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30 commits
| Author | SHA1 | Message | Date | |
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WQS
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6ed97f033b
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feat(auto_resource): reuse parsed resource ownership per batch (#529)
* perf(auto_resource): reuse historical ownership lookup per batch Share a lazy ownership index across routed processors and expire it at the end of each resource batch. Refresh changed days and their safe aliases after writes, deletes, and partial failures. Add regression coverage for scan counts, ownership, lookup scope isolation, and retry behavior. * fix(auto_resource): reconcile shared lookup across active batches * fix(auto_resource): refresh batch ownership from filesystem metadata * refactor(auto_resource): simplify batch ownership lookup Keep per-day ownership caches paired with pre-read metadata and refresh changed days before subsequent resources. Remove reverse-index bookkeeping, post-read stabilization retries, and recursive scope fallback. Handle late ELOOP errors on Python 3.13 while preserving other OS errors. Update regression tests for cross-resource freshness and retain safety and lifecycle coverage. * refactor(auto_resource): streamline batch lookup refresh * refactor(auto_resource): scope ownership cache to batch mutations Replace filesystem snapshots with one lazy historical lookup shared by resource processors. Reload only days changed by this invocation and discard the cache when it ends. Reuse canonical daily-note scans for symlink safety and Python 3.13 compatibility. Consolidate regression tests around the narrowed batch contract. Validation: Python 3.11, 3.12 and 3.13 core/plugin suites each passed 1407 tests; pre-commit --all-files and offline lookup/deletion comparison passed. * refactor(auto_resource): reuse initial ownership without refreshes * test(auto_resource): streamline ownership lookup regression coverage |
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Sen Huang
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05958d4d8b
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feat(evolve): tag auto-dream outputs (#538) | ||
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jinliyl
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7e25d4679b
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feat: auto-tag plugin-generated reports (#534)
* feat(plugins): auto-tag generated reports * fix(logging): forward host records on Python 3.13 * refactor(tags): decouple auto tagging from index updates * fix(tags): bind auto tagging to configured index * fix(tags): preserve standalone default index * fix(tags): make auto tagging best effort |
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xyf2020
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06fb46fa48
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feat(tags): add configurable tag indexing and filtered hybrid search (#530)
* Add optional tag generation and normalization to auto memory * Add tag index components and clean up temporary JSONL files * Preserve tag index state when reconciliation fails * Refactor and streamline application implementation * Fix pylint C1803 warnings in tag normalization tests * Document optional tag index configuration * Make tag index failures non-blocking and disable auto-memory tags * Add configurable tag indexing and tag listing * Add tag-filtered hybrid search with exact candidate ranking * Remove obsolete generated files * Rename tag index key to tag_key and reject reserved fields * Extract automatic tagging into a dedicated step * Restrict frontmatter updates to authorized keys * Refine tag filtering and automatic memory tagging * Require underscore-separated tags in auto-tag prompts - Forbid spaces in tags and require underscores (e.g. sam_altman) in both English and Chinese auto_tag prompts, with English examples switched to English entities (OpenAI, gold) - Drop prompt-string assertions superseded by the new tagging rule - Merge construction/runtime tag_key validation tests into one parametrized case * Make max_tags_per_file configurable in auto-tag step * Consolidate tag index tests * Fix search test fixture lint warnings * Align tag contracts and index health behavior * Fall back when tag index is unavailable --------- Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com> |
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imrewce
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354837f9af
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feat(proactive): separate proactive refresh from auto dream (#488)
* refractor(proactive): upgrade proactive feature with disentangled job and steps * refactor(proactive): apply audit fixes - rename read-side job 'proactive' -> 'proactive_read' (less confusing vs the refresh pipeline) - drop dedicated agent_wrapper.proactive; extraction reuses the default wrapper - simplify schema: remove unused ProactiveExtractOutput/TopicUpdate, drop resource_paths - extract no longer scans resource/ directly (daily notes already carry resource content) - update tests and docs accordingly * feat(proactive): strict extract-output gate and prompt total budget - parse_extract_reply now requires a contract section (follow_ups/extends/updates as a list); non-empty replies with misspelled section names trigger the existing one-shot retry instead of silently checkpointing changed files - pack_paths gains max_total_chars; extract packs newest daily material first, keeps the first file on overflow, and records omitted files in a trailer (default budget 300000 chars, configurable via max_total_chars) - tests: schema gate unit, schema-error retry e2e, budget unit + e2e * feat(proactive): add scenario-card plan step and generative agenda step * feat(proactive): digest-personal profile personalization and leaner LLM contract - extract/plan/agenda now draw a user profile block from <digest_dir>/personal/*.md (frontmatter description + body excerpt, per-file budget, profile.md fallback) - all daily access honours the configured daily_dir (prompt paths parameterized, config-driven fallbacks) so workspaces using e.g. memory/ work unchanged - schema trim: drop dead fields errors/material_paths, carry_forward_all -> count - shrink LLM output contract: new topics emit title/reason/confidence/paths only; keywords removed end-to-end, evidence derived from paths[0] (updates keep it) * fix(proactive): skip checkpoint when extract reply stays unusable after retry Two consecutive unparseable replies now short-circuit the round without checkpointing, so the same material is retried next round instead of being silently consumed (closes the residual audit #1 gap: the structural gate detected schema-wrong output but a double failure still checkpointed). * fix(proactive): replace running bool with reference-counted job activity tracker for the idle gate * refactor(proactive): remove job activity tracking and idle gate, restore job tree to upstream * fix(proactive): address second audit round (readonly reader, mtime checkpoint, wider fallbacks, profile containment, horizon content, expiry boundary) * refactor(dream): strip interests.yaml ownership from dream, proactive is now the sole writer * refactor(dream): separate proactive topic generation * ci: update renamed auto dream smoke test * fix(proactive): complete refresh migration and docs --------- Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com> |
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xyf2020
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f04eedb3ab
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feat(Tag filter): Add an optional rebuildable tag index for file frontmatter (#517)
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* Add optional tag generation and normalization to auto memory * Add tag index components and clean up temporary JSONL files * Preserve tag index state when reconciliation fails * Refactor and streamline application implementation * Fix pylint C1803 warnings in tag normalization tests * Document optional tag index configuration * Make tag index failures non-blocking and disable auto-memory tags * fix(tag-index): fail closed and support reindexing * fix(tag-index): preserve complete query expressions --------- Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com> |
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WQS
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5c17874f73
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feat(auto_resource): interpret image resources into daily notes (#500)
* feat: add auto_image step for image resource caption notes * feat: wire image resources into the resource watch loop * refactor: split auto resource processors behind router * refactor: align resource processor module names * refactor: preserve auto resource compatibility * refactor: clarify auto resource routing structure * fix: address auto resource review concerns * test: scope auto resource fixtures * docs: align auto resource processor wording * test: cover image resize failures * fix: harden image resource lifecycle * fix: preserve resource image detail and linked daily ownership * style(file-graph): stabilize multiline docstring formatting |
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jinliyl
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f5ec230fef
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feat: add DSH memory integration and organize extensions (#461)
* feat: add DSH memory integration and organize extensions * fix: support newer DSH release candidates * fix: address DSH integration review feedback * fix: handle DSH cross-day retry edge cases |
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jinliyl
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d3aee1adf5
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feat(evolve): report auto-dream file changes (#458)
* feat(evolve): report auto-dream content changes * perf(evolve): use lightweight dream snapshots |
