everything in :mod:`mdnorm.features` refuses to look forward. A label has to,
because a label *is* the future: the thing you are trying to predict. That
reversal is the whole difficulty of this module — the one series in a research
dataset that is... | Harvestgroup360/market-data-normalizer | src/mdnorm/labels.py | .py | 34b9feb96deacc9a | 7.42 | 6 |
"""Venue-specific normalizers.
Each function takes one raw record and returns a :class:`MarketEvent`.
They are intentionally small and pure so they are trivial to test and reuse.
"""
from __future__ import annotations
from decimal import Decimal
from typing import Any, Mapping
from .schema import EventType, MarketEv... | Harvestgroup360/market-data-normalizer | src/mdnorm/normalizers.py | .py | dc02a2cb100c4e1f | 7.42 | 6 |
"""Flatten events and bars into plain dicts.
The last mile of any pipeline is getting normalized objects into a DataFrame,
a CSV writer, or a JSON payload. These helpers turn ``MarketEvent`` and ``Bar``
into flat, JSON-serialisable dicts. ``Decimal`` values are emitted as strings by
default (lossless); pass ``as_float... | Harvestgroup360/market-data-normalizer | src/mdnorm/records.py | .py | c63e630643c48eab | 7.42 | 6 |
"""Unified market-data schema.
All venue-specific feeds are normalized into a single, exchange-agnostic
representation so downstream research and execution code never has to care
where a tick came from.
"""
from __future__ import annotations
from dataclasses import dataclass
from decimal import Decimal
from enum impo... | Harvestgroup360/market-data-normalizer | src/mdnorm/schema.py | .py | ba396fa4f81dffee | 7.42 | 6 |
"""Trading sessions and calendar filtering.
Raw feeds run around the clock; research rarely should. Overnight prints,
weekend maintenance windows and pre-market crossings all distort features
that were meant to describe regular trading hours.
A :class:`Session` describes a recurring local-time window — regular US
equ... | Harvestgroup360/market-data-normalizer | src/mdnorm/sessions.py | .py | 3719b3327f98df1f | 7.42 | 6 |
"""Consolidate and clean up multiple event streams.
Real setups pull from several venues and reconnect often, so you end up with
interleaved feeds and replayed duplicates. These helpers merge streams into one
chronological timeline and drop exact duplicate events.
"""
from __future__ import annotations
from typing im... | Harvestgroup360/market-data-normalizer | src/mdnorm/streams.py | .py | 7bea078522bc163f | 7.42 | 6 |
"""Canonical symbol normalization.
Venues spell the same instrument in many ways (``BTCUSDT``, ``XBTUSD``,
``btc_usd``). Traded pairs are mapped to a single canonical ``BASE-QUOTE``
form. Single-listed instruments — equities, ETFs, indices — have no quote
leg and keep their plain ticker (``AAPL``, ``SPY``, ``BRK.B``).... | Harvestgroup360/market-data-normalizer | src/mdnorm/symbols.py | .py | 8fa9893235b98bee | 7.42 | 6 |
"""Timestamp parsing helpers.
Everything is normalized to integer nanoseconds since the Unix epoch (UTC).
