mirror of
https://gitee.com/wanwujie/deer-flow
synced 2026-04-15 03:04:44 +08:00
894875ab1b
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode) Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai> Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
133 lines
4.6 KiB
Python
133 lines
4.6 KiB
Python
import json
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import logging
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from fastapi import APIRouter
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from pydantic import BaseModel, Field
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from deerflow.models import create_chat_model
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api", tags=["suggestions"])
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class SuggestionMessage(BaseModel):
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role: str = Field(..., description="Message role: user|assistant")
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content: str = Field(..., description="Message content as plain text")
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class SuggestionsRequest(BaseModel):
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messages: list[SuggestionMessage] = Field(..., description="Recent conversation messages")
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n: int = Field(default=3, ge=1, le=5, description="Number of suggestions to generate")
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model_name: str | None = Field(default=None, description="Optional model override")
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class SuggestionsResponse(BaseModel):
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suggestions: list[str] = Field(default_factory=list, description="Suggested follow-up questions")
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def _strip_markdown_code_fence(text: str) -> str:
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stripped = text.strip()
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if not stripped.startswith("```"):
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return stripped
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lines = stripped.splitlines()
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if len(lines) >= 3 and lines[0].startswith("```") and lines[-1].startswith("```"):
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return "\n".join(lines[1:-1]).strip()
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return stripped
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def _parse_json_string_list(text: str) -> list[str] | None:
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candidate = _strip_markdown_code_fence(text)
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start = candidate.find("[")
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end = candidate.rfind("]")
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if start == -1 or end == -1 or end <= start:
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return None
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candidate = candidate[start : end + 1]
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try:
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data = json.loads(candidate)
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except Exception:
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return None
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if not isinstance(data, list):
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return None
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out: list[str] = []
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for item in data:
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if not isinstance(item, str):
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continue
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s = item.strip()
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if not s:
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continue
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out.append(s)
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return out
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def _extract_response_text(content: object) -> str:
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if isinstance(content, str):
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return content
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if isinstance(content, list):
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parts: list[str] = []
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for block in content:
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if isinstance(block, str):
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parts.append(block)
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elif isinstance(block, dict) and block.get("type") in {"text", "output_text"}:
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text = block.get("text")
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if isinstance(text, str):
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parts.append(text)
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return "\n".join(parts) if parts else ""
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if content is None:
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return ""
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return str(content)
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def _format_conversation(messages: list[SuggestionMessage]) -> str:
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parts: list[str] = []
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for m in messages:
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role = m.role.strip().lower()
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if role in ("user", "human"):
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parts.append(f"User: {m.content.strip()}")
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elif role in ("assistant", "ai"):
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parts.append(f"Assistant: {m.content.strip()}")
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else:
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parts.append(f"{m.role}: {m.content.strip()}")
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return "\n".join(parts).strip()
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@router.post(
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"/threads/{thread_id}/suggestions",
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response_model=SuggestionsResponse,
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summary="Generate Follow-up Questions",
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description="Generate short follow-up questions a user might ask next, based on recent conversation context.",
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)
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async def generate_suggestions(thread_id: str, request: SuggestionsRequest) -> SuggestionsResponse:
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if not request.messages:
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return SuggestionsResponse(suggestions=[])
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n = request.n
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conversation = _format_conversation(request.messages)
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if not conversation:
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return SuggestionsResponse(suggestions=[])
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prompt = (
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"You are generating follow-up questions to help the user continue the conversation.\n"
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f"Based on the conversation below, produce EXACTLY {n} short questions the user might ask next.\n"
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"Requirements:\n"
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"- Questions must be relevant to the conversation.\n"
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"- Questions must be written in the same language as the user.\n"
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"- Keep each question concise (ideally <= 20 words / <= 40 Chinese characters).\n"
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"- Do NOT include numbering, markdown, or any extra text.\n"
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"- Output MUST be a JSON array of strings only.\n\n"
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"Conversation:\n"
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f"{conversation}\n"
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)
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try:
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model = create_chat_model(name=request.model_name, thinking_enabled=False)
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response = model.invoke(prompt)
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raw = _extract_response_text(response.content)
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suggestions = _parse_json_string_list(raw) or []
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cleaned = [s.replace("\n", " ").strip() for s in suggestions if s.strip()]
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cleaned = cleaned[:n]
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return SuggestionsResponse(suggestions=cleaned)
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except Exception as exc:
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logger.exception("Failed to generate suggestions: thread_id=%s err=%s", thread_id, exc)
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return SuggestionsResponse(suggestions=[])
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