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5 Commits
| Author | SHA1 | Message | Date | |
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Amorend
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85c3909c2e
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feat: show real-time context window usage (#3125) (#3183)
* feat: show real-time context window usage in chat UI (#3125) Adds a `context_usage` block to `GET /api/threads/{id}/token-usage` (token count from the live checkpoint, the thread model's `context_window`, and a percentage), introduces a new `ModelConfig.context_window` distinct from the per-call `max_tokens` output cap, and surfaces the percentage in the chat header — inside `TokenUsageIndicator` when token-usage tracking is on, or as a standalone badge when it's off so context capacity stays visible independent of cost tracking. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * feat: per-category breakdown for context window usage Replace the single-number context_usage payload with a Claude-Code-style breakdown — messages, system prompt, skills, system/MCP tools (active + deferred), custom agents, memory injection, autocompact buffer, and free space — and surface it in the chat UI with a segmented progress bar and per-row table. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * docs(config): document context_window across model examples Add `context_window` to every example model in config.example.yaml so the new chat-UI "% context used" indicator works out of the box for whichever example a user adopts. Each value is the published default at the time of writing; users are pointed at the official model spec to verify. Bumps config_version to 11 so `make config-upgrade` flags outdated user configs. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * style: ruff format (line-length 240) No behavior change — collapses two multi-line expressions that fit on one line under the project's 240-char limit. Picked up by `make format`. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * review: address Copilot bot comments on #3183 - token-usage-indicator: switch `{contextPercentage && (...)}` to an explicit `!= null` check. (The string `"0"` is actually truthy in JS so the original code wasn't buggy, but the explicit check is clearer.) - context-usage-breakdown: drop the `useMemo` around segments/totals — the computation is O(n) over a handful of rows and the previous memo deps omitted `t.contextUsage.categories`, so the bar's tooltips/aria-labels could stay in the old language after a locale switch. - context_usage._split_tools: snapshot MCP names from `get_cached_mcp_tools()` directly instead of re-reading `extensions_config.json` after `get_available_tools()` already loaded it. Removes redundant file I/O on every `/token-usage` poll. (`get_available_tools()` still emits its own INFO logs — silencing those is out of scope here.) Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * style(frontend): prettier --write context-usage-breakdown CI's `pnpm format` (prettier --check) caught two lines previously formatted by hand. Collapses one comma to fit on one line; no behavior change. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> * fix(gateway): correct context-usage breakdown + add exact token counting The context-usage indicator shipped two bugs that silently zeroed whole breakdown rows (both caught by try/except, so the feature looked alive but produced wrong numbers): 1. _count_system_prompt passed app_config= to get_deferred_tools_prompt_section, which only accepts deferred_names -> TypeError swallowed -> system_prompt row always 0, and used_tokens/percentage undercounted by the full prompt. Also subtracted the deferred section twice (the rendered prompt already excluded it). Fix: derive deferred names deterministically and pass them to apply_prompt_template; drop the redundant subtraction. 2. _split_tools imported a non-existent get_deferred_registry -> ImportError swallowed -> all four tool-category rows always 0. Fix: classify via the public is_mcp_tool predicate + tool_search.enabled (mirrors build_deferred_tool_setup); the MCP tag is set by get_available_tools. Added token_usage.counting (approximate|exact). 'exact' routes text/schema/ message counting through the model tokenizer (tiktoken cl100k_base) via the existing memory-module machinery (lazy load + cache + cooldown + CJK-aware fallback), so CJK-heavy threads stop being undercounted by chars//4. Regression + e2e tests added; 6621 backend tests pass. * fix(gateway): harden context usage accounting * fix(gateway): count promoted MCP tools as active in context usage Promoted tools (deferred MCP tools the thread has fetched via tool_search) have their full schema bound on every subsequent turn by DeferredToolFilterMiddleware, so they consume context like any active tool. The breakdown previously left them in the reserved *_deferred rows, under- counting the thread's used_tokens. Classification now treats a tool as deferred only when tool_search is enabled, it is MCP-sourced, AND it has not been promoted. The promoted set is read from the checkpoint's channel_values and scoped by catalog hash — matching the runtime middleware, so a stale promotion from MCP-config drift cannot inflate the active count. The static system prompt still lists all deferred tool names (promotions only affect schema binding, not the prompt), so _count_system_prompt's deferred rendering is intentionally left unchanged. 8 new tests cover classification, catalog-hash scoping (match / drift / compute-failure / malformed), and checkpoint extraction. * fix(context): address review feedback * fix(context): count structured message payloads * fix(context): harden usage accounting * fix(config): bump schema for context usage fields * refactor: narrow context usage to core indicator --------- Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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Huixin615
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88e36d9686
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fix(#3189): prevent write_file streaming timeout on long reports (#3195)
* fix(#3189): prevent write_file streaming timeout on long reports Adds a layered defense against StreamChunkTimeoutError caused by oversized single-shot write_file tool calls: - factory: default stream_chunk_timeout to 240s for OpenAI-compatible clients (overridable via ModelConfig.stream_chunk_timeout in config.yaml) - sandbox/tools: server-side 80 KB length guard on non-append write_file calls (configurable via DEERFLOW_WRITE_FILE_MAX_BYTES env var, 0 disables); rejects oversized payloads with a structured error pointing the model at str_replace or append=True - middleware: classify StreamChunkTimeoutError as transient but cap retries at 1 via per-exception _RETRY_BUDGET_OVERRIDES (same-payload retry on a chunk-gap timeout buffers the same way upstream; full 3-attempt loop would stack 6-12 min of dead air) - middleware: surface an actionable user-facing message for stream-drop exceptions instead of leaking the raw langchain stack - prompts: add a routing-style File Editing Workflow hint to both lead_agent and general_purpose subagent prompts, pointing the model at str_replace for incremental edits (mirrors Claude Code's Edit / Codex's apply_patch) - tests: behavioural coverage for size guard, retry budget override, stream-drop user message, factory default injection Refs #3189 * fix(#3189): drop stream_chunk_timeout for non-OpenAI providers Address CR feedback on PR #3195: - factory: pop `stream_chunk_timeout` from kwargs for any model_use_path other than `langchain_openai:ChatOpenAI` instead of returning early. `ModelConfig.stream_chunk_timeout` is part of the shared schema, so a user-supplied value on a non-OpenAI provider would otherwise be forwarded to its constructor and raise `TypeError: unexpected keyword argument`. - factory: rewrite docstring to describe the actual `exclude_none=True` behaviour (explicit null is excluded and falls back to the default) instead of the misleading "None falling out via exclude_none=True keeps its value". - tests: add regression coverage asserting the kwarg is stripped before reaching a non-OpenAI provider's constructor. Refs: bytedance#3189 * fix(#3189): restrict stream-drop user copy to StreamChunkTimeoutError only Per CR on #3195: narrow _STREAM_DROP_EXCEPTIONS to StreamChunkTimeoutError. Generic httpx RemoteProtocolError / ReadError fall back to the standard 'temporarily unavailable' copy, since they routinely fire on transient network blips where the 'split the output' guidance is misleading. Retry/backoff classification is unchanged — both remain transient/retriable. Tests updated to reflect new copy, plus a symmetric regression test for ReadError. --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> |
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shivam johri
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194bab4691
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feat(config): add when_thinking_disabled support for model configs (#1970)
* feat(config): add when_thinking_disabled support for model configs Allow users to explicitly configure what parameters are sent to the model when thinking is disabled, via a new `when_thinking_disabled` field in model config. This mirrors the existing `when_thinking_enabled` pattern and takes full precedence over the hardcoded disable behavior when set. Backwards compatible — existing configs work unchanged. Closes #1675 * fix(config): address copilot review — gate when_thinking_disabled independently - Switch truthiness check to `is not None` so empty dict overrides work - Restructure disable path so when_thinking_disabled is gated independently of has_thinking_settings, allowing it to work without when_thinking_enabled - Update test to reflect new behavior |
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mxyhi
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e119dc74ae
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feat(codex): support explicit OpenAI Responses API config (#1235)
* feat: support explicit OpenAI Responses API config Co-authored-by: Codex <noreply@openai.com> * Update backend/packages/harness/deerflow/config/model_config.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Codex <noreply@openai.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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DanielWalnut
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76803b826f
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refactor: split backend into harness (deerflow.*) and app (app.*) (#1131)
* refactor: extract shared utils to break harness→app cross-layer imports Move _validate_skill_frontmatter to src/skills/validation.py and CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py. This eliminates the two reverse dependencies from client.py (harness layer) into gateway/routers/ (app layer), preparing for the harness/app package split. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: split backend/src into harness (deerflow.*) and app (app.*) Physically split the monolithic backend/src/ package into two layers: - **Harness** (`packages/harness/deerflow/`): publishable agent framework package with import prefix `deerflow.*`. Contains agents, sandbox, tools, models, MCP, skills, config, and all core infrastructure. - **App** (`app/`): unpublished application code with import prefix `app.*`. Contains gateway (FastAPI REST API) and channels (IM integrations). Key changes: - Move 13 harness modules to packages/harness/deerflow/ via git mv - Move gateway + channels to app/ via git mv - Rename all imports: src.* → deerflow.* (harness) / app.* (app layer) - Set up uv workspace with deerflow-harness as workspace member - Update langgraph.json, config.example.yaml, all scripts, Docker files - Add build-system (hatchling) to harness pyproject.toml - Add PYTHONPATH=. to gateway startup commands for app.* resolution - Update ruff.toml with known-first-party for import sorting - Update all documentation to reflect new directory structure Boundary rule enforced: harness code never imports from app. All 429 tests pass. Lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: add harness→app boundary check test and update docs Add test_harness_boundary.py that scans all Python files in packages/harness/deerflow/ and fails if any `from app.*` or `import app.*` statement is found. This enforces the architectural rule that the harness layer never depends on the app layer. Update CLAUDE.md to document the harness/app split architecture, import conventions, and the boundary enforcement test. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add config versioning with auto-upgrade on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated. This adds a config_version field and auto-upgrade mechanism so breaking changes (like src.* → deerflow.* renames) are applied automatically before services start. - Add config_version: 1 to config.example.yaml - Add startup version check warning in AppConfig.from_file() - Add scripts/config-upgrade.sh with migration registry for value replacements - Add `make config-upgrade` target - Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services - Add config error hints in service failure messages Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix comments * fix: update src.* import in test_sandbox_tools_security to deerflow.* Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: handle empty config and search parent dirs for config.example.yaml Address Copilot review comments on PR #1131: - Guard against yaml.safe_load() returning None for empty config files - Search parent directories for config.example.yaml instead of only looking next to config.yaml, fixing detection in common setups Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: correct skills root path depth and config_version type coercion - loader.py: fix get_skills_root_path() to use 5 parent levels (was 3) after harness split, file lives at packages/harness/deerflow/skills/ so parent×3 resolved to backend/packages/harness/ instead of backend/ - app_config.py: coerce config_version to int() before comparison in _check_config_version() to prevent TypeError when YAML stores value as string (e.g. config_version: "1") - tests: add regression tests for both fixes Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: update test imports from src.* to deerflow.*/app.* after harness refactor Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |