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* feat(daily-paper): add daily paper cookbook workflow with schema and tests - Introduce daily paper schema types (DailyBriefOutput, PaperInfo, PaperNoteOutput, etc.) - Create daily paper cookbook module with analyze, collect, digest, rank, and select steps - Add cookbook entry point and integrate into main steps module - Replace job config export with daily brief output in schema exports - Add comprehensive unit tests covering pipeline, filtering, and output generation - Update dependencies including openai-codex and pypdf packages - Configure standalone daily paper cron job with proper scheduling and routing * test(daily_paper): update tests to use Claude Code wrapper exclusively - Add test to verify web search is disallowed by default in Claude Code - Update imports to include DailyBriefOutput, PaperNoteOutput, and PaperSelection schemas - Change test name from standalone_config_has_backend_split to reflect Claude Code only usage - Remove default agent wrapper and configure all steps to use Claude Code wrapper - Rename select_wrapper to cc_wrapper for clarity and consistency - Remove duplicate Claude Code wrapper initialization - Update test assertions to verify output schema usage matches expected sequence - Remove unused as_llm component from standalone configuration test * refactor(agent-wrapper): simplify skill resolution logic across all wrappers - Replace duplicate skill resolution code with centralized _resolve_project_skills method - Add project_path property with configurable relative path resolution - Introduce proper validation for skill names and directory existence - Change Codex wrapper to use project_path instead of workspace_path for skills - Add SKILL.md requirement validation for project skills - Remove redundant skill processing logic from individual wrappers * feat(daily_paper): add daily paper workflow with PDF analysis and brief generation - Implement shared state management and file helpers for daily-paper steps - Add PDF download and text extraction capabilities with arXiv integration - Create paper collection step with Hugging Face weekly/monthly rankings - Build ranking system using reciprocal-rank fusion with memory keyword scoring - Add Claude Code integration for paper analysis and detailed note generation - Implement digest step to create final five-minute brief from detailed notes - Add configuration for standalone daily cookbook application with cron scheduling - Create typed schema for paper information, selection, and output formats - Add atomic file writing with temporary file safety mechanisms - Implement exclusion logic for previously recommended papers and daily filters * feat(daily_paper): add DingTalk notification integration and enhance logging - Integrate DingTalk markdown send step to notify groups about daily paper briefs - Add comprehensive logging throughout daily paper workflow including start/finish events - Update daily paper analysis prompt to include code repository context requirement - Configure DingTalk notification in daily_cookbook.yaml with app credentials - Add dingtalk-stream dependency for proactive message API integration - Enhance daily paper README with DingTalk notification section and updated flow chart - Implement detailed logging for each step including paper processing and agent calls - Add test coverage for DingTalk markdown sending functionality and configuration - Update pre-commit config to exclude skills directory from checks - Add .claude/skills to gitignore for local development environment * refactor(dingtalk): move dingtalk_stream import to local scope and improve code safety - Moved global dingtalk_stream import to local scope in send.py to avoid eager loading - Added dynamic import with error handling for optional dependency cases - Updated test suite to verify lazy loading behavior works correctly - Fixed markdown title generation by using safe variable naming in wait.py - Enhanced test coverage for arxiv PDF download caching functionality - Updated application context initialization with proper resource directory configuration - Modified paper metadata to include source PDF path reference in output files * refactor(daily_paper): remove manifest system and store selection metadata in digest files - Remove JSON manifest creation and storage functionality - Store selection data directly in digest file frontmatter instead of separate manifest files - Add load_saved_selection method to rebuild selection from digest and paper-note metadata - Update README documentation to reflect new cookbook workflow architecture - Modify test cases to verify selection metadata in digest files instead of manifest JSON - Remove unused json import from multiple daily paper modules - Integrate PaperSelection schema for proper data validation in stored metadata * docs(daily_paper): add bilingual cookbook guides
93 lines
2.2 KiB
TOML
93 lines
2.2 KiB
TOML
[project]
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name = "reme-ai"
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dynamic = ["version"]
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description = "Remember Me, Refine Me."
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readme = "README.md"
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authors = [
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{ name = "EconML team of Alibaba Tongyi Lab", email = "jinli.yl@alibaba-inc.com" },
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]
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license = "Apache-2.0"
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requires-python = ">=3.11"
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keywords = ["llm", "memory", "agent", "agentscope", "ai", "mcp", "reme"]
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classifiers = [
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"Development Status :: 4 - Beta",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.11",
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"Operating System :: OS Independent",
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"Intended Audience :: Developers",
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"Intended Audience :: Science/Research",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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]
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dependencies = [
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"aiofiles>=24.1.0",
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"croniter>=2.0",
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"fastapi>=0.135.1",
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"fastmcp>=3.1.0",
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"httpx>=0.28.1",
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"loguru>=0.7.3",
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"mistletoe>=1.5.1",
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"numpy>=2.2.6",
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"openai>=2.26.0",
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"psutil>=5.9",
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"pydantic>=2.12.5",
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"python-frontmatter>=1.1.0",
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"pyyaml>=6.0.3",
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"rich>=14.3.3",
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"uvicorn>=0.41.0",
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"watchfiles>=1.1.1",
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"zstandard>=0.23.0",
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]
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[project.optional-dependencies]
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core = [
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"agentscope==2.0.4.post1",
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"claude-agent-sdk>=0.2.123",
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"dingtalk-stream>=0.24.3",
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"openai-codex>=0.144.4",
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"faiss-cpu>=1.13.2",
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"jieba>=0.42.1",
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"rjieba>=0.2.1",
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"neo4j>=6.2.0",
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"networkx>=3.4.2",
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"pypdf>=5.0.0",
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]
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dev = [
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"pre-commit",
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"pytest>=8.0",
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"pytest-asyncio>=0.23",
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]
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full = [
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"reme-ai[core]",
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"reme-ai[dev]",
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]
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[project.urls]
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Homepage = "https://github.com/agentscope-ai/ReMe"
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Documentation = "https://reme.agentscope.io/"
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Repository = "https://github.com/agentscope-ai/ReMe"
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[project.scripts]
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reme = "reme.reme:main"
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[tool.setuptools]
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packages = { find = { where = ["."], include = ["reme*"] } }
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include-package-data = true
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[tool.setuptools.package-data]
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"*" = ["py.typed", "**/*.yaml", "**/*.json"]
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"reme.components.tokenizer" = ["stopwords"]
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[tool.setuptools.dynamic]
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version = { attr = "reme.__version__" }
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[build-system]
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requires = ["setuptools>=45", "wheel"]
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build-backend = "setuptools.build_meta"
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[tool.pytest.ini_options]
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asyncio_default_fixture_loop_scope = "function"
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testpaths = ["tests"]
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python_files = ["test_*.py"]
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python_functions = ["test_*"]
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