"""
from __future__ import annotations
from datetime import datetime, timezone
_NS_PER_S = 1_000_000_000
def epoch_to_ns(value: float | int, unit: str = "s") -> int:
"""Convert an epoch timestamp expressed... | Harvestgroup360/market-data-normalizer | src/mdnorm/timeutil.py | .py | 315bfad5e1e04d66 | 7.42 | 6 |
"""实时双语字幕 GUI 应用(Windows 主入口)。
把 ASR + 翻译流水线放后台线程,字幕推到透明悬浮窗显示。
音频源默认 WASAPI loopback(系统声音);用 --input 可改成文件(便于在任意平台预览 UI)。
运行(Windows):
pip install PySide6 pyaudiowpatch
set DEEPSEEK_API_KEY=你的key
python app.py # 抓系统声音
python app.py --input demo.mp4 # 用文件预览
"""
from __future__... | superLin006/LiveBabel | app.py | .py | d56d162da3c2da53 | 7.42 | 6 |
"""两遍 ASR 引擎。
Pass1(流式 zipformer):每帧解码,产出会变动的 volatile 文本,并负责 endpoint 检测。
Pass2(非流式 Qwen3-ASR):endpoint 触发时,对该句缓存的音频复识一次,
得到更准、不抖的定稿文本。
对外只暴露三件事:
feed(samples) 喂一帧音频
poll() -> Event 拿当前状态:文本更新 / 句子结束(committed)
内部维护"当前句"的音频缓冲,以便 commit 时交给 Pass2。
"""
from __future__ impor... | superLin006/LiveBabel | livebabel/asr/asr_engine.py | .py | 9139fd20bfef1a7a | 7.42 | 6 |
"""音频输入层抽象。
设计目标:把"音频从哪来"和"怎么处理"彻底解耦。
现在(WSL)用文件源验证逻辑;以后(Windows)只需新增一个 WasapiLoopbackSource
实现同样的接口,主流程一行不用改。
所有源统一输出:16kHz、单声道、float32、[-1,1] 的 PCM 块(numpy array)。
"""
from __future__ import annotations
import subprocess
import time
from abc import ABC, abstractmethod
from typing import Iterator
import numpy as ... | superLin006/LiveBabel | livebabel/asr/audio_source.py | .py | b5867ff300ae158d | 7.42 | 6 |
"""麦克风输入采集(会议模式用,代表"我")。
与 WasapiLoopbackSource 同接口(frames() 产出 16k mono float32 块),但抓的是
默认输入设备(麦克风),不是 loopback。会议模式里:
* 麦克风流 = 本机用户("我")
* 系统声音 loopback = 远端所有人
两路各跑一套 ASR,转录按来源标上说话人,实现无需 torch 的"我/远端"区分。
依赖 pyaudiowpatch(Windows);普通 PyAudio 也兼容,这里统一用 pyaudiowpatch。
"""
from __future__ import annotations
impo... | superLin006/LiveBabel | livebabel/asr/audio_source_mic.py | .py | f4b0861fb40c9a20 | 7.42 | 6 |
"""Windows 系统声音采集(WASAPI loopback)。
抓"扬声器/耳机正在播放的声音"——无论来自视频播放器、浏览器、会议软件都行。
依赖 pyaudiowpatch(PyAudio 的 WASAPI loopback 分支),只能在 Windows 上跑:
pip install pyaudiowpatch
设计目标:
* 启动时正确抓到【当前默认输出设备】的声音。
* 在不同电脑上通用(设备数量/型号/是否有同名设备都能处理)。
* 输出与 FileSource 一致:16kHz mono float32 块,主流程不用改。
不做运行中自动切换设备(简单可靠优先)。切了输出设备请重启... | superLin006/LiveBabel | livebabel/asr/audio_source_windows.py | .py | 01b160f18166bd9e | 7.42 | 6 |
"""Qwen3-ASR ONNX model file selection.
The application uses Qwen3-ASR for Pass2 re-recognition and offline subtitle
transcription. This module keeps provider-specific file selection in one
place without carrying an experimental Qwen streaming implementation.
