- Select one storage backend per instance via AGENT_STORAGE, retaining
memory as the backward-compatible default. Manage the selected async
repository, official checkpointer and connection pools in lifespan;
fail startup on unavailable or uninitialized storage without fallback.
- Add SQLite and PostgreSQL adapters, schema initialization CLI, sample
PostgreSQL compose configuration and a Windows-compatible serve entry.
SQLite enforces single-instance file ownership; PostgreSQL uses a
dedicated pool for session advisory locks plus version/epoch fencing.
- Make repository IO and commit callbacks awaitable. Persist business
fields, a complete committed graph snapshot and turn result/version in
one business transaction before success. Rebuild execution checkpoints
from that snapshot, discarding uncommitted progress after interruption.
- Support optional Idempotency-Key on durable chat requests. Replay
committed results and return 409 on changed request content; delete
removes business/history data and replay records while retaining only
an epoch/version tombstone to reject stale commits.
- Document migration, database switching boundaries, backup/deployment
expectations and crash recovery. Ignore generated database files.
Validation: 315 tests passed with real SQLite and isolated PostgreSQL,
including abrupt child-process exits before/after business commit;
both backends passed CLI migration and actual HTTP server restart smoke.
Existing API tests were rechecked after isolating them from user storage.
An initial Windows CreateProcess permission failure did not recur in the
full diagnostic run; failure assertions were not skipped or relaxed.
Delete checkpoints before removing business fields. Suppress only an
explicit CheckpointNotFoundError; propagate storage failures and
cancellation so the endpoint cannot report false success. Prefer async
checkpoint deletion and fail clearly when cleanup is unsupported.
Classify SSE error events as 401 for authentication, 429 for rate limits,
and 500 for other failures, using the same fixed messages as non-stream
responses. Errors terminate the stream without a success done event or
provider exception text in the response.
Validation: 286 offline tests passed (19 added), including failed-delete
HTTP retry with preserved business/checkpoint state, explicit missing
threads, cancellation, missing cleanup capability, and HTTP SSE errors
before and after text output.
- Validate stage prefixes before forwarding model tokens. Invalid prefixes
may use the existing repair budget; once output starts, validation failure
aborts the turn without appending a regenerated reply. Bound the token
queue and close inner streams when consumption stops.
- Replace delete-time lock eviction with reference-counted session locks
covering holders and waiters. Serialize set/get with chat/stream/delete
and release cancelled waiters without replacing a live lock.
- Store person synonyms under workflow-native driver keys and expose
consistent alias views to single/group reads and graph prompt injection.
- Separate committed field patches from public formUpdate visibility.
Commit callbacks keep repository fields synchronized even when updates
are hidden or the consumer closes after graph completion.
- Disable OpenAI SDK automatic retries. Own bounded retry attempts in the
application, use 1/2/4 second backoff, retry streams only before text is
emitted, enforce attempt timeouts, and close upstream/client resources.
- Translate FastGPT SDK max_retries (total attempts) from the configured
extra-retry count, and verify the real SDK loop uses four attempts.
- Document the per-LLM budget and streaming failure semantics without
claiming the whole multi-call HTTP turn has the same timeout.
Validation: 267 offline tests passed, including actual SDK requests through
MockTransport, stream repair/abort, timeout/close, lock races, aliases and
formUpdate visibility; existing four dependency deprecation warnings.
FastGPT maintains full history server-side; LangGraph truncated the
injected history at a hardcoded 50 messages, so long conversations
behaved differently across backends.
- Config.AGENT_HISTORY_MESSAGES (env): max messages injected into the
model prompt (recent N, both roles counted); default 50 unchanged;
larger values support long conversations; 0 = no truncation, matching
FastGPT's full-history semantics. Only the injected window is
affected - dialogue stays fully persisted in the checkpoint.
- validate(): rejects negative values; 0 and positive accepted
- conversation_history reads the config (import-time class attribute,
monkeypatched in tests); explicit None-check keeps 0 falsy-safe
- .env.example documents the knob
Verified: 225 unit tests (6 new history-window tests)
Replaces the unequal SLA (LLM 30s/2 retries vs FastGPT client 60s/3)
that made the LangGraph backend look less stable under gray release.
- core/fastgpt_client: FASTGPT_TIMEOUT_SECONDS / FASTGPT_MAX_RETRIES
module constants (were inline literals in lifespan)
- agent/llm: OpenAILLMService defaults 60.0s / 3 retries
- core/config: named-profile fallback defaults 60/3 (prefixed and
JSON-dict forms)
- contract test test/backends/test_sla_alignment.py pins both sides to
the same constants so the SLA cannot drift apart again
- retry backoff intentionally differs (FastGPT fixed 1s vs LLM
exponential) and is documented; aligned parameters are per-call
timeout and max retry count
Verified: 215 unit tests (3 new SLA contract tests)
- fields_registry: 24 business keys in acd/human1/human2 groups with
value_type, writable and SensitiveLevel metadata; strict bool/int
parsing (no bool('0') trap); INTERNAL_FIELD_KEYS protection list
- repository: SessionRepository protocol + InMemorySessionRepository
(idempotent delete; PostgreSQL swap-in is assignment 7)
- AccidentAppService: chat/set_info/get_info/delete_session share one
business state - chat injects latest repository fields into the graph
and writes back validated field diffs; set/get/delete make zero LLM
calls and zero helper conversations (includeInputInfo accepted but
unused); unknown get keys keep the '' JSON-empty-string contract,
unknown set keys are rejected by whitelist
- ChatInput.injected_fields neutral contract extension; LangGraphBackend
merges injected fields into graph input (set_info visible next chat)
- endpoints: thin layer - langgraph mode routes business state through
the app service (fastgpt mode keeps the legacy path); delete cleans
repository + graph checkpoint, idempotent
- tests: registry completeness (sfzmwh/sjwh/csbw included), app service
combos with LLM-call spy, HTTP acceptance flow (set -> get -> chat ->
groups -> delete -> no leak, idempotent re-delete)
- docs/assignment6-compat.md: behavior diff list vs FastGPT status quo
and the audit backlog (arbitrary set_info key usage, stream formUpdate
write-back, sensitive-field display boundary)
Verified: 200 unit tests (172 existing + 28 new)
- Config.llm_profiles: LLM_PROVIDERS declares names, each group defined by
LLM_<NAME>_BASE_URL/_API_KEY/_MODEL (required) and optional _TIMEOUT_SECONDS/
_MAX_RETRIES/_TEMPERATURE/_EXTRA_BODY; JSON-dict form of LLM_PROVIDERS also
supported. LLM_PROVIDER selects the active group at runtime; empty/fake =
offline scripted model
- removed fixed openai/kimi groups (AGENT_LLM_PROVIDER, KIMI_LLM_*)
- validate(): incomplete groups and unknown LLM_PROVIDER fail fast with
the configured-name list
- OpenAILLMService: http client trust_env from LLM_HTTP_TRUST_ENV (default
False - local gateways must bypass the Windows system proxy)
- build_llm_service(provider): explicit name or LLM_PROVIDER default
- .env/.env.example: deepseek + kimi groups side by side, switch by
LLM_PROVIDER=kimi (thinking off via EXTRA_BODY reasoning_effort=none)
- eval probe scripts updated to the new config interface
Verified: 172 unit tests; live calls succeed on both providers
(deepseek 28s, kimi 6.6s, both emitting valid <state> prefixes)
- prompts/collection.md: versioned collection system prompt extracted
from workflow node yQaBxfrWjbRr with source/version/porting notes
- llm.py: LLMService protocol; FakeLLMService (scripted, records
calls); OpenAILLMService (async, wait_for timeout with cancellation,
retry only on timeout/429/connection, errors normalized)
- collect.py: run_collect reference impl - one LLM call produces
state prefix + body, controlled repair (max 1 retry) for missing
prefix or illegal stage proposal, whitelist guard, CollectReplyError
without raw model content; dialogue history + confirmed fields
injected into prompt so the model skips known info (作业4-5)
- fields.py / clock.py: three-state field candidates (unknown/
candidate/confirmed), per-type validation (count not inferred from
description, future time rejected), injectable Clock
- graph.py: welcome node - first message returns fixed 1001 greeting
without LLM (mirrors workflow is_first_message -> Assigned Reply#3),
route empty stage to welcome
- endpoints/delete_session: backend switch - langgraph clears graph
checkpoint, fastgpt path unchanged
- config: AGENT_LLM_PROVIDER fake|openai with validation
- untrack .env (secrets), move template to root .env.example
Verified:
- pytest 103 passed; smoke turns 1/2/1
- Real LLM e2e: POST /chat multi-turn context works
- Golden eval collection_skip_known_info: 12/12 cases pass
- Golden eval no_false: 8/10 cases pass; 4 confirm/photo cases fail
at final step - model routes on short reply '对' (prompt-adherence
gap, photo/confirm stages are assignment 5 scope); recorded in
evals/results/20261020-144856
Known limits: field extraction from model reply not wired (stub);
photo/confirm nodes still scaffold; clarify counting is approximate.
- src/backends/langgraph.py: LangGraphBackend implements ChatBackend;
complete() runs one graph turn per session (thread_id=sessionId) and
returns state-prefixed content; stream() emits the full state prefix
before body fragments (full-answer slicing, not yet real incremental
output - assignment 8)
- src/core/config.py: AGENT_BACKEND=fastgpt|langgraph, langgraph mode
no longer requires FastGPT credentials at startup
- src/core/fastgpt_client.py: lifespan builds the backend by switch
- test/backends/test_langgraph_backend.py: adapter acceptance tests
Verified:
- pytest: 48 passed
- AGENT_BACKEND=langgraph uvicorn: POST /chat -> 1002;
browser_addon -> browser_addon.1002; SSE = stage_code, text_delta,
single done
Known limit: stream slices a complete answer; no formUpdate deltas yet
(assignment 6).
- Replaced direct FastGPT client usage with a backend-neutral chat interface, allowing for improved flexibility and maintainability.
- Introduced a new `ChatBackend` protocol and implemented `FastGPTBackend` to handle chat operations.
- Updated the chat endpoint to utilize the new backend structure, enhancing the handling of chat requests and responses.
- Added comprehensive tests to ensure compatibility and functionality of the new backend integration.
Eric Wang