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jinliyl
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215c1f72f2
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feat: refine local-first research and memory workflows (#444)
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* feat: refine local-first research workflows * fix: delegate structured output tool choice * refactor(auto-fin): fetch and filter rolling CLS news * fix(auto-fin): keep imports portable across platforms * feat(auto-fin): expose CLS fetch controls * fix(auto-fin): propagate configurable news window * feat(auto_fin): normalize hybrid wikilinks in report body - Add _normalize_hybrid_wikilinks method to remove redundant Markdown destinations - Use regex to identify hybrid wikilinks with optional destinations - Replace redundant destinations with simpler wikilink format for clarity - Ensure normalization is failure-safe with exception handling and logging - Update report body normalization process to apply hybrid wikilink fix - Add unit tests to verify correct normalization and failure safety behavior * fix(dream): serialize integration with application-wide asyncio lock - Add application-wide asyncio.Lock to serialize digest writes during integration - Update _snapshot_digest to capture metadata per bucket - Validate bucket association when recovering from file changes - Add tests ensuring recovery only from the correct bucket - Add tests confirming integration lock is shared across application context - Enhance strict topic YAML loading validation in dream utils - Add tests for strict topic loading rejecting invalid or lossy fields * fix(cookbook): enable configurable job_tools for digest and merge steps - Update daily_cookbook.yaml to add job_tools: [memory_search, read] in digest steps - Modify DailyPaperDigestStep to read job_tools from kwargs instead of fixed list - Modify AutoFinMergeStep to similarly read job_tools from kwargs - Update tests to pass job_tools explicitly when invoking these steps - Remove hardcoded _TOOLS constants and replace with dynamic job_tools handling * fix: retry incomplete dream receipts * perf(pdf): increase max PDF pages limit from 20 to 35 - Updated configuration max_pdf_pages from 20 to 35 in daily_cookbook.yaml - Modified code to extract up to 35 pages instead of 20 in analyze.py - Updated README and README_ZH to document the increased max_pdf_pages - Adjusted unit test assertions to reflect new max_pdf_pages limit of 35 * fix memory integration and daily paper links * docs clarify cookbook tool usage |
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jinliyl
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c5d92a24ab
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feat: weave dream wikilinks into contextual prose (#428)
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jinliyl
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9218a2d0e3
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refactor: derive dialog paths from session_dir (#421)
* refactor: derive dialog paths from session directory * fix: normalize configured session paths * fix: align dialog watch paths with writers * fix: reject absolute session directories |
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xyf2020
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5bc46c88b6
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feat(benchmark): enhance session memory retrieval and isolate benchmark assets (#409)
* chore(benchmark): isolate dataset/workspaces/results per benchmark
- Move shared benchmark/{datasets,memory_workspaces,results} into per-benchmark subdirs benchmark/<name>/{dataset,workspaces,results}
- Update beam/longmemeval config.yaml and run.py path defaults
- Relocate longmemeval download.py to benchmark/longmemeval/ (downloads into dataset/ subdir); inline dataset download docs into README
- Update .gitignore: benchmark/*/{dataset,workspaces,results}/
- Move result-{beam,longmemeval}.md to benchmark/results_md/ and drop result- prefix; update README links
- Fix stale path refs in llm_judge.py and logs/demo_search_format.py
* feat(benchmark): add read tool to agentic answer and update BEAM results
- Add 'read' to job_tools in BaseAgenticAnswerStep for file reading capability
- Document read tool usage in lme/agentic_answer.yaml system prompt
- Update result-beam.md with latest evaluation scores (OVERALL: 0.623/0.580)
* feat(auto_memory): add source line-number markers for note traceability
- Add _format_history hook in AutoMemoryStep with line-number annotation
- Override in BeamAutoMemoryStep to prefix each turn with [Ln] for citation
- Add session_file variable to prompt templates for source marker paths
- Simplify repeated extraction rules by referencing system prompt
- Enhance agentic_answer search strategy (multi-search, read tool hint)
- Add warning log on ReadStep failure
* feat(beam): enhance auto_memory with source markers and pilot ingest tooling
* refactor(beam): rename max_chunk_words to max_segment_words, drop one-off pilot scripts
* feat: add CompressorStep and search_v2 dual-mode session compression
- Add CompressorStep (reme/steps/evolve/compressor.py) for direct LLM
text compression with optional query-guided relevance filtering
- Extend search_v2_step to support query-aware and query-independent
session transcript compression via _compress injected kwargs
- Refactor _source_format.py: split into render_chunk_entries +
join_chunk_entries; session chunks now render line-aligned with
L<n>: prefixes for verbatim/compressed parity
- Add JOB_TOOLS and INJECTED_JOB_KWARGS to BaseAgenticAnswerStep for
per-subclass tool and parameter injection
- LmeAgenticAnswerStep injects _search._compress payload to enable
query-aware compression during benchmark evaluation
- Record compression ablation results in result-longmemeval.md
- Add unit tests for CompressorStep and search compression paths
* refactor(compress): relax session compression to lenient format-preserving strategy and update LME results
* refactor(benchmark): make session compression config-driven via compress_session flag
Move session-transcript compression from LME hard-coded injection to a
runtime context flag set by evaluation.compress_session in each
benchmark config. Compression is off by default for both BEAM and LME,
and BaseAgenticAnswerStep now conditionally injects the _search compress
payload only when the flag is truthy.
* feat(lme/auto_memory): add source attribution markers with line numbers
Add _format_history to annotate each turn with [Ln] line numbers and
expose {session_file} in prompts so the agent can emit bare wikilink-style
source markers like [[session/dialog/s1.jsonl#L1-L2,L5-L6]] at the end
of factual entries. Consolidate the per-prompt body/format rules into
references to the system prompt to avoid drift, and add frontmatter-
protection guidance for the edit tool.
* feat: improve agentic answer prompt and update beam 100K results
- Strengthen abstention rule: prohibit extrapolation from related but
non-direct evidence
- Add multi-angle search after preliminary answer to check for
conflicting/supplementary/updated information
- Add max-iteration fallback to 'Information not found'
- Update beam.md with 100K results (agentscope 2.0.4.post1, from scratch)
including per-type token consumption and memory construction stats
- config.yaml: 100K dataset, 20 workers for BEAM evaluation
- run.py: add memory construction token usage tracking (default agent)
- Overall: 0.635 → 0.654 (+0.019), contradiction_resolution: 0.338 → 0.478
(+0.140), abstention: 0.500 → 0.525 (+0.025)
* feat(read): add session-aware formatting for read tool and update BEAM eval
- Add truncate_session_output in _file_io.py to render jsonl session
lines as [speaker @ time] content before byte-budget truncation
- Add read_step_format_session flag to ReadStep, honoring injected
job kwargs (precedence) and YAML fallback
- Inject read_step_format_session=True into BaseAgenticAnswerStep
so agentic answer reads render session transcripts human-readably
- Refine BEAM agentic_answer prompt: continue multi-angle search
after preliminary answer, forbid fabrication/extrapolation
- Update BEAM config to 1M variant and add sequential 100K-eval /
1M-build shell script
- Refresh benchmark/results_md/beam.md with latest results
* chore(config): disable expand_links in beam and lme search_v2 configs
* refactor(beam): drop one-off sequential 100K-eval-then-1M-build script
* fix(benchmark): add compressor job to beam config and fix BEAM clone instructions
- Add compressor job and compressor as_llm component to reme/config/beam.yaml
(aligned with lme.yaml) so that compress_session: true works for BEAM
- Add graceful degradation guard in search_v2._compress_session_entries:
when the compressor job is missing from the active config, log a warning
and skip compression instead of raising 'Job compressor not found'.
Skipped when there is no app_context so unit tests mocking run_job still
drive compression behavior.
- Fix BEAM download instructions in README.md/README_ZH.md: add mkdir -p
before cd benchmark/beam/dataset (the directory is gitignored and absent
in a fresh clone)
* fix(steps): guard compressor exceptions and fix ReadStep boolean override
1. search_v2: catch per-entry exceptions from run_job('compressor') inside
compress() so asyncio.gather never propagates a compressor failure (e.g.
temporary LLM outage). The failing entry keeps its original body while
remaining entries are still compressed, preserving already-retrieved
search results.
2. read: replace 'context_value or yaml_value' with an existence check so
that a runtime-injected False can explicitly disable a YAML-true
read_step_format_session flag.
Add focused unit tests for both paths.
* fix(search_v2): use existence check for strict_date_filter boolean override
Replace 'context_value or yaml_value' with an existence-based check so
that a runtime-injected False can explicitly disable a YAML-true
strict_date_filter flag, consistent with the read_step_format_session fix.