"""
from __future__ import annotations
import os
def q... | superLin006/LiveBabel | livebabel/asr/qwen3_model.py | .py | 2abd7e7118685d18 | 7.42 | 6 |
"""翻译层:DeepSeek API。
只翻译已定稿(committed)的句子。要点:
* 异步:放后台线程跑,不阻塞 ASR 主循环。
* 带上下文:把最近几句已译内容作为上下文,保证术语/代词一致、措辞连贯。
* 缓存:相同原文不重复请求,省钱省延迟。
* 优雅降级:没有 API key 或请求失败时,返回占位串,不影响晃动验证。
key 从环境变量 DEEPSEEK_API_KEY 读,绝不硬编码。
"""
from __future__ import annotations
import os
import queue
import threading
from collections impor... | superLin006/LiveBabel | livebabel/core/translator.py | .py | 02fb9d41554fc24e | 7.42 | 6 |
"""全局热键监听:按住说话,松开结束。Windows 用 keyboard。
回调:
on_start() —— 右 Ctrl 按下后开始听写
on_stop() —— 右 Ctrl 松开后结束听写
默认热键为键盘右侧 Ctrl:
* 按住右 Ctrl:开始录音和识别。
* 松开右 Ctrl:结束录音并输出最终文字。
注意:keyboard 在 Linux 需 root(WSL 无效),Windows 普通权限可用。
监听回调在 keyboard 的内部线程,务必只发信号、不做重活。
"""
from __future__ import annotations
import sys
import thr... | superLin006/LiveBabel | livebabel/dictation/hotkey.py | .py | d996001b74e25107 | 7.42 | 6 |
"""把文字注入当前焦点输入框。平台抽象,Windows 先行。
两种方式:
* paste: 写系统剪贴板 → 模拟 Ctrl+V → 恢复原剪贴板。中文最稳,默认。
* type : 逐字键入(keyboard.write)。不污染剪贴板,但中文/特殊字符易错,备选。
注入靠模拟按键 → 必须有真实桌面(WSL 无效)。Windows 用 keyboard;
macOS 后续用 pynput(需辅助功能权限)。
"""
from __future__ import annotations
import sys
import time
_IS_WIN = sys.platform.startswith("win"... | superLin006/LiveBabel | livebabel/dictation/injector.py | .py | a4f1feb948949bfe | 7.42 | 6 |
"""听写服务编排:热键 → 两阶段识别(草稿浮窗) → 松开定稿注入。
线程模型(关键):
* keyboard 钩子回调在 keyboard 的内部线程,**只能发信号**,不能在那儿做
剪贴板/Qt/注入操作 —— Windows OLE 剪贴板需主线程 COM 上下文,否则
OleSetClipboard 报 CoInitialize 未调用。
* 用内部信号 _reqStart/_reqStop 以 QueuedConnection 投递到 Qt 主线程;
开始录音在主线程触发,结束后的识别在后台线程执行,最终注入回到主线程。
* engine 内部的采集/识别仍在它自己的工作线程;草... | superLin006/LiveBabel | livebabel/dictation/service.py | .py | c401b99409540981 | 7.42 | 6 |
"""定位 ffmpeg 可执行文件,并给出友好报错。
查找顺序:
1. 环境变量 LIVEBABEL_FFMPEG 指定的完整路径
2. 项目根的 ffmpeg/ 目录(ffmpeg[.exe]),方便随项目分发、不用配 PATH
3. 系统 PATH 里的 ffmpeg
找不到时抛出带安装指引的清晰错误,而不是看不懂的 WinError 2。
"""
from __future__ import annotations
import os
import shutil
import subprocess
import sys
from livebabel.paths import res
def run_... | superLin006/LiveBabel | livebabel/ffmpeg_tool.py | .py | 9da49a7315ab79eb | 7.42 | 6 |
"""字幕历史记录:每次运行把最终定稿字幕自动存成 .srt + .txt,方便事后查看。
* .srt:带时间轴的标准双语字幕(原文一行、译文一行),可配视频或用播放器打开。
* .txt:原文/译文对照纯文本,方便快速翻阅、复制。
只记录"最终(committed 且非 provisional)"字幕。临时译文不写入历史。
文件按启动时间命名,存到 history/ 目录。增量写入(每来一条就落盘),
程序中途退出也不丢内容。
"""
from __future__ import annotations
import os
import time
from datetime import datetime
fro... | superLin006/LiveBabel | livebabel/history_writer.py | .py | c119a14b81e6047b | 7.42 | 6 |
"""离线说话人分离(声纹聚类)。
会议结束后对某一路(通常"远端")整段音频做声纹聚类,细分成"发言人1/2/3…"。
实现:VAD 切语音段 → sherpa speaker-embedding 逐段提声纹 → 球面 K-means 聚类。
不用 sherpa 内置的 OfflineSpeakerDiarization——实测它对中文多人对话会把清晰可分的
段全压成一个人(282:23)。改用「逐段 embedding + 自家 K-means」:实测同一人句内聚
0.7+、不同人 0.15~0.35,K-means(cosine 质心)能稳定分开,凝聚聚类则因雪球效应失败。
纯 ONNX + numpy,不依赖 torc... | superLin006/LiveBabel | livebabel/meeting/diarize.py | .py | f80e48f020e6eff5 | 7.42 | 6 |
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