mirror of
https://github.com/bytedance/deer-flow.git
synced 2026-08-10 06:49:00 +00:00
ac18f518c8
* feat(sandbox): add Tenki cloud sandbox provider Adds deerflow.community.tenki, a SandboxProvider backed by Tenki cloud microVMs, alongside the existing e2b_sandbox / boxlite / aio_sandbox backends. Selected via `sandbox.use: deerflow.community.tenki:TenkiSandboxProvider` (resolved by class path, so the change is purely additive). The full Sandbox contract is implemented — execute_command plus read/write/update/download_file and list_dir/glob/grep — with file ops run as busybox-portable shell commands (cat / find / grep / chunked base64), reusing deerflow.sandbox.search, mirroring e2b_sandbox and boxlite. Tenki's SDK is synchronous, so unlike boxlite there is no event-loop bridge. Tenki sandboxes run as an unprivileged user with /mnt root-owned, so the /mnt/user-data virtual prefix is remapped under the writable home dir (like e2b_sandbox); the provider also best-effort sudo-symlinks /mnt/user-data to that home dir so agent shell commands using the literal path still work. Sandboxes are pooled per (user, thread) with warm reclaim, a replica cap, and an idle reaper via the shared WarmPoolLifecycleMixin. Transient transport blips get one bounded retry; terminal session errors evict and recreate. Only the stable Tenki surface is used (create/terminate + exec/shell/fs) — no volumes, snapshots, or template builds — so any stock base image works. The tenki-sandbox SDK is an optional extra (deerflow-harness[tenki]) and is imported lazily, so a default install and every other provider are unaffected. Tested: unit suite runs in CI without tenki-sandbox installed; a live integration test and full-surface e2e were verified against real Tenki sandboxes. * fix(sandbox): remove unsafe auto-retry from Tenki exec Pre-merge review caught that the transient-transport retry sat at the universal _exec layer, so it retried every operation — execute_command and base64 file-write chunks included. gRPC has no exactly-once guarantee: a "socket closed" ack-drop after the server already ran the op means the retry runs it twice, double-firing command side effects and duplicating a write chunk mid-file (silent binary corruption on multi-chunk writes). exec is not idempotent, so it must not be auto-retried. Reverts to the boxlite/e2b behavior: a transient error surfaces to the caller (returned as text by execute_command, raised by the file ops); a terminal session error still evicts the sandbox so the next acquire rebuilds it. Verified live end-to-end across 31 edge cases (empty/binary/unicode/chunk-boundary files, shell-metachar content, error paths, list/glob/grep, warm-pool reclaim, concurrency). * fix(sandbox): address Tenki provider review feedback - Use Tenki's native sandbox.fs API for all file transport (read_text, read_bytes, write_stream, mkdir) instead of cat/chunked-base64 over shell. Uploads stream in 1 MiB frames; append is read-modify-write because the write stream has no append mode (same approach as community/e2b_sandbox). - download_file streams via fs.read_stream and enforces the 100 MB cap on bytes actually received, closing the TOCTOU window between the old wc -c size probe and the read. - list_dir/glob/grep report paths back under /mnt/user-data instead of the sandbox-internal home dir, so results feed straight into the file APIs. - Create with wait=False and await wait_ready() here: create(wait=True) raises with the session handle still inside the SDK, leaking a running microVM this provider could never terminate. - Configure the sandbox lifetime (max_duration, default 4h) and expose sticky; without it Tenki reaps a reused thread's sandbox after ~30 min. - close() terminates before marking the adapter closed and re-raises real failures, so a failed termination stays retryable instead of silently leaking a billed microVM; an already-gone session still counts as closed. - Bump the optional extra to tenki-sandbox>=0.4.0 and commit backend/uv.lock. * fix(sandbox): scope tenki grep() glob filter to its directory prefix Mirrors #4168, which fixed the same defect in the E2B provider. The tenki adapter reduced a directory-scoped pattern like "src/*.js" to its basename before filtering, so the search silently broadened to every matching-extension file in the tree. Post-filter grep's hits through path_matches() against the path relative to the search root, the same way glob() already does, so both agree on what a directory-scoped pattern means. * fix(sandbox): address Tenki provider review — eviction, id width, write lock, grep -H Four fixes from the upstream review: download_file no longer swallows terminal transport errors. The broad `except OSError: raise` re-raised ConnectionError/BrokenPipeError/EOFError (all OSError subclasses that _is_terminal_failure treats as terminal) before _note_failure ran, so a session that died mid-download was never evicted. Only our own EFBIG size-cap now passes through without eviction. Sandbox id widened from 32 to 64 bits (`[:8]` to `[:16]`), matching community/e2b_sandbox. The warm pool is keyed by this id with no full-seed fallback, so a collision could let one user reclaim another's parked sandbox on a multi-tenant gateway. _fs_op now holds the lock across the op, not just the fs lookup, so concurrent calls on the same sandbox serialise over the SDK's shared connection. The eviction callback runs after the lock is released to avoid a lock-order deadlock with the provider. The append read-modify-write is serialised by a dedicated _write_lock so two concurrent appends can't clobber each other. grep passes -H so a search whose path resolves to a single file still prints the filename; without it the file:line:text unpack dropped every match. * fix(sandbox): address Tenki provider review round 2 - validate config `environment` at load time (_validate_extra_env) so a bad key fails fast instead of surfacing as an SDK error mid-command - document the deliberate lock decision in download_file: the instance lock is dropped before streaming so a 100 MB download can't block every other tool; terminal transport errors still evict via _note_failure - tighten the terminal-error comment to note ConnectionError/BrokenPipeError/ EOFError are also treated terminal via isinstance - document TenkiSandboxProvider in backend/AGENTS.md (provider detail, warm-pool destroy hook, community provider list) - add a commented Tenki block to config.example.yaml for parity with AIO/BoxLite - tests: config env validation, grep -F/case-sensitive flags, glob include_dirs, list_dir max_depth, bootstrap-failure warning branch * fix(sandbox): make Tenki bootstrap non-interactive and time-bounded The create-time bootstrap runs under the per-scope acquire lock, so a hang would stall acquire for that scope indefinitely: - use `sudo -n` so a password-requiring sudoers entry fails fast (swallowed by the existing `|| true`) instead of blocking on a tty password prompt - pass a timeout to the bootstrap `remote.exec` so any other stall drops to the existing warning path rather than wedging acquire Best-effort by design; the file APIs still work via the home remap on failure. * test(sandbox): pin Tenki bootstrap timeout to its actual value Assert bootstrap["timeout"] == _BOOTSTRAP_TIMEOUT instead of `is not None`, so a regression to timeout=0 (treated as no timeout by some SDKs) or an unrelated value is caught rather than passing a weaker non-None check. --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2317 lines
108 KiB
YAML
2317 lines
108 KiB
YAML
# Configuration for the DeerFlow application
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#
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# Guidelines:
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# - Copy this file to `config.yaml` and customize it for your environment
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# - The default path of this configuration file is `config.yaml` in the project root.
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# You can set `DEER_FLOW_PROJECT_ROOT` to define that root explicitly, or use
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# `DEER_FLOW_CONFIG_PATH` to point at a specific config file.
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# - Runtime state defaults to `.deer-flow` under the project root. Override it
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# with `DEER_FLOW_HOME` when you need a different writable data directory.
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# - Environment variables are available for all field values. Example: `api_key: $OPENAI_API_KEY`
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# - The `use` path is a string that looks like "package_name.sub_package_name.module_name:class_name/variable_name".
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# ============================================================================
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# Config Version (used to detect outdated config files)
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# ============================================================================
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# Bump this number when the config schema changes.
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# Run `make config-upgrade` to merge new fields into your local config.yaml.
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config_version: 29
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# ============================================================================
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# Logging
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# ============================================================================
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# Log level for deerflow modules (debug/info/warning/error)
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log_level: info
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# Request trace correlation for Gateway logs, HTTP response headers, and
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# Langfuse metadata. Disabled by default to preserve existing HTTP/log output.
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logging:
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enhance:
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enabled: false
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format: text
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# ============================================================================
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# Agent Extensions
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# ============================================================================
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# Optional AgentMiddleware classes loaded into the lead and subagent runtime
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# middleware chains after built-in runtime middlewares, but before the
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# safety/clarification tail. Missing packages, invalid classes, and broken
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# modules fail loudly at agent creation with an actionable import error.
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# The same zero-argument class list applies to both lead and subagent runtimes;
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# lead-only vs subagent-only configuration is not expressible yet. Treat these
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# files as trusted operator config because middleware classes execute code.
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# Uncomment this block to define middlewares in config.yaml. Leaving it commented
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# lets extensions_config.json remain the source of truth for extension packages.
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# extensions:
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# middlewares:
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# - my_company.deerflow_middlewares:DomainGuardMiddleware
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# - my_company.deerflow_middlewares:LatencyStampingMiddleware
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# ============================================================================
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# Tracing / Observability (Monocle)
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# ============================================================================
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# Optional agent tracing via Monocle. Configured through environment variables
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# (MONOCLE_TRACING, MONOCLE_EXPORTERS, OKAHU_API_KEY — like LangSmith/Langfuse),
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# not config.yaml keys, and OFF by default. See README.md → "Monocle Tracing"
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# for setup, what each exporter captures, and where the trace data goes.
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# ============================================================================
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# Token Usage
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# ============================================================================
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# Enable token usage collection and display.
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# When enabled, DeerFlow records input/output/total tokens per model call
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# and shows usage metadata in the workspace UI when providers return it.
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token_usage:
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enabled: true
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# ============================================================================
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# Token Budget — Per-run token limits
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# ============================================================================
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# Prevents runaway API costs by enforcing hard token limits per run.
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# When warn_threshold is crossed, the agent receives an in-context warning.
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# When hard_stop_threshold is crossed, tool_calls are stripped and the agent
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# is forced to produce a final answer immediately.
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token_budget:
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enabled: false # Set to true to activate budget enforcement
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max_tokens: 200000 # Total token limit (input + output) per run
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max_input_tokens: null # Optional separate input-only limit
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max_output_tokens: null # Optional separate output-only limit
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warn_threshold: 0.8 # Warn at 80% of the budget
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hard_stop_threshold: 1.0 # Force stop at 100% of the budget
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# ============================================================================
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# Recursion Limit — Hard ceiling for a client-supplied run recursion_limit
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# ============================================================================
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# A run's recursion_limit caps the number of LangGraph super-steps (each is at
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# least one LLM call). The Gateway never trusts a client-supplied value
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# verbatim: any value above this ceiling is clamped down to it, preventing
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# runaway API cost / DoS. Invalid or non-positive client values fall back to
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# the server default of 100. Raise this only if you legitimately run very
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# deeply nested subagent graphs.
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max_recursion_limit: 1000
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# ============================================================================
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# Models Configuration
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# ============================================================================
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# Configure available LLM models for the agent to use
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#
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# Optional per-model pricing (powers the real-cost display on the workspace
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# console). Add a `pricing` block to any model entry; use ONE currency across
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# all models. Prices are per one million tokens.
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#
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# pricing:
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# currency: CNY # ISO code shown in the console (CNY, USD, ...)
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# input_per_million: 8.0 # price per 1M input tokens (cache miss)
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# output_per_million: 32.0 # price per 1M output tokens
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# input_cache_hit_per_million: 0.8 # price per 1M cache-hit input tokens
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# # (optional; omit → hits billed at miss price)
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models:
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# Example: Volcengine (Doubao) model
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# - name: doubao-seed-1.8
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# display_name: Doubao-Seed-1.8
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# use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
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# model: doubao-seed-1-8-251228
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# api_base: https://ark.cn-beijing.volces.com/api/v3
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# api_key: $VOLCENGINE_API_KEY
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# timeout: 600.0
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# max_retries: 2
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# supports_thinking: true
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# supports_vision: true
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# supports_reasoning_effort: true
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# when_thinking_enabled:
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# extra_body:
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# thinking:
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# type: enabled
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# when_thinking_disabled:
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# extra_body:
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# thinking:
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# type: disabled
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# Example: Volcengine Coding Plan (one key, multi-vendor gateway)
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# The Coding Plan endpoint (/api/coding/v3) lets you access models from
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# Doubao, GLM, DeepSeek, Kimi, and MiniMax with a single API key.
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# Each model may differ in thinking/vision support - configure per-model.
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#
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# - name: glm-5.2-cp
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# display_name: GLM-5.2 (Coding Plan)
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# use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
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# model: glm-5.2
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# api_base: https://ark.cn-beijing.volces.com/api/coding/v3
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# api_key: $VOLCENGINE_API_KEY
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# timeout: 600.0
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# max_retries: 2
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# supports_thinking: true
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# supports_vision: false
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# supports_reasoning_effort: true
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# when_thinking_enabled:
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# extra_body:
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# thinking:
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# type: enabled
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# when_thinking_disabled:
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# extra_body:
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# thinking:
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# type: disabled
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#
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# - name: deepseek-v4-pro-cp
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# display_name: DeepSeek-V4-Pro (Coding Plan)
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# use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
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# model: deepseek-v4-pro
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# api_base: https://ark.cn-beijing.volces.com/api/coding/v3
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# api_key: $VOLCENGINE_API_KEY
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# timeout: 600.0
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# max_retries: 2
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# supports_thinking: true
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# supports_vision: false
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# supports_reasoning_effort: true
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# when_thinking_enabled:
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# extra_body:
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# thinking:
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# type: enabled
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# when_thinking_disabled:
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# extra_body:
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# thinking:
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# type: disabled
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# Example: OpenAI model
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# - name: gpt-4
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# display_name: GPT-4
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# use: langchain_openai:ChatOpenAI
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# model: gpt-4
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# api_key: $OPENAI_API_KEY # Use environment variable
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# request_timeout: 600.0
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# max_retries: 2
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# max_tokens: 4096
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# temperature: 0.7
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# supports_vision: true # Enable vision support for view_image tool
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# Example: OpenAI Responses API model
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# - name: gpt-5-responses
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# display_name: GPT-5 (Responses API)
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# use: langchain_openai:ChatOpenAI
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# model: gpt-5
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# api_key: $OPENAI_API_KEY
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# request_timeout: 600.0
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# max_retries: 2
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# use_responses_api: true
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# output_version: responses/v1
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# supports_vision: true
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# Example: Ollama (native provider — preserves thinking/reasoning content)
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#
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# IMPORTANT: Use langchain_ollama:ChatOllama instead of langchain_openai:ChatOpenAI
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# for Ollama models. The OpenAI-compatible endpoint (/v1/chat/completions) does NOT
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# return reasoning_content as a separate field — thinking content is either flattened
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# into <think> tags or dropped entirely (ollama/ollama#15293). The native Ollama API
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# (/api/chat) correctly separates thinking from response content.
