Fix API errors and improve customer discovery with real web results

- Fix usage/stats 500: use Date() not datetime.date() for SQL cast
- Fix customers 422: raise size limit to 1000
- Replace unreliable MCP client with direct Bing batch search for discovery
- Batch all search queries in one browser session (faster)
- Show real company names/URLs from Bing, not generic templates
- Smart filter for non-business results (news, blogs, forums)
- Fallback suggestions when search results are insufficient
- Frontend: clickable contact URLs, provider indicator, better layout

backend/app/ai/providers/nvidia.py

@@ -28,10 +28,11 @@ class NvidiaProvider(OpenAIProvider):
         messages.append({"role": "user", "content": message})
         t1 = time.time()
 
+        max_tokens = 800 if "JSON" in (system or "").upper() else 300
         kwargs = {
             "model": self.model,
             "messages": messages,
-            "max_tokens": 300,
+            "max_tokens": max_tokens,
             "temperature": 0.3,
         }
         resp = await self.client.chat.completions.create(**kwargs)

backend/app/api/v1/customer.py

@@ -17,7 +17,7 @@ router = APIRouter()
 async def list_customers(
     status: Optional[str] = None,
     page: int = Query(1, ge=1),
-    size: int = Query(20, ge=1, le=100),
+    size: int = Query(20, ge=1, le=1000),
     user_id: str = Depends(get_current_user_id),
     db: AsyncSession = Depends(get_db),
 ):

backend/app/services/.gitignore

@@ -0,0 +1 @@
+_batch_search.js

backend/app/services/discovery.py

@@ -1,11 +1,10 @@
-import asyncio
 import json
 import logging
-from typing import Dict, Any, Optional
+from typing import Dict, Any, Optional, Union
 
 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
+from app.services.mcp_search_server import search_bing_batch
 
 logger = logging.getLogger(__name__)
 
@@ -35,27 +34,32 @@ class DiscoveryService:
 
     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)
+
+        all_results = await self._web_search_all(queries)
+        companies = []
+        provider = "template"
         if all_results:
+            raw = all_results.get("results", [])
+            companies = [self._to_company(r) for r in raw[:12]]
+            provider = all_results.get("provider", "web_search")
+
+        good_enough = [c for c in companies if self._looks_like_business(c)]
+        if len(good_enough) < 3:
+            logger.info(f"Web search returned only {len(good_enough)} good results, supplementing with suggestions")
+            extras = self._suggest_companies(product_description, target_market)
+            seen_names = set(c.get("name", "") for c in good_enough)
+            for c in extras:
+                if c.get("name") and c["name"] not in seen_names:
+                    seen_names.add(c["name"])
+                    good_enough.append(c)
+
         return {
-                "companies": all_results[:15],
+            "companies": good_enough[:15],
             "query": product_description,
             "market": target_market,
-                "provider": "mcp_search",
+            "provider": provider,
         }
 
-        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}
@@ -117,83 +121,115 @@ URL: {company_url}
             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:
+    async def _web_search_all(self, queries: list) -> dict:
-        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):
+            results = await search_bing_batch(queries[:4], max_per_query=5)
-                try:
+            if results:
-                    results = await coro
+                return {"results": self._dedup_and_filter(results)[:15], "provider": "bing"}
-                    for r in results:
+        except Exception as e:
-                        url = r.get("url", "").rstrip("/")
+            logger.warning(f"Bing batch search failed: {e}")
-                        if url and url not in seen_urls:
+
-                            seen_urls.add(url)
+        results = await search_companies(queries[0], max_results=10)
-                            all_results.append(r)
+        if results:
-                except (asyncio.TimeoutError, Exception) as e:
+            return {"results": results[:15], "provider": "google_cse"}
-                    logger.debug(f"MCP search query failed: {e}")
+
-        except asyncio.TimeoutError:
+        return {}
-            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 = []
+        junk = ["sciencedirect", "mdpi", "springer", "wiley", "acm.org",
+                "ieee.org", "researchgate", "nature.com", "oup.com",
+                "sagepub", "tandfonline", "ncbi", "semanticscholar",
+                "britannica", "dictionary", "cambridge", "iciba", "wikipedia",
+                "w3.org", "whatsapp.com", "wechat.com", "qq.com",
+                "zhihu.com", "sogou.com", "163.com", "sohu.com", "sina.com",
+                "taobao.com", "tmall.com", "alipay.com", "alibaba.com",
+                "csdn.net", "blog.csdn", "jianshu.com", "36kr.com",
+                "huxiu.com", "geekpark.net", "leiphone.com",
+                "medium.com", "wordpress.com", "blogspot.com",
+                "youtube.com", "facebook.com", "twitter.com", "instagram.com",
+                "reddit.com", "quora.com"]
         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"]):
+            if any(tld in hostname for tld in [".edu", ".ac.", ".gov", ".edu.cn"]):
                 continue
-            if any(domain in hostname for domain in
+            if any(domain in hostname for domain in junk):
-                   ["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:
+    def _to_company(self, r: dict) -> dict:
-        all_results = []
+        url = r.get("url", "")
-        seen_urls = set()
+        title = r.get("title", url)[:60]
-        for q in queries[:3]:
+        snippet = r.get("snippet", "")[:200]
-            results = await search_companies(q, max_results=8)
+        return {
-            for r in results:
+            "name": title,
-                url = r["url"].rstrip("/")
+            "description": snippet,
-                if url not in seen_urls:
+            "country": "",
-                    seen_urls.add(url)
+            "match_score": 60,
-                    all_results.append(r)
+            "contact": url[:100] if url else "暂无",
-            if len(all_results) >= 15:
+            "source": "web",
-                break
+        }
-        return self._dedup_and_filter(all_results)[:15]
+
+    def _looks_like_business(self, c: dict) -> bool:
+        name = c.get("name", "")
+        snippet = c.get("description", "")
+        junk_words = ["news", "review", "blog", "dictionary", "translate",
+                       "wikipedia", "百科", "词典", "新闻", "评测",
+                       "price", "shop", "buy online", "forum", "subscribe",
+                       "专业媒体", "行业媒体", "新媒体", "门户"]
+        name_lower = name.lower()
+        if any(w in name_lower for w in junk_words):
+            return False
+        snippet_lower = snippet.lower()
+        newsy = ["news", "review", "blog post", "article", "dictionary",
+                 "专业媒体", "行业媒体", "新媒体"]
+        if any(w in snippet_lower for w in newsy):
+            biz_words = ["company", "inc", "ltd", "corp", "gmbh", "llc",
+                         "manufacturer", "supplier", "exporter",
+                         "wholesale", "distributor", "trading",
+                         "import", "enterprise", "co.", "factory",
+                         "industry", "electric", "solar", "energy",
+                         "automotive", "vehicle", "官网", "有限公司",
+                         "集团", "股份", "实业"]
+            if not any(w in snippet_lower for w in biz_words):
+                return False
+        return True
 
     def _build_queries(self, product: str, market: str) -> list:
-        return [
+        import re
+        has_cjk = bool(re.search(r'[\u4e00-\u9fff]', product))
+        queries = [
             f"{product} importer {market}",
             f"{product} distributor {market}",
             f"{product} wholesale buyer {market}",
             f"{product} procurement {market}",
-            f"{product} company {market}",
+            f"{product} trading 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}",
         ]
+        if has_cjk:
+            queries += [
+                f"{product} {market} 进口商",
+                f"{product} {market} 经销商",
+                f"{product} {market} 采购",
+                f"{product} {market} 批发",
+            ]
+        b2b_queries = [
+            f"{product} buyer {market} alibaba",
+            f"{product} supplier {market}",
+            f"{product} wholesale price {market}",
+        ]
+        return queries + b2b_queries
 
-    def _extract_json(self, text: str) -> Optional[dict]:
+    def _extract_json(self, text: str) -> Optional[Union[dict, list]]:
         text = text.strip()
         for prefix in ["```json", "```", "```JSON"]:
             if text.startswith(prefix):
@@ -215,49 +251,37 @@ URL: {company_url}
                     pass
         return None
 
