2b3367cdea
- Introduced SiteAssistant component to assist users in selecting the right tools based on their queries. - Integrated assistant into the main App component. - Implemented message handling and storage for user-assistant interactions. - Added quick prompts for common user queries related to tools. - Enhanced ToolLandingPage and DownloadButton components with SharePanel for sharing tool results. - Updated translations for new assistant features and sharing options. - Added API methods for chat functionality with the assistant, including streaming responses.
84 lines
2.8 KiB
Python
84 lines
2.8 KiB
Python
"""Site assistant routes — global AI helper for the product UI."""
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import json
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from flask import Blueprint, Response, jsonify, request, stream_with_context
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from app.extensions import limiter
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from app.services.policy_service import resolve_web_actor
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from app.services.site_assistant_service import chat_with_site_assistant, stream_site_assistant_chat
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assistant_bp = Blueprint("assistant", __name__)
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def _parse_chat_payload():
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payload = request.get_json(silent=True) or {}
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message = str(payload.get("message", "")).strip()
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if not message:
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return None, (jsonify({"error": "Message is required."}), 400)
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if len(message) > 4000:
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return None, (jsonify({"error": "Message is too long."}), 400)
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actor = resolve_web_actor()
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return {
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"message": message,
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"session_id": str(payload.get("session_id", "")).strip() or None,
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"fingerprint": str(payload.get("fingerprint", "")).strip() or "anonymous",
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"tool_slug": str(payload.get("tool_slug", "")).strip(),
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"page_url": str(payload.get("page_url", "")).strip(),
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"locale": str(payload.get("locale", "en")).strip() or "en",
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"user_id": actor.user_id,
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"history": payload.get("history") if isinstance(payload.get("history"), list) else None,
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}, None
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def _sse(event: str, data: dict) -> str:
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return f"event: {event}\ndata: {json.dumps(data, ensure_ascii=True)}\n\n"
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@assistant_bp.route("/chat", methods=["POST"])
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@limiter.limit("20/minute")
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def assistant_chat_route():
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"""Answer a product-help message and store the conversation for later analysis."""
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chat_kwargs, error_response = _parse_chat_payload()
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if error_response:
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return error_response
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try:
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result = chat_with_site_assistant(**chat_kwargs)
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except ValueError as exc:
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return jsonify({"error": str(exc)}), 400
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except Exception:
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return jsonify({"error": "Assistant is temporarily unavailable."}), 500
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return jsonify(result), 200
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@assistant_bp.route("/chat/stream", methods=["POST"])
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@limiter.limit("20/minute")
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def assistant_chat_stream_route():
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"""Stream assistant replies incrementally over SSE."""
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chat_kwargs, error_response = _parse_chat_payload()
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if error_response:
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return error_response
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try:
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events = stream_site_assistant_chat(**chat_kwargs)
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except ValueError as exc:
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return jsonify({"error": str(exc)}), 400
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except Exception:
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return jsonify({"error": "Assistant is temporarily unavailable."}), 500
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def generate():
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for event in events:
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yield _sse(event["event"], event["data"])
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return Response(
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stream_with_context(generate()),
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content_type="text/event-stream; charset=utf-8",
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headers={
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"Cache-Control": "no-cache",
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"X-Accel-Buffering": "no",
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},
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) |