feat(backend): 生成PPT时预处理用户提示词

backend/app/gateway/services.py

@@ -10,12 +10,14 @@ from __future__ import annotations
 import asyncio
 import json
 import logging
+import os
 import re
 import time
 from typing import Any
 
 from fastapi import HTTPException, Request
 from langchain_core.messages import HumanMessage
+from openai import AsyncOpenAI
 
 from app.gateway.deps import get_checkpointer, get_run_manager, get_store, get_stream_bridge
 from deerflow.runtime import (
@@ -32,6 +34,17 @@ from deerflow.runtime import (
 )
 
 logger = logging.getLogger(__name__)
+# 预处理提示词的大模型
+
+PPT_INSUFFICIENT_INFO_FORWARD = "用户想生成ppt，但是没有输入足够多的信息，所以先向用户询问更多信息"
+PPT_SELECTOR_SYSTEM_PROMPT = """#PPT
+你是 PPT 技能选择器，严格执行以下流程：
+用户输入生成 PPT 相关指令后，询问：你需要使用哪个生成 PPT 的技能？可选技能：1. ppt_gen_html（生成 HTML 形式 PPT）2. ppt_gen_reference（根据文档生成 PPT）
+记住用户最初的 PPT 指令。
+用户选择技能后，仅输出固定语句，无任何多余内容：
+选 ppt_gen_html：{user_input}，使用 ppt_gen_html 这个 skill 来完成
+选 ppt_gen_reference：{user_input}，使用 ppt_gen_reference 这个 skill 来完成
+注：“{user_input}” 特指用户最初输入的 PPT 制作指令，非选择回复。"""
 
 
 # ---------------------------------------------------------------------------
@@ -94,6 +107,137 @@ def normalize_input(raw_input: dict[str, Any] | None) -> dict[str, Any]:
     return raw_input
 
 
+def _extract_text_content(content: Any) -> str:
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts: list[str] = []
+        for item in content:
+            if isinstance(item, dict):
+                text = item.get("text")
+                if isinstance(text, str) and text.strip():
+                    parts.append(text.strip())
+            elif isinstance(item, str) and item.strip():
+                parts.append(item.strip())
+        return "\n".join(parts)
+    return str(content or "")
+
+
+def _extract_last_human_text(graph_input: dict[str, Any]) -> str:
+    messages = graph_input.get("messages")
+    if not isinstance(messages, list):
+        return ""
+    for msg in reversed(messages):
+        if isinstance(msg, HumanMessage):
+            return _extract_text_content(msg.content).strip()
+        if isinstance(msg, dict):
+            role = str(msg.get("role", msg.get("type", ""))).lower()
+            if role in {"user", "human"}:
+                return _extract_text_content(msg.get("content")).strip()
+    return ""
+
+
+def _is_ppt_request(text: str) -> bool:
+    lowered = text.lower()
+    return any(token in lowered for token in ("ppt", "slides", "powerpoint", "幻灯片", "演示文稿"))
+
+
+def _heuristic_has_enough_ppt_info(text: str) -> bool:
+    lowered = text.lower()
+    if len(lowered.strip()) < 12:
+        return False
+
+    score = 0
+    if len(lowered) >= 24:
+        score += 1
+    if re.search(r"(关于|主题|topic|题目|on\s+)", lowered):
+        score += 1
+    if re.search(r"(面向|给|用于|目的|audience|for\s+)", lowered):
+        score += 1
+    if re.search(r"(\d+\s*(页|p|slides?)|大纲|目录|章节|结构)", lowered):
+        score += 1
+    if re.search(r"(风格|配色|模板|视觉|语气|style|tone)", lowered):
+        score += 1
+    if re.search(r"(根据|参考|数据|附件|文档|material|reference)", lowered):
+        score += 1
+    return score >= 2
+
+
+async def _deepseek_ppt_info_check(user_text: str) -> bool:
+    enabled = os.getenv("PPT_PRECHECK_ENABLED", "true").strip().lower()
+    if enabled in {"0", "false", "off", "no"}:
+        return True
+
+    base_url = os.getenv("PPT_PRECHECK_BASE_URL", "").strip()
+    api_key = os.getenv("PPT_PRECHECK_API_KEY", "").strip()
+    model = os.getenv("PPT_PRECHECK_MODEL", "deepseek-chat").strip()
+    timeout_s = float(os.getenv("PPT_PRECHECK_TIMEOUT_SECONDS", "10").strip() or "10")
+
+    if not base_url or not api_key:
+        return _heuristic_has_enough_ppt_info(user_text)
+
+    check_instruction = (
+        "你现在只做“PPT信息是否足够”的判断，不做技能追问。"
+        "判断标准：至少包含主题 + 另一个关键信息（受众/用途/页数或结构/风格/参考资料）。"
+        "仅输出一个词：ENOUGH 或 INSUFFICIENT。"
+    )
+    system_prompt = f"{PPT_SELECTOR_SYSTEM_PROMPT}\n\n{check_instruction}"
+
+    try:
+        client = AsyncOpenAI(base_url=base_url, api_key=api_key, timeout=timeout_s)
+        resp = await client.chat.completions.create(
+            model=model,
+            temperature=0,
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_text},
+            ],
+        )
+        content = (resp.choices[0].message.content or "").strip().upper()
+        if "INSUFFICIENT" in content:
+            return False
+        if "ENOUGH" in content:
+            return True
+        logger.warning("PPT precheck unexpected output: %r; fallback to heuristic", content)
+    except Exception:
+        logger.warning("PPT precheck via DeepSeek failed; fallback to heuristic", exc_info=True)
+
+    return _heuristic_has_enough_ppt_info(user_text)
+
+
+def _overwrite_last_human_message(graph_input: dict[str, Any], text: str) -> None:
+    messages = graph_input.get("messages")
+    if not isinstance(messages, list):
+        graph_input["messages"] = [HumanMessage(content=text)]
+        return
+
+    for idx in range(len(messages) - 1, -1, -1):
+        msg = messages[idx]
+        if isinstance(msg, HumanMessage):
+            msg.content = text
+            return
+        if isinstance(msg, dict):
+            role = str(msg.get("role", msg.get("type", ""))).lower()
+            if role in {"user", "human"}:
+                msg["content"] = text
+                return
+
+    messages.append(HumanMessage(content=text))
+
+
+async def _maybe_apply_ppt_precheck(graph_input: dict[str, Any]) -> None:
+    user_text = _extract_last_human_text(graph_input)
+    if not user_text or not _is_ppt_request(user_text):
+        return
+
+    enough = await _deepseek_ppt_info_check(user_text)
+    if enough:
+        return
+
+    _overwrite_last_human_message(graph_input, PPT_INSUFFICIENT_INFO_FORWARD)
+    logger.info("PPT precheck flagged insufficient info; forwarded clarification instruction")
+
+
 _DEFAULT_ASSISTANT_ID = "lead_agent"
 
 
@@ -282,6 +426,7 @@ async def start_run(
 
     agent_factory = resolve_agent_factory(body.assistant_id)
     graph_input = normalize_input(body.input)
+    await _maybe_apply_ppt_precheck(graph_input)
     config = build_run_config(thread_id, body.config, body.metadata, assistant_id=body.assistant_id)
 
     if "configurable" in config and isinstance(config["configurable"], dict):

backend/tests/test_gateway_services.py

@@ -3,6 +3,9 @@
 from __future__ import annotations
 
 import json
+from unittest.mock import AsyncMock, patch
+
+from langchain_core.messages import HumanMessage
 
 
 def test_format_sse_basic():
@@ -81,6 +84,55 @@ def test_normalize_input_passthrough():
     assert result == {"custom_key": "value"}
 
 
+def test_extract_last_human_text_from_human_message():
+    from app.gateway.services import _extract_last_human_text
+
+    graph_input = {
+        "messages": [
+            HumanMessage(content="第一条"),
+            HumanMessage(content=[{"type": "text", "text": "我要做一个产品发布会PPT"}]),
+        ]
+    }
+    assert _extract_last_human_text(graph_input) == "我要做一个产品发布会PPT"
+
+
+def test_is_ppt_request():
+    from app.gateway.services import _is_ppt_request
+
+    assert _is_ppt_request("帮我做个PPT")
+    assert _is_ppt_request("Please generate slides for roadmap")
+    assert not _is_ppt_request("帮我写一段 SQL")
+
+
+def test_heuristic_has_enough_ppt_info():
+    from app.gateway.services import _heuristic_has_enough_ppt_info
+
+    assert not _heuristic_has_enough_ppt_info("做个ppt")
+    assert _heuristic_has_enough_ppt_info("做一个关于Q2复盘的PPT，面向管理层，10页，简洁风格")
+
+
+def test_overwrite_last_human_message():
+    from app.gateway.services import _overwrite_last_human_message
+
+    graph_input = {"messages": [HumanMessage(content="请生成PPT")]}
+    _overwrite_last_human_message(graph_input, "用户想生成ppt，但是没有输入足够多的信息，所以先向用户询问更多信息")
+    assert graph_input["messages"][-1].content == "用户想生成ppt，但是没有输入足够多的信息，所以先向用户询问更多信息"
+
+
+def test_maybe_apply_ppt_precheck_rewrites_when_insufficient():
+    from app.gateway.services import _maybe_apply_ppt_precheck
+
+    graph_input = {"messages": [HumanMessage(content="帮我做个PPT")]}
+    with patch(
+        "app.gateway.services._deepseek_ppt_info_check",
+        new=AsyncMock(return_value=False),
+    ):
+        import asyncio
+
+        asyncio.run(_maybe_apply_ppt_precheck(graph_input))
+    assert graph_input["messages"][-1].content == "用户想生成ppt，但是没有输入足够多的信息，所以先向用户询问更多信息"
+
+
 def test_build_run_config_basic():
     from app.gateway.services import build_run_config