feat: paginate candidate model recommendations

2026-09-01 09:48:01 +08:00
parent d97b788e0e
commit 8a695900f3
9 changed files with 598 additions and 52 deletions
--- a/shared/runtime/README.md
+++ b/shared/runtime/README.md
@@ -48,13 +48,26 @@ messages are ignored silently: the bridge sends no Feishu reply, makes no API
 request, and appends no record. Only a message containing exactly one complete,
 rule-valid eRob model and exactly one positive quantity enters the query workflow.
 This gate applies even when the bot receives every message in a group; an @mention
-alone does not bypass it. The bridge invokes only the existing controlled
-delivery-prediction script. It generates the full Cartesian
+alone does not bypass it. After a valid initial query, the same sender in the same
+chat may ask whether there are other candidate models. The bridge keeps that
+continuation context in memory for six hours, never shares it across senders or
+chats, and stays silent if no matching context exists. A bridge restart clears
+the context, so the sender must resend the complete model and quantity. The
+continuation wording is flexible: `还有吗`, `有没有别的`, `再推荐几个`, `继续`,
+`下一批`, and `more candidates` are examples rather than fixed commands. The
+bridge still requires both continuation intent and valid context, so unrelated
+phrases such as `more interesting` or `继续查询英语例句` do not trigger the old query.
+
+The bridge invokes only the existing controlled delivery-prediction script. It
+generates the full Cartesian
 set of candidates allowed by the packaged Skill: brake upgrades, encoder
 upgrades, sensor upgrades, low-temperature grease upgrades, and DZ/LF reducer
 brand variants. Strong constraints and version stay unchanged. The original
-model is queried first; valid candidates are reported in rule order, while
-missing or unsupported candidates are summarized under `不可用候选`.
+model is queried first as a baseline and does not count toward the recommendation
+batch. The first reply queries at most four candidate models; a valid continuation
+queries the next four without repeating earlier candidates or the original
+baseline. Valid candidates are reported in rule order, while missing or
+unsupported candidates are summarized under `不可用候选`.

 On a managed network, the bridge uses the macOS system trust store. The proxy
 root certificate must be installed and trusted under the AR51-approved network-access procedure; never disable TLS
--- a/shared/runtime/feishu_bot_bridge.py
+++ b/shared/runtime/feishu_bot_bridge.py
@@ -9,6 +9,7 @@ import re
 import subprocess
 import sys
 import threading
+import time
 import unicodedata
 from dataclasses import dataclass
 from datetime import datetime
@@ -76,6 +77,77 @@ ALLOWED_VERSIONS = {
    "170F": {"V3"},
    "170H": {"V3"},
 }
+CANDIDATE_BATCH_SIZE = 4
+CANDIDATE_CONTINUATION_TTL_SECONDS = 6 * 60 * 60
+CANDIDATE_CONTINUATION_SHORT_PHRASES = {
+    "还有吗",
+    "还有呢",
+    "还有没有",
+    "有没有",
+    "有吗",
+    "其他呢",
+    "其他的呢",
+    "别的呢",
+    "剩下的呢",
+    "余下的呢",
+    "后面的呢",
+    "继续",
+    "继续吧",
+    "继续看",
+    "继续看看",
+    "继续推荐",
+    "接着来",
+    "接着看",
+    "再来几个",
+    "再给几个",
+    "再给我几个",
+    "再推荐几个",
+    "再查几个",
+    "再看几个",
+    "再看看",
+    "多来几个",
+    "多推荐几个",
+    "推荐更多",
+    "更多",
+    "下一批",
+    "下一组",
+    "换一批",
+    "再来一批",
+    "下一个",
+    "往下看",
+}
+CANDIDATE_CONTINUATION_PATTERNS = (
+    re.compile(
+        r"(?:还有没有|还有|是否还有|有没有|有无)"
+        r"(?:其他|别的|更多|剩余|余下|后续|类似)?(?:的)?"
+        r"(?:候选型号|候选|型号|方案|选择|选项|可选项|替代型号|替代方案|推荐)"
+    ),
+    re.compile(
+        r"(?:继续|接着|再|多)(?:推荐|查询|查看|展示|看看|看|给|来).{0,6}"
+        r"(?:其他|别的|更多|剩余|余下|后续)?(?:的)?"
+        r"(?:候选型号|候选|型号|方案|选择|选项|可选项|替代型号|替代方案)"
+    ),
+    re.compile(
+        r"(?:候选型号|候选|型号|方案|选择|选项|可选项|替代型号|替代方案)"
+        r".{0,6}(?:还有|有吗|更多|其他|别的|剩余|余下|继续|再来)"
+    ),
+    re.compile(
+        r"(?:还有|有没有)(?:别的|其他|更多|新的|剩余|余下|类似)"
+        r"(?:的)?(?:吗|呢|有吗)?$"
+    ),
+    re.compile(r"(?:还有|有没有)(?:哪些|什么)(?:其他)?(?:候选|型号|方案|选择|选项|推荐)?$"),
+    re.compile(
+        r"(?:可以|请|麻烦|帮我)?(?:再|多)(?:推荐|查询|查看|看|给|来)"
+        r"(?:我)?(?:几个|一些)(?:候选|型号|方案|选择|选项)?(?:吗|吧)?$"
+    ),
+    re.compile(r"(?:下一批|下一组)(?:候选|型号|方案|选择|选项)?$"),
+    re.compile(r"(?:换|再来|再给我)(?:一批|一组|几个|一些)(?:候选|型号|方案|选择|选项)?(?:吗|吧)?$"),
+    re.compile(r"(?:more|other|remaining|next)(?:candidates?|models?|options?|alternatives?|batch)"),
+    re.compile(
+        r"(?:continue|showme|giveme|recommend)(?:more|other|remaining)?"
+        r"(?:candidates?|models?|options?|alternatives?)"
+    ),
+)


@dataclass(frozen=True)
@@ -84,6 +156,14 @@ class RequestInput:
    quantity: int


+@dataclass(frozen=True)
+class CandidateContinuation:
+    request: RequestInput
+    next_offset: int
+    total_candidates: int
+    expires_at: float
+
+
 class InputError(ValueError):
    pass

@@ -92,6 +172,10 @@ class CandidateUnavailableError(RuntimeError):
    pass


+_candidate_continuations: dict[str, CandidateContinuation] = {}
+_candidate_continuation_lock = threading.Lock()
+
+
 def load_dotenv() -> None:
    """Load simple KEY=VALUE pairs from the ignored local .env file."""
    env_file = PROJECT_ROOT / ".env"
@@ -166,6 +250,69 @@ def parse_trigger_request(text: str) -> RequestInput | None:
        return None


+def is_candidate_continuation_request(text: str) -> bool:
+    normalized_text = unicodedata.normalize("NFKC", text).lower()
+    compact_text = re.sub(r"[\s，。！？、；：,.!?;:]+", "", normalized_text)
+    compact_text = re.sub(r"^(?:@?_user_\d+)+", "", compact_text)
+    if compact_text in CANDIDATE_CONTINUATION_SHORT_PHRASES:
+        return True
+    return any(pattern.search(compact_text) for pattern in CANDIDATE_CONTINUATION_PATTERNS)
+
+
+def conversation_key(data: lark.im.v1.P2ImMessageReceiveV1) -> str | None:
+    event = getattr(data, "event", None)
+    message = getattr(event, "message", None)
+    sender = getattr(event, "sender", None)
+    sender_id = getattr(sender, "sender_id", None)
+    chat_id = getattr(message, "chat_id", None)
+    open_id = getattr(sender_id, "open_id", None)
+    if not isinstance(chat_id, str) or not chat_id:
+        return None
+    if not isinstance(open_id, str) or not open_id:
+        return None
+    return f"{chat_id}:{open_id}"
+
+
+def clear_candidate_continuation(key: str | None) -> None:
+    if not key:
+        return
+    with _candidate_continuation_lock:
+        _candidate_continuations.pop(key, None)
+
+
+def remember_candidate_continuation(
+    key: str | None,
+    request: RequestInput,
+    next_offset: int,
+    total_candidates: int,
+) -> None:
+    if not key:
+        return
+    with _candidate_continuation_lock:
+        if next_offset >= total_candidates:
+            _candidate_continuations.pop(key, None)
+            return
+        _candidate_continuations[key] = CandidateContinuation(
+            request=request,
+            next_offset=next_offset,
+            total_candidates=total_candidates,
+            expires_at=time.monotonic() + CANDIDATE_CONTINUATION_TTL_SECONDS,
+        )
+
+
+def get_candidate_continuation(key: str | None) -> CandidateContinuation | None:
+    if not key:
+        return None
+    with _candidate_continuation_lock:
+        state = _candidate_continuations.get(key)
+        if state is None:
+            return None
+        if state.expires_at <= time.monotonic():
+            _candidate_continuations.pop(key, None)
+            return None
+        return state
+
+
 def build_model(fields: dict[str, str]) -> str:
    closing_bracket = "]" if fields["bracket"] == "[" else ")"
    return (
@@ -663,25 +810,39 @@ def write_record(
        file.write(record)


-def build_report(request: RequestInput) -> str:
-    baseline_payload = run_controlled_query(request)
-    baseline = lead_time_details(baseline_payload, request.quantity)
-    if not baseline["has_lead_time"]:
-        raise RuntimeError("原型号接口未返回可用交期汇总，未生成候选结果。")
+def build_report(request: RequestInput, candidate_offset: int = 0) -> str:
+    if candidate_offset < 0:
+        raise InputError("候选批次位置无效，请重新发起型号和数量查询。")

-    candidates = [
-        {
-            "index": 1,
-            "model": request.model,
-            "type": "原型号，DZ" if "[" in request.model else "原型号，LF",
-            "details": baseline,
-            "reason": "原始需求基准，用于交期测算与候选比较。",
-            "difference": "无",
-            "confirmation": "无型号差异；需确认正式交付节点和承诺边界。",
-        }
+    all_candidate_specs = generate_candidate_specs(request.model)
+    candidate_specs = all_candidate_specs[
+        candidate_offset : candidate_offset + CANDIDATE_BATCH_SIZE
    ]
+    is_initial_batch = candidate_offset == 0
+    if not is_initial_batch and not candidate_specs:
+        return f"AM516 已无其他规则候选型号。\n\n{DISCLAIMER}"
+
+    candidates: list[dict[str, Any]] = []
+    baseline: dict[str, Any] | None = None
+    if is_initial_batch:
+        baseline_payload = run_controlled_query(request)
+        baseline = lead_time_details(baseline_payload, request.quantity)
+        if not baseline["has_lead_time"]:
+            raise RuntimeError("原型号接口未返回可用交期汇总，未生成候选结果。")
+        candidates.append(
+            {
+                "index": 1,
+                "record_order": 1,
+                "model": request.model,
+                "type": "原型号，DZ" if "[" in request.model else "原型号，LF",
+                "details": baseline,
+                "reason": "原始需求基准，用于交期测算与候选比较。",
+                "difference": "无",
+                "confirmation": "无型号差异；需确认正式交付节点和承诺边界。",
+            }
+        )
+
    unavailable: list[dict[str, str]] = []
-    candidate_specs = generate_candidate_specs(request.model)

    def query_candidate(spec: dict[str, str]) -> tuple[dict[str, str], dict[str, Any] | None]:
        try:
@@ -691,40 +852,77 @@ def build_report(request: RequestInput) -> str:
        details = lead_time_details(payload, request.quantity)
        return spec, details if details["has_lead_time"] else None

-    with concurrent.futures.ThreadPoolExecutor(max_workers=6) as executor:
-        future_map = {
-            executor.submit(query_candidate, spec): spec for spec in candidate_specs
-        }
-        for future in concurrent.futures.as_completed(future_map):
-            spec, details = future.result()
-            if details is None:
-                unavailable.append(spec)
-                continue
-            candidates.append({**spec, "details": details})
+    if candidate_specs:
+        with concurrent.futures.ThreadPoolExecutor(
+            max_workers=min(CANDIDATE_BATCH_SIZE, len(candidate_specs))
+        ) as executor:
+            future_map = {
+                executor.submit(query_candidate, spec): spec for spec in candidate_specs
+            }
+            for future in concurrent.futures.as_completed(future_map):
+                spec, details = future.result()
+                if details is None:
+                    unavailable.append(spec)
+                    continue
+                candidates.append({**spec, "details": details})

-    candidate_order = {spec["model"]: index for index, spec in enumerate(candidate_specs)}
-    candidates[1:] = sorted(candidates[1:], key=lambda item: candidate_order[item["model"]])
+    candidate_order = {
+        spec["model"]: index for index, spec in enumerate(all_candidate_specs)
+    }
+    candidate_start = 1 if is_initial_batch else 0
+    candidates[candidate_start:] = sorted(
+        candidates[candidate_start:], key=lambda item: candidate_order[item["model"]]
+    )
    unavailable.sort(key=lambda item: candidate_order[item["model"]])
-    candidates[0]["record_order"] = 1
-    for candidate in candidates[1:]:
+    for candidate in candidates[candidate_start:]:
        candidate["record_order"] = candidate_order[candidate["model"]] + 2
+        candidate["index"] = candidate["record_order"]
    for candidate in unavailable:
        candidate["record_order"] = candidate_order[candidate["model"]] + 2
-    for index, candidate in enumerate(candidates, start=1):
-        candidate["index"] = index