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#
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# Install: cd backend && uv pip install 'deerflow-harness[ollama]'
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#
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# - name: qwen3-local
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# display_name: Qwen3 32B (Ollama)
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# use: langchain_ollama:ChatOllama
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# model: qwen3:32b
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# base_url: http://localhost:11434 # No /v1 suffix — uses native /api/chat
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# num_predict: 8192
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# temperature: 0.7
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# reasoning: true # Passes think:true to Ollama native API
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# supports_thinking: true
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# supports_vision: false
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#
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# - name: gemma4-local
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# display_name: Gemma 4 27B (Ollama)
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# use: langchain_ollama:ChatOllama
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# model: gemma4:27b
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# base_url: http://localhost:11434
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# num_predict: 8192
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# temperature: 0.7
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# reasoning: true
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# supports_thinking: true
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# supports_vision: true
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#
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# For Docker deployments, use host.docker.internal instead of localhost:
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# base_url: http://host.docker.internal:11434
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# Example: Anthropic Claude model (with extended thinking)
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# supports_thinking: true is required — without it, DeerFlow silently falls
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# back to non-thinking mode even when the UI thinking toggle is on.
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# budget_tokens is required by the Anthropic API when thinking.type=enabled
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# (no server default; min 1024; must be less than max_tokens).
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# - name: claude-sonnet-4
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# display_name: Claude Sonnet 4
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# use: langchain_anthropic:ChatAnthropic
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# model: claude-sonnet-4-20250514
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# api_key: $ANTHROPIC_API_KEY
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# default_request_timeout: 600.0
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# max_retries: 2
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# max_tokens: 16000
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# supports_vision: true
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# supports_thinking: true
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# when_thinking_enabled:
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# thinking:
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# type: enabled
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# budget_tokens: 4096 # required; min 1024; must be < max_tokens
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# when_thinking_disabled:
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# thinking:
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# type: disabled
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# Example: Google Gemini model (native SDK, no thinking support)
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# - name: gemini-2.5-pro
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# display_name: Gemini 2.5 Pro
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# use: langchain_google_genai:ChatGoogleGenerativeAI
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# model: gemini-2.5-pro
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# gemini_api_key: $GEMINI_API_KEY
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# timeout: 600.0
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# max_retries: 2
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# max_tokens: 8192
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# supports_vision: true
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# Example: Gemini model via OpenAI-compatible gateway (with thinking support)
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# Use PatchedChatOpenAI so that tool-call thought_signature values on tool_calls
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# are preserved across multi-turn tool-call conversations — required by the
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# Gemini API when thinking is enabled. See:
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# https://docs.cloud.google.com/vertex-ai/generative-ai/docs/thought-signatures
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# - name: gemini-2.5-pro-thinking
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# display_name: Gemini 2.5 Pro (Thinking)
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# use: deerflow.models.patched_openai:PatchedChatOpenAI
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# model: google/gemini-2.5-pro-preview # model name as expected by your gateway
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# api_key: $GEMINI_API_KEY
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# base_url: https://<your-openai-compat-gateway>/v1
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# request_timeout: 600.0
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# max_retries: 2
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# max_tokens: 16384
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# supports_thinking: true
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# supports_vision: true
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# when_thinking_enabled:
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# extra_body:
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# thinking:
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# type: enabled
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# when_thinking_disabled:
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# extra_body:
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# thinking:
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# type: disabled
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# Example: Xiaomi MiMo model (with thinking support)
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# MiMo thinking mode returns reasoning_content and requires that field to be
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# replayed on historical assistant messages in multi-turn agent/tool-call
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# conversations. Use PatchedChatMiMo instead of plain ChatOpenAI.
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# Use https://api.xiaomimimo.com/v1 with pay-as-you-go `sk-...` keys.
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# Use your Token Plan regional URL (for example
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# https://token-plan-cn.xiaomimimo.com/v1) with Token Plan `tp-...` keys.
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# PatchedChatMiMo is model-id agnostic; use it for every MiMo thinking model
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# entry you configure (for example mimo-v2.5-pro, mimo-v2.5, mimo-v2-pro,
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# mimo-v2-omni, or mimo-v2-flash), including models referenced by subagent
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# model overrides.
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# See: https://platform.xiaomimimo.com/docs/en-US/usage-guide/passing-back-reasoning_content
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# - name: mimo-v2.5-pro
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# display_name: MiMo V2.5 Pro
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# use: deerflow.models.patched_mimo:PatchedChatMiMo
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# model: mimo-v2.5-pro
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# api_key: $MIMO_API_KEY
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# base_url: https://api.xiaomimimo.com/v1
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# request_timeout: 600.0
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# max_retries: 2
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# max_tokens: 8192
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# supports_thinking: true
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# supports_vision: false
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# when_thinking_enabled:
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# extra_body:
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# thinking:
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# type: enabled
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# when_thinking_disabled:
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# extra_body:
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# thinking:
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# type: disabled
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# Example: DeepSeek V4 model (with thinking support)
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# - name: deepseek-v4
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# display_name: DeepSeek V4 (Thinking)
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# use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
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# model: deepseek-v4-pro
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# api_key: $DEEPSEEK_API_KEY
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# timeout: 600.0
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# max_retries: 2
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# max_tokens: 8192
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# supports_thinking: true
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# supports_vision: false # DeepSeek V4 does not support vision
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# when_thinking_enabled:
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# extra_body:
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# thinking:
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# type: enabled
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# when_thinking_disabled:
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# extra_body:
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# thinking:
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# type: disabled
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# Example: Kimi K2.5 model
|
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# - name: kimi-k2.5
|
|
# display_name: Kimi K2.5
|
|
# use: deerflow.models.patched_deepseek:PatchedChatDeepSeek
|
|
# model: kimi-k2.5
|
|
# api_base: https://api.moonshot.cn/v1
|
|
# api_key: $MOONSHOT_API_KEY
|
|
# timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 32768
|
|
# supports_thinking: true
|
|
# supports_vision: true # Check your specific model's capabilities
|
|
# when_thinking_enabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: enabled
|
|
# when_thinking_disabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: disabled
|
|
|
|
# Example: Novita AI (OpenAI-compatible)
|
|
# Novita provides an OpenAI-compatible API with competitive pricing
|
|
# See: https://novita.ai
|
|
# - name: novita-deepseek-v3.2
|
|
# display_name: Novita DeepSeek V3.2
|
|
# use: langchain_openai:ChatOpenAI
|
|
# model: deepseek/deepseek-v3.2
|
|
# api_key: $NOVITA_API_KEY
|
|
# base_url: https://api.novita.ai/openai
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# temperature: 0.7
|
|
# supports_thinking: true
|
|
# supports_vision: true
|
|
# when_thinking_enabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: enabled
|
|
# when_thinking_disabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: disabled
|
|
|
|
# Example: StepFun (阶跃星辰) reasoning models
|
|
# StepFun provides OpenAI-compatible API with reasoning models.
|
|
# With reasoning_format: deepseek-style, the API returns reasoning_content
|
|
# (same field as DeepSeek), which must be replayed on historical assistant
|
|
# messages in multi-turn tool-call conversations.
|
|
# Use PatchedChatStepFun instead of plain ChatOpenAI.
|
|
# Docs: https://platform.stepfun.com/docs/api-reference/chat-completions
|
|
# - name: step-3.7-flash
|
|
# display_name: Step 3.7 Flash
|
|
# use: deerflow.models.patched_stepfun:PatchedChatStepFun
|
|
# model: step-3.7-flash
|
|
# api_key: $STEPFUN_API_KEY
|
|
# base_url: https://api.stepfun.com/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# supports_thinking: true
|
|
# supports_reasoning_effort: true
|
|
# supports_vision: true
|
|
# when_thinking_enabled:
|
|
# extra_body:
|
|
# reasoning_format: deepseek-style
|
|
# when_thinking_disabled:
|
|
# extra_body:
|
|
# reasoning_format: deepseek-style
|
|
|
|
# Example: MiniMax (OpenAI-compatible) - International Edition
|
|
# MiniMax provides high-performance models with 512K context window and 128K max output
|
|
# Docs: https://platform.minimax.io/docs/api-reference/text-openai-api
|
|
# - name: minimax-m3
|
|
# display_name: MiniMax M3
|
|
# use: deerflow.models.patched_minimax:PatchedChatMiniMax
|
|
# model: MiniMax-M3
|
|
# api_key: $MINIMAX_API_KEY
|
|
# base_url: https://api.minimax.io/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
|
|
# supports_vision: true
|
|
# supports_thinking: true
|
|
# # PatchedChatMiniMax is the MiniMax adapter: it enables reasoning_split and
|
|
# # maps MiniMax's structured reasoning into reasoning_content (the field
|
|
# # DeerFlow understands), and it strips the per-message `name` field that
|
|
# # DeerFlow middlewares attach — MiniMax rejects requests whose user-message
|
|
# # names differ with "user name must be consistent (2013)". Declare the
|
|
# # thinking toggle so non-thinking paths (flash mode, follow-up suggestions,
|
|
# # title/memory generation) truly disable reasoning instead of spending
|
|
# # tokens on it.
|
|
# when_thinking_enabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: adaptive
|
|
# when_thinking_disabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: disabled
|
|
|
|
# NOTE: M2.x models always think — passing thinking:{type:disabled} has no
|
|
# effect (per MiniMax docs), so the toggle above is omitted for M2.7. The
|
|
# follow-up-suggestions endpoint strips inline <think> defensively regardless.
|
|
# Still use the PatchedChatMiniMax adapter: it strips the per-message `name`
|
|
# field DeerFlow middlewares attach, which MiniMax otherwise rejects with
|
|
# "user name must be consistent (2013)".
|
|
# - name: minimax-m2.7
|
|
# display_name: MiniMax M2.7
|
|
# use: deerflow.models.patched_minimax:PatchedChatMiniMax
|
|
# model: MiniMax-M2.7
|
|
# api_key: $MINIMAX_API_KEY
|
|
# base_url: https://api.minimax.io/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
|
|
# supports_vision: false # M2.7 is text-only; M3 supports vision
|
|
# supports_thinking: true
|
|
|
|
# - name: minimax-m2.7-highspeed
|
|
# display_name: MiniMax M2.7 Highspeed
|
|
# use: deerflow.models.patched_minimax:PatchedChatMiniMax
|
|
# model: MiniMax-M2.7-highspeed
|
|
# api_key: $MINIMAX_API_KEY
|
|
# base_url: https://api.minimax.io/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
|
|
# supports_vision: false # M2.7 is text-only; M3 supports vision
|
|
# supports_thinking: true
|
|
|
|
# Example: MiniMax (OpenAI-compatible) - CN 中国区用户
|
|
# MiniMax provides high-performance models with 512K context window and 128K max output
|
|
# Docs: https://platform.minimaxi.com/docs/api-reference/text-openai-api
|
|
# - name: minimax-m3
|
|
# display_name: MiniMax M3
|
|
# use: deerflow.models.patched_minimax:PatchedChatMiniMax
|
|
# model: MiniMax-M3
|
|
# api_key: $MINIMAX_API_KEY
|
|
# base_url: https://api.minimaxi.com/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
|
|
# supports_vision: true
|
|
# supports_thinking: true
|
|
# # PatchedChatMiniMax is the MiniMax adapter: it enables reasoning_split and
|
|
# # maps MiniMax's structured reasoning into reasoning_content (the field
|
|
# # DeerFlow understands), and it strips the per-message `name` field that
|
|
# # DeerFlow middlewares attach — MiniMax rejects requests whose user-message
|
|
# # names differ with "user name must be consistent (2013)". Declare the
|
|
# # thinking toggle so non-thinking paths (flash mode, follow-up suggestions,
|
|
# # title/memory generation) truly disable reasoning instead of spending
|
|
# # tokens on it.
|
|
# when_thinking_enabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: adaptive
|
|
# when_thinking_disabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: disabled
|
|
|
|
# NOTE: M2.x models always think — passing thinking:{type:disabled} has no
|
|
# effect (per MiniMax docs), so the toggle above is omitted for M2.7. The
|
|
# follow-up-suggestions endpoint strips inline <think> defensively regardless.
|
|
# Still use the PatchedChatMiniMax adapter: it strips the per-message `name`
|
|
# field DeerFlow middlewares attach, which MiniMax otherwise rejects with
|
|
# "user name must be consistent (2013)".
|
|
# - name: minimax-m2.7
|
|
# display_name: MiniMax M2.7
|
|
# use: deerflow.models.patched_minimax:PatchedChatMiniMax
|
|
# model: MiniMax-M2.7
|
|
# api_key: $MINIMAX_API_KEY
|
|
# base_url: https://api.minimaxi.com/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
|
|
# supports_vision: false # M2.7 is text-only; M3 supports vision
|
|
# supports_thinking: true
|
|
|
|
# - name: minimax-m2.7-highspeed
|
|
# display_name: MiniMax M2.7 Highspeed
|
|
# use: deerflow.models.patched_minimax:PatchedChatMiniMax
|
|
# model: MiniMax-M2.7-highspeed
|
|
# api_key: $MINIMAX_API_KEY
|
|
# base_url: https://api.minimaxi.com/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 4096
|
|
# temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
|
|
# supports_vision: false # M2.7 is text-only; M3 supports vision
|
|
# supports_thinking: true
|
|
|
|
# Example: OpenRouter (OpenAI-compatible)
|
|
# OpenRouter models use the same ChatOpenAI + base_url pattern as other OpenAI-compatible gateways.
|
|
# - name: openrouter-gemini-2.5-flash
|
|
# display_name: Gemini 2.5 Flash (OpenRouter)
|
|
# use: langchain_openai:ChatOpenAI
|
|
# model: google/gemini-2.5-flash-preview
|
|
# api_key: $OPENAI_API_KEY
|
|
# base_url: https://openrouter.ai/api/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 8192
|
|
# temperature: 0.7
|
|
|
|
# Example: Atlas Cloud (OpenAI-compatible)
|
|
# Atlas Cloud exposes a single OpenAI-compatible endpoint in front of many open
|
|
# models (DeepSeek, Qwen, Kimi, GLM, MiniMax, Llama, ...), so it uses the same
|
|
# ChatOpenAI + base_url pattern as other OpenAI-compatible gateways.
|
|
# Browse model ids at https://api.atlascloud.ai/v1/models — see https://atlascloud.ai
|
|
# - name: atlascloud-deepseek-v3.2
|
|
# display_name: DeepSeek V3.2 (Atlas Cloud)
|
|
# use: langchain_openai:ChatOpenAI
|
|
# model: deepseek-ai/DeepSeek-V3.2-Exp
|
|
# api_key: $ATLASCLOUD_API_KEY
|
|
# base_url: https://api.atlascloud.ai/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 8192
|
|
# temperature: 0.7
|
|
# supports_vision: false
|
|
#
|
|
# For reasoning models on Atlas Cloud (e.g. a Qwen3 *-thinking id), use the
|
|
# patched OpenAI-compatible adapter so reasoning_content is replayed across
|
|
# multi-turn tool-call conversations:
|
|
# - name: atlascloud-qwen3-thinking
|
|
# display_name: Qwen3 235B Thinking (Atlas Cloud)
|
|
# use: deerflow.models.patched_openai:PatchedChatOpenAI
|
|
# model: qwen/qwen3-235b-a22b-thinking-2507
|
|
# api_key: $ATLASCLOUD_API_KEY
|
|
# base_url: https://api.atlascloud.ai/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 8192
|
|
# supports_thinking: true
|
|
# supports_vision: false
|
|
# when_thinking_enabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: enabled
|
|
# when_thinking_disabled:
|
|
# extra_body:
|
|
# thinking:
|
|
# type: disabled
|
|
|
|
# Example: vLLM 0.19.0 (OpenAI-compatible, with reasoning toggle)
|
|
# DeerFlow's vLLM provider preserves vLLM reasoning across tool-call turns and
|
|
# toggles Qwen-style reasoning by writing
|
|
# extra_body.chat_template_kwargs.enable_thinking=true/false.
|
|
# Some reasoning models also require the server to be started with
|
|
# `vllm serve ... --reasoning-parser <parser>`.
|
|
# - name: qwen3-32b-vllm
|
|
# display_name: Qwen3 32B (vLLM)
|
|
# use: deerflow.models.vllm_provider:VllmChatModel
|
|
# model: Qwen/Qwen3-32B
|
|
# api_key: $VLLM_API_KEY
|
|
# base_url: http://localhost:8000/v1
|
|
# request_timeout: 600.0
|
|
# max_retries: 2
|
|
# max_tokens: 8192
|
|
# supports_thinking: true
|
|
# supports_vision: false
|
|
# when_thinking_enabled:
|
|
# extra_body:
|
|
# chat_template_kwargs:
|
|
# enable_thinking: true
|
|
|
|
|
|
# Example: Qwen3-Coder deployed on MindIE Engine
|
|
# - name: Qwen3_Coder_480B_MindIE
|
|
# display_name: Qwen3-Coder-480B (MindIE)
|
|
# use: deerflow.models.mindie_provider:MindIEChatModel
|
|
# model: Qwen3-Coder-480B-A35B-Instruct-Client
|
|
# base_url: http://localhost:8989/v1
|
|
# api_key: $OPENAI_API_KEY
|
|
# temperature: 0
|
|
# max_retries: 1
|
|
# supports_thinking: false
|
|
# supports_vision: false
|
|
# supports_reasoning_effort: false
|
|
# # --- Advanced Network Settings ---
|
|
# # Due to MindIE's streaming limitations with tool calling, the provider
|
|
# # uses mock-streaming (awaiting full generation). Extended timeouts are required.
|
|
# read_timeout: 900.0 # 15 minutes to prevent drops during long document generation
|
|
# connect_timeout: 30.0
|
|
# write_timeout: 60.0
|
|
# pool_timeout: 30.0
|
|
|
|
# ============================================================================
|
|
# Tool Groups Configuration
|
|
# ============================================================================
|
|
# Define groups of tools for organization and access control
|
|
|
|
tool_groups:
|
|
- name: web
|
|
- name: file:read
|
|
- name: file:write
|
|
- name: bash
|
|
- name: browser
|
|
|
|
# ============================================================================
|
|
# Tools Configuration
|
|
# ============================================================================
|
|
# Configure available tools for the agent to use
|
|
|
|
tools:
|
|
# Web search tool (uses DuckDuckGo, no API key required)
|
|
- name: web_search
|
|
group: web
|
|
use: deerflow.community.ddg_search.tools:web_search_tool
|
|
max_results: 5
|
|
# backend: auto # DDGS backend(s): auto, duckduckgo, brave, wikipedia, etc.
|
|
# region: wt-wt # wt-wt is normalized for Wikipedia when backend includes auto/all/wikipedia.
|
|
# safesearch: moderate # on, moderate, off
|
|
|
|
# Web search tool (uses SearXNG, self-hosted, no API key required)
|
|
# SearXNG is a free internet metasearch engine which aggregates results from
|
|
# various search services. Deploy your own instance: https://github.com/searxng/searxng
|
|
# For Docker deployments, use the Docker service name instead of localhost.
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.searxng.tools:web_search_tool
|
|
# base_url: http://localhost:8088 # SearXNG instance URL (default: :8088; Docker: http://searxng:8080)
|
|
# max_results: 5 # Maximum number of search results
|
|
|
|
# Web search tool (uses Serper - Google Search API, requires SERPER_API_KEY)
|
|
# Serper provides real-time Google Search results. Sign up at https://serper.dev
|
|
# Note: set SERPER_API_KEY in your environment before starting the app.
|
|
# Avoid putting literal API keys in config.yaml; use the $VAR form instead.
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.serper.tools:web_search_tool
|
|
# max_results: 5 # capped at 10 by the Serper provider
|
|
# # api_key: $SERPER_API_KEY # Optional explicit env-var reference
|
|
|
|
# Web search tool (uses Brave Search API, requires BRAVE_SEARCH_API_KEY)
|
|
# Brave Search returns results from an independent index. Sign up at
|
|
# https://brave.com/search/api/ to get a key. Unlike the DuckDuckGo
|
|
# `backend: brave` option above, this calls the official Brave API directly.
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.brave.tools:web_search_tool
|
|
# max_results: 5 # Capped at 20 by the Brave Search API
|
|
# # api_key: $BRAVE_SEARCH_API_KEY # Optional if the env var is set
|
|
|
|
# Web search tool (requires Tavily API key)
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.tavily.tools:web_search_tool
|
|
# max_results: 5
|
|
# # api_key: $TAVILY_API_KEY # Set if needed
|
|
|
|
# Web search tool (uses InfoQuest, requires InfoQuest API key)
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.infoquest.tools:web_search_tool
|
|
# # Used to limit the scope of search results, only returns content within the specified time range. Set to -1 to disable time filtering
|
|
# search_time_range: 10
|
|
|
|
# Web search tool (uses Exa, requires EXA_API_KEY)
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.exa.tools:web_search_tool
|
|
# max_results: 5
|
|
# search_type: auto # Options: auto, neural, keyword
|
|
# contents_max_characters: 1000
|
|
# # api_key: $EXA_API_KEY
|
|
|
|
# Web search tool (uses Firecrawl, requires FIRECRAWL_API_KEY)
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.firecrawl.tools:web_search_tool
|
|
# max_results: 5
|
|
# # api_key: $FIRECRAWL_API_KEY
|
|
|
|
# Web search tool (uses GroundRoute, requires GROUNDROUTE_API_KEY)
|
|
# GroundRoute is a meta search layer: one API in front of six engines (Serper,
|
|
# Brave, Exa, Tavily, Firecrawl, Perplexity). It routes each query to the cheapest
|
|
# engine that clears a quality bar and fails over if one is down. Pricing is
|
|
# gain-share (you keep about half of any cache savings). Get a key at
|
|
# https://groundroute.ai/keys
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.groundroute.tools:web_search_tool
|
|
# max_results: 5 # Clamped to 1-50 by GroundRoute
|
|
# # api_key: $GROUNDROUTE_API_KEY # Optional if the env var is set
|
|
|
|
# Web search tool (uses fastCRW - Firecrawl-compatible web scraper, single binary,
|
|
# self-host or cloud. Cloud requires CRW_API_KEY; self-host may need no key.)
|
|
# - name: web_search
|
|
# group: web
|
|
# use: deerflow.community.fastcrw.tools:web_search_tool
|
|
# max_results: 5
|
|
# # api_key: $CRW_API_KEY
|
|
# # base_url: https://fastcrw.com/api # default cloud; set to e.g. http://localhost:3000 for self-host
|
|
|
|
# Web fetch tool (uses Browserless - headless Chrome, self-hosted or cloud)
|
|
# Browserless renders pages with a real headless Chrome, ideal for JavaScript-heavy
|
|
# sites and SPAs. Deploy your own: https://github.com/browserless/browserless
|
|
# For Docker deployments, use the Docker service name instead of localhost.
|
|
# NOTE: Only one web_fetch provider can be active at a time.
|
|
# Comment out the Jina AI web_fetch entry below before enabling this one.
|
|
# - name: web_fetch
|
|
# group: web
|
|
# use: deerflow.community.browserless.tools:web_fetch_tool
|
|
# base_url: http://localhost:3032 # Browserless instance URL (default: :3032; Docker: http://browserless:3000)
|
|
# # token: $BROWSERLESS_TOKEN # API token (required for Browserless Cloud; optional for self-hosted)
|
|
# timeout_s: 30 # Request timeout in seconds
|
|
# # allow_private_addresses: false # SSRF guard: keep false in production. Set true ONLY for intentional internal targets.
|
|
# # wait_for_event: "networkidle" # Wait for a page event before returning (e.g. "load", "networkidle")
|
|
# # wait_for_timeout_ms: 2000 # Extra wait after page load in milliseconds
|
|
# # wait_for_selector: "article" # CSS selector to wait for before returning
|
|
|
|
# Web fetch tool (uses Crawl4AI - self-hosted headless Chromium, no API key)
|
|
# Crawl4AI returns server-cleaned "fit" markdown directly (no readability step needed),
|
|
# ideal for JavaScript-heavy sites. Self-host (JWT auth is off by default, no key):
|
|
# docker run -d -p 11235:11235 --shm-size=1g unclecode/crawl4ai:0.8.6
|
|
# For Docker deployments, use the Docker service name instead of localhost.
|
|
# NOTE: Only one web_fetch provider can be active at a time.
|
|
# Comment out the Jina AI web_fetch entry below before enabling this one.
|
|
# - name: web_fetch
|
|
# group: web
|
|
# use: deerflow.community.crawl4ai.tools:web_fetch_tool
|
|
# base_url: http://localhost:11235 # Crawl4AI server URL (Docker: http://crawl4ai:11235)
|
|
# timeout: 30 # Request timeout in seconds
|
|
# # allow_private_addresses: false # SSRF guard: keep false in production. Set true ONLY for intentional internal targets.
|
|
# # filter: fit # Markdown filter: fit (default) | raw | bm25 | llm
|
|
# # token: $CRAWL4AI_TOKEN # Bearer token (only if the server has JWT auth enabled)
|
|
|
|
# Web capture tool (uses Browserless /screenshot to render a page as an artifact)
|
|
# Browserless captures JavaScript-heavy pages with a real headless Chrome and
|
|
# writes the screenshot into the current thread's outputs. It can run against
|
|
# a self-hosted Browserless instance without a token, or Browserless Cloud with
|
|
# BROWSERLESS_TOKEN. For Docker deployments, use the Docker service name instead
|
|
# of localhost.
|
|
# - name: web_capture
|
|
# group: web
|
|
# use: deerflow.community.browserless.tools:web_capture_tool
|
|
# base_url: http://localhost:3032 # Browserless instance URL (Docker: http://browserless:3000)
|
|
# # token: $BROWSERLESS_TOKEN # Required for Browserless Cloud; optional for self-hosted
|
|
# timeout_s: 30 # Request timeout in seconds
|
|
# output_format: png # png, jpeg, or webp
|
|
# full_page: true # Capture entire page instead of viewport only
|
|
# viewport_width: 1280
|
|
# viewport_height: 720
|
|
# # wait_for_selector: "main" # CSS selector to wait for before capturing
|
|
# # wait_for_selector_timeout_ms: 5000
|
|
# # wait_for_timeout_ms: 1000 # Extra wait after navigation in milliseconds
|
|
# # best_attempt: true # Continue with current page state if waits time out
|
|
# # allow_private_addresses: false # SSRF guard: keep false in production. Set true ONLY to
|
|
# # # capture internal/private targets (loopback, RFC1918, etc.)
|
|
|
|
# Agentic browser control (stateful navigate → observe → click/type loop).
|
|
# Unlike web_fetch/web_capture (read-only, stateless), these tools keep a live
|
|
# per-thread Playwright browser so the agent can interact with JavaScript-heavy
|
|
# pages, fill forms, and follow multi-step flows. Elements are addressed by the
|
|
# numeric [ref] index returned in each page snapshot.
|
|
#
|
|
# Requires the optional dependency, installed once per environment:
|
|
# cd backend && uv sync --extra browser && uv run playwright install chromium
|
|
# make dev / Docker startup auto-detect an active browser_navigate entry and
|
|
# preserve the browser extra during dependency sync.
|
|
#
|
|
# Uncomment the whole block to enable. Launch and URL-policy settings are read
|
|
# canonically from browser_navigate and shared by every browser tool + Live.
|
|
# - name: browser_navigate
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_navigate_tool
|
|
# headless: true # Set false only for local, trusted debugging
|
|
# timeout_ms: 30000 # Per-action navigation/interaction timeout
|
|
# viewport_width: 1280
|
|
# viewport_height: 720
|
|
# # allow_private_addresses: false # SSRF guard: keep false in production
|
|
# # cdp_url: http://127.0.0.1:9222 # Attach to YOUR running Chrome (Codex-style)
|
|
# # allow_unguarded_cdp: false # REQUIRED true with cdp_url: attaching to an
|
|
# # # existing Chrome prevents DeerFlow from
|
|
# # # enforcing its subresource/redirect SSRF guard.
|
|
# # # instead of launching a private headless one.
|
|
# # # Start Chrome with --remote-debugging-port=9222
|
|
# # # so you watch the agent drive your real browser
|
|
# # # with your real login sessions. Local/trusted only;
|
|
# # # never enable for an untrusted CDP endpoint.
|
|
# # # Chrome must be version-matched to the bundled
|
|
# # # Playwright; a much newer Chrome can reject the
|
|
# # # CDP handshake. If so, use headless: false to launch
|
|
# # # Playwright's own visible browser instead.
|
|
# # Multi-worker note: browser sessions live in one Gateway worker's memory.
|
|
# # Keep GATEWAY_WORKERS=1 while this tool group is enabled.
|
|
# - name: browser_snapshot
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_snapshot_tool
|
|
# - name: browser_click
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_click_tool
|
|
# - name: browser_type
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_type_tool
|
|
# - name: browser_get_text
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_get_text_tool
|
|
# max_chars: 8000 # Truncation cap for browser_get_text output
|
|
# - name: browser_back
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_back_tool
|
|
# - name: browser_screenshot
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_screenshot_tool
|
|
# - name: browser_close
|
|
# group: browser
|
|
# use: deerflow.community.browser_automation.tools:browser_close_tool
|
|
|
|
# Web fetch tool (uses Exa)
|
|
# NOTE: Only one web_fetch provider can be active at a time.
|
|
# Comment out the Jina AI web_fetch entry below before enabling this one.
|
|
# - name: web_fetch
|
|
# group: web
|
|
# use: deerflow.community.exa.tools:web_fetch_tool
|
|
# # api_key: $EXA_API_KEY
|
|
|
|
# Web fetch tool (uses Jina AI reader)
|
|
- name: web_fetch
|
|
group: web
|
|
use: deerflow.community.jina_ai.tools:web_fetch_tool
|
|
timeout: 10
|
|
# Optional proxy for restricted networks / Docker / WSL.
|
|
# Use host.docker.internal instead of 127.0.0.1 when the proxy runs on the host.
|
|
# proxy: $HTTPS_PROXY
|
|
# trust_env: true
|
|
|
|
# Web fetch tool (uses InfoQuest)
|
|
# - name: web_fetch
|
|
# group: web
|
|
# use: deerflow.community.infoquest.tools:web_fetch_tool
|
|
# # Overall timeout for the entire crawling process (in seconds). Set to positive value to enable, -1 to disable
|
|
# timeout: 10
|
|
# # Waiting time after page loading (in seconds). Set to positive value to enable, -1 to disable
|
|
# fetch_time: 10
|
|
# # Timeout for navigating to the page (in seconds). Set to positive value to enable, -1 to disable
|
|
# navigation_timeout: 30
|
|
|
|
# Web fetch tool (uses Firecrawl, requires FIRECRAWL_API_KEY)
|
|
# - name: web_fetch
|
|
# group: web
|
|
# use: deerflow.community.firecrawl.tools:web_fetch_tool
|
|
# # api_key: $FIRECRAWL_API_KEY
|
|
|
|
# Web fetch tool (uses GroundRoute, requires GROUNDROUTE_API_KEY)
|
|
# Fetches a page's extracted text via GroundRoute mode=page.
|
|
# NOTE: Only one web_fetch provider can be active at a time.
|
|
# Comment out the Jina AI web_fetch entry above before enabling this one.
|
|
# - name: web_fetch
|
|
# group: web
|
|
# use: deerflow.community.groundroute.tools:web_fetch_tool
|
|
# # api_key: $GROUNDROUTE_API_KEY
|
|
|
|
# Web fetch tool (uses fastCRW - Firecrawl-compatible web scraper, single binary,
|
|
# self-host or cloud. Cloud requires CRW_API_KEY; self-host may need no key.)
|
|
# NOTE: Only one web_fetch provider can be active at a time.
|
|
# Comment out the Jina AI web_fetch entry above before enabling this one.
|
|
# - name: web_fetch
|
|
# group: web
|
|
# use: deerflow.community.fastcrw.tools:web_fetch_tool
|
|
# # api_key: $CRW_API_KEY
|
|
# # base_url: https://fastcrw.com/api # default cloud; set to e.g. http://localhost:3000 for self-host
|
|
# # allow_private_addresses: false # SSRF guard: keep false in production. Set true ONLY for intentional internal targets.