* refactor(search): simplify strict_date_filter fallback to truthiness-or
* style(test): rename unused param to satisfy pylint W0613
---------
Co-authored-by: sa-buc <jiangniurou.xyf@dail-algo011164204033.ET135>
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jinliyl
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a9ec334adc
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feat: simplify wikilink semantics and support line anchors (#412)
* feat: simplify local links and support line anchors * fix: align line anchor tests with CI lint * fix: preserve local links across file moves * fix: encode markdown paths when rewriting links * refactor(read): keep explicit line range parameters * fix: simplify legacy link predicate compatibility * docs: align local link behavior with implementation * fix: skip unsupported markdown destination escapes * fix: normalize workspace link paths across platforms * fix: bound markdown link scanning * fix: keep local link processing linear * docs: clarify permissive markdown link parsing * fix: handle local link processing failures * refactor: limit file links to wikilink syntax * docs: align wikilink contract with implementation * fix: normalize dream and neighbor paths on Windows * fix: resolve workspace path for neighbor expansion |
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Sen Huang
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550317c3bf
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Revert "feat(plugin): add ReMe integration for Codex (#372)" (#400)
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This reverts commit
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DiegoCluv7
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a367c2ce13
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feat(plugin): add ReMe integration for Codex (#372)
* feat(plugin): add ReMe integration for Codex * fix(plugin): fix Codex plugin port, transcript ingestion, and Windows support * fix(plugin): correct Codex transcript schema, path validation, and hook fixes * test(plugin): add MCP round-trip tests * fix(plugin): rewrite parser and tests. * fix(plugin): reserve id-less messages, cover marketplace manifest, error handling, path fixes, and main sync Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com> |
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xyf2020
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f34dcdb09b
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feat(Step tools): add white/black path prefix permission filtering to read, edit, write (#391)
* feat(read): add white/black path prefix permission filtering to ReadStep * feat: add PrefixCheck mixin for path-prefix permission in file I/O steps * feat: add injected_job_kwargs mechanism and refine path-prefix permission * refactor(file_io): consolidate prefix_check into _path module |
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jinliyl
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1687179f84
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feat: add Auto Fin cookbook and managed outbound proxy support (#392)
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* feat: add ssh proxy * feat: add ssh proxy * feat: add ssh proxy * feat: add ssh proxy * feat: add prompt * feat: add agent wrapper * feat: add agent wrapper * feat: add agent wrapper * feat: add tushare skill * feat: add tushare skill * feat: add tushare skill * feat: add none stream * chore(deps): update dependency versions in pyproject.toml - Bump claude-agent-sdk from 0.2.123 to 0.2.126 - Upgrade pre-commit to version 4.6.1 or higher - Upgrade pytest to version 9.1.1 or higher * feat(agent_wrapper): add session compaction support and unify session commands - Introduce compact_session method to BaseAgentWrapper and implement it in AsAgentWrapper, CcAgentWrapper, and CodexAgentWrapper - Add session_command module with SessionCommandResult dataclass and handle_session_command function for /clear and /compact commands - Update __init__.py exports to include session_command handlers - Modify DingTalkWaitStep to handle session commands via handle_session_command function - Remove streaming mode from DingTalkWaitStep and simplify reply handling to final Markdown replies only - Add unit tests for session compaction methods and session command handling across wrappers and DingTalk integration - Clean up and remove obsolete streaming and card rendering code from DingTalk wait step - Adjust daily_cookbook.yaml to remove stream and card_update_interval config entries for DingTalk wait step * feat(auto_fin): add Auto Fin simulated portfolio cookbook workflow - Add comprehensive Auto Fin schema exports for multiple models and enums - Implement base class and helpers for Auto Fin analysis steps - Create file, state, and formatting utilities for Auto Fin with atomic file writes and locking - Define Auto Fin pipeline with four analysis agents: backtest, event, portfolio, and US correlation - Register Auto Fin package in cookbook workflows and schema initialization - Add detailed documentation in markdown describing the system design, workflow, and data contracts * feat(outbound_proxy): add application-scoped outbound HTTP proxy components - Introduce BaseOutboundProxy and OutboundProxyEndpoint as core contracts - Implement FixedHttpOutboundProxy for external HTTP proxy integration - Add SshHttpOutboundProxy providing SSH-backed local HTTP proxy tunnels - Register outbound proxy components in component registry and enumeration - Update components package to include outbound_proxy module - Add dependency on pproxy for SSH HTTP proxy bridging - Include comprehensive unit tests covering proxy lifecycle, validation, environment merging, error handling, readiness, and monitoring mechanisms * refactor(network): replace SSH proxy with explicit HTTP outbound proxy - Remove SSH proxy helper implementation and references in codebase - Add support for explicit HTTP proxy URL in arXiv and HuggingFace clients - Modify clients to use async context manager for consistent resource handling - Update daily paper steps to forward outbound proxy configuration explicitly - Change tests to cover new proxy usage model and remove SSH proxy mocks - Add outbound proxy component configuration in daily_cookbook.yaml - Ensure proxy URL usage disables environment trust in HTTP clients - Fix app context component enum access to be defensive against missing keys * feat(agent_wrapper): add managed proxy support for command environments - Introduce BaseOutboundProxy binding in BaseAgentWrapper for outbound proxy management - Add bash_environment and command_proxy_environment properties to apply proxy settings - Update WorkspaceBackend instantiation in AsAgentWrapper to use bash_environment - Inject managed proxy export commands into Claude Code Bash commands via hooks - Enhance CodexAgentWrapper to include managed proxy in shell environment policy - Modify daily_cookbook.yaml steps to specify outbound_proxy as default where needed - Add comprehensive unit tests verifying managed proxy injection and environment isolation - Ensure subprocess_environment remains unchanged while proxy is applied selectively to commands * refactor(memory): replace search job_tools with memory in daily cookbook config - Change workspace_dir default from .reme to reme_workspace - Replace search job_tools with memory across multiple components and jobs - Update descriptions to reflect long-term memory retrieval instead of search - Modify system prompts to instruct using memory for retrieving notes - Adjust unit tests to verify memory job_tools and job presence instead of search - Ensure consistency in configuration and tests for memory backend usage * refactor(config): rename memory to memory_search in daily cookbook config - Change all occurrences of "memory" to "memory_search" in job_tools and job definitions - Update related system prompts to reflect the new memory_search terminology - Modify unit tests to assert the presence of memory_search instead of memory - Ensure consistency across skills, job tools, and backend configurations in multiple components * feat(auto_fin): add deterministic quantitative research and ranking fusion - Introduce new schema models: EtfScore, RankingMetrics, ExtremeAnalysis, DimensionRanking, and FusionRanking to represent deterministic research outputs - Add ranking data to event, backtest, us_correlation, and portfolio analysis outputs - Implement ranking_section renderer to format Top20 scores and diagnostics in Markdown - Develop AutoFinQuantStep for deterministic ETF ranking using TuShare data, Polars, and a custom extremely randomized tree ensemble - Integrate quantitative rankings into backtest and portfolio analysis steps and reports - Extend auto_fin pipeline with new quant_enabled and quant_required config options - Enforce ranking constraints like unique codes, contiguous ranks, and normalized fusion weights - Update analysis YAMLs with rules limiting data freshness, universe, and ranking usage - Incorporate ranking outputs into all major markdown report bodies in Auto Fin pipeline - Add concurrency-limited asynchronous TuShare client to fetch required market data - Introduce cross-sectional rank correlation and NDCG metrics for ranking quality evaluation * feat(auto_fin): implement stage-wise notification and reporting for analysis pipeline - Refactor notification config in daily_cookbook.yaml to support dispatch steps - Update AutoFinNotificationStep to deduplicate notifications per run stage - Add _notify_stage method in pipeline to send notifications for each analysis stage - Implement persistence and notification for event, backtest, US correlation, and portfolio stages - Modify pipeline flow to persist reports and notify after each stage completion - Adjust metadata to track notifications and errors per stage - Update tests to verify stage-wise notification sending and deduplication - Remove older combined report persistence in favor of modular stage handling * feat(auto_fin): add outbound proxy support for Tushare API usage - Introduce BaseOutboundProxy reference in AutoFinPipelineStep and AutoFinQuantStep - Update TushareResearchClient and trade calendar fetch to accept and use proxy URL - Create _ProxiedTushareApi adapter to route Tushare requests via explicit HTTP proxy - Modify create_tushare_api utility to optionally return proxied API client - Add unit tests covering proxy forwarding and client behavior with managed proxies - Ensure proxy usage respects explicit proxy URL over environment fallback - Integrate outbound proxy into data fetching and quantitative research steps * feat(auto_fin): enforce checkpoint time validation and add state models - Introduce AnalysisState base class and specific states for event, backtest, and US correlation analyses - Replace analysis output types with corresponding state classes in run schemas - Add require_checkpoint_reached method to validate decision_at/data_cutoff against current time - Enforce checkpoint time checks before analysis steps in event, backtest, portfolio, and quant analyses - Refactor quant data loading to include adjustment factors and apply price adjustments without fallback - Update analysis YAML docs to require real-time checkpoint validation and forbid using future data - Improve portfolio run serialization by excluding redundant legacy fields and nested proposed actions - Add helper to extract readable sections from persisted checkpoint documents - Fix event analysis output validation to reject events and sources with future timestamps * feat(auto_fin): auto-select latest reached checkpoint if none specified - Extend checkpoint config to accept empty string for auto selection - Add static method to compute latest checkpoint reached by current time - Modify pipeline step to auto-select checkpoint based on trade calendar and time - Adjust force flag default depending on whether checkpoint is explicit or auto - Log details when checkpoint is auto-selected to improve observability - Add comprehensive tests for auto checkpoint selection logic and edge cases - Remove deprecated default and required constraints from force parameter in config * refactor(auto_fin): unify datetime comparison with compare_datetimes utility - Replace direct datetime comparisons with compare_datetimes function calls - Use cmp_to_key with compare_datetimes for sorting datetime tuples and lists - Update validation logic in backtest, event, analysis, and ledger modules for consistent datetime handling - Add unit tests to verify handling of naive and aware datetime comparisons in event and backtest validations - Ensure marked_at and interval_end timestamps are set and compared consistently using compare_datetimes - Improve correctness of ordering and conditional checks related to timestamps throughout auto_fin steps and ledger code * feat(auto_fin): add datetime comparison helper for mixed timezone data - Implement compare_datetimes function to handle naive and aware datetimes - Ensure naive datetime is interpreted in the known timezone of the counterpart - Facilitate comparisons between legacy and timezone-aware Auto Fin data - Add module docstring explaining purpose of the helpers * docs(auto_fin): enforce unique ETF representative per sub-theme in analysis rules - Update backtest.yaml to recommend or highlight only one ETF per sub-theme for ETF analyses - Modify event.yaml to map only one representative ETF per sub-theme, avoiding duplicate recommendations - Revise portfolio.yaml to restrict holdings/buys to a single ETF per sub-theme, preventing repeated buys of highly overlapping ETFs - Adjust us_correlation.yaml to retain only one representative A-share ETF per sub-theme for mapping or recommendation - Add test to verify presence of new sub-theme uniqueness guidance in step prompts * feat(auto_fin): separate draft model and include deterministic fusion ranking - Introduce _PortfolioProposalDraft pydantic model for agent-authored fields before ranking - Discard any "fusion_ranking" data from draft to prevent conflicts with canonical ranking - Modify AutoFinPortfolioStep to receive draft, enrich with fusion_ranking, and produce final output - Update tests to use _PortfolioProposalDraft and validate deterministic fusion ranking propagation - Add async test verifying fusion ranking is correctly set in portfolio output with no errors * refactor(auto_fin): rewrite and simplify Auto Fin schema and steps - Remove legacy Auto Fin analysis step modules and helpers - Replace complex ranking and portfolio models with simplified current-news models - Update schema to focus on news-case workflow with new domain models - Remove A-share decision checkpoints and backtest details from schema - Simplify recommendation and decision output structures - Clean up deprecated state and utility functions - Update Auto Fin steps initialization to new pipeline steps only - Improve uniqueness validation for themes and ETFs in research plan * feat(auto_fin): implement full local cache and analysis workflow for Auto Fin - Add AutoFinDataStep to prepare and cache daily TuShare data with lookback - Add AutoFinAnalysisStep to analyze cached data and generate Markdown report - Implement detailed time window, ETF filtering, and historical case validation - Introduce YAML prompts for planning and decision-making steps - Update .gitignore to include reme_workspace/ - Clean up config and import structure for auto_fin steps - Remove old pipeline.py and consolidate functionality into new modules - Use polars for efficient CSV reading and data processing - Ensure atomic writes and strict JSON serialization for cache files - Enforce rules on news timing, ETF universe, and historical case usage * fix(auto_fin): restrict news data source to '财联社' in analysis and cache - Update analysis templates to specify current news as from '财联社' only - Modify news fetching functions to filter by source '财联社' - Add validation method to check cached news source correctness - Update news caching logic to exclude non-'财联社' news - Enhance unit tests with multiple sources to ensure filtering works - Confirm news API calls include source filter parameter as '财联社' * refactor(auto_fin): convert I/O methods to asynchronous implementations - Change _news, _dataset, and _theme_data methods to async for improved concurrency - Move JSONL and CSV reading operations to asynchronous wrappers using asyncio.to_thread - Remove synchronous _read_jsonl and _read_csv functions, integrate them as static async class methods - Update cache validation methods to async, awaiting I/O operations accordingly - Adjust usage of dataset and news retrieval in analysis step to await asynchronous methods - Add async unit test to validate JSONL reading with unicode line separators - Preserve existing functionality while enabling non-blocking file and data access * fix(nx_file_graph): defer networkx import and improve dependency handling - Move networkx import inside NxFileGraph constructor for lazy loading - Raise ImportError with original exception context if networkx is missing - Remove module-level fallback assignment of nx to None - Expand test to block loading of multiple optional core dependencies eagerly - Change exception type in test from ModuleNotFoundError to AssertionError - Update test comments to reflect broader optional dependency checks * feat(embedding_store): add quota retry delay mechanism for embedding requests - Introduce quota_retry_delay parameter to configure wait time before retry on quota exhaustion - Implement detection of insufficient quota errors in LocalEmbeddingStore without external SDK - Add retry logic with custom delay when quota is insufficient during embedding requests - Update configuration to set max_retries and quota_retry_delay defaults for embedding store - Add unit tests covering quota exhaustion retry behavior with delay and opt-in control - Ensure existing retry behavior remains unchanged if quota_retry_delay is not set * feat(auto_fin): add detailed logging to analysis and data fetching steps - Add _preview static method for bounded diagnostic output in analysis.py - Log prompt start, completion, errors, and validation details in _reply method - Add info logs for major processing steps in execute method of analysis.py - Add debug and info logs for cache validation, data fetching, and pagination in data.py - Log conditions for skipping reports and cache plans in data.py execute method - Log download summaries and cache writes for news and ETF data - Improve error logging with exception details in cache validation functions - Ensure all logs include context such as record counts, paths, and parameters * refactor(auto_fin): overhaul Auto Fin workflow and schema contracts - Replace old Auto Fin schema models with comprehensive new data classes - Remove legacy Auto Fin analysis step in favor of modular agent-based steps - Introduce AutoFinAgentStep for validating structured agent replies - Simplify data cleaning and JSONL writing utilities for news cache - Remove synchronous and asynchronous dataset methods from analysis step - Redefine Auto Fin analysis configuration for 360-day news retention and multi-step pipeline - Remove embedded analysis prompt templates and replace with agent-driven logic - Update __init__.py exports to match new step implementations and remove deprecated classes - Improve error handling and validation in agent step reply processing - Clean up redundant imports and unused code in analysis and data preparation modules * feat(auto_fin): add detailed logging for analysis and data processing steps - Add timing logs to measure agent prompt processing duration in analysis.py - Log news cache hits and news write paths with record counts in data.py - Include detailed info logs for news download start and completion in data.py - Add start, progress, and completion logs with topic and event counts in history.py - Log start and completion of merge step including path and ETF count in merge.py - Add start and done logs with window and news counts in topic.py * feat(auto_fin): enhance schema and steps with detailed ETF and event modeling - Replace and add multiple AutoFin schema classes to support detailed ETF selection, historical research, market analysis, forecast models, and report output with validation - Implement Shanghai timezone normalization and strict validation in schema models - Remove deprecated AutoFin analysis agent step and consolidate reply handling in base step - Introduce AutoFinStep base class with shared helpers for prompt handling, data fetching, logging, and JSONL file operations - Add AutoFinDataStep to manage daily news data complete with schedule validation, caching, and source validation logic - Update cookbook configuration to customize auto_fin step parameters and simplify outbound proxy settings - Refactor imports and clean unused code for better maintainability * feat(auto_fin): introduce detailed historical event resolution and market similarity analysis - Add AutoFinHistoricalEventReference and AutoFinHistoricalSimilarity models for refined event referencing and similarity judgment - Implement validation to ensure non-empty critical fields and uniqueness of historical news IDs - Develop method to resolve Agent-selected historical event references from workspace files with strict path and existence checks - Enrich historical events with market entry and future returns data after resolution - Redesign market step to calculate similarity-weighted ETF forecasts based on matched historical event similarities - Enforce validation on matched historical events for uniqueness and proper weight summation - Simplify merge step output to final Markdown report without YAML frontmatter and redundant fields - Update user instructions for history search, market, and merge steps to reflect new data structures and responsibilities - Adjust test suite to cover new schema and step behavior changes, including enhanced validation and JSON output formats * feat(auto_fin): add new cron jobs and output analysis jsonl - Add new cron jobs auto_fin_1145_cron and auto_fin_1800_cron with auto_fin_steps - Change auto_fin_0930_cron schedule to run Monday to Sunday - Extend merge step to write analysis data to auto_fin_analysis.jsonl - Update unit tests to verify new cron jobs and their steps configuration * fix(auto_fin): improve atomic file write and refresh daily index - Change temporary file naming to include UUID for uniqueness and hidden prefix - Replace atomic write method from using Path.replace to os.replace with safe unlink - Add import and use os.replace for safer file replace operation - Refresh daily index after writing auto finance markdown and JSONL files - Import and call refresh_day_index in merge step to update file index asynchronously * docs(cookbook): add optional SSH proxy configuration in README files - Introduce optional SSH proxy setup in auto-fin and daily_paper cookbooks - Provide instructions to enable outbound proxy via `daily_cookbook.yaml` and environment variables - Add `REME_PROXY_IP` and `REME_PROXY_ACCOUNT` environment variables descriptions in multiple README files - Update English and Chinese README and README_ZH documents with proxy details - Maintain consistent formatting of environment variable tables across documents * fix(file_io): include schema_version in hidden metadata keys - Added "schema_version" to _INDEX_HIDDEN_METADATA_KEYS in _daily_index.py - Updated _render_notes_block to always include additional keys regardless of schema_version fix(deps): move pproxy dependency to later in pyproject.toml - Removed pproxy from early dependencies list - Added pproxy back near the end of dependency list for better ordering fix(outbound_proxy): require pproxy package for ssh_http proxy - Added importlib.util check for pproxy package presence - Raise RuntimeError if pproxy is not installed when using SSH HTTP outbound proxy - Improved error message suggests installing reme-ai with 'core' extra * docs(readme): update News section with new Cookbook workflows - Clarify introduction of optional Cookbooks with Daily Paper and Auto Fin workflows - Update English README to reflect both paper discovery and file-native ETF event research - Revise Chinese README to include financial news and historical market data research capability - Maintain announcement of paper acceptance at Findings of ACL 2026 * feat(auto_fin): add calculation results to final Markdown output - Implement _calculation_results to summarize forecast for each ETF analyzed - Include program-calculated results in the JSON input for the Markdown report - Update YAML template to incorporate calculation results and adjust recommendation rules - Refine recommendation logic to rely on event impact judgments combined with calculation outputs - Modify tests to verify presence of calculation results and updated report content and format * up prompt * fix(keyword_index): ignore non-indexable chunks during keyword sync - Add is_indexable method to base and BM25 keyword index classes to check text tokenizability - Update local file store to exclude non-indexable chunks from expected document IDs to prevent rebuild - Fix JSONL chunker to correctly handle Unicode line separator U+2028 inside JSON strings without splitting - Add test to ensure non-empty but non-indexable chunk does not trigger keyword index rebuild - Add test to verify U+2028 character does not cause incorrect JSONL record splitting |
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xyf2020
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7b1da5a9ee
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feat(benchmark): add BEAM & restructure LongMemEval evaluation framework (#375)
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* feat(eval): add LongMemEval evaluation framework with tool_defaults date injection
- Add evaluation/longmemeval/ with run.py, config.yaml, and test scripts
- Add reme/config/longmemeval.yaml for evaluation-specific model config
- Add tool_defaults mechanism to as_agent_wrapper for injecting default
tool kwargs (uses setdefault so LLM-provided values take priority)
- Pass tool_defaults={'daily_write': {'date': day}} in auto_memory to
ensure notes always use the correct historical date
- Add timestamp interpolation (_interpolate_timestamps) in auto_memory
for filling missing created_at fields via linear interpolation
- Evaluation pipeline: ingest sessions -> dream -> search -> answer -> judge
- Uses qwen3.6-flash for memory, qwen3.7-max for answer/judge
* chore: gitignore logs/results/demo.py, keep empty dirs
* chore: update .gitignore
* feat(eval): add multiprocessing and session time filtering to longmemeval runner
- Replace async execution with synchronous + multiprocessing for parallel item evaluation - Add filter_future_sessions option to only ingest sessions <= question date - Add question_types filtering in config - Add result summary with binary accuracy and avg score - Update config defaults (oracle variant, 50 items, 32 workers) - Minor code style fixes in agent_wrapper and auto_memory
* feat: add bench_query_step with ReAct agent for benchmark query phase
- Add BenchQueryStep using agent_wrapper with search job tool
- Replace manual search+LLM answer in run.py with bench_query_job
- Remove unused answer LLM config from longmemeval.yaml
- Register benchmark step module in steps/__init__.py
* feat: add start_date/end_date time filter support for search job
- Add _extract_date_from_path to extract validated YYYY-MM-DD from chunk paths
- Add start_date/end_date filtering in _matches_search_filter
- Implement progressive recall in FaissLocalFileStore.vector_search
- Promote start_date/end_date from context to search_filter in SearchStep
- Add start_date/end_date parameters to search job in default.yaml
- Add unit tests for date filter functionality
* fix: validate/normalize date filters and harden _extract_date_from_path
Address three code-review comments on the time_filter search feature:
1. Validate/normalize start_date and end_date before string comparison.
_matches_search_filter does lexicographic comparison against path_date
(always canonical YYYY-MM-DD). Raw caller values like '2026-2-28' or
'abc' would produce silently wrong results. Now SearchStep normalizes
valid dates via extract_daily_date (with strptime fallback for
non-zero-padded input) and silently ignores invalid dates with a
logger.warning, removing them from the filter.
2. Clarify behavior for paths without embedded dates.
Added optional strict_date_filter parameter (default False). When True
and at least one date bound is active, chunks whose path yields no date
(e.g. digest/personal/topic.md) are excluded. When False (default),
the existing behavior is preserved — dateless paths pass through.
3. Harden _extract_date_from_path against non-standard suffixes.
Previously parts[1].split('.')[0] accepted '2026-05-18.anything' as a
valid date. Now only exact 'YYYY-MM-DD' (dir) and 'YYYY-MM-DD.md'
(day-index) forms are accepted.
* feat(eval): LLM-as-Judge per-type prompt routing, binary-only, progress tracking
- Remove 0-5 score metric, keep only binary (yes/no) classification
- Load per-question-type judge prompts from llm-as-judge.json
(temporal-reasoning, knowledge-update, single-session-preference, __default__)
- Replace SCORE_JUDGE_PROMPT with type-specific BINARY_JUDGE_PROMPT template
- judge_response(): parameter 'metric' -> 'question_type', returns single 'judgment'
- Summary output: add per-type accuracy breakdown, remove score stats
- Add progress tracking: background thread prints PROGRESS every 10min
- Add FINAL progress line and total elapsed time on completion
- Add --log-level, --reme-log-level, -q CLI arguments
- Parallel mode: pool.map -> pool.imap_unordered for real-time progress
- config.yaml: full oracle (10000 items), 32 workers, all question types
- Add kill.sh (process cleanup) and run_async.sh (background eval launcher)
* docs: add LongMemEval oracle evaluation results (61.6% accuracy)
* feat(bench): add MAX_ITERATION limit to BenchQueryStep and add _auto_memory.yaml
* feat: add golden session benchmark & eval_only mode with refined prompt
- Add benchmark/longmemeval/run_golden_session.py for golden session evaluation
- Refine PROMPTED_SYSTEM_PROMPT: concise answer rule, remove 'Information not found' fallback
- Add eval_only mode to run.py (--eval_only flag)
- Add multiple eval config variants (evalonly, full, test5)
- Add analyze_results.py for result parsing
- Update auto_memory.yaml, longmemeval.yaml, application_config
- Update result-longmemeval.md with latest evaluation results
- Add benchmark results to .gitignore
* update: refine answer prompts and increase max iteration to 6 - Tighten prompted-answer system prompt for more concise output - Comment out 'Information not found' fallback rule - Increase MAX_ITERATION from 5 to 6 in bench_query - Add recall_eval.py - Update evaluation results
* feat(chunker): add dedicated JSON and JSONL file chunkers (cherry-pick from upstream #325)
- Add JsonFileChunker: structure-aware chunking preserving nested key paths,
optional list-to-dict conversion, size measured by json.dumps() char count
- Add JsonlFileChunker: line-aligned sliding-window chunking with configurable
overlap, supports char/byte mode switching
- Register both chunkers in default.yaml (json for .json, jsonl for .jsonl)
- Add comprehensive unit tests (21 + 20 test cases)
* feat(service): add CLI service for local job execution (from upstream #334)
- Introduce CliService to execute single jobs locally without serving ports
- Add prepare_start_config and should_precheck_start functions for CLI job setup
- Update reme start command to use CLI service when job argument is provided
- Add show_metadata to client kwargs for optional CLI metadata output
- Add unit tests for CLI service functionality and configuration handling
* feat(steps): add BM25/vector search steps, Python execute step, and draft steps (from upstream #334)
- Add Bm25SearchStep for plain BM25 keyword search with tool_context deduplication
- Add VectorSearchStep for plain vector search with tool_context deduplication
- Add PythonExecuteStep to run Python code in subprocess with timeout handling
- Add AddDraftStep/ReadAllDraftStep for draft accumulation scoped by tool context
- Update SearchStep with tool_context dedup, dynamic default limit via REME_SEARCH_LIMIT env,
and candidate_multiplier default changed from 3.0 to 5.0
- Add comprehensive unit tests for all new steps
* feat(search): add tool context deduplication and improve search configuration (#321)
* feat(search): add tool context deduplication and improve search configuration
- Modify _make_tool methods to accept and inject tool_context_id parameter
- Add tool_context_id handling in AS and CC agent wrappers
- Increase search candidate multiplier from 3.0 to 5.0 in default config
- Extend HTTP client timeout from 30s to 3600s
- Add tool context deduplication logic to prevent duplicate search results
- Implement TTL-based expiration for seen chunks in tool contexts
- Add comprehensive unit tests for tool context deduplication behavior
- Update .gitignore to exclude longmemeval directory
- Add time import for timestamp functionality in search step
* refactor(search): replace time module with datetime for timestamp generation
- Removed unused time import
- Added static method _now_ts using datetime.timestamp
- Updated clock parameter to use _now_ts method instead of time.time
- Maintained same timestamp precision and functionality
* fix(file_io): fix risk of out-workspace paths (#322)
* fix(file_io): fix risk of out-workspace paths
* chore(file_io): remove unused unittest file
* fix(as_embedding): support both agentscope 2.0.2 and 2.0.3 (#323)
2.0.3 promoted `dimensions` to a required first-class constructor
argument while keeping a backfill from `parameters.dimensions`; 2.0.2
has no such argument and reads `dimensions` from `Parameters`. Keep
`dimensions` in `Parameters` for both versions and, when the model
constructor accepts `dimensions`, pass `dimensions=None` so 2.0.3's
backfill promotes it out of `parameters`.
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* Bump version to 0.4.0.7
* refactor: delegate LLM-as-Judge to answer_judge_step and update eval config/results
- run.py: replace inline judge logic with judge_response_via_job using app.run_job('answer_judge')
- longmemeval.yaml: expand benchmark configuration
- bench_query.py: enhance benchmark query step
- result-longmemeval.md: update evaluation results
- judge_all_plus_results.json: add judge all-plus results
* refactor: split longmemeval.yaml into lme.yaml/beam.yaml and unify job names
- Split reme/config/longmemeval.yaml into lme.yaml (LongMemEval) and beam.yaml (BEAM)
- Unify job names across both configs: agentic_answer, answer_judge, context_answer
- Update evaluation/longmemeval/run.py and evaluation/beam/run_beam_eval.py to use unified job names
- Update all evaluation config YAMLs to reference lme.yaml
- Add BEAM benchmark step implementations (agentic_answer, context_answer, llm_judge)
- Remove obsolete config_test5.yaml and test_5sessions.py
* eval: BEAM 100K & LongMemEval cleaned-S 评测结果记录
- BEAM 100K eval-only (32并发, 20 case): Agentic 0.631, Prompted 0.468
- LongMemEval final GT (500题): Agentic 89.0%, Prompted 83.6%
- 新增 benchmark/result-beam.md, benchmark/result-longmemeval.md
- benchmark/beam/config.yaml: num_workers=32
* refactor: restructure benchmark directory and clean up gitignore rules
- Consolidate benchmark outputs to benchmark/results/ with .gitkeep
- Remove old benchmark scripts, configs and result files from benchmark/beam/ and benchmark/longmemeval/
- Add datasets/README.md and datasets/README_EN.md with download instructions
- Add datasets/longmemeval/download.py and final_groundtruth_cleaned_s.json
- Add memory_workspaces .gitkeep placeholders
- Restructure .gitignore: fix duplicate entries, add BEAM dataset exclusion, refine logs/results ignore patterns
- Remove stale result-beam.md and result-longmemeval.md from project root
* chore: clean up longmemeval benchmark scripts and update dataset docs
- Remove obsolete longmemeval benchmark runner/stats scripts
- Update datasets/longmemeval README and add Chinese translation
- Clean up final_groundtruth_cleaned_s.json
* docs(benchmark): add reproduction guide for LongMemEval and BEAM
- Add bilingual README for benchmark runners (EN/ZH)
- Cover prerequisites, dataset download, run commands, configs, outputs, logs, and kill.sh
* refactor: migrate auto_memory steps from evolve to benchmark-specific modules
- Split auto_memory into beam and lme benchmark-specific implementations
- Add auto_memory.py and auto_memory.yaml under steps/benchmark/beam and steps/benchmark/lme
- Slim down evolve/auto_memory.py and auto_memory.yaml to shared base only
- Remove obsolete evolve/_auto_memory.yaml
- Update benchmark run.py, config YAMLs, and step __init__.py registrations
- Update llm_judge and context_answer minor adjustments
- Remove outdated test_lme_final_answer_review.py
* revert(as_agent_wrapper): sync with upstream/main
Remove local-only comment to keep file identical with upstream/main.
* style: add trailing commas in benchmark __init__.py __all__ lists
* chore: disable vector_weight range assertion in SearchStep
* chore: add tests/integration/logs/ to .gitignore
* refactor: replace scipy.stats.kendalltau with pure numpy implementation
scipy is not listed in project dependencies. Implement Kendall's tau-b
rank correlation using only numpy to remove the undeclared dependency.
* feat(benchmark): add binary score metrics, update BEAM 1M results, and improve LLM retry/prompt config
- benchmark/beam/run.py: add binary score calculation per rubric item and per-type/overall binary stats
- benchmark/beam/config.yaml: switch to 1M dataset, reduce workers to 18
- benchmark/result-beam.md: add 1M evaluation results with binary scores
- benchmark/result-longmemeval.md: minor formatting
- reme/config/beam.yaml: increase max_retries to 5 and add retry_delay 5.0 for all LLM components
- reme/config/lme.yaml: increase max_retries to 5 and add retry_delay for judge/prompted/bench components
- reme/steps/benchmark/lme/agentic_answer.yaml: improve search strategy and answer rules prompts
* fix(benchmark): fix line-too-long and add pylint disable for main()
* refactor(longmemeval): use single cleaned-S dataset with embedded ground truth
- Switch to agentscope-ai/ReMe_longmemeval_clean_s_v2 HuggingFace source
- Remove separate final_groundtruth_cleaned_s.json (ground truth now in data file)
- Simplify download.py to fetch only longmemeval_s_reme_cleaned.json
- Remove dataset.variant and dataset.ground_truth_path config options
- Update benchmark and datasets READMEs to reflect new workflow
- Update .gitignore for new dataset filename
* fix: rename loop variable to avoid pylint redefined-outer-name warning
* refactor(benchmark): restructure datasets/memory_workspaces into benchmark and simplify auto_memory steps
* refactor(benchmark): extract BaseAgenticAnswerStep into base module
- Add reme/steps/benchmark/base/agentic_answer.py with shared agentic answer logic
- Refactor beam/lme AgenticAnswerStep to inherit from BaseAgenticAnswerStep
- Simplify lme/context_answer.py and update context_answer.yaml
- Update result-longmemeval.md with latest evaluation results (agentic 91.0%)
* refactor(benchmark): remove context_answer steps and unused configs
- Remove beam/lme context_answer job definitions and step implementations
- Remove prompted LLM component from beam.yaml and lme.yaml
- Delete jinli_lme.yaml (no longer needed)
- Simplify benchmark run.py scripts
- Clean up .gitkeep files and update .gitignore
- Remove unused import in search.py
* chore: remove benchmark/results/.gitkeep
---------
Co-authored-by: sa-buc <jiangniurou.xyf@dail-algo011164204033.ET135>
Co-authored-by: jinliyl <6469360+jinliyl@users.noreply.github.com>
Co-authored-by: imrewce <wce@pku.edu.cn>
Co-authored-by: Sen Huang <48879559+ployts@users.noreply.github.com>
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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jinliyl
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e7d44f6f3b
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refactor(agent): unify agent subprocess env, sessions, skills, and MCP/service jobs (#382)
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* feat(config): add environment variable configuration for agent subprocesses - Add environment field to ApplicationConfig to store variables for agent subprocesses - Remove dynamic loading of .env files in agent wrappers - Introduce subprocess_environment property in base agent wrapper - Pass application-level environment variables to Claude Code and Codex agents - Load environment variables once at startup and pass to ReMe application - Remove dependency on load_env utility in agent wrapper implementations - Update tests to use configured environment instead of dynamic loading - Remove unused environment loading utilities and related test cases * refactor(mcp): remove channel notification system and related components - Removed channel notification step implementation - Removed claim channel step implementation - Removed ChannelSink class from MCP service - Removed channel-related documentation from AGENTS.md - Removed channel instruction text from MCP service - Removed all channel-related tests - Updated application context metadata comment to remove channel sink reference - Removed channel module initialization and imports * feat(service): add job whitelisting capability to BaseService - Add optional jobs parameter to BaseService.__init__ to configure job whitelist - Store jobs as set in self.jobs attribute for efficient lookup operations - Modify add_jobs method to filter jobs based on whitelist configuration - Update documentation in both English and Chinese to describe new feature - Add comprehensive unit tests for job whitelisting behavior - Implement flowchart update showing new filtering logic - Preserve existing enable_serve flag behavior alongside new whitelisting * refactor(service): enhance service job validation and MCP tool injection - Add strict validation for service jobs whitelist with detailed error messages - Implement injected job arguments support for MCP services with conflict detection - Add tool error handling for unsuccessful responses in MCP services - Remove duplicate job names in Codex agent wrapper using dict.fromkeys - Update MCP server argument format from single JSON array to repeated --job flags - Add comprehensive test coverage for job injection and error handling scenarios - Update documentation to reflect service job validation and MCP features - Ensure application cleanup occurs even when service lifespan encounters errors * feat(agent): update skill handling to preserve existing Claude skills - Change skills parameter processing to use 'all' instead of filtered list - Add logic to select project skills without restricting Claude's existing skills - Update variable naming from 'skills' to 'selected_skills' for clarity - Modify application context metadata documentation to clarify in-memory state usage - Add test case to verify configured skills are added without filtering existing skills - Update internal skill directory handling to use renamed variable consistently * refactor(agent): restructure agent wrapper components and session storage - Move CcFileSessionStore to separate module for better organization - Add SDK package version logging in base agent wrapper - Update Claude Code agent to use new session store structure with project keys - Refactor Claude Code agent wrapper to use proper type hints and SDK integration - Add support for server tool use events in Claude Code message processing - Improve error handling and resource cleanup in streaming operations - Update Codex agent wrapper with proper type annotations and configuration - Remove deprecated system prompt mode handling from Claude Code wrapper - Fix session path construction for Claude Code transcript storage - Update dependency injection and configuration handling patterns * fix(cc_agent_wrapper): resolve Claude Code SDK integration issues - Added dataclass import and created _BlockState for content block metadata tracking - Implemented proper MCP server name constant and tool context ID validation - Fixed tool_context_id injection to prevent duplicate assignment errors - Resolved skills parameter handling in build_options method - Enhanced job tools integration with MCP servers mapping validation - Replaced deprecated block_ids/block_types/tool_call_names with block_states dict - Updated message_delta to emit USAGE chunks instead of REPLY_END - Fixed stream result handling to ensure proper REPLY_END emission - Improved error handling for session mirror failures and rate limits - Added proper cleanup for expected trailing errors in streams - Refactored Codex agent wrapper initialization and configuration management - Removed obsolete system_prompt_mode from default config - Enhanced test coverage for new block state and error handling features - Fixed async generator handling with aclosing context manager - Improved chunk type mapping for Claude Code SDK events * refactor(tests): remove demo config tests from config parser test suite - Removed test_demo_config_registers_llm_jobs function and its assertions - Eliminated verification of LLM demo job configurations - Removed checks for agent wrapper component settings - Deleted assertions for model configurations and parameters - Cleaned up deprecated test cases related to demo config parsing * refactor(evolve): simplify Claude Code session store path structure - Removed redundant project key subdirectory from session link generation - Updated CcFileSessionStore initialization to use direct session directory path - Maintained existing session layout compatibility for backward compatibility - Added unit tests to verify session persistence behavior with existing transcripts - Ensured UUID-based session files remain accessible at expected locations - Preserved existing session directory structure without additional nesting * refactor(agent): defer optional Codex SDK imports until first use - Moved openai-codex imports inside functions to avoid mandatory dependencies - Added TYPE_CHECKING guard for development time type checking only - Implemented lazy loading mechanism with _get_async_codex_class function - Updated AsyncCodex initialization to occur on demand rather than at module level - Maintained backward compatibility while improving import performance - Added test case to verify package import works without optional Codex SDK - Updated agentscope dependency to version 2.0.4.post1 in pyproject.toml * test(embedded): add compatibility tests for in-process ReMe embedding - Add test suite for QwenPaw-style embedded configurations - Verify optional defaults remain preserved in embedded configs - Ensure in-process application API stays compatible - Test model injection and lifecycle management compatibility - Remove obsolete hermes agent plugin tests - Update CLI import test to cover multiple optional SDKs - Block claude_agent_sdk and openai_codex during import testing |
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Sen Huang
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55ef4bd6ad
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fix(proactive): expose topics in primary answer (#380) | ||
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jinliyl
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c3b1e93918
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feat(index): add file size limits and oversized file handling (#362)
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* feat(index): add file size limits and oversized file handling - Implement max_file_bytes configuration option for content processing jobs - Add default 20MB file size limit for background processing in default config - Skip oversized files during auto_resource step with appropriate metadata - Clear stale index entries when oversized files are modified - Add size-based filtering logic to update_changes step with skip reporting - Include file size validation in UpdateIndexStep with proper response handling - Add comprehensive tests for oversized file scenarios in auto_resource and update_index - Document file size limits in constants with appropriate thresholds * chore(version): bump version to 0.4.1.1 - Update __version__ from 0.4.1.0 to 0.4.1.1 in __init__.py * fix(index): isolate batch metadata and handle file races |
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Ziyang Guo
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c060933e4d
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fix(auto-memory): preserve message timestamps (#310)
* fix(auto-memory): preserve message timestamps * fix(auto-memory): infer daily date from messages * feat(file_io): add strict date parsing and improve daily date handling - Add new parse_daily_date function for strict YYYY-MM-DD validation - Replace extract_daily_date with parse_daily_date for explicit date validation - Change _messages_day to use max date instead of min for historical imports - Reorder imports to maintain consistent module ordering - Move session message saving after date validation in auto_memory - Add comprehensive tests for invalid date rejection before saving - Add tests for strict YYYY-MM-DD date format validation - Update test names to reflect latest date behavior --------- Co-authored-by: Ziyang Guo <121015044+RunMarshal@users.noreply.github.com> Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com> |
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Sen Huang
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3dee10d4f9
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feat: add Claude Code plugin with auto-memory functionality (#297)
* feat: add Claude Code plugin with auto-memory functionality * refactor(auto_memory): fix spacing in json parsing logic |
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jinliyl
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ffb4d08c4f
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feat(mem): Enhance daily note system with metadata handling and write functionality (#295)
* feat(file_io): add daily_write step for creating daily notes with conversation metadata - Add DailyWriteStep class that delegates to write job for creating daily notes - Register daily_write job in default configuration with proper parameters - Include validation for name and session_id path components - Add test coverage for daily_write functionality including metadata handling - Preserve existing job execution method in application.py after repositioning - Update base_step.py to use positional-only parameter syntax for job methods - Import and expose DailyWriteStep in file_io module initialization - Override reserved metadata keys (name, description, session_id, source_conversation) with fixed values - Refresh daily index after successful write operation - Generate proper source conversation links in markdown format * feat(daily): refactor daily note system with enhanced metadata handling - Introduce validate_filename_component function and export it - Add _INDEX_HIDDEN_METADATA_KEYS to hide conversation metadata from index - Update scan_notes to exclude hidden metadata keys from index rendering - Modify auto_memory to use daily_write tool and manage session frontmatter - Implement session note lookup and renaming based on frontmatter name - Update daily_list to return flattened note metadata including session info - Change daily_write to dispatch write step instead of running job - Add test cases for updated daily note functionality and metadata handling - Update version from 0.4.0.2 to 0.4.0.3 * fix(evolve): correct metadata update in auto memory response - Fixed trailing comma issue in metadata dictionary update - Ensured proper formatting of response metadata structure - Maintained existing functionality while fixing syntax error * refactor(auto_resource): replace daily_create with dynamic note management - Remove DailyCreateStep and related exports from file_io module - Replace static daily note creation with dynamic resource-linked card system - Implement LLM-suggested naming with frontmatter-driven file management - Add source_resource linking for tracking original files - Introduce collision handling with hash-based suffixes - Update documentation to reflect new resource card workflow - Modify auto_resource prompts to use write/edit tools instead of daily_create - Adjust test fixture comments to match new agent behavior - Update framework diagrams and quick start examples accordingly * feat(app): add version info to app initialization and update auto-memory logic - Include version number in application startup logging - Remove tool result truncation logic from auto-memory step - Update auto-memory to exclude tool_result blocks from saved history - Add test case to verify tool results are filtered out from message saving - Update YAML prompts to clarify filename naming rules without dates - Modify configuration to support new dispatch steps format with persistence control * feat(auto_memory): add note modification tracking and optimize frontmatter updates - Add _note_bytes and _note_modified methods to track actual file changes - Optimize frontmatter updates by checking existing metadata before update - Add modified flag to response metadata indicating actual note changes - Update logging to include modified status in various operations - Add comprehensive tests for modified/unmodified detection scenarios - Enhance result hook logic to skip when no actual changes occur - Refactor metadata handling to properly track creation vs modification status |
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jinliyl
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8b82ff88d0
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feat(evolve): enhance agent reply processing and logging capabilities (#293)
* feat(evolve): enhance agent reply processing and logging capabilities - Add agent_reply_result_text function to extract final user-visible text from agent replies - Implement comprehensive logging throughout auto_memory, auto_resource, and dream modules - Add max_units configuration option to limit extracted memory units - Improve error handling and validation in auto_resource step - Refactor dream extract step to respect max_units limit during processing - Enhance summary rendering in dream finish step with detailed breakdown - Add result hook functionality for embedding hosts integration - Implement loose resource filename handling for root-level resources - Update test cases to reflect new functionality and improved error messages * test(background-steps): update fake upsert function to include created parameter - Modified fake_upsert function to accept 'created' parameter instead of '_created' - Added 'created' field to captured dictionary in fake_upsert function - Included 'created': True in the expected response dictionary for test case - Updated test assertion to match new parameter structure |
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jinliyl
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7d86658f33
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Refactor logging levels and add dream schema definitions (#291)
* chore(logging): change info logs to debug level for data loading operations - Changed stopwords loading log from info to debug level - Changed file catalog nodes loading log from info to debug level - Changed file graph nodes loading log from info to debug level * feat(dream): add dream schema definitions and enum for auto-dream functionality - Add DreamBucketEnum with procedure, personal, and wiki values - Create comprehensive dream-related Pydantic models including DreamUnit, DreamTopic, DreamExtractOutput, IntegrateOutcome, TopicSelectionOutput, ProactiveResult, and DreamState - Move schema definitions from local step module to shared schema package - Update dream extraction and integration steps to use new enum-based bucket validation - Initialize digest directories for each dream bucket type - Enhance embedding store health check with workspace directory logging * refactor(tests): update DreamState import path in test_auto_dream.py - Move DreamState import from reme.steps.evolve.dream.schema to reme.schema - Maintain same functionality with updated module reference - Align import with new schema location in project structure |
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jinliyl
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a3bd81bde2
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Update version to 0.4.0.2 and improve tokenizer index handling (#290)
* fix(core): update version number to 0.4.0.1 - Incremented version from 0.4.0.0 to 0.4.0.1 in __init__.py * fix(index): remove stopwords path from tokenizer config and add keyword index repair - Remove stopwords_path from tokenizer config to prevent index forking by install path - Add _sync_keyword_index_from_chunks method to repair keyword index when persisted state mismatches - Implement test for keyword index repair from persisted chunks when missing - Add test to verify tokenizer fingerprint ignores stopwords absolute path - Update version from 0.4.0.1 to 0.4.0.2 * feat(dream): add scan_days parameter to dream extraction process - Add scan_days configuration option to default.yaml with default value of 2 - Implement recent_dates utility function to calculate date ranges for scanning - Modify DreamExtractStep to scan multiple days based on scan_days parameter - Update dream extraction to process files across multiple dates instead of single day - Extend DreamState schema to include dates and scan_days fields - Update DreamTopicsStep to handle multi-day topic processing - Modify finish step to checkpoint files from all scanned dates - Add comprehensive tests for multi-day scanning functionality - Update prompt templates to include scan dates information - Refactor topics writing logic to target specific date rather than current date |
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Sen Huang
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e31db5fe19
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docs: rename vault_dir to workspace_dir in documentation and examples (#286)
* docs: rename vault_dir to workspace_dir in documentation and examples * refactor(extract): format long method call across multiple lines * refactor(extract): format system prompt parameters for better readability |
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jinliyl
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206a53e5ed
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init: reme version 0.4.0 (#284) |