    generation_time = datetime.now().astimezone()
    write_record(request, candidates, unavailable, generation_time)
-    data_timestamp = baseline["timestamp"] or f"{generation_time:%Y-%m-%d %H:%M}"
+    data_timestamp = (
+        baseline["timestamp"]
+        if baseline and baseline["timestamp"]
+        else next(
+            (
+                candidate["details"]["timestamp"]
+                for candidate in candidates
+                if candidate["details"].get("timestamp")
+            ),
+            f"{generation_time:%Y-%m-%d %H:%M}",
+        )
+    )
+    queried_end = candidate_offset + len(candidate_specs)
+    remaining_count = len(all_candidate_specs) - queried_end
+    if is_initial_batch:
+        batch_scope = (
+            f"本次先推荐{len(candidate_specs)}个候选型号（原型号另作基准）"
+            if remaining_count
+            else f"本次已推荐全部{len(candidate_specs)}个候选型号（原型号另作基准）"
+        )
+    else:
+        batch_scope = f"本次继续推荐第{candidate_offset + 1}-{queried_end}个候选型号"
+    if remaining_count:
+        batch_scope += f"；尚有{remaining_count}个规则候选未查询"
+    else:
+        batch_scope += "；规则候选已全部查询"
+
    report_lines = [
-        f"关节模组交期预估报告 | {generation_time:%Y-%m-%d %H:%M}",
+        (
+            f"关节模组交期预估报告 | {generation_time:%Y-%m-%d %H:%M}"
+            if is_initial_batch
+            else f"关节模组交期预估报告 | {generation_time:%Y-%m-%d %H:%M}（其他候选）"
+        ),
        "",
        f"输入需求：{request.model}，{request.quantity}台",
        f"数据时间戳：{data_timestamp}",
        "状态：试运行版输出 / 内部候选",
        "判断等级：AM516算法预测参考，需人工复核",
+        f"候选范围：{batch_scope}",
        "",
-        "总体判断：",
+        "总体判断：" if is_initial_batch else "本批次判断：",
        *overall_judgment_lines(candidates),
        "",
    ]
@@ -739,6 +937,13 @@ def build_report(request: RequestInput) -> str:
        )
    else:
        report_lines.append("- 无（本次已查询候选均返回交期汇总）")
+    if remaining_count:
+        report_lines.append(
+            f"其他候选：尚有{remaining_count}个未查询；"
+            "如需继续，可说“还有吗”“再推荐几个”“继续”等类似表达。"
+        )
+    else:
+        report_lines.append("其他候选：规则候选已全部查询。")
    report_lines.extend(["", DISCLAIMER])
    return "\n".join(report_lines)

@@ -765,7 +970,10 @@ def is_allowed_sender(data: lark.im.v1.P2ImMessageReceiveV1) -> bool:

 def post_paragraph(line: str) -> list[dict[str, Any]]:
    element: dict[str, Any] = {"tag": "text", "text": line or " "}
-    if line == "总体判断：" or line == "不可用候选：" or re.match(r"^\d+\.\s+eRob", line):
+    if (
+        line in {"总体判断：", "本批次判断：", "不可用候选："}
+        or re.match(r"^\d+\.\s+eRob", line)
+    ):
        element["style"] = ["bold"]
    return [element]

@@ -831,16 +1039,42 @@ def handle_message(client: lark.Client, data: lark.im.v1.P2ImMessageReceiveV1) -
    if not text or not message_id:
        return

+    key = conversation_key(data)
    request = parse_trigger_request(text)
+    candidate_offset = 0
+    continuation_state: CandidateContinuation | None = None
+    if request is None and is_candidate_continuation_request(text):
+        continuation_state = get_candidate_continuation(key)
+        if continuation_state is not None:
+            request = continuation_state.request
+            candidate_offset = continuation_state.next_offset
    if request is None:
        logging.info(
-            "Feishu message ignored: no complete AM516 model-and-quantity request; message_id=%s",
+            "Feishu message ignored: no complete AM516 request or active candidate continuation; message_id=%s",
            message_id,
        )
        return

+    if continuation_state is None:
+        clear_candidate_continuation(key)
+
    try:
-        report = build_report(request)
+        report = (
+            build_report(request)
+            if candidate_offset == 0
+            else build_report(request, candidate_offset=candidate_offset)
+        )
+        total_candidates = (
+            continuation_state.total_candidates
+            if continuation_state is not None
+            else len(generate_candidate_specs(request.model))
+        )
+        remember_candidate_continuation(
+            key,
+            request,
+            min(candidate_offset + CANDIDATE_BATCH_SIZE, total_candidates),
+            total_candidates,
+        )
    except InputError as exc:
        report = f"AM516 内部候选查询已停止：{exc}\n\n{DISCLAIMER}"
    except RuntimeError as exc: