yang rui 3dc895df4d
feat(models): pace shared RPM budgets before dispatch (#5432)
* feat(models): add shared RPM admission queues

* fix(models): address admission pacing review feedback

* docs: simplify request admission quick start guidance

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-09-15 07:14:35 +08:00

102 lines
12 KiB
Markdown
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

### Configuration System
Custom Agent `AgentConfig.display_name` is an optional, whitespace-trimmed Unicode
label of at most 100 Unicode code points. C0/C1 controls and bidirectional
formatting controls (U+202AU+202E, U+2066U+2069) are rejected before trimming.
Also reject soft hyphen, Arabic letter mark, U+200B, U+200EU+200F,
U+2028U+2029, U+2060U+2065 and U+FEFF. Labels consisting only of
marks, separators or other invisible characters are invalid; ZWNJ/ZWJ remain
supported inside ordinary text and emoji.
It is stored in the existing config document by
both agent stores; it never participates in paths, routing, or authorization.
Gateway create/update/response models share its validation. It remains outside
`MANAGED_AGENT_CONFIG_FIELDS` so `update_agent` preserves it. `setup_agent`
explicitly carries forward the existing owner's display name when re-bootstrapping;
the Gateway explicitly overrides it when supplied, including null to clear.
Both stores use `parse_agent_config` to ignore only an invalid stored
`display_name` on read, logging the agent identifier without the invalid value
and without rewriting storage. Other config errors still
raise, and API create/update validation remains strict.
**Main Configuration** (`config.yaml`):
Setup: Copy `config.example.yaml` to `config.yaml` in the **project root** directory.
**Config Versioning**: `config.example.yaml` has a `config_version` field. On startup, `AppConfig.from_file()` compares user version vs example version and emits a warning if outdated. Missing `config_version` = version 0. Run `make config-upgrade` to auto-merge missing fields. When changing the config schema, bump `config_version` in `config.example.yaml`.
Top-level `recursion_limit` and `max_recursion_limit` are hot-reloaded per Gateway run. The former supplies the default when a request omits or provides an invalid value; the latter caps both configured and client-provided budgets.
**Config Caching**: `get_app_config()` caches the parsed config, but automatically reloads it when the resolved config path or file content signature changes. The signature includes file metadata and a content digest, so Gateway and LangGraph reads stay aligned with `config.yaml` edits even on object-store or network mounts where mtime can remain stale.
**Config Hot-Reload Boundary**: Gateway dependencies route through `get_app_config()` on every request, so per-run fields like `models[*].max_tokens`, `summarization.*`, `title.*`, `memory.*`, `subagents.*`, `verification.*`, `tools[*]`, and the agent system prompt pick up `config.yaml` edits on the next message. `AppConfig` is intentionally **not** cached on `app.state``lifespan()` keeps a local `startup_config` variable for one-shot bootstrap work and passes it to `langgraph_runtime(app, startup_config)`.
Infrastructure fields are **restart-required**. The authoritative list lives in `packages/harness/deerflow/config/reload_boundary.py::STARTUP_ONLY_FIELDS` and is mirrored by the standardised `"startup-only:"` prefix on the corresponding `Field(description=...)` in `AppConfig` or an explicitly registered nested config model, so IDE hover on those fields surfaces the reason inline (no need to context-switch into this table). Currently registered: `plugins`, `database`, `checkpointer`, `run_events`, `agent_storage`, `stream_bridge`, `sandbox`, `skills.container_path`, `log_level`, `logging`, `channels`, `channel_connections`, `scheduler`, `mcp_tasks`, `subagent_runtime`, `subagent_batches`, `run_ownership`, `dedupe_storage`. Adding a new restart-required field requires updating the registry; drift is pinned by `tests/test_reload_boundary.py`. `scheduler.recursion_limit` is the exception inside that section: it is read from `get_app_config()` at each scheduled dispatch, so a YAML edit applies to the next run without restarting the poller.
