Add admin-frontend and user-frontend standalone projects, certification/invoice/discovery features, fix auth header and theme consistency

backend/app/services/discovery.py

@@ -0,0 +1,272 @@
+import asyncio
+import json
+import logging
+from typing import Dict, Any, Optional
+
+from app.ai.router import get_ai_router
+from app.services.search_web import search_companies, fetch_page_text
+from app.services.mcp_search_client import mcp_search
+
+logger = logging.getLogger(__name__)
+
+ANALYZE_MATCH_PROMPT = """你是外贸客户分析专家。分析目标公司的业务描述，判断其与用户产品的匹配度。
+
+请以 JSON 格式返回（不要用 markdown 代码块标记）：
+{
+  "match_score": 0-100,
+  "match_reason": "为什么匹配/不匹配",
+  "company_summary": "这家公司的主要业务",
+  "product_fit": "产品匹配度说明",
+  "contact_info": {
+    "emails": ["找到的邮箱"],
+    "phones": ["找到的电话"],
+    "social": ["LinkedIn等社媒链接"]
+  }
+}
+
+只返回 JSON，不要其他内容。"""
+
+
+class DiscoveryService:
+    def __init__(self):
+        ai_router = get_ai_router()
+        self.ai = ai_router
+        self._ai_available = len(ai_router.providers) > 0
+
+    async def search(self, product_description: str, target_market: str) -> Dict[str, Any]:
+        queries = self._build_queries(product_description, target_market)
+        all_results = await self._mcp_search_all(queries)
+        if all_results:
+            return {
+                "companies": all_results[:15],
+                "query": product_description,
+                "market": target_market,
+                "provider": "mcp_search",
+            }
+
+        all_results = await self._google_search_all(queries)
+        if all_results:
+            return {
+                "companies": all_results[:15],
+                "query": product_description,
+                "market": target_market,
+                "provider": "web_search",
+            }
+
+        logger.info("No real search results, using AI strategy")
+        return await self._ai_strategy(product_description, target_market)
+
+    async def analyze(self, company_url: str, product_description: str) -> Dict[str, Any]:
+        page_text = await fetch_page_text(company_url)
+        company_info = {"url": company_url}
+        if page_text:
+            company_info["page_text"] = page_text[:2500]
+
+        if not self._ai_available:
+            return self._template_analysis(company_url)
+
+        prompt = f"""用户的产品：{product_description}
+
+目标公司信息：
+URL: {company_url}
+网页内容：{page_text[:2500] if page_text else "无法获取网页内容"}
+
+请分析该公司的业务与用户产品的匹配度。"""
+        try:
+            result = await self.ai.chat(prompt, system_prompt=ANALYZE_MATCH_PROMPT)
+            content = result.get("reply", "")
+            parsed = self._extract_json(content)
+            if parsed:
+                parsed["url"] = company_url
+                parsed["provider"] = result.get("provider_used", "unknown")
+                return parsed
+        except (json.JSONDecodeError, Exception) as e:
+            logger.warning(f"Analysis AI parse failed: {e}")
+            return self._template_analysis(company_url)
+
+    async def outreach(self, company_info: Dict[str, Any], product_info: Dict[str, Any]) -> Dict[str, Any]:
+        if not self._ai_available:
+            return self._template_outreach(company_info, product_info)
+
+        prompt = f"""目标公司信息：
+{json.dumps(company_info, ensure_ascii=False)}
+
+我的产品信息：
+{json.dumps(product_info, ensure_ascii=False)}
+
+请生成个性化触达文案。"""
+        system = """你是外贸开发信专家。根据目标公司信息和你的产品，生成个性化触达文案。
+
+请以 JSON 格式返回（不要用 markdown 代码块标记）：
+{
+  "subject": "邮件标题（如适用）",
+  "linkedin_message": "LinkedIn 私信文案（150字以内）",
+  "whatsapp_message": "WhatsApp 消息文案（100字以内）",
+  "email_body": "邮件正文（含开头问候、自我介绍、价值主张、行动号召、签名）",
+  "key_points": ["客户关注的3个要点"],
+  "tips": ["发送时的建议"]
+}"""
+        try:
+            result = await self.ai.chat(prompt, system_prompt=system)
+            content = result.get("reply", "")
+            parsed = self._extract_json(content)
+            if parsed:
+                parsed["provider"] = result.get("provider_used", "unknown")
+                return parsed
+        except (json.JSONDecodeError, Exception) as e:
+            logger.warning(f"Outreach AI parse failed: {e}")
+            return self._template_outreach(company_info, product_info)
+
+    async def _mcp_search_all(self, queries: list) -> list:
+        seen_urls = set()
+        tasks = [asyncio.create_task(mcp_search(q, max_results=6)) for q in queries[:2]]
+        all_results = []
+        try:
+            for coro in asyncio.as_completed(tasks, timeout=8):
+                try:
+                    results = await coro
+                    for r in results:
+                        url = r.get("url", "").rstrip("/")
+                        if url and url not in seen_urls:
+                            seen_urls.add(url)
+                            all_results.append(r)
+                except (asyncio.TimeoutError, Exception) as e:
+                    logger.debug(f"MCP search query failed: {e}")
+        except asyncio.TimeoutError:
+            logger.warning("MCP search overall timeout")
+        finally:
+            for t in tasks:
+                if not t.done():
+                    t.cancel()
+            await asyncio.gather(*tasks, return_exceptions=True)
+        if all_results:
+            return self._dedup_and_filter(all_results)[:15]
+        return []
+
+    def _dedup_and_filter(self, results: list) -> list:
+        seen = set()
+        filtered = []
+        for r in results:
+            url = r.get("url", "").rstrip("/")
+            title = r.get("title", "")
+            if not url or url in seen:
+                continue
+            seen.add(url)
+            s = url.split("/")[2] if "://" in url else url
+            hostname = s.split(":")[0].lower() if ":" in s else s.lower()
+            if any(tld in hostname for tld in [".cn", ".com.cn", ".edu", ".ac.", ".gov"]):
+                continue
+            if any(domain in hostname for domain in
+                   ["sciencedirect", "mdpi", "springer", "wiley", "acm.org",
+                    "ieee.org", "researchgate", "nature.com", "oup.com",
+                    "sagepub", "tandfonline", "ncbi", "semanticscholar",
+                    "britannica", "dictionary", "cambridge", "iciba", "wikipedia"]):
+                continue
+            filtered.append(r)
+        return filtered
+
+    async def _google_search_all(self, queries: list) -> list:
+        all_results = []
+        seen_urls = set()
+        for q in queries[:3]:
+            results = await search_companies(q, max_results=8)
+            for r in results:
+                url = r["url"].rstrip("/")
+                if url not in seen_urls:
+                    seen_urls.add(url)
+                    all_results.append(r)
+            if len(all_results) >= 15:
+                break
+        return self._dedup_and_filter(all_results)[:15]
+
+    def _build_queries(self, product: str, market: str) -> list:
+        return [
+            f"{product} importer {market}",
+            f"{product} distributor {market}",
+            f"{product} wholesale buyer {market}",
+            f"{product} procurement {market}",
+            f"{product} company {market}",
+            f"buy {product} from {market}",
+            f"{product} supply chain {market}",
+            f"top {product} manufacturers {market}",
+            f"{product} import export {market}",
+            f"{product} trading company {market}",
+        ]
+
+    def _extract_json(self, text: str) -> Optional[dict]:
+        text = text.strip()
+        for prefix in ["```json", "```", "```JSON"]:
+            if text.startswith(prefix):
+                text = text[len(prefix):]
+        for suffix in ["```"]:
+            if text.endswith(suffix):
+                text = text[:-len(suffix)]
+        text = text.strip()
+        try:
+            return json.loads(text)
+        except json.JSONDecodeError:
+            import re
+            brace = text.find("{")
+            end = text.rfind("}")
+            if brace >= 0 and end > brace:
+                try:
+                    return json.loads(text[brace:end+1])
+                except json.JSONDecodeError:
+                    pass
+        return None
+
+    async def _ai_strategy(self, product: str, market: str) -> Dict[str, Any]:
+        if not self._ai_available:
+            return self._template_strategy(product, market)
+        system = """你是外贸客户发现专家。根据用户的产品和目标市场，分析出潜在买家画像和获取策略。
+
+请以 JSON 格式返回（不要用 markdown 代码块标记）：
+{
+  "buyer_personas": [{"type": "", "description": "", "channels": [], "search_queries": []}],
+  "strategy": "",
+  "tips": []
+}"""
+        prompt = f"产品：{product}\n目标市场：{market}\n请分析潜在买家画像和获取策略。"
+        try:
+            result = await self.ai.chat(prompt, system_prompt=system)
+            content = result.get("reply", "")
+            parsed = self._extract_json(content)
+            if parsed:
+                parsed["provider"] = result.get("provider_used", "unknown")
+                return parsed
+            return self._template_strategy(product, market)
+        except Exception as e:
+            logger.warning(f"AI strategy failed: {e}")
+            return self._template_strategy(product, market)
+
+    def _template_strategy(self, product: str, market: str) -> Dict[str, Any]:
+        return {
+            "buyer_personas": [
+                {"type": "进口商/批发商", "description": f"从中国进口{product}并在{market}批发的贸易商", "channels": ["LinkedIn", "Google"], "search_queries": [f"{product} importer {market}"]},
+                {"type": "品牌商/OEM买家", "description": f"在{market}销售自有品牌{product}的公司", "channels": ["LinkedIn", "行业展会"], "search_queries": [f"{product} manufacturer {market}"]},
+            ],
+            "strategy": f"建议在 LinkedIn 和 Google 搜索 {market} 的 {product} 相关公司",
+            "tips": ["使用多个搜索词", "找到公司后在 LinkedIn 找决策人"],
+            "provider": "template",
+        }
+
+    def _template_analysis(self, url: str) -> Dict[str, Any]:
+        return {
+            "match_score": 50,
+            "match_reason": "无法获取网页内容进行分析，建议手动查看",
+            "url": url,
+            "provider": "template",
+        }
+
+    def _template_outreach(self, company: Dict[str, Any], product: Dict[str, Any]) -> Dict[str, Any]:
+        company_name = company.get("name", "")
+        product_name = product.get("name", "")
+        return {
+            "subject": f"关于{product_name}的合作机会",
+            "linkedin_message": f"您好！了解到贵司{company_name}在经营相关业务，我们专业生产{product_name}，品质稳定，价格有竞争力。如有兴趣，我可以发详细资料供参考。",
+            "whatsapp_message": f"Hello! We are a professional {product_name} manufacturer. Interested in exploring cooperation? Happy to share details.",
+            "email_body": f"Dear {company_name} team,\n\nWe are a professional {product_name} manufacturer with competitive pricing and consistent quality. Would you be open to a quick chat to explore potential cooperation?\n\nBest regards,\n[Your Name]",
+            "key_points": ["产品质量有保障", "价格有竞争力", "可定制"],
+            "tips": ["发送前先了解对方背景", "LinkedIn 消息要简短"],
+            "provider": "template",
+        }