|
|
|
|
# Image search tool (uses DuckDuckGo)
|
|
# Use this to find reference images before image generation
|
|
- name: image_search
|
|
group: web
|
|
use: deerflow.community.image_search.tools:image_search_tool
|
|
max_results: 5
|
|
|
|
# Image search tool (uses InfoQuest)
|
|
# - name: image_search
|
|
# group: web
|
|
# use: deerflow.community.infoquest.tools:image_search_tool
|
|
# # Used to limit the scope of image search results, only returns content within the specified time range. Set to -1 to disable time filtering
|
|
# image_search_time_range: 10
|
|
# # Image size filter. Options: "l" (large), "m" (medium), "i" (icon).
|
|
# image_size: "i"
|
|
|
|
# Image search tool (uses Serper - Google Images API, requires SERPER_API_KEY)
|
|
# Serper provides real-time Google Images results. Sign up at https://serper.dev
|
|
# Note: set SERPER_API_KEY in your environment before starting the app.
|
|
# Avoid putting literal API keys in config.yaml; use the $VAR form instead.
|
|
# - name: image_search
|
|
# group: web
|
|
# use: deerflow.community.serper.tools:image_search_tool
|
|
# max_results: 5 # capped at 10 by the Serper provider
|
|
# # api_key: $SERPER_API_KEY # Optional explicit env-var reference
|
|
|
|
# Image search tool (uses Brave Image Search API, requires BRAVE_SEARCH_API_KEY)
|
|
# Brave provides independent image results and works alongside the Brave web search tool.
|
|
# Note: set BRAVE_SEARCH_API_KEY in your environment before starting the app.
|
|
# Avoid putting literal API keys in config.yaml; use the $VAR form instead.
|
|
# - name: image_search
|
|
# group: web
|
|
# use: deerflow.community.brave.tools:image_search_tool
|
|
# max_results: 5 # capped at 200 by Brave Image Search
|
|
# # country: US
|
|
# # search_lang: en
|
|
# # safesearch: strict
|
|
# # spellcheck: true
|
|
# # api_key: $BRAVE_SEARCH_API_KEY # Optional explicit env-var reference
|
|
|
|
# File operations tools
|
|
- name: ls
|
|
group: file:read
|
|
use: deerflow.sandbox.tools:ls_tool
|
|
|
|
- name: read_file
|
|
group: file:read
|
|
use: deerflow.sandbox.tools:read_file_tool
|
|
|
|
- name: glob
|
|
group: file:read
|
|
use: deerflow.sandbox.tools:glob_tool
|
|
max_results: 200
|
|
|
|
- name: grep
|
|
group: file:read
|
|
use: deerflow.sandbox.tools:grep_tool
|
|
max_results: 100
|
|
|
|
- name: write_file
|
|
group: file:write
|
|
use: deerflow.sandbox.tools:write_file_tool
|
|
|
|
- name: str_replace
|
|
group: file:write
|
|
use: deerflow.sandbox.tools:str_replace_tool
|
|
|
|
# Bash execution tool
|
|
# Active only when using an isolated shell sandbox or when
|
|
# sandbox.allow_host_bash: true explicitly opts into host bash.
|
|
- name: bash
|
|
group: bash
|
|
use: deerflow.sandbox.tools:bash_tool
|
|
|
|
# ============================================================================
|
|
# Tool Search Configuration (Deferred Tool Loading)
|
|
# ============================================================================
|
|
# When enabled, MCP tools are not loaded into the agent's context directly.
|
|
# Instead, they are listed by name in the system prompt and discoverable
|
|
# via the tool_search tool at runtime.
|
|
# This reduces context usage and improves tool selection accuracy when
|
|
# multiple MCP servers expose a large number of tools.
|
|
|
|
tool_search:
|
|
enabled: false
|
|
# When tool_search is enabled, PR1 MCP routing metadata can auto-promote
|
|
# matching deferred MCP tool schemas before a model call. This is the maximum
|
|
# number of matched schemas promoted per model call. Valid range: 1..5.
|
|
auto_promote_top_k: 3
|
|
|
|
# ============================================================================
|
|
# Tool Output Budget Protection
|
|
# ============================================================================
|
|
# Prevents oversized tool results from blowing the model context window.
|
|
# Outputs exceeding `externalize_min_chars` are persisted to disk and replaced
|
|
# with a compact typed synopsis + file reference. The model can read the full output
|
|
# via read_file. When disk persistence is unavailable, outputs exceeding
|
|
# `fallback_max_chars` are head+tail truncated instead.
|
|
#
|
|
# `exempt_tools` prevents persist→read→persist infinite loops for read tools.
|
|
# `tool_overrides` allows per-tool threshold customization.
|
|
|
|
tool_output:
|
|
enabled: true
|
|
externalize_min_chars: 12000
|
|
# Sampling budget for the inline raw head/tail sample appended to every
|
|
# typed synopsis; ignored for binary-like output, which carries its own sample.
|
|
preview_head_chars: 2000
|
|
preview_tail_chars: 1000
|
|
fallback_max_chars: 30000
|
|
fallback_head_chars: 8000
|
|
fallback_tail_chars: 3000
|
|
storage_subdir: ".tool-results"
|
|
exempt_tools:
|
|
- read_file
|
|
- read_file_tool
|
|
# tool_overrides:
|
|
# web_search: 8000
|
|
# bash: 20000
|
|
|
|
# ============================================================================
|
|
# Suggestions Configuration
|
|
# ============================================================================
|
|
# Configure whether the agent automatically generates follow-up question
|
|
# suggestions at the end of each response.
|
|
|
|
suggestions:
|
|
enabled: true
|
|
|
|
|
|
# ============================================================================
|
|
# Input Polish Configuration
|
|
# ============================================================================
|
|
# Configure whether the composer can rewrite draft input before sending.
|
|
|
|
input_polish:
|
|
enabled: true
|
|
# Maximum draft length accepted by /api/input-polish.
|
|
max_chars: 4000
|
|
# Optional fast model for draft polishing. Leave null to use the default chat model.
|
|
# For best UX, set this to your lowest-latency inexpensive model.
|
|
model_name: null
|
|
|
|
|
|
# ============================================================================
|
|
# Loop Detection Configuration
|
|
# ============================================================================
|
|
# Detect and interrupt repeated identical tool-call loops.
|
|
# Frequency thresholds are safety limits for repeated use of the same tool type.
|
|
|
|
loop_detection:
|
|
enabled: true
|
|
warn_threshold: 3
|
|
hard_limit: 5
|
|
window_size: 20
|
|
max_tracked_threads: 100
|
|
tool_freq_warn: 30
|
|
tool_freq_hard_limit: 50
|
|
# Per-tool overrides for tool_freq_warn / tool_freq_hard_limit. Values can be
|
|
# higher or lower than the global defaults. Commonly used to raise thresholds
|
|
# for high-frequency tools like bash in batch workflows (e.g. RNA-seq pipelines)
|
|
# without weakening protection on every other tool.
|
|
# tool_freq_overrides:
|
|
# bash:
|
|
# warn: 150
|
|
# hard_limit: 300
|
|
|
|
# ============================================================================
|
|
# Tool Progress State Machine Configuration (RFC #3177)
|
|
# ============================================================================
|
|
# Detects tool stagnation and repetition at the (thread, tool) level.
|
|
# Tracks consecutive "no-new-info" calls (error, partial_success, near-duplicate success).
|
|
# Three transition paths (determined by deerflow_tool_meta.recoverable_by_model):
|
|
# recoverable=true (no_results, not_found, permission): ACTIVE → WARNED (terminal; hint re-injected each call)
|
|
# recoverable=false (rate_limited, transient): ACTIVE → WARNED → BLOCKED after warn_escalation_count more
|
|
# recoverable=false + action=stop (auth, config): ACTIVE → BLOCKED immediately
|
|
# Requires ToolErrorHandlingMiddleware to be active (always on).
|
|
|
|
# tool_progress:
|
|
# enabled: false
|
|
# stagnation_threshold: 3 # Consecutive problems before WARNED
|
|
# warn_escalation_count: 2 # More problems after WARNED before BLOCKED
|
|
# inject_assessment: true
|
|
# jaccard_similarity_threshold: 0.8 # Word-set similarity threshold for near-duplicate detection
|
|
# min_word_count_for_similarity: 10 # Min unique words to apply Jaccard check
|
|
# max_tracked_threads: 100
|
|
# exempt_tools:
|
|
# - ask_clarification
|
|
# - write_todos
|
|
# - present_files
|
|
# - task
|
|
|
|
# ============================================================================
|
|
# Read-Before-Write File Gate (issue #3857)
|
|
# ============================================================================
|
|
# Blocks write_file (append / overwrite of an existing file) and str_replace
|
|
# unless the agent has read the file's current version first; any write
|
|
# invalidates earlier reads, forcing a re-read between consecutive edits.
|
|
# Deterministic guardrail against blind duplicate appends in long tasks.
|
|
|
|
read_before_write:
|
|
enabled: true
|
|
|
|
# ============================================================================
|
|
# Provider Safety Termination Configuration
|
|
# ============================================================================
|
|
# Intercept AIMessages where the provider stopped generation for safety reasons
|
|
# (e.g. OpenAI finish_reason='content_filter', Anthropic stop_reason='refusal',
|
|
# Gemini finish_reason='SAFETY') while still returning tool_calls. The
|
|
# tool_calls in such responses are typically truncated/unreliable and must
|
|
# not be executed. See issue #3028 for the full failure mode.
|
|
#
|
|
# Detectors are loaded by class path via reflection (same pattern as
|
|
# guardrails / models / tools). The built-in set covers OpenAI-compatible
|
|
# content_filter, Anthropic refusal, and Gemini SAFETY/BLOCKLIST/
|
|
# PROHIBITED_CONTENT/SPII/RECITATION.
|
|
|
|
safety_finish_reason:
|
|
enabled: true
|
|
# Leave `detectors` unset to use the built-in detector set. Set to a
|
|
# non-empty list to fully override (use `enabled: false` to disable instead
|
|
# of providing an empty list).
|
|
#
|
|
# Example — extend the OpenAI-compatible detector for a Chinese provider
|
|
# whose gateway uses a non-standard finish_reason token:
|
|
# detectors:
|
|
# - use: deerflow.agents.middlewares.safety_termination_detectors:OpenAICompatibleContentFilterDetector
|
|
# config:
|
|
# finish_reasons: ["content_filter", "sensitive", "risk_control"]
|
|
# - use: deerflow.agents.middlewares.safety_termination_detectors:AnthropicRefusalDetector
|
|
# - use: deerflow.agents.middlewares.safety_termination_detectors:GeminiSafetyDetector
|
|
#
|
|
# Example — add a custom detector for an in-house provider:
|
|
# detectors:
|
|
# - use: my_company.deerflow_ext:WenxinSafetyDetector
|
|
# config:
|
|
# error_codes: [336003, 17, 18]
|
|
|
|
# ============================================================================
|
|
# Sandbox Configuration
|
|
# ============================================================================
|
|
# Choose between local sandbox (direct execution) or Docker-based AIO sandbox
|
|
|
|
# Option 1: Local Sandbox (Default)
|
|
# Executes commands directly on the host machine
|
|
uploads:
|
|
# Application-level upload limits enforced by the gateway and exposed to the
|
|
# frontend before file selection.
|
|
max_files: 10
|
|
max_file_size: 52428800 # 50 MiB
|
|
max_total_size: 104857600 # 100 MiB
|
|
# Automatic Office/PDF conversion runs on the backend host before sandbox
|
|
# isolation applies. Keep this disabled unless uploads come from a fully
|
|
# trusted source and you intentionally accept host-side parser risk.
|
|
auto_convert_documents: false
|
|
# Controls which PDF-to-Markdown converter is used whenever PDF conversion
|
|
# runs. Automatic upload conversion is gated separately by
|
|
# auto_convert_documents.
|
|
# auto — prefer pymupdf4llm when installed; fall back to MarkItDown for
|
|
# image-based or encrypted PDFs (recommended default).
|
|
# pymupdf4llm — always use pymupdf4llm (must be installed: uv add pymupdf4llm).
|
|
# Better heading/table extraction; faster on most files.
|
|
# markitdown — always use MarkItDown (original behaviour, no extra dependency).
|
|
pdf_converter: auto
|
|
|
|
sandbox:
|
|
use: deerflow.sandbox.local:LocalSandboxProvider
|
|
# Host bash execution is disabled by default because LocalSandboxProvider is
|
|
# not a secure isolation boundary for shell access. Enable only for fully
|
|
# trusted, single-user local workflows.
|
|
allow_host_bash: false
|
|
# Optional: Mount additional host directories into the sandbox.
|
|
# Each mount maps a host path to a virtual container path accessible by the agent.
|
|
# Note: with LocalSandboxProvider under `make up` (docker-compose), host_path is
|
|
# checked from inside the deer-flow-gateway container — you must also bind-mount
|
|
# the same directory into services.gateway.volumes in docker/docker-compose.yaml
|
|
# for this mount to take effect (see issue #3244).
|
|
# mounts:
|
|
# - host_path: /home/user/my-project # Absolute path; see note above for Docker mode
|
|
# container_path: /mnt/my-project # Virtual path inside the sandbox
|
|
# read_only: true # Whether the mount is read-only (default: false)
|
|
|
|
# Tool output truncation limits (characters).
|
|
# bash uses middle-truncation (head + tail) since errors can appear anywhere in the output.
|
|
# read_file and ls use head-truncation since their content is front-loaded.
|
|
# Set to 0 to disable truncation.
|
|
bash_output_max_chars: 20000
|
|
read_file_output_max_chars: 50000
|
|
ls_output_max_chars: 20000
|
|
|
|
# Maximum wall-clock seconds a single host bash command may run before it is
|
|
# terminated (process group and all). A blocking foreground command — e.g. a
|
|
# server started without backgrounding — is killed after this long so the
|
|
# agent's turn cannot hang. Start long-lived processes in the background with
|
|
# output redirected (e.g. `your-command > /tmp/server.log 2>&1 &`) when you
|
|
# need logs; unredirected background output is drained with bounded capture
|
|
# and excess output is discarded.
|
|
bash_command_timeout: 600
|
|
|
|
# Option 2: Container-based AIO Sandbox
|
|
# Executes commands in isolated containers (Docker or Apple Container)
|
|
# On macOS: Automatically prefers Apple Container if available, falls back to Docker
|
|
# On other platforms: Uses Docker
|
|
# Uncomment to use:
|
|
# sandbox:
|
|
# use: deerflow.community.aio_sandbox:AioSandboxProvider
|
|
#
|
|
# # Optional: Container image to use (works with both Docker and Apple Container)
|
|
# # Default: enterprise-public-cn-beijing.cr.volces.com/vefaas-public/all-in-one-sandbox:latest
|
|
# # The mirror's `:latest` tag is frozen on an old pre-1.9.3 digest that lacks
|
|
# # the /v1/bash/* routes required-secrets skills need (see #3921/#3922), so
|
|
# # pin an explicit version instead — recommended: 1.11.0 (multi-arch, works
|
|
# # on both x86_64 and arm64). Custom images should extend the default image
|
|
# # or implement the same AIO sandbox HTTP API used by agent-sandbox. See
|
|
# # backend/docs/CONFIGURATION.md.
|
|
# # image: enterprise-public-cn-beijing.cr.volces.com/vefaas-public/all-in-one-sandbox:1.11.0
|
|
#
|
|
# # Optional: Base port for sandbox containers (default: 8080)
|
|
# # port: 8080
|
|
|
|
# # Optional: Maximum number of concurrent sandbox containers (default: 3)
|
|
# # When the limit is reached the least-recently-used sandbox is evicted to
|
|
# # make room for new ones. Use a positive integer here; omit this field to use the default.
|
|
# # replicas: 3
|
|
#
|
|
# # Optional: Prefix for container names (default: deer-flow-sandbox)
|
|
# # container_prefix: deer-flow-sandbox
|
|
#
|
|
# # Optional: Additional mount directories from host to container
|
|
# # NOTE: Skills directory is automatically mounted from skills.path to skills.container_path
|
|
# # mounts:
|
|
# # # Other custom mounts
|
|
# # - host_path: /path/on/host
|
|
# # container_path: /home/user/shared
|
|
# # read_only: false
|
|
# #
|
|
# # # DeerFlow will surface configured container_path values to the agent,
|
|
# # # so it can directly read/write mounted directories such as /home/user/shared
|
|
#
|
|
# # Optional: Environment variables to inject into the sandbox container
|
|
# # Values starting with $ will be resolved from host environment variables
|
|
# # environment:
|
|
# # NODE_ENV: production
|
|
# # DEBUG: "false"
|
|
# # API_KEY: $MY_API_KEY # Reads from host's MY_API_KEY env var
|
|
# # DATABASE_URL: $DATABASE_URL # Reads from host's DATABASE_URL env var
|
|
#
|
|
# # Optional: Cross-instance container ownership (issue #4206).
|
|
# #
|
|
# # Gateway instances share sandbox containers but each keeps its own in-memory
|
|
# # warm pool. Without shared ownership state, one instance's startup
|
|
# # reconciliation adopts a container another instance is actively using and
|
|
# # later idle-destroys it — tool calls then fail with 502 / connection refused.
|
|
# #
|
|
# # Single gateway instance? Leave this out; `memory` is the default and the
|
|
# # cross-instance kill cannot happen.
|
|
# #
|
|
# # MULTIPLE gateway instances / workers sharing one container backend
|
|
# # (load-balanced deployments, Docker Compose) MUST set type: redis. Docker
|
|
# # Compose already sets DEER_FLOW_STREAM_BRIDGE_REDIS_URL, which is taken as
|
|
# # proof the deployment is multi-instance, so redis ownership is inferred even
|
|
# # if this section is omitted.
|
|
# #
|
|
# # The redis ownership store requires the optional `redis` extra. It is
|
|
# # auto-detected from this section on `make dev` and always installed in the
|
|
# # Docker image. To install it manually:
|
|
# # cd backend && uv sync --all-packages --extra redis
|
|
# #
|
|
# # ownership:
|
|
# # type: memory # single gateway instance only
|
|
# #
|
|
# # ownership:
|
|
# # type: redis # required for multi-instance / load-balanced
|
|
# # redis_url: redis://redis:6379/0
|
|
# # renewal_interval_seconds: 30 # how often an owner refreshes its leases
|
|
# # ttl_multiplier: 4 # lease TTL = interval x this (min 2, so a
|
|
# # # single missed renewal cannot expire a live
|
|
# # # owner). Liveness is deliberately independent
|
|
# # # of idle_timeout: renewal keeps running even
|
|
# # # at idle_timeout: 0.
|
|
# # key_prefix: deerflow:sandbox:owner
|
|
# #
|
|
# # NOTE: the redis ownership store is fail-closed, matching the stream bridge's
|
|
# # fail-hard policy. Redis.from_url is lazy so a down Redis does not block
|
|
# # startup, but a sandbox whose ownership cannot be published is not handed out
|
|
# # — acquiring raises instead. The alternative (proceed unowned) is exactly the
|
|
# # #4206 cross-instance kill. Run Redis with HA / a restart policy.
|
|
# #
|
|
# # NOTE: the other boundary is the lease TTL (renewal_interval_seconds x
|
|
# # ttl_multiplier). A Redis outage longer than the TTL can let a reconciling
|
|
# # instance adopt a live owner's container: a lapsed lease is indistinguishable
|
|
# # from a dead owner, so one TTL of adoption grace is the whole safety margin.
|
|
# # Size the TTL against your Redis availability target (HA Redis keeps this
|
|
# # window out of reach).
|
|
|
|
# Option 3: BoxLite micro-VM Sandbox
|
|
# Runs each sandbox as a BoxLite micro-VM. Released boxes stay in an in-process
|
|
# warm pool and can be reclaimed by the same user/thread without a cold start.
|
|
# Requires the boxlite runtime and host virtualization support (KVM on Linux,
|
|
# Hypervisor.framework on macOS).
|
|
# sandbox:
|
|
# use: deerflow.community.boxlite:BoxliteProvider
|
|
# image: python:3.12-slim
|
|
#
|
|
# # Optional: Per-box memory and CPU limits.
|
|
# # memory_mib: 1024
|
|
# # cpus: 2
|
|
#
|
|
# # Optional: Maximum active + warm BoxLite VMs per gateway process (default: 3).
|
|
# # Active boxes are never evicted; only warm-pool boxes are stopped to make room.
|
|
# # replicas: 3
|
|
#
|
|
# # Optional: Seconds before an idle warm-pool VM is stopped (default: 600).
|
|
# # Set to 0 to keep warm VMs until shutdown or replica eviction.
|
|
# # idle_timeout: 600
|
|
#
|
|
# # Optional: Skip the reclaim health check for very recently released VMs.
|
|
# # Default 0.0 keeps reliability-first validation before warm reuse.
|
|
# # health_check_skip_seconds: 0.0
|
|
#
|
|
# # Optional: Environment variables to inject into every command.
|
|
# # environment:
|
|
# # PYTHONUNBUFFERED: "1"
|
|
#
|
|
# Option 4: Provisioner-managed AIO Sandbox (docker-compose-dev)
|
|
# Each sandbox_id gets a dedicated Pod in k3s, managed by the provisioner.
|
|
# Recommended for production or advanced users who want better isolation and scalability.:
|
|
# sandbox:
|
|
# use: deerflow.community.aio_sandbox:AioSandboxProvider
|
|
# provisioner_url: http://provisioner:8002
|
|
# # API key for provisioner authentication. Must match PROVISIONER_API_KEY
|
|
# # set on the provisioner container. Both sides must have the same value set;
|
|
# # the provisioner rejects all /api/* requests when PROVISIONER_API_KEY is unset.
|
|
# # Generate a strong key: openssl rand -hex 32
|
|
# # provisioner_api_key: $PROVISIONER_API_KEY
|
|
# # Note: provisioner-created Pods use the provisioner's SANDBOX_IMAGE
|
|
# # environment variable, not sandbox.image from this config file.
|
|
|
|
# Option 5: Tenki cloud microVM Sandbox
|
|
# Runs each sandbox as an isolated Tenki cloud microVM. Released sandboxes stay
|
|
# in an in-process warm pool and are reclaimed by the same user/thread without a
|
|
# cold start. Requires the optional SDK: pip install "deerflow-harness[tenki]".
|
|
# sandbox:
|
|
# use: deerflow.community.tenki:TenkiSandboxProvider
|
|
# # api_key: $TENKI_API_KEY # falls back to TENKI_API_KEY / TENKI_AUTH_TOKEN env var
|
|
# # base_url: https://tenki.cloud # optional; SDK default when omitted
|
|
# # image: my-base-image # optional; Tenki account default base image when omitted
|
|
# # project_id: proj_... # optional; auto-selected if the account has exactly one
|
|
# # workspace_id: ws_... # optional; auto-selected if the account has exactly one
|
|
# # cpu_cores: 2 # optional per-sandbox vCPUs
|
|
# # memory_mb: 2048 # optional per-sandbox memory
|
|
# # replicas: 3 # active + warm microVM cap per gateway process
|
|
# # idle_timeout: 600 # warm microVM idle seconds before terminate; 0 disables
|
|
# # max_duration: 14400 # Tenki sandbox lifetime in seconds; 0 uses the account default
|
|
# # sticky: false # pin the microVM to its host (only matters with pause/resume)
|
|
# # home_dir: /home/tenki # writable dir backing /mnt/user-data
|
|
# # environment: # injected into every command (and as create-time env)
|
|
# # PYTHONUNBUFFERED: "1"
|
|
|
|
# ============================================================================
|
|
# Subagents Configuration
|
|
# ============================================================================
|
|
# Configure timeouts for subagent execution
|
|
# Subagents are background workers delegated tasks by the lead agent
|
|
|
|
# subagents:
|
|
# # Default timeout (seconds) for built-in subagents (default: 1800 = 30 min).
|
|
# # Custom agents use their own timeout_seconds (default 900) unless overridden.
|
|
# timeout_seconds: 1800
|
|
# # Optional global max-turn override for all subagents.
|
|
# # Built-in defaults: general-purpose=150, bash=60. Leave unset to keep them.
|
|
# # max_turns: 120
|
|
#
|
|
# # Total number of subagent delegations allowed in one lead-agent run.
|
|
# # This is a deterministic backstop against repeated planning checkpoints
|
|
# # launching legal-sized batches forever. The default 6 allows two full
|
|
# # batches at the default concurrency of 3. Valid config range: 1-50.
|
|
# # Per-request runtime context can temporarily override this with
|
|
# # `max_total_subagents`, clamped to the same 1-50 range.
|
|
# max_total_per_run: 6
|
|
#
|
|
# # Per-run token ceiling for subagents (#3875 Phase 2). A backstop against a
|
|
# # subagent that burns tokens on trivial work. At the hard-stop threshold the
|
|
# # in-flight turn is capped (tool calls stripped, finish_reason forced to
|
|
# # "stop") so the run completes naturally with a final answer; the result is
|
|
# # stamped `completed` + `subagent_stop_reason=token_capped` so the lead and
|
|
# # UI can tell a budget-capped completion from a clean one. The 2,000,000
|
|
# # default is a generous ceiling — lower it to tighten cost controls. A
|
|
# # per-agent `token_budget` override (see `agents:` below) wins over this.
|
|
# # token_budget:
|
|
# # enabled: true
|
|
# # max_tokens: 2000000
|
|
# # warn_threshold: 0.7 # log a warning once this fraction of the budget is spent
|
|
#
|
|
# # Optional per-agent overrides (applies to both built-in and custom agents)
|
|
# agents:
|
|
# general-purpose:
|
|
# timeout_seconds: 2700 # 45 minutes for very long deep-research tasks
|
|
# max_turns: 250 # raise above the 150 default for very deep tasks
|
|
# # token_budget: # per-agent override of the global token_budget above
|
|
# # max_tokens: 3000000 # raise the ceiling for deep-research tasks
|
|
# # model: qwen3:32b # Use a specific model (default: inherit from lead agent)
|
|
# # skills: # Skill whitelist (default: inherit all enabled skills)
|
|
# # - web-search
|
|
# # - data-analysis
|
|
# bash:
|
|
# timeout_seconds: 300 # 5 minutes for quick command execution
|
|
# max_turns: 80
|
|
# # skills: [] # No skills for bash agent
|
|
#
|
|
# # Custom subagent types: define specialized agents with their own prompts,
|
|
# # tools, skills, and model configuration. Custom agents are available via
|
|
# # the `task` tool alongside built-in types (general-purpose, bash).
|
|
# # custom_agents:
|
|
# # analysis:
|
|
# # description: "Data analysis specialist for processing datasets and generating insights"
|
|
# # system_prompt: |
|
|
# # You are a data analysis subagent. Focus on:
|
|
# # - Processing and analyzing datasets
|
|
# # - Generating visualizations
|
|
# # - Providing statistical insights
|
|
# # tools: # Tool whitelist (null = inherit all)
|
|
# # - bash
|
|
# # - read_file
|
|
# # - write_file
|
|
# # skills: # Skill whitelist (null = inherit all, [] = none)
|
|
# # - data-analysis
|
|
# # - visualization
|
|
# # model: inherit # 'inherit' uses parent's model
|
|
# # max_turns: 80
|
|
# # timeout_seconds: 600
|
|
#
|
|
# # Model override: by default, subagents inherit the lead agent's model.
|
|
# # Set `model` to use a different model (e.g., a local Ollama model for cost savings).
|
|
# # The model name must match a name defined in the `models:` section above.
|
|
|
|
# ============================================================================
|
|
# ACP Agents Configuration
|
|
# ============================================================================
|
|
# Configure external ACP-compatible agents for the built-in `invoke_acp_agent` tool.
|
|
|
|
# acp_agents:
|
|
# claude_code:
|
|
# # DeerFlow expects an ACP adapter here. The standard `claude` CLI does not
|
|
# # speak ACP directly. Install `claude-agent-acp` separately or use:
|
|
# command: npx
|
|
# args: ["-y", "@zed-industries/claude-agent-acp"]
|
|
# description: Claude Code for implementation, refactoring, and debugging
|
|
# model: null
|
|
# # auto_approve_permissions: false # Set to true to auto-approve ACP permission requests
|
|
# # timeout_seconds: 1800 # Abort + kill the subprocess if it doesn't respond in time (default: 1800 = 30 min)
|
|
# # env: # Optional: inject environment variables into the agent subprocess
|
|
# # ANTHROPIC_API_KEY: $ANTHROPIC_API_KEY # $VAR resolves from host environment
|
|
#
|
|
# codex:
|
|
# # DeerFlow expects an ACP adapter here. The standard `codex` CLI does not
|
|
# # speak ACP directly. Install `codex-acp` separately or use:
|
|
# command: npx
|
|
# args: ["-y", "@zed-industries/codex-acp"]
|
|
# description: Codex CLI for repository tasks and code generation
|
|
# model: null
|
|
# # auto_approve_permissions: false # Set to true to auto-approve ACP permission requests
|
|
# # env: # Optional: inject environment variables into the agent subprocess
|
|
# # OPENAI_API_KEY: $OPENAI_API_KEY # $VAR resolves from host environment
|
|
|
|
# ============================================================================
|
|
# Skills Configuration
|
|
# ============================================================================
|
|
# Configure skills directory for specialized agent workflows
|
|
|
|
skills:
|
|
# Path to skills directory on the host (relative to project root or absolute)
|
|
# Default: skills under the project root
|
|
# Override with DEER_FLOW_SKILLS_PATH when this field is omitted.
|
|
# Uncomment to customize:
|
|
# path: /absolute/path/to/custom/skills
|
|
|
|
# Path where skills are mounted in the sandbox container
|
|
# This is used by the agent to access skills in both local and Docker sandbox
|
|
# Default: /mnt/skills
|
|
container_path: /mnt/skills
|
|
|
|
# Deferred skill discovery (default: false)
|
|
# When enabled, only skill names appear in the system prompt (<skill_index>).
|
|
# The LLM discovers skill details on demand via the describe_skill tool.
|
|
# This keeps the system prompt compact and prefix-cache friendly when many
|
|
# skills are installed.
|
|
# deferred_discovery: true
|
|
|
|
# ============================================================================
|
|
# SkillScan Configuration
|
|
# ============================================================================
|
|
# Native deterministic skill safety scanning. This runs before the LLM skill
|
|
# scanner on skill install/update and agent-managed skill writes.
|
|
skill_scan:
|
|
# Set false to disable the new deterministic analyzers (nested-archive,
|
|
# secret-pattern, and other content-level checks). Safe archive extraction
|
|
# (path traversal, symlinks, executable-binary, total-size, and entry-count
|
|
# limits) and the LLM skill scanner still run unconditionally.
|
|
enabled: true
|
|
|
|
# Note: To restrict which skills are loaded for a specific custom agent,
|
|
# define a `skills` list in that agent's `config.yaml` (e.g. `agents/my-agent/config.yaml`):
|
|
# - Omitted or null: load all globally enabled skills (default)
|
|
# - []: disable all skills for this agent
|
|
# - ["skill-name"]: load only specific skills
|
|
|
|
# ============================================================================
|
|
# Title Generation Configuration
|
|
# ============================================================================
|
|
# Automatic conversation title generation settings
|
|
|
|
title:
|
|
enabled: true
|
|
max_words: 6
|
|
max_chars: 60
|
|
model_name: null # null = fast local fallback; set a model name to use LLM title generation
|
|
|
|
# ============================================================================
|
|
# Summarization Configuration
|
|
# ============================================================================
|
|
# Automatically summarize conversation history when token limits are approached
|
|
# This helps maintain context in long conversations without exceeding model limits
|
|
|
|
summarization:
|
|
enabled: true
|
|
|
|
# Model to use for summarization.
|
|
# null = summarize with the model the run actually uses (the lead run's model, a
|
|
# subagent's own model, or a thread's custom-agent model), NOT models[0].
|
|
# set = that model generates; if its provider fails, compaction falls back to the
|
|
# run's own model so a broken summary provider cannot disable compaction.
|
|
# Recommended: Use a lightweight, cost-effective model like "gpt-4o-mini" or similar
|
|
model_name: null
|
|
|
|
# Trigger conditions - at least one required
|
|
# Summarization runs when ANY threshold is met (OR logic)
|
|
# You can specify a single trigger or a list of triggers
|
|
trigger:
|
|
# Trigger when token count reaches 32000
|
|
- type: tokens
|
|
value: 32000
|
|
# Uncomment to also trigger when message count reaches 50
|
|
# - type: messages
|
|
# value: 50
|
|
# Uncomment to trigger when 80% of model's max input tokens is reached
|
|
# - type: fraction
|
|
# value: 0.8
|
|
|
|
# Context retention policy after summarization
|
|
# Specifies how much recent history to preserve
|
|
keep:
|
|
# Keep the most recent 10 messages (recommended)
|
|
type: messages
|
|
value: 10
|
|
# Alternative: Keep specific token count
|
|
# type: tokens
|
|
# value: 3000
|
|
# Alternative: Keep percentage of model's max input tokens
|
|
# type: fraction
|
|
# value: 0.3
|
|
|
|
# Maximum tokens to keep when preparing messages for summarization
|
|
# Set to null to skip trimming (not recommended for very long conversations)
|
|
trim_tokens_to_summarize: 15564
|
|
|
|
# Custom summary prompt template (null = use default LangChain prompt)
|
|
# The prompt should guide the model to extract important context
|
|
summary_prompt: null
|
|
|
|
# Loaded SKILL.md references (read_file calls under skills.container_path) are
|
|
# captured into the durable skill_context channel and re-injected after
|
|
# compaction as name/path/description reminders. The full skill body is not
|
|
# persisted; the agent should re-read the file before applying instructions.
|
|
# Tool names counted as skill reads:
|
|
# Legacy preserve_recent_skill_* summarization settings are no longer used;
|
|
# skill retention is handled by this durable reference channel instead. Set
|
|
# this list to [] to disable durable skill-reference capture.
|
|
skill_file_read_tool_names:
|
|
- read_file
|
|
- read
|
|
- view
|
|
- cat
|
|
|
|
# ============================================================================
|
|
# Memory Configuration
|
|
# ============================================================================
|
|
# Global memory mechanism (pluggable + self-contained).
|
|
#
|
|
# Shared fields (host level, backend-agnostic):
|
|
# enabled - Master switch for the memory mechanism (call-site gate)
|
|
# injection_enabled - Whether to inject memory into the system prompt (call-site gate)
|
|
# shutdown_flush_timeout_seconds - Hard budget (s) to drain pending updates on Gateway graceful shutdown (default: 30)
|
|
# manager_class - Backend selector: registered name (deermem/noop) or dotted path
|
|
# backend_config - Backend-private config dict (passthrough; each backend self-interprets)
|
|
#
|
|
# DeerMem-private fields live under ``backend_config`` (NOT at the memory: top level):
|
|
# storage_path - Data root. Empty = deer-flow base_dir (factory injects absolute
|
|
# runtime_home). Absolute path = that root. Relative = CWD-relative.
|
|
# model - LLM config for memory extraction: {provider, model, api_key, base_url,
|
|
# temperature}. Omit all fields = no extraction (non-LLM ops still work).
|
|
# debounce_seconds - Debounce wait before processing queued updates (default: 30)
|
|
# max_facts - Maximum facts to store (default: 100)
|
|
# fact_confidence_threshold - Minimum confidence for storing facts (default: 0.7)
|
|
# max_injection_tokens - Token budget for memory injection (default: 2000)
|
|
# token_counting - tiktoken (accurate, network on first use) or char (network-free)
|
|
# guaranteed_categories - Fact categories always injected (default: ["correction"])
|
|
# guaranteed_token_budget - Token ceiling for guaranteed categories (default: 500)
|
|
# staleness_review_enabled - Enable staleness pruning (default: true)
|
|
# staleness_age_days - Age threshold for staleness candidates (default: 90)
|
|
# staleness_min_candidates - Minimum stale facts to trigger review (default: 3)
|
|
# staleness_max_removals_per_cycle - Safety cap on removals per cycle (default: 10)
|
|
# staleness_protected_categories - Categories exempt from staleness review (default: ["correction"])
|
|
# staleness_max_lifetime_multiplier - Creation-time cap multiplier for a fact LLM-assigned
|
|
# expected_valid_days; new facts clamped to
|
|
# staleness_age_days x multiplier. Default 20.0
|
|
# (90 x 20 = 1800d ~ 5 years) supports the very-stable
|
|
# prompt tier. (default: 20.0, range: 1.0-100.0)
|
|
# staleness_max_extension_days - Absolute ceiling (in days) on expected_valid_days after a
|
|
# lifetime extension (staleFactsToExtend). Prevents timedelta
|
|
# overflow and LLM misfire from permanently deferring a fact.
|
|
# (default: 3650, range: 90-36500)
|
|
memory:
|
|
enabled: true
|
|
injection_enabled: true # Whether to inject memory into system prompt
|
|
# Hard budget (seconds) to drain pending memory updates on Gateway graceful
|
|
# shutdown. Each pending item does one LLM call, so large IM batches may need
|
|
# more. Must fit inside the pod's K8s terminationGracePeriodSeconds (channel
|
|
# stop + this drain + buffer) or K8s SIGKILLs the drain -- set that on the
|
|
# gateway Helm deployment (see deploy/helm/deer-flow). Default 30s.
|
|
shutdown_flush_timeout_seconds: 30.0
|
|
# Memory backend selector. Either a registered backend name (matching a
|
|
# backends/<name>/ folder that exposes MANAGER_CLASS, e.g. deermem / noop)
|
|
# or a dotted import path to a MemoryManager subclass.
|
|
manager_class: deermem
|
|
# Memory operation mode:
|
|
# middleware (default) - passive background extraction after each turn.
|
|
# tool - experimental opt-in; the model calls memory_search/memory_add/
|
|
# memory_update/memory_delete directly. This gives the model agency over
|
|
# memory writes, but effectiveness depends on model tool-use behavior.
|
|
# Only one mode runs at a time. (tool mode calls the MemoryManager ABC --
|
|
# memory_search/add/update/delete go through the active backend; backends
|
|
# without fact-CRUD return a JSON error instead of crashing.)
|
|
mode: middleware
|
|
# Backend-private config (a dict), passed verbatim to the backend __init__.
|
|
# Each backend self-interprets it (DeerMem parses it into DeerMemConfig).
|
|
backend_config:
|
|
storage_path: "" # empty = deer-flow base_dir (factory injects absolute runtime_home); a non-empty path is the root DIRECTORY (per-user memory under {storage_path}/users/{uid}/memory.json)
|
|
storage_class: file # file (default) or a dotted MemoryStorage class path; invalid persistent backends fail fast
|
|
strict_user_scope: false # set true in authenticated deployments after all callers propagate user_id
|
|
manifest_filename: memory.json # user-global JSON: version/revision/time + user/history only; no facts or fact index
|
|
file_lock_timeout_seconds: 10 # per-scope cross-process advisory lock timeout (single-machine local filesystem)
|
|
retrieval_adapter: "" # optional dotted factory(config) supplied by the retrieval module
|
|
debounce_seconds: 30 # Wait time before processing queued updates
|
|
# Backpressure cap on pending items. 0 = unlimited. At the cap, new
|
|
# non-signal updates are rejected (QueueFull); signal updates are always
|
|
# admitted so important memories are never shed.
|
|
queue_max_depth: 1000
|
|
model: # LLM for memory extraction; omit all fields = no extraction (non-LLM ops still work; an update raises)
|
|
# provider: openai
|
|
# model: gpt-4o-mini
|
|
# api_key: $OPENAI_API_KEY
|
|
# base_url: # optional, for OpenAI-compatible gateways (e.g. DeepSeek)
|
|
# temperature: # optional
|
|
max_facts: 100 # Maximum number of facts to store
|
|
fact_confidence_threshold: 0.7 # Minimum confidence for storing facts
|
|
max_injection_tokens: 2000 # Maximum tokens for memory injection
|
|
# Token counting strategy for memory-injection budgeting:
|
|
# tiktoken (default) - accurate, but the encoding BPE data may be
|
|
# downloaded from a public network endpoint on first use. In
|
|
# network-restricted environments this download can block for a long
|
|
# time (see issues #3402 / #3429). Pre-cache the encoding or set this
|
|
# to "char" to avoid it.
|
|
# char - network-free CJK-aware character-based estimate; never touches
|
|
# tiktoken. Slightly less precise budgeting, zero network I/O.
|
|
token_counting: tiktoken
|
|
# Guaranteed injection: fact categories that bypass the regular token budget
|
|
# and draw from a reserved allowance, so high-signal corrections (e.g.
|
|
# "don use pip, use uv") survive even when the budget is tight.
|
|
guaranteed_categories:
|
|
- correction
|
|
guaranteed_token_budget: 500
|
|
# Staleness review: periodically prune aged facts that may no longer reflect
|
|
# the user current situation. When triggered, the LLM reviews facts older
|
|
# than their individual review window (expected_valid_days, or
|
|
# staleness_age_days as fallback) during the normal memory-update call (same
|
|
# LLM invocation - no extra API call) and decides KEEP, REMOVE, or EXTEND
|
|
# for each. The LLM assigns expected_valid_days when creating a fact; EXTEND
|
|
# (staleFactsToExtend) recalibrates that window at review time.
|
|
staleness_review_enabled: true
|
|
staleness_age_days: 90
|
|
staleness_min_candidates: 3
|
|
staleness_max_removals_per_cycle: 10
|
|
staleness_protected_categories:
|
|
- correction
|
|
staleness_max_lifetime_multiplier: 20.0 # creation cap = staleness_age_days x multiplier (90 x 20 = 1800d)
|
|
staleness_max_extension_days: 3650 # absolute ceiling on extended expected_valid_days (~10 years)
|
|
# Memory consolidation (opt-in, lossy: source facts are replaced by a
|
|
# synthesized one; only consolidatedFrom IDs are kept). Runs in the same
|
|
# memory-update LLM call as extraction/staleness - no extra API cost.
|
|
# consolidation_enabled defaults to false because consolidation is lossy.
|
|
consolidation_enabled: false # set true to opt into fact consolidation
|
|
consolidation_min_facts: 8 # min facts in one category to trigger review (3-30)
|
|
consolidation_max_groups_per_cycle: 3 # max groups merged per update cycle (1-10)
|
|
consolidation_max_sources: 8 # max source facts per consolidation group (2-20)
|
|
# extraction_callback is a host-injected post-extraction observability hook
|
|
# (token usage, facts accepted/rejected, rejection rate). The factory
|
|
# injects a logging default; set programmatically to emit a Langfuse span.
|
|
# Message processing (externalized patterns / prompt templates):
|
|
# patterns_dir - dir with correction.yaml / reinforcement.yaml overriding
|
|
# the bundled signal-detection patterns. None (default) =
|
|
# bundled core/message_patterns/. When explicitly set, both
|
|
# files must exist (typos or missing mounts raise an error).
|
|
# prompts_dir - dir with custom memory-extraction prompt templates
|
|
# (memory_update.chat.yaml, staleness_review.yaml,
|
|
# consolidation.yaml, fact_extraction.yaml). None (default)
|
|
# = bundled core/prompts/. Supports per-agent subdirectories.
|
|
# patterns_dir: "" # empty = bundled defaults
|
|
# prompts_dir: "" # empty = bundled defaults
|
|
|
|
# ============================================================================
|
|
# Custom Agent Management API
|
|
# ============================================================================
|
|
# Controls whether the HTTP gateway exposes custom-agent SOUL/USER.md management.
|
|
# Keep this disabled unless the gateway is behind a trusted authenticated admin boundary.
|
|
agents_api:
|
|
enabled: false
|
|
|
|
# ============================================================================
|
|
# Skill Self-Evolution Configuration
|
|
# ============================================================================
|
|
# Allow the agent to autonomously create and improve skills in skills/custom/.
|
|
skill_evolution:
|
|
enabled: false # Set to true to allow agent-managed writes under skills/custom
|
|
moderation_model_name: null # Model for LLM-based security scanning (null = use default model)
|
|
security_fail_closed: true # Moderation model unavailable: true blocks all writes; false allows non-executable content with a warning (executable is always blocked)
|
|
|
|
# ============================================================================
|
|
# Checkpointer Configuration (DEPRECATED — use `database` instead)
|
|
# ============================================================================
|
|
# Legacy standalone checkpointer config. Kept for backward compatibility.
|
|
# Prefer the unified `database` section below, which drives the LangGraph
|
|
# checkpointer, LangGraph Store, and DeerFlow application data (runs,
|
|
# feedback, events) from a single backend setting.
|
|
#
|
|
# If both `checkpointer` and `database` are present, `checkpointer`
|
|
# takes precedence for the LangGraph checkpointer and Store only.
|
|
#
|
|
# checkpointer:
|
|
# type: sqlite
|
|
# connection_string: checkpoints.db
|
|
#
|
|
# checkpointer:
|
|
# type: postgres
|
|
# connection_string: postgresql://user:password@localhost:5432/deerflow
|
|
|
|
# ============================================================================
|
|
# Database
|
|
# ============================================================================
|
|
# Unified storage backend for the LangGraph checkpointer, LangGraph Store,
|
|
# and DeerFlow application data (runs, threads metadata, feedback, etc.).
|
|
#
|
|
# backend: memory -- No persistence, data lost on restart
|
|
# backend: sqlite -- Single-node deployment, files in sqlite_dir
|
|
# backend: postgres -- Production multi-node deployment
|
|
#
|
|
# If this section is omitted or empty in config.yaml, DeerFlow uses:
|
|
# backend: sqlite
|
|
# sqlite_dir: .deer-flow/data
|
|
#
|
|
# SQLite mode uses a single deerflow.db file with WAL journal mode
|
|
# for the checkpointer, Store, and application data.
|
|
#
|
|
# Postgres mode: put your connection URL in .env as DATABASE_URL,
|
|
# then reference it here with $DATABASE_URL.
|
|
#
|
|
# Install the driver — Issue #2754 fix lands `UV_EXTRAS` in every code path:
|
|
# Local `make dev` auto-detects from `database.backend: postgres` below
|
|
# and passes `--extra postgres` to `uv sync` on every restart, so
|
|
# the extra is no longer wiped. To opt in explicitly (or layer
|
|
# extras like `postgres,ollama`), set in project-root .env:
|
|
# UV_EXTRAS=postgres
|
|
# Docker dev `make docker-start` reads `UV_EXTRAS` from project-root .env via
|
|
# `env_file`. Set:
|
|
# UV_EXTRAS=postgres
|
|
# Multiple extras (`postgres,ollama`) supported here too — see
|
|
# docker/dev-entrypoint.sh.
|
|
# Docker img build-arg `UV_EXTRAS=postgres,discord docker compose build`
|
|
# supports comma- or whitespace-separated extras at build time
|
|
# (backend/Dockerfile expands them to repeated `--extra` flags).
|
|
#
|
|
# First-time bootstrap (before `make dev`):
|
|
# cd backend && uv sync --all-packages --extra postgres
|
|
# (--all-packages propagates the extra into workspace members — see PR #2584)
|
|
#
|
|
# NOTE: When both `checkpointer` and `database` are configured,
|
|
# `checkpointer` takes precedence for the LangGraph checkpointer and Store;
|
|
# `database` still controls DeerFlow application data.
|
|
# If you use `database`, you can remove the `checkpointer` section.
|
|
# database:
|
|
# backend: sqlite
|
|
# sqlite_dir: .deer-flow/data
|
|
#
|
|
# database:
|
|
# backend: postgres
|
|
# postgres_url: $DATABASE_URL
|
|
database:
|
|
backend: sqlite
|
|
sqlite_dir: .deer-flow/data
|
|
# Recycle app ORM PostgreSQL connections before the environment's idle cutoff.
|
|
pool_recycle: 300
|
|
# App ORM PostgreSQL command timeout. Set to null to disable it or raise it
|
|
# for intentionally long commands.
|
|
command_timeout: 30
|
|
# Restart required. Use one value across every process sharing this database.
|
|
# full: current full-message checkpoints; delta: DeltaChannel for messages.
|
|
checkpoint_channel_mode: full
|
|
|
|
# ============================================================================
|
|
# Run Events Configuration
|
|
# ============================================================================
|
|
# Storage backend for run events (messages + execution traces).
|
|
#
|
|
# backend: memory -- No persistence, data lost on restart (default)
|
|
# backend: db -- SQL database via ORM, full query capability (production)
|
|
# backend: jsonl -- Append-only JSONL files (lightweight single-node persistence)
|
|
#
|
|
# run_events:
|
|
# backend: memory
|
|
# max_trace_content: 10240 # Truncation threshold for trace content (db backend, bytes)
|
|
# track_token_usage: true # Accumulate token counts to RunRow
|
|
run_events:
|
|
backend: memory
|
|
max_trace_content: 10240
|
|
track_token_usage: true
|
|
|
|
# ============================================================================
|
|
# Agent Storage Configuration
|
|
# ============================================================================
|
|
# Where custom agent DEFINITIONS (config.yaml + SOUL.md) are stored. This is
|
|
# separate from `database` (run/thread/event data) and from agent memory.
|
|
# Restart-required (the backend is captured at Gateway lifespan startup).
|
|
#
|
|
# backend: file -- Per-user files under {base_dir}/users/{uid}/agents/ (default).
|
|
# Single-node only: an agent created on one node is invisible
|
|
# to other nodes without a shared mount.
|
|
# backend: db -- A row per agent in the shared SQL persistence layer, so every
|
|
# node sees the same agents. Requires database.backend to be
|
|
# 'sqlite' or 'postgres' (rejected at startup on 'memory').
|
|
#
|
|
# Switching an existing install to 'db'? Import the on-disk agents once with:
|
|
# python backend/scripts/migrate_agents_to_db.py # --dry-run to preview
|
|
# The source files are left in place, so reverting to 'file' is a clean rollback.
|
|
#
|
|
# agent_storage:
|
|
# backend: file
|
|
agent_storage:
|
|
backend: file
|
|
|
|
# ============================================================================
|
|
# Scheduled Tasks Configuration
|
|
# ============================================================================
|
|
# Background scheduler for one-time and recurring (cron) agent runs.
|
|
# All fields are restart-required (captured at Gateway lifespan startup).
|
|
#
|
|
# Multi-worker note: the scheduler runs once per uvicorn worker. SQLite silently
|
|
# ignores row-level locks, so multiple workers can double-fire the same task.
|
|
# For multi-worker deployments (GATEWAY_WORKERS > 1), use the Postgres database
|
|
# backend, where FOR UPDATE SKIP LOCKED serializes claims correctly.
|
|
#
|
|
# scheduler:
|
|
# enabled: false # Master switch for the background poller
|
|
# poll_interval_seconds: 5 # How often to scan for due tasks
|
|
# lease_seconds: 120 # Claim lease; a crashed process's task becomes reclaimable after this
|
|
# max_concurrent_runs: 3 # Global cap on active scheduled runs; each poll claims only into the remaining budget
|
|
# min_once_delay_seconds: 60 # Minimum future offset for one-time tasks at creation time
|
|
scheduler:
|
|
enabled: false
|
|
poll_interval_seconds: 5
|
|
lease_seconds: 120
|
|
max_concurrent_runs: 3
|
|
min_once_delay_seconds: 60
|
|
|
|
# ============================================================================
|
|
# Run Ownership Configuration
|
|
# ============================================================================
|
|
# Controls cross-process run ownership for multi-worker deployments.
|
|
# When GATEWAY_WORKERS > 1, each worker claims runs with a lease; the heartbeat
|
|
# renews leases, and reconciliation recovers orphaned runs from crashed workers.
|
|
#
|
|
# CLOCK-SYNC REQUIREMENT (multi-worker only): reconciliation compares another
|
|
# worker's UTC lease timestamp against this worker's datetime.now(UTC). Worker
|
|
# clocks MUST be synced (NTP / chrony / systemd-timesyncd — default on K8s and
|
|
# cloud VMs) within a few seconds. grace_seconds is the skew budget; worst case
|
|
# (owning worker's heartbeat just about to fire), a peer whose clock is more
|
|
# than grace_seconds ahead can mis-reclaim a still-live run as an orphan. Raise
|
|
# grace_seconds if your environment cannot keep clocks within a few seconds;
|
|
# the trade-off is longer recovery latency for genuinely dead workers
|
|
# (lease_seconds + grace_seconds from last heartbeat to reclaim).
|
|
#
|
|
# The owning worker itself does NOT use grace_seconds as extra execution time.
|
|
# If renewal cannot be confirmed before lease_seconds expires, it cancels the
|
|
# local run and suppresses durable finalization; grace_seconds only delays when
|
|
# a peer may reclaim the expired row.
|
|
|
|
run_ownership:
|
|
lease_seconds: 30 # Seconds before a run lease expires if not renewed.
|
|
# Heartbeat renews every lease_seconds / 3.
|
|
grace_seconds: 10 # Extra seconds past expiry before reclaiming an orphaned run.
|
|
# Also the cross-worker clock-skew budget — see note above.
|
|
heartbeat_enabled: false # Set to true for GATEWAY_WORKERS > 1
|
|
|
|
# ============================================================================
|
|
# Stream Bridge Configuration
|
|
# ============================================================================
|
|
# The stream bridge carries live agent events from gateway workers to SSE
|
|
# clients. Docker Compose sets DEER_FLOW_STREAM_BRIDGE_REDIS_URL automatically,
|
|
# so Docker deployments use Redis Streams even if this section is omitted.
|
|
#
|
|
# The redis bridge requires the optional `redis` extra. It is auto-detected from
|
|
# this section on `make dev`, and always installed in the Docker image. To install
|
|
# it manually: cd backend && uv sync --all-packages --extra redis
|
|
#
|
|
# stream_bridge:
|
|
# type: memory # single-process only
|
|
# queue_maxsize: 256 # data events retained per run. A reconnect
|
|
# # older than this window receives SSE `gap`.
|
|
#
|
|
# stream_bridge:
|
|
# type: redis # recommended for Docker / multi-worker gateway
|
|
# redis_url: redis://redis:6379/0
|
|
# queue_maxsize: 256 # data events retained per run (Redis MAXLEN).
|
|
# # Older valid cursors receive SSE `gap`.
|
|
# stream_ttl_seconds: 86400 # rolling TTL for retained stream buffers.
|
|
# # Refreshed on each publish/publish_end; set 0
|
|
# # to disable. This is not a run timeout.
|
|
# recovered_stream_cleanup_delay_seconds: 60 # seconds to wait after
|
|
# # publishing END for a recovered orphan run
|
|
# # before deleting the stream key.
|
|
# max_connections: 100 # optional pool ceiling. Each live SSE client
|
|
# # holds one connection blocked in XREAD ... BLOCK
|
|
# # for up to heartbeat_interval (15s), so hundreds
|
|
# # of concurrent clients open hundreds of
|
|
# # connections. Unset = redis-py default (unbounded).
|
|
#
|
|
# NOTE: the redis bridge is fail-hard in v1. Redis.from_url is lazy, so a down
|
|
# Redis does not block gateway startup, but the first publish/xread raises. A
|
|
# mid-run Redis outage fails the active run — there is no automatic retry/backoff
|
|
# or fallback to the in-memory bridge. Run Redis with HA / a restart policy.
|
|
|
|
# ============================================================================
|
|
# User-Owned IM Channel Connections
|
|
# ============================================================================
|
|
# Lets logged-in users connect their own IM accounts from the DeerFlow frontend
|
|
# while reusing the existing `channels` runtime configuration below.
|
|
#
|
|
# Security notes:
|
|
# - No public IP, OAuth callback URL, or provider webhook is required.
|
|
# - Provider bot/app credentials stay under `channels.*`.
|
|
# - `channel_connections` stores per-user bindings and one-time connect codes.
|
|
# - Telegram uses a deep link when `bot_username` is configured.
|
|
# - Slack, Discord, Feishu, DingTalk, WeChat, and WeCom use `/connect <code>`
|
|
# through the already-running bot/app.
|
|
#
|
|
# channel_connections:
|
|
# enabled: false
|
|
# # Security: keep this enabled unless you intentionally want legacy open-bot behavior.
|
|
# # Disabling it lets unbound external IM users create DeerFlow threads/runs.
|
|
# require_bound_identity: true
|
|
#
|
|
# telegram:
|
|
# enabled: false
|
|
# bot_username: $TELEGRAM_BOT_USERNAME
|
|
#
|
|
# slack:
|
|
# enabled: false
|
|
#
|
|
# discord:
|
|
# enabled: false
|
|
#
|
|
# feishu:
|
|
# enabled: false
|
|
#
|
|
# dingtalk:
|
|
# enabled: false
|
|
#
|
|
# wechat:
|
|
# enabled: false
|
|
#
|
|
# wecom:
|
|
# enabled: false
|
|
|
|
# ============================================================================
|
|
# IM Channels Configuration
|
|
# ============================================================================
|
|
# Connect DeerFlow to external messaging platforms.
|
|
# All channels use outbound connections (WebSocket or polling) — no public IP required.
|
|
|
|
# channels:
|
|
# # LangGraph-compatible Gateway API base URL for thread/message management (default: http://localhost:8001/api)
|
|
# # For Docker deployments, use the Docker service name instead of localhost:
|
|
# # langgraph_url: http://gateway:8001/api
|
|
# # gateway_url: http://gateway:8001
|
|
# langgraph_url: http://localhost:8001/api
|
|
# # Gateway API URL for auxiliary queries like /models, /memory (default: http://localhost:8001)
|
|
# gateway_url: http://localhost:8001
|
|
# #
|
|
# # Docker Compose note:
|
|
# # If channels run inside the gateway container, use container DNS names instead
|
|
# # of localhost, for example:
|
|
# # langgraph_url: http://gateway:8001/api
|
|
# # gateway_url: http://gateway:8001
|
|
# # You can also set DEER_FLOW_CHANNELS_LANGGRAPH_URL / DEER_FLOW_CHANNELS_GATEWAY_URL.
|
|
#
|
|
# # Optional: default mobile/session settings for all IM channels
|
|
# session:
|
|
# assistant_id: lead_agent # or a custom agent name; custom agents route via lead_agent + agent_name
|
|
# config:
|
|
# recursion_limit: 100
|
|
# context:
|
|
# thinking_enabled: true
|
|
# is_plan_mode: false
|
|
# subagent_enabled: false
|
|
#
|
|
# feishu:
|
|
# enabled: false
|
|
# app_id: $FEISHU_APP_ID
|
|
# app_secret: $FEISHU_APP_SECRET
|
|
# # domain: https://open.feishu.cn # China (default)
|
|
# # domain: https://open.larksuite.com # International
|
|
#
|
|
# slack:
|
|
# enabled: false
|
|
# bot_token: $SLACK_BOT_TOKEN # xoxb-...
|
|
# app_token: $SLACK_APP_TOKEN # xapp-... (Socket Mode)
|
|
# allowed_users: [] # empty = allow all; can also be a single Slack user ID string, e.g. U123456, but list form is recommended
|
|
#
|
|
# telegram:
|
|
# enabled: false
|
|
# bot_token: $TELEGRAM_BOT_TOKEN
|
|
# allowed_users: [] # empty = allow all
|
|
#
|
|
# wechat:
|
|
# enabled: false
|
|
# bot_token: $WECHAT_BOT_TOKEN
|
|
# ilink_bot_id: $WECHAT_ILINK_BOT_ID
|
|
# # Optional: allow first-time QR bootstrap when bot_token is absent
|
|
# qrcode_login_enabled: true
|
|
# # Optional: sent as iLink-App-Id header when provided
|
|
# ilink_app_id: ""
|
|
# # Optional: sent as SKRouteTag header when provided
|
|
# route_tag: ""
|
|
# allowed_users: [] # empty = allow all
|
|
# # Optional: timing values must be positive finite seconds
|
|
# polling_timeout: 35
|
|
# polling_retry_delay: 5
|
|
# # QR poll interval when qrcode_login_enabled is true
|
|
# qrcode_poll_interval: 2
|
|
# # QR bootstrap timeout
|
|
# qrcode_poll_timeout: 180
|
|
# # Optional: persist getupdates cursor under the gateway container volume
|
|
# state_dir: ./.deer-flow/wechat/state
|
|
# # Optional: max inbound image size in bytes before skipping download
|
|
# max_inbound_image_bytes: 20971520
|
|
# # Optional: max outbound image size in bytes before skipping upload
|
|
# max_outbound_image_bytes: 20971520
|
|
# # Optional: max inbound file size in bytes before skipping download
|
|
# max_inbound_file_bytes: 52428800
|
|
# # Optional: max outbound file size in bytes before skipping upload
|
|
# max_outbound_file_bytes: 52428800
|
|
# # Optional: allowed file extensions for regular file receive/send
|
|
# allowed_file_extensions: [".txt", ".md", ".pdf", ".csv", ".json", ".yaml", ".yml", ".xml", ".html", ".log", ".zip", ".doc", ".docx", ".xls", ".xlsx", ".ppt", ".pptx", ".rtf"]
|
|
#
|
|
# # Optional: channel-level session overrides
|
|
# session:
|
|
# assistant_id: mobile-agent # custom agent names are supported here too
|
|
# context:
|
|
# thinking_enabled: false
|
|
#
|
|
# # Optional: per-user overrides by user_id
|
|
# users:
|
|
# "123456789":
|
|
# assistant_id: vip-agent
|
|
# config:
|
|
# recursion_limit: 150
|
|
# context:
|
|
# thinking_enabled: true
|
|
# subagent_enabled: true
|
|
# wecom:
|
|
# enabled: false
|
|
# bot_id: $WECOM_BOT_ID
|
|
# bot_secret: $WECOM_BOT_SECRET
|
|
#
|
|
# dingtalk:
|
|
# enabled: false
|
|
# client_id: $DINGTALK_CLIENT_ID
|
|
# client_secret: $DINGTALK_CLIENT_SECRET
|
|
# allowed_users: [] # empty = allow all
|
|
# card_template_id: "" # Optional: AI Card template ID for streaming updates
|
|
#
|
|
# discord:
|
|
# enabled: false
|
|
# bot_token: $DISCORD_BOT_TOKEN
|
|
# allowed_guilds: [] # empty = allow all guilds; can also be a single guild ID
|
|
# mention_only: false # If true, only respond when the bot is mentioned
|
|
# allowed_channels: [] # Optional: channel IDs exempt from mention_only (bot responds without mention)
|
|
# thread_mode: false # If true, group a channel conversation into a thread
|
|
|
|
# ============================================================================
|
|
# Guardrails Configuration
|
|
# ============================================================================
|
|
# Optional pre-execution authorization for tool calls.
|
|
# When enabled, every tool call passes through the configured provider
|
|
# before execution. Three options: built-in allowlist, OAP policy provider,
|
|
# or custom provider. See backend/docs/GUARDRAILS.md for full documentation.
|
|
#
|
|
# Providers are loaded by class path via resolve_variable (same as models/tools).
|
|
|
|
# --- Option 1: Built-in AllowlistProvider (zero external deps) ---
|
|
# guardrails:
|
|
# enabled: true
|
|
# provider:
|
|
# use: deerflow.guardrails.builtin:AllowlistProvider
|
|
# config:
|
|
# denied_tools: ["bash", "write_file"]
|
|
|
|
# --- Option 2: OAP passport provider (open standard, any implementation) ---
|
|
# The Open Agent Passport (OAP) spec defines passport format and decision codes.
|
|
# Any OAP-compliant provider works. Example using APort (reference implementation):
|
|
# pip install aport-agent-guardrails && aport setup --framework deerflow
|
|
# guardrails:
|
|
# enabled: true
|
|
# provider:
|
|
# use: aport_guardrails.providers.generic:OAPGuardrailProvider
|
|
|
|
# --- Option 3: Custom provider (any class with evaluate/aevaluate methods) ---
|
|
# guardrails:
|
|
# enabled: true
|
|
# provider:
|
|
# use: my_package:MyGuardrailProvider
|
|
# config:
|
|
# key: value
|
|
|
|
# ============================================================================
|
|
# Authorization Configuration
|
|
# ============================================================================
|
|
# Fine-grained resource authorization (RBAC and beyond). Disabled by default;
|
|
# every authenticated user has access to all resources.
|
|
# See RFC: https://github.com/bytedance/deer-flow/issues/4063
|
|
#
|
|
# authorization:
|
|
# enabled: true
|
|
# fail_closed: true # block on provider error / unresolved identity
|
|
# default_role: user # applied when user_role is None; built-in RBAC requires this role below
|
|
# provider:
|
|
# use: deerflow.authz.rbac:RbacAuthorizationProvider
|
|
# config:
|
|
# # A known role with no policy for a resource is unrestricted for it.
|
|
# # Define both `tools` and `routes` wherever access should be constrained.
|
|
# roles:
|
|
# admin:
|
|
# tools: {allow: "*"}
|
|
# routes: {allow: "*"}
|
|
# user:
|
|
# tools: {allow: "*", deny: ["update_agent"]}
|
|
# routes: {allow: "*"}
|
|
# guest:
|
|
# tools: {allow: ["web_search", "read_file"]}
|
|
# routes: {allow: ["threads:read", "runs:read"]}
|
|
authorization:
|
|
enabled: false
|
|
|
|
# ============================================================================
|
|
# Circuit Breaker Configuration
|
|
# ============================================================================
|
|
# Circuit breaker for LLM calls prevents repeated requests to a failing provider.
|
|
# When the failure threshold is reached, subsequent calls fast-fail until recovery.
|
|
#
|
|
# This is useful for:
|
|
# - Avoiding rate-limit bans during provider outages
|
|
# - Reducing resource exhaustion from retry loops
|
|
# - Gracefully degrading when LLM services are unavailable
|
|
|
|
# circuit_breaker:
|
|
# # Number of consecutive failures before opening the circuit (default: 5)
|
|
# failure_threshold: 5
|
|
# # Time in seconds before attempting to recover (default: 60)
|
|
# recovery_timeout_sec: 60
|
|
|
|
# ============================================================================
|
|
# LLM Call Concurrency Configuration
|
|
# ============================================================================
|
|
# Cap the number of concurrently in-flight LLM calls process-wide. A provider
|
|
# burst-rate (limit_burst_rate) error fires on the *slope* of the request rate,
|
|
# not on a static quota - so the morning peak (e.g. 08:30) ramping from ~0 to
|
|
# full throttle in seconds gets rejected even when total RPM is within budget.
|
|
# Capping concurrency caps that slope. Retries alone make it worse (they add
|
|
# demand inside the very burst being throttled); pair this cap with the
|
|
# decorrelated-jitter backoff already built into the LLM error-handling
|
|
# middleware, and ideally an nginx `limit_req` at the ingress.
|
|
#
|
|
# 0 disables the cap (default) - existing deployments see no behavior change.
|
|
#
|
|
# Per-process, not per-cluster: the cap bounds in-flight LLM calls within ONE
|
|
# gateway process. With GATEWAY_WORKERS > 1 the aggregate cap across the
|
|
# deployment is effectively `max_concurrent_calls * GATEWAY_WORKERS`, and a
|
|
# multi-node rollout multiplies it further - size the per-process value with
|
|
# that in mind (and pair it with an nginx `limit_req` at the ingress for a
|
|
# true cluster-wide slope cap).
|
|
#
|
|
# Startup-only: the cap is captured at the first LLM run and frozen for the
|
|
# process lifetime. Editing `max_concurrent_calls` here takes effect only after
|
|
# a gateway restart; the other `llm_call.*` knobs below remain hot-reloadable.
|
|
# Freezing the cap avoids the downscale and config-freshness races that a
|
|
# runtime-mutable, process-wide/cross-loop limiter would otherwise hit (a
|
|
# lowered cap could keep admitting queued waiters, or a stale config snapshot
|
|
# constructed after a fresher one could restore a higher cap).
|
|
|
|
# llm_call:
|
|
# # Max concurrently in-flight LLM calls across the whole process (default: 0 = disabled)
|
|
# max_concurrent_calls: 0
|
|
# # Max LLM call attempts for retriable transient errors, 1 = no retry (default: 3)
|
|
# retry_max_attempts: 3
|
|
# # Base delay (ms) for the decorrelated-jitter retry backoff (default: 1000)
|
|
# retry_base_delay_ms: 1000
|
|
# # Hard cap (ms) on any single retry backoff delay (default: 8000)
|
|
# retry_cap_delay_ms: 8000
|
|
# # Backoff base (ms) used ONLY for burst-rate (limit_burst_rate) 429s - higher
|
|
# # than retry_base_delay_ms so the single burst retry lands after the throttle
|
|
# # window subsides. Ignored when the provider sends Retry-After (default: 5000)
|
|
# burst_retry_base_delay_ms: 5000
|
|
|
|
# ============================================================================
|
|
# SSO / OIDC Authentication (optional)
|
|
# ============================================================================
|
|
# Enable SSO login via any OIDC-compatible provider (Keycloak, Google, Azure AD, Okta, etc.).
|
|
# When enabled, the login page will show SSO buttons alongside the standard email/password form.
|
|
#
|
|
# Provider configuration:
|
|
# - issuer: The OIDC issuer URL (e.g. https://keycloak.example.com/realms/deerflow)
|
|
# - client_id: OAuth2 client ID from the provider
|
|
# - client_secret: OAuth2 client secret ($ENV_VAR references supported)
|
|
# - redirect_uri: Callback URL. In production, this must match what you configure in
|
|
# the provider. Defaults to a self-derived URL in development.
|
|
#
|
|
# Keycloak setup:
|
|
# 1. Create a client with type "confidential" and Standard Flow enabled
|
|
# 2. Add Valid Redirect URI: http://localhost:8001/api/v1/auth/callback/keycloak
|
|
# 3. Add Web Origin: http://localhost:8001 (or your frontend origin)
|
|
|
|
# ============================================================================
|
|
# Local (email/password) authentication
|
|
# ============================================================================
|
|
# Self-registration via POST /api/v1/auth/register is open by default: anyone
|
|
# who can reach the Gateway may create a regular user account.
|
|
#
|
|
# The OIDC provisioning policy below (allowed_email_domains, require_verified_email,
|
|
# auto_create_users) is enforced only in the SSO callback. It does NOT constrain local
|
|
# registration, so on an SSO-provisioned deployment leaving this open lets a visitor
|
|
# create an account outside that policy. Set allow_registration: false there.
|
|
#
|
|
# The first admin account is always created through /initialize regardless of this
|
|
# setting, so turning it off cannot lock you out of a fresh install.
|
|
|
|
# auth:
|
|
# local:
|
|
# allow_registration: false
|
|
#
|
|
# oidc:
|
|
# enabled: true
|
|
# # Base URL of the frontend, used for redirects after SSO callback.
|
|
# # In production behind a reverse proxy, set this to the public frontend URL
|
|
# # (e.g. https://deerflow.example.com). In development, leave unset.
|
|
# # frontend_base_url: http://localhost:3000
|
|
# providers:
|
|
# keycloak:
|
|
# display_name: Keycloak
|
|
# issuer: https://keycloak.example.com/realms/deerflow
|
|
# client_id: deerflow
|
|
# client_secret: $KEYCLOAK_CLIENT_SECRET
|
|
# # Optional: explicitly set the callback URL.
|
|
# # redirect_uri: https://deerflow.example.com/api/v1/auth/callback/keycloak
|
|
# scopes:
|
|
# - openid
|
|
# - email
|
|
# - profile
|
|
# token_endpoint_auth_method: client_secret_post
|
|
#
|
|
# # User provisioning settings (safe defaults shown below):
|
|
# auto_create_users: true # Auto-create DeerFlow account on first SSO login
|
|
# require_verified_email: true # Reject SSO logins without verified email
|
|
# # allowed_email_domains: # Restrict to specific email domains
|
|
# # - example.com
|
|
# admin_emails: [] # Auto-grant admin role to these emails
|
|
#
|
|
# # Security features (enabled by default):
|
|
# pkce_enabled: true # PKCE (S256) for authorization code flow
|
|
# nonce_enabled: true # Nonce validation in ID tokens
|