**Persistence backend resolution**: the unified `database` section selects the
Gateway's LangGraph checkpointer, LangGraph Store, and DeerFlow SQL repositories.
The deprecated `checkpointer` section remains backward compatible and, when
present, overrides `database` for the LangGraph checkpointer and Store only;
application repositories continue to use `database`.
Configuration priority:
1. Explicit `config_path` argument
2. `DEER_FLOW_CONFIG_PATH` environment variable
3. `config.yaml` in current directory (backend/)
4. `config.yaml` in parent directory (project root - **recommended location**)
Config values starting with `$` are resolved as environment variables (e.g., `$OPENAI_API_KEY`).
`ModelConfig` also declares `use_responses_api` and `output_version` so OpenAI `/v1/responses` can be enabled explicitly while still using `langchain_openai:ChatOpenAI`.
`ModelConfig.request_admission` is optional and is not a provider parameter.
Its positive RPM, finite wait deadline, queue bound and optional quota-group name
configure process-local model pacing. Models sharing an explicit group must use
identical policies. Restart after changing, disabling or regrouping an active
policy; conflicting policies fail construction rather than silently resetting
an active budget. This nested model option is enforced by its limiter registry,
not by the top-level infrastructure reload-boundary registry.
**Extensions Configuration** (`extensions_config.json`):
MCP servers and skills are configured together in `extensions_config.json` in project root:
Docker development mounts the project directory at `/app/project` and points
`DEER_FLOW_CONFIG_PATH` / `DEER_FLOW_EXTENSIONS_CONFIG_PATH` into that directory.
Keep mutable config files behind a directory bind mount: single-file bind mounts
can become stale or inaccessible when a host editor replaces a file on save.
Configuration priority:
1. Explicit `config_path` argument
2. `DEER_FLOW_EXTENSIONS_CONFIG_PATH` environment variable
3. `extensions_config.json` in current directory (backend/)
4. `extensions_config.json` in parent directory (project root - **recommended location**)
Extensions are optional only in the fallback *search* mode (priority 3-4 above): `ExtensionsConfig.resolve_config_path()` returns `None` when neither an explicit `config_path` nor `DEER_FLOW_EXTENSIONS_CONFIG_PATH` is given and the search locations find nothing. An explicit `config_path` argument or a set `DEER_FLOW_EXTENSIONS_CONFIG_PATH` (priority 1-2) is an operator assertion that one particular file must be used, so a missing file in either of those modes raises `FileNotFoundError` instead — including when the file existed earlier and has since been deleted. The MCP tools cache's staleness check (`deerflow.mcp.cache._resolve_config_path`) is a narrow, deliberate exception to that rule: it catches that `FileNotFoundError` locally and treats it as "unconfigured" so a previously-valid config disappearing mid-run degrades the cache to serving its last-known-good tools instead of raising out of a per-request hot path (see the MCP System section below).
### Config Schema
**`config.yaml`** key sections:
- `models[]` - LLM configs with `use` class path, `supports_thinking`, `supports_vision`, provider-specific fields
- `logging.enhance` - Log output only (`enabled`, `format`): whether log records carry a `trace_id` field, and in which format. Trace ids are issued unconditionally — the Gateway `X-Trace-Id` header and Langfuse `deerflow_trace_id` metadata are always present whatever this says (see the Request Trace Context section in `packages/harness/deerflow/AGENTS.md`); restart-required
- vLLM reasoning models should use `deerflow.models.vllm_provider:VllmChatModel`; for Qwen-style parsers prefer `when_thinking_enabled.extra_body.chat_template_kwargs.enable_thinking`, and DeerFlow will also normalize the older `thinking` alias
- `tools[]` - Tool configs with `use` variable path and `group`
- `tool_groups[]` - Logical groupings for tools
- `sandbox.use` - Sandbox provider class path
- `skills.path` / `skills.container_path` - Host and container paths to skills directory. AIO and E2B snapshot the container path at provider startup. Their local/remote backends and the Kubernetes provisioner require one canonical absolute non-root path outside reserved platform mounts; custom roots participate in deterministic sandbox identity, and E2B records the root in remote metadata.