-    async def _ai_strategy(self, product: str, market: str) -> Dict[str, Any]:
+    def _suggest_companies(self, product: str, market: str) -> list:
-        if not self._ai_available:
+        return [
-            return self._template_strategy(product, market)
+            {"name": f"{product} Importers in {market}", "description": f"在 {market} 从事 {product} 进口和批发的贸易商和专业进口商", "country": market, "match_score": 80, "contact": f"在 LinkedIn 搜索 '{product} importer {market}'", "source": "建议"},
-        system = """你是外贸客户发现专家。根据用户的产品和目标市场，列出15家有可能采购该产品的潜在公司。
+            {"name": f"{product} Distributors in {market}", "description": f"在 {market} 分销 {product} 的分销渠道商和批发商", "country": market, "match_score": 75, "contact": f"在 Google/Bing 搜索 '{product} distributor {market}'", "source": "建议"},
-
+            {"name": f"{market} Trade Association", "description": f"联系 {market} 的相关行业协会获取会员企业名录", "country": market, "match_score": 70, "contact": f"搜索 '{market} {product} association'", "source": "建议"},
-请以 JSON 格式返回（不要用 markdown 代码块标记）：
+            {"name": f"Alibaba {market} Buyers", "description": f"在 Alibaba.com 搜索 '{product}' 并筛选 {market} 买家", "country": market, "match_score": 75, "contact": "https://www.alibaba.com", "source": "建议"},
-{
+            {"name": f"LinkedIn {market} Decision Makers", "description": f"在 LinkedIn 搜索 '{market} {product} procurement/sourcing manager' 找决策人", "country": market, "match_score": 65, "contact": "LinkedIn Premium", "source": "建议"},
-  "companies": [
+            {"name": f"{market} Import-Export Records", "description": f"在 importgenius.com 搜索 {product} 在 {market} 的进口记录，找到真实买家", "country": market, "match_score": 70, "contact": "https://www.importgenius.com", "source": "建议"},
-    {"name": "公司名称", "description": "公司业务简介", "country": "所在国家", "match_score": 匹配度0-100, "contact": "联系方式（有就写，没有写'需进一步查找'）", "source": "推荐来源说明"}
+        ]
-  ],
-  "strategy": "整体获取策略建议",
-  "tips": ["搜索建议1", "搜索建议2"]
-}
-
-要求：
-- 公司名称要真实感，不要编造知名大公司
-- 公司业务要与产品相关
-- 匹配度要有区分度，60-95之间
-- 至少返回10家
-- 只返回 JSON，不要其他内容"""
-
-        prompt = f"产品：{product}\n目标市场：{market}\n请列出在该市场可能采购该产品的公司。"
-        try:
-            result = await self.ai.chat(prompt, system_prompt=system)
-            content = result.get("reply", "")
-            parsed = self._extract_json(content)
-            if parsed and "companies" in parsed:
-                parsed["provider"] = result.get("provider_used", "unknown")
-                parsed["ai_generated"] = True
-                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]:
+        search_terms = [
+            f"{product} importer {market}",
+            f"{product} distributor {market}",
+            f"{product} wholesale {market}",
+            f"{product} buyers {market}",
+        ]
+        b2b_sites = ["Alibaba.com", "TradeIndia.com", "GlobalSources.com", "Made-in-China.com"]
         return {
             "companies": [
-                {"name": f"{product} Importers in {market} (示例)", "description": f"在{market}从事{product}进口和批发的贸易商，建议在LinkedIn上搜索相关关键词", "country": market, "match_score": 75, "contact": "需进一步查找", "source": "AI推荐"},
+                {"name": f"{product} Importers in {market}", "description": f"使用Google/Bing搜索 '{product} importer {market}' 可找到正在采购该产品的进口商", "country": market, "match_score": 80, "contact": "通过搜索结果获取", "source": "搜索建议"},
-                {"name": f"{product} Distributors in {market} (示例)", "description": f"在{market}分销{product}的渠道商，建议通过Google搜索关键词", "country": market, "match_score": 70, "contact": "需进一步查找", "source": "AI推荐"},
+                {"name": f"{product} Distributors in {market}", "description": f"使用Google/Bing搜索 '{product} distributor {market}' 可找到分销渠道商", "country": market, "match_score": 75, "contact": "通过搜索结果获取", "source": "搜索建议"},
+                {"name": f"{product} Wholesale Buyers in {market}", "description": f"使用Google/Bing搜索 '{product} wholesale {market}' 可找到批发采购商", "country": market, "match_score": 70, "contact": "通过搜索结果获取", "source": "搜索建议"},
+                {"name": f"{market} {product} Trade Partners", "description": f"在B2B平台（{', '.join(b2b_sites[:3])}）搜索 {market} 买家发布的采购需求", "country": market, "match_score": 65, "contact": "B2B平台站内信", "source": "B2B平台"},
             ],
-            "strategy": f"建议在 LinkedIn 和 Google 搜索 {market} 的 {product} 相关公司，使用导入商、批发商、经销商等关键词组合",
+            "strategy": f"推荐搜索计划：\n1. 搜索 '{' '.join(search_terms[:2])}' 直接找客户\n2. 在 LinkedIn 搜索 '{market} {product} manager' 找决策人\n3. 在 {b2b_sites[0]} 和 {b2b_sites[1]} 查找 {market} 买家询盘\n4. 参加 {market} 相关行业展会获取名录",
-            "tips": ["使用多个搜索词组合", "找到公司后在 LinkedIn 找决策人", "查看公司网站了解其业务范围"],
+            "tips": [
+                f"把搜索词 '{product} importer {market}' 改成当地语言效果更好",
+                "找到公司后访问官网，在 About/Team 页面找决策人LinkedIn",
+                "用 SimilarWeb 查看目标公司网站流量和来源",
+                "在行业协会网站查找会员名录"],
             "provider": "template",
             "ai_generated": True,
         }

backend/app/services/mcp_search_server.py

@@ -4,6 +4,7 @@ import logging
 import os
 import subprocess
 from typing import List, Dict
+import functools
 
 from mcp.server.fastmcp import FastMCP
 
@@ -11,22 +12,29 @@ logger = logging.getLogger(__name__)
 PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
 NODE_BIN = "/usr/bin/node"
 
-BING_SCRIPT = r"""
+BATCH_SCRIPT = r"""
 const p = require('puppeteer');
 (async () => {
-  const b = await p.launch({headless:true,args:['--no-sandbox','--disable-setuid-sandbox','--disable-blink-features=AutomationControlled']});
+  const queries = JSON.parse(process.argv[process.argv.length - 2]);
+  const max = parseInt(process.argv[process.argv.length - 1] || '6', 10);
+  const sk = ['bing.com','google.com','facebook.com','twitter.com','instagram.com','youtube.com','reddit.com','amazon.com','walmart.com','w3.org','whatsapp.com','wechat.com','qq.com','taobao.com','tmall.com','alipay.com','zhihu.com','baike.baidu.com','sogou.com','163.com','sohu.com','sina.com','iciba.com','cambridge','britannica','sciencedirect','mdpi.com','springer','wiley.com','acm.org','ieee.org','researchgate','semanticscholar','ncbi.nlm.nih','nature.com','oup.com','sagepub','tandfonline','pinterest','ebay','dictionary','translate'];
+
+  try {
+    const b = await p.launch({headless:true,args:['--no-sandbox','--disable-setuid-sandbox','--disable-blink-features=AutomationControlled'],timeout:10000});
+    const allResults = [];
+    const seenUrls = new Set();
+
+    for (const q of queries) {
+      try {
         const page = await b.newPage();
         await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36');
         await page.setExtraHTTPHeaders({'Accept-Language':'en-US,en;q=0.9'});
-  await page.evaluateOnNewDocument(() => { Object.defineProperty(navigator, 'webdriver', {get:()=>undefined}); });
+
-  const q = process.argv[process.argv.length - 2];
+        const url = 'https://www.bing.com/search?q=' + encodeURIComponent(q) + '&setlang=en-US&cc=US';
-  const max = parseInt(process.argv[process.argv.length - 1] || '10', 10);
+        await page.goto(url, {waitUntil:'domcontentloaded',timeout:8000});
-  const sk = ['bing.com','google.com','facebook.com','twitter.com','instagram.com','youtube.com','reddit.com','amazon.com','wikipedia.org','baidu.com','linkedin.com','pinterest.com','ebay.com','walmart.com','w3.org','whatsapp.com','wechat.com','qq.com','taobao.com','tmall.com','alibaba.com','alipay.com','dict','dictionary','translate','zhihu.com','baike.baidu.com','sogou.com','163.com','sohu.com','sina.com','iciba.com','cambridge','britannica','sciencedirect','mdpi.com','springer','wiley.com','acm.org','ieee.org','researchgate','semanticscholar','ncbi.nlm.nih','nature.com','oup.com','sagepub','tandfonline'];
+        await page.waitForSelector('.b_algo', {timeout:4000}).catch(()=>{});
-  try {
+
-    await page.goto('https://cn.bing.com/search?q=' + encodeURIComponent(q) + '&setlang=en-US&cc=US', {waitUntil:'domcontentloaded',timeout:10000});
-    await page.waitForSelector('.b_algo', {timeout:5000}).catch(()=>{});
         const results = await page.evaluate((m, sk) => {
-      const reCJK = /[\u4e00-\u9fff\u3400-\u4dbf]/;
           const found = []; const seen = new Set();
           document.querySelectorAll('li.b_algo').forEach(li => {
             const a = li.querySelector('h2 a'); if (!a) return;
@@ -35,55 +43,64 @@ const p = require('puppeteer');
             seen.add(url);
             if (sk.some(d => url.includes(d))) return;
             const hostname = url.replace(/^https?:\/\//,'').split('/')[0];
-        if (hostname.endsWith('.cn') || hostname.endsWith('.com.cn') || hostname.endsWith('.edu') || hostname.endsWith('.ac')) return;
+            if (hostname.endsWith('.edu') || hostname.endsWith('.ac') || hostname.endsWith('.gov')) return;
             const title = (a.textContent||'').trim().substring(0,100);
-        if (reCJK.test(title)) return;
             const s = li.querySelector('.b_caption p, .b_lineclamp2');
             found.push({title, url, snippet:s?s.textContent.trim().substring(0,200):''});
           });
           return found.slice(0,m);
         }, max, sk);
-    console.log(JSON.stringify(results));
+
-  } catch(e) { console.log('[]'); }
+        for (const r of results) {
+          if (!seenUrls.has(r.url)) {
+            seenUrls.add(r.url);
+            allResults.push(r);
+          }
+        }
+        await page.close();
+      } catch(e) { /* skip failed query */ }
+    }
+    console.log(JSON.stringify(allResults.slice(0, max * queries.length)));
     await b.close();
+  } catch(e) { console.log('[]'); }
 })();
 """
 
 
-BING_SCRIPT_FILE = os.path.join(os.path.dirname(__file__), "_bing_search.js")
+BATCH_SCRIPT_FILE = os.path.join(os.path.dirname(__file__), "_batch_search.js")
 NODE_MODULES = os.path.join(PROJECT_ROOT, "node_modules")
 
 
-async def search_bing(query: str, max_results: int = 10) -> List[Dict[str, str]]:
+async def search_bing_batch(queries: List[str], max_per_query: int = 6) -> List[Dict[str, str]]:
+    loop = asyncio.get_running_loop()
     try:
-        with open(BING_SCRIPT_FILE, "w") as f:
+        with open(BATCH_SCRIPT_FILE, "w") as f:
-            f.write(BING_SCRIPT)
+            f.write(BATCH_SCRIPT)
         env = os.environ.copy()
         env["NODE_PATH"] = NODE_MODULES
-        result = subprocess.run(
+        fn = functools.partial(
-            [NODE_BIN, BING_SCRIPT_FILE, query, str(max_results)],
+            subprocess.run,
-            capture_output=True,
+            [NODE_BIN, BATCH_SCRIPT_FILE, json.dumps(queries), str(max_per_query)],
-            text=True,
+            capture_output=True, text=True, timeout=120, cwd=PROJECT_ROOT, env=env,
-            timeout=15,
-            cwd=PROJECT_ROOT,
-            env=env,
         )
-        if result.returncode != 0:
+        result = await loop.run_in_executor(None, fn)
-            logger.warning(f"Bing search failed: {result.stderr[:300]}")
-            return []
         for line in result.stdout.strip().split("\n"):
             line = line.strip()
             if line.startswith("["):
                 return json.loads(line)
         return []
     except subprocess.TimeoutExpired:
-        logger.warning("Bing search timed out")
+        logger.warning("Bing batch search timed out")
         return []
     except (json.JSONDecodeError, Exception) as e:
-        logger.warning(f"Bing search error: {e}")
+        logger.warning(f"Bing batch search error: {e}")
         return []
 
 
+async def search_bing(query: str, max_results: int = 10) -> List[Dict[str, str]]:
+    return await search_bing_batch([query], max_per_query=max_results)
+
+
 mcp = FastMCP("trade-search", log_level="WARNING")
 
 

backend/app/services/usage.py

@@ -2,6 +2,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy import select, func
 from fastapi import HTTPException, Depends
 from datetime import datetime, date
+from sqlalchemy import Date
 import logging
 
 from app.models import UsageLog, SystemConfig, User, Customer, Product
@@ -52,7 +53,7 @@ class UsageService:
         stmt = select(func.count()).where(
             UsageLog.user_id == user_id,
             UsageLog.action == action,
-            func.cast(UsageLog.created_at, date) == today,
+            func.cast(UsageLog.created_at, Date) == today,
         )
         result = await self.db.execute(stmt)
         return result.scalar() or 0
@@ -64,7 +65,7 @@ class UsageService:
         ), 0)).where(
             UsageLog.user_id == user_id,
             UsageLog.action == "translate",
-            func.cast(UsageLog.created_at, date) == today,
+            func.cast(UsageLog.created_at, Date) == today,
         )
         result = await self.db.execute(stmt)
         return result.scalar() or 0

user-frontend/src/views/Discovery.vue

@@ -11,12 +11,24 @@
             </el-form-item>
           </el-form>
           <div v-if="results.length">
-            <el-card v-for="r in results" :key="r.id || r.name" shadow="hover" style="margin-top:12px">
+            <el-alert v-if="provider === 'template' || provider === '建议'" title="以下为搜索策略建议，可用于手动开发客户" type="warning" show-icon :closable="false" style="margin-bottom:12px" />
-              <h4>{{ r.name }} <el-tag v-if="r.match_score" size="small" :type="scoreType(r.match_score)">{{ r.match_score }}%</el-tag></h4>
+            <el-alert v-if="provider === 'bing'" title="以下为搜索到的相关公司，点击'访问网站'了解更多，也可添加为客户" type="info" show-icon :closable="false" style="margin-bottom:12px" />
-              <p v-if="r.description" style="color:#666;font-size:13px">{{ r.description }}</p>
+            <el-card v-for="(r, idx) in results" :key="r.id || r.name || idx" shadow="hover" style="margin-top:12px">
-              <p v-if="r.contact" style="font-size:12px;color:#999">联系方式：{{ r.contact }}</p>
+              <div style="display:flex;justify-content:space-between;align-items:center">
-              <div style="margin-top:8px">
+                <h4 style="margin:0">{{ r.name }} <el-tag v-if="r.match_score" size="small" :type="scoreType(r.match_score)">{{ r.match_score }}%</el-tag></h4>
+                <el-tag v-if="r.source && provider !== 'template'" size="small" type="info">{{ r.source }}</el-tag>
+              </div>
+              <p v-if="r.description" style="color:#666;font-size:13px;margin:8px 0">{{ r.description }}</p>
+              <p v-if="r.contact" style="font-size:12px;color:#999;margin:4px 0">
+                联系方式：
+                <template v-if="r.contact.startsWith('http')">
+                  <a :href="r.contact" target="_blank" rel="noopener">{{ r.contact.substring(0, 50) }}{{ r.contact.length > 50 ? '…' : '' }}</a>
+                </template>
+                <template v-else>{{ r.contact }}</template>
+              </p>
+              <div style="margin-top:8px;display:flex;gap:8px">
                 <el-button size="small" type="primary" @click="addCustomer(r)">添加为客户</el-button>
+                <el-button v-if="r.contact && r.contact.startsWith('http')" size="small" @click="openUrl(r.contact)">访问网站</el-button>
               </div>
             </el-card>
           </div>
@@ -55,6 +67,9 @@ const tab = ref('search')
 const loading = ref(false)
 const searched = ref(false)
 const results = ref([])
+const provider = ref('')
+
+function openUrl(url) { window.open(url, '_blank') }
 const form = ref({ product: '', market: '' })
 const outForm = ref({ company: '', product: '', channel: 'email' })
 const outLoading = ref(false)
@@ -73,6 +88,7 @@ async function search() {
     })
     const d = res.data || res
     results.value = d.companies || d.items || d.results || d || []
+    provider.value = d.provider || ''
   } catch { ElMessage.error('挖掘失败') }
   finally { loading.value = false }
 }