mirror of
https://github.com/agentscope-ai/ReMe.git
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* refactor(core): replace text truncation utilities with new marker system - Remove old truncate_text_utils module and its exports - Replace TRUNCATION_MARKER_START with _TRUNCATION_NOTICE_MARKER constant - Update as_msg_stat.py to split content using new marker format - Modify FileIO tool to use TRUNCATION_NOTICE_MARKER for continuation hints - Change is_truncated function checks to use marker presence detection - Move transformers dependency from main deps to light extra dependencies - Update tool result compactor tests to verify marker instead of is_truncated calls * feat(file_io): enhance file operations with path resolution and append functionality - Add expanduser() to resolve file paths with ~ symbol - Implement proper file existence and type validation in update_file - Add new append_file method to append content to files - Update truncation notice format for better readability - Fix typo in error message from "provide" to "provided" - Update transformers dependency in pyproject.toml - Remove duplicate transformers dependency from light extras * refactor(file_io): disable pylint too-many-return-statements warning * perf(file_watcher): increase default polling delay and optimize watcher configuration - Increased default poll_delay_ms from 1000ms to 2000ms to reduce CPU usage - Removed force_polling parameter as it's no longer needed with updated polling strategy - Simplified async watch configuration by removing conditional force_polling logic - Reduced overall system resource consumption during file watching operations * refactor(memory): update conversation log documentation in memory summary - Changed "Raw conversation logs" to "Earlier conversation logs" for clarity - Added warning note about potentially large dialog file sizes - Improved formatting with additional line break for better readability - Maintained existing compressed summary integration unchanged * feat(memory): add long-term memory support to file-based memory system - Initialize _long_term_memory attribute as empty string - Add memories section to content when long-term memory exists - Consolidate summary and memories into single user message - Format memories with markdown header # Memories - Maintain existing compressed summary functionality - Join multiple content parts with double newlines
130 lines
3.2 KiB
TOML
130 lines
3.2 KiB
TOML
[build-system]
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requires = ["setuptools", "wheel"]
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build-backend = "setuptools.build_meta"
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[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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authors = [
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{ name = "jinli.yl", email = "jinli.yl@alibaba-inc.com" },
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{ name = "dengjiaji.djj", email = "dengjiaji.djj@alibaba-inc.com" },
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{ name = "caozouying.czy", email = "caozouying.czy@alibaba-inc.com" },
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{ name = "weikangzhou.zwk", email = "weikangzhou.zwk@alibaba-inc.com" },
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]
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license = { file = "LICENSE" }
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readme = "README.md"
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requires-python = ">=3.10"
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classifiers = [
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"Development Status :: 4 - Beta",
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"Intended Audience :: Developers",
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: Apache Software License",
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"Operating System :: OS Independent",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.10",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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"Topic :: Software Development :: Libraries :: Python Modules",
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"Topic :: Software Development :: Libraries :: Application Frameworks",
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"Typing :: Typed",
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]
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keywords = ["llm", "memory", "experience", "memoryscope", "ai", "mcp", "http", "reme", "personal"]
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dependencies = [
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"sqlite-vec>=0.1.6",
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"prompt_toolkit>=3.0.52",
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"rich>=14.2.0",
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"asyncpg>=0.31.0",
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"chromadb>=1.3.5",
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"dashscope>=1.25.1",
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"elasticsearch>=9.2.0",
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"fastapi>=0.121.3",
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"fastmcp>=2.14.1",
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"httpx>=0.28.1",
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"loguru>=0.7.3",
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"mcp>=1.25.0",
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"numpy>=2.2.6",
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"openai>=2.8.1",
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"pandas>=2.3.3",
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"pydantic>=2.12.4",
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"qdrant-client>=1.16.0",
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"tavily-python>=0.7.13",
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"tiktoken>=0.12.0",
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"tqdm>=4.67.1",
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"transformers>=4.57.3",
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"uvicorn>=0.40.0",
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"watchfiles>=1.1.1",
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"pyyaml>=6.0.3",
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]
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[project.optional-dependencies]
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ray = [
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"ray",
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]
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dev = [
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"jupyter-book",
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"ghp-import",
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"myst-nb",
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"sphinxcontrib-bibtex",
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"furo",
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"sphinxcontrib-mermaid",
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"pre-commit",
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]
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full = [
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"reme_ai[dev,ray,light]",
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]
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litellm = [
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"litellm==1.80.0",
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]
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light = [
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"agentscope==1.0.17",
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"flowllm[reme]>=0.2.0.10",
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]
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[tool.setuptools.packages.find]
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where = ["."]
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include = ["reme_ai*", "reme*"]
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exclude = ["test*", "cookbook*", "doc*", "library*", "dist*"]
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[tool.setuptools.package-data]
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reme_ai = [
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"**/*.yaml",
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"**/*.py",
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"**/*.json",
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]
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reme = [
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"**/*.yaml",
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"**/*.py",
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"**/*.json",
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]
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[tool.setuptools.dynamic]
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version = { attr = "reme.__version__" }
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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_ai.main:main"
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reme2 = "reme.reme:main"
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remecli = "reme.reme_cli:main"
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[tool.pytest.ini_options]
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asyncio_default_fixture_loop_scope = "function"
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# Script-style tests that need to be run with `python test_*.py`
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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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# Exclude script-style tests that require manual execution
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addopts = "--ignore=tests/test_embedding.py --ignore=tests/test_embedding_cache.py --ignore=tests/test_embedding_sync.py --ignore=tests/test_file_store.py"
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# python -m build && twine upload dist/*
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