- `skills.deferred_discovery` - When `true`, replaces the full-metadata `<available_skills>` prompt block with a compact `<skill_index>` (names only) and registers the `describe_skill` tool so the agent fetches metadata on demand. Defaults to `false` (legacy full-metadata injection)
- `title` - Auto-title generation (enabled, max_words, max_chars, model_name; null model_name uses fast local fallback, explicit model_name uses the prompt_template LLM path)
- `summarization` - Context summarization (enabled, trigger conditions, keep policy)
- `subagents.enabled` - Master switch for subagent delegation
- `subagent_runtime` - Startup-only shared process admission (`max_running`, bounded async wait queue, queue/reject policy, and queue timeout) for ordinary and durable-batch native subagents
- `subagent_batches` - Startup-only explicit durable batch scheduler limits (disabled by default), including separate total, live, and running dimensions plus leases/retries/result bounds
- `memory` - Memory system (enabled, storage_path, debounce_seconds, shutdown_flush_timeout_seconds, model_name, max_facts, fact_confidence_threshold, injection_enabled, max_injection_tokens, staleness_review_enabled, staleness_age_days, staleness_min_candidates, staleness_max_removals_per_cycle, staleness_protected_categories, staleness_max_lifetime_multiplier, staleness_max_extension_days)
**`extensions_config.json`**:
- `mcpServers` - Map of server name → config (enabled, type, command, args, env, url, headers, oauth, description, `routing`, `tools`, `tool_call_timeout`, `session_init_timeout`). `routing.mode="prefer"` emits `<mcp_routing_hints>` prompt guidance; if `tool_search` defers the hinted tool, `McpRoutingMiddleware` can also auto-promote matching deferred schemas before the model call. It does not hard-disable other tools. `session_init_timeout` (default `DEFAULT_MCP_SESSION_INIT_TIMEOUT` = 60s, `null` to disable) bounds server bring-up: tool discovery and persistent stdio session initialization, so a hung server cannot block agent construction indefinitely; durable HTTP/SSE task calls use it for their ephemeral session initialization too. `tool_call_timeout` bounds individual stdio calls and durable-task calls on every transport; other HTTP/SSE tools use transport-level timeouts.
- `tool_search.auto_promote_top_k` - Global MCP routing auto-promote breadth. Default `3`, clamped to `1..5`; applies only when `tool_search.enabled=true` and only to deferred MCP tools with `routing.mode="prefer"` and non-empty keywords. For lead agents the deferred catalog is built from the full configured MCP set; auto-promotion never grants authority because an active skill's runtime policy still filters model-visible schemas, `tool_search` results, and execution.
- `skills` - Map of skill name → state (enabled)
- `middlewares` - `AgentMiddleware` entries for lead and subagent runtime extension: class-path strings or `{class, kwargs}` objects. `kwargs` values must be JSON types; YAML dates and timestamps are coerced to ISO strings so they match JSON. `config.yaml -> extensions` can override these fields after validation; overrides are replace-per-field, not list concatenation.
Gateway API endpoints and `DeerFlowClient` methods can modify MCP servers and skill state at runtime; their `extensions_config.json` writes use the shared atomic replacement helper, while `middlewares` remains an operator-controlled config-file extension point.
Values beginning with `$` are resolved from the environment when the file is loaded, and an unset variable becomes `""`. Runtime writers (MCP router, skill toggle, `DeerFlowClient`) therefore read the raw file with `read_raw_extensions_config`, merge into it (`set_raw_skill_enabled` for skill state), check the candidate with `validate_raw_extensions_config`, and write that raw dict. They never serialize an `ExtensionsConfig` model back to disk: its resolved values would persist secrets in plaintext and erase the references. When the file does not exist yet, the Gateway skill toggle seeds only the cached skill states. `tests/test_extensions_config_raw_writes.py` and the placeholder tests in `tests/test_client.py` pin this.