TradeMate Dev
bed5c7abef
- Separate workspace landing from login for better UX - Referral system rewards both parties with Pro days - Quota enforcement prevents abuse without breaking endpoints - 7-day free trial with auto-downgrade on expiry - Admin-managed search provider config (SearXNG, Bing) - 15% discount on annual subscriptions - MCP search server wrapping opencode search - Fix discovery module field name mismatch causing 422
285 lines
12 KiB
Python
285 lines
12 KiB
Python
import asyncio
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import json
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import logging
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from typing import Dict, Any, Optional
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from app.ai.router import get_ai_router
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from app.services.search_web import search_companies, fetch_page_text
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from app.services.mcp_search_client import mcp_search
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logger = logging.getLogger(__name__)
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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。
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请以 JSON 格式返回（不要用 markdown 代码块标记）：
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{
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"match_score": 0-100,
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"match_reason": "为什么匹配/不匹配",
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"company_summary": "这家公司的主要业务",
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"product_fit": "产品匹配度说明",
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"contact_info": {
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"emails": ["找到的邮箱"],
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"phones": ["找到的电话"],
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"social": ["LinkedIn等社媒链接"]
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}
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}
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只返回 JSON，不要其他内容。"""
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class DiscoveryService:
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def __init__(self):
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ai_router = get_ai_router()
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self.ai = ai_router
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self._ai_available = len(ai_router.providers) > 0
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async def search(self, product_description: str, target_market: str) -> Dict[str, Any]:
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queries = self._build_queries(product_description, target_market)
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all_results = await self._mcp_search_all(queries)
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if all_results:
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return {
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"companies": all_results[:15],
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"query": product_description,
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"market": target_market,
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"provider": "mcp_search",
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}
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all_results = await self._google_search_all(queries)
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if all_results:
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return {
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"companies": all_results[:15],
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"query": product_description,
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"market": target_market,
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"provider": "web_search",
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}
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logger.info("No real search results, using AI strategy")
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return await self._ai_strategy(product_description, target_market)
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async def analyze(self, company_url: str, product_description: str) -> Dict[str, Any]:
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page_text = await fetch_page_text(company_url)
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company_info = {"url": company_url}
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if page_text:
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company_info["page_text"] = page_text[:2500]
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if not self._ai_available:
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return self._template_analysis(company_url)
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prompt = f"""用户的产品：{product_description}
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目标公司信息：
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URL: {company_url}
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网页内容：{page_text[:2500] if page_text else "无法获取网页内容"}
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请分析该公司的业务与用户产品的匹配度。"""
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try:
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result = await self.ai.chat(prompt, system_prompt=ANALYZE_MATCH_PROMPT)
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content = result.get("reply", "")
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parsed = self._extract_json(content)
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if parsed:
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parsed["url"] = company_url
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parsed["provider"] = result.get("provider_used", "unknown")
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return parsed
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except (json.JSONDecodeError, Exception) as e:
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logger.warning(f"Analysis AI parse failed: {e}")
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return self._template_analysis(company_url)
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async def outreach(self, company_info: Dict[str, Any], product_info: Dict[str, Any]) -> Dict[str, Any]:
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if not self._ai_available:
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return self._template_outreach(company_info, product_info)
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prompt = f"""目标公司信息：
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{json.dumps(company_info, ensure_ascii=False)}
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我的产品信息：
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{json.dumps(product_info, ensure_ascii=False)}
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请生成个性化触达文案。"""
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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。
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请以 JSON 格式返回（不要用 markdown 代码块标记）：
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{
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"subject": "邮件标题（如适用）",
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"linkedin_message": "LinkedIn 私信文案（150字以内）",
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"whatsapp_message": "WhatsApp 消息文案（100字以内）",
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"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）",
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"key_points": ["客户关注的3个要点"],
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"tips": ["发送时的建议"]
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}"""
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try:
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result = await self.ai.chat(prompt, system_prompt=system)
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content = result.get("reply", "")
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parsed = self._extract_json(content)
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if parsed:
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parsed["provider"] = result.get("provider_used", "unknown")
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return parsed
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except (json.JSONDecodeError, Exception) as e:
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logger.warning(f"Outreach AI parse failed: {e}")
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return self._template_outreach(company_info, product_info)
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async def _mcp_search_all(self, queries: list) -> list:
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seen_urls = set()
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tasks = [asyncio.create_task(mcp_search(q, max_results=6)) for q in queries[:2]]
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all_results = []
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try:
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for coro in asyncio.as_completed(tasks, timeout=8):
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try:
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results = await coro
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for r in results:
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url = r.get("url", "").rstrip("/")
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if url and url not in seen_urls:
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seen_urls.add(url)
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all_results.append(r)
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except (asyncio.TimeoutError, Exception) as e:
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logger.debug(f"MCP search query failed: {e}")
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except asyncio.TimeoutError:
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logger.warning("MCP search overall timeout")
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finally:
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for t in tasks:
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if not t.done():
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t.cancel()
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await asyncio.gather(*tasks, return_exceptions=True)
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if all_results:
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return self._dedup_and_filter(all_results)[:15]
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return []
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def _dedup_and_filter(self, results: list) -> list:
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seen = set()
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filtered = []
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for r in results:
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url = r.get("url", "").rstrip("/")
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title = r.get("title", "")
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if not url or url in seen:
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continue
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seen.add(url)
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s = url.split("/")[2] if "://" in url else url
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hostname = s.split(":")[0].lower() if ":" in s else s.lower()
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if any(tld in hostname for tld in [".cn", ".com.cn", ".edu", ".ac.", ".gov"]):
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continue
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if any(domain in hostname for domain in
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["sciencedirect", "mdpi", "springer", "wiley", "acm.org",
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"ieee.org", "researchgate", "nature.com", "oup.com",
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"sagepub", "tandfonline", "ncbi", "semanticscholar",
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"britannica", "dictionary", "cambridge", "iciba", "wikipedia"]):
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continue
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filtered.append(r)
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return filtered
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async def _google_search_all(self, queries: list) -> list:
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all_results = []
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seen_urls = set()
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for q in queries[:3]:
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results = await search_companies(q, max_results=8)
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for r in results:
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url = r["url"].rstrip("/")
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if url not in seen_urls:
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seen_urls.add(url)
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all_results.append(r)
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if len(all_results) >= 15:
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break
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return self._dedup_and_filter(all_results)[:15]
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def _build_queries(self, product: str, market: str) -> list:
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return [
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f"{product} importer {market}",
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f"{product} distributor {market}",
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f"{product} wholesale buyer {market}",
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f"{product} procurement {market}",
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f"{product} company {market}",
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f"buy {product} from {market}",
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f"{product} supply chain {market}",
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f"top {product} manufacturers {market}",
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f"{product} import export {market}",
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f"{product} trading company {market}",
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]
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def _extract_json(self, text: str) -> Optional[dict]:
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text = text.strip()
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for prefix in ["```json", "```", "```JSON"]:
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if text.startswith(prefix):
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text = text[len(prefix):]
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for suffix in ["```"]:
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if text.endswith(suffix):
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text = text[:-len(suffix)]
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text = text.strip()
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try:
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return json.loads(text)
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except json.JSONDecodeError:
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import re
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brace = text.find("{")
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end = text.rfind("}")
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if brace >= 0 and end > brace:
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try:
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return json.loads(text[brace:end+1])
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except json.JSONDecodeError:
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pass
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return None
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async def _ai_strategy(self, product: str, market: str) -> Dict[str, Any]:
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if not self._ai_available:
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return self._template_strategy(product, market)
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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。
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请以 JSON 格式返回（不要用 markdown 代码块标记）：
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{
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"companies": [
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{"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"}
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],
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"strategy": "整体获取策略建议",
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"tips": ["搜索建议1", "搜索建议2"]
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}
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要求：
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- 公司名称要真实感，不要编造知名大公司
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- 公司业务要与产品相关
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- 匹配度要有区分度，60-95之间
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- 至少返回10家
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- 只返回 JSON，不要其他内容"""
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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。"
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try:
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result = await self.ai.chat(prompt, system_prompt=system)
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content = result.get("reply", "")
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parsed = self._extract_json(content)
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if parsed and "companies" in parsed:
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parsed["provider"] = result.get("provider_used", "unknown")
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parsed["ai_generated"] = True
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return parsed
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return self._template_strategy(product, market)
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except Exception as e:
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logger.warning(f"AI strategy failed: {e}")
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return self._template_strategy(product, market)
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def _template_strategy(self, product: str, market: str) -> Dict[str, Any]:
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return {
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"companies": [
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{"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"},
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{"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"},
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],
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"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",
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"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"],
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"provider": "template",
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"ai_generated": True,
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}
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def _template_analysis(self, url: str) -> Dict[str, Any]:
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return {
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"match_score": 50,
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"match_reason": "无法获取网页内容进行分析，建议手动查看",
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"url": url,
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"provider": "template",
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}
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def _template_outreach(self, company: Dict[str, Any], product: Dict[str, Any]) -> Dict[str, Any]:
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company_name = company.get("name", "")
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product_name = product.get("name", "")
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return {
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"subject": f"关于{product_name}的合作机会",
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"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。",
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"whatsapp_message": f"Hello! We are a professional {product_name} manufacturer. Interested in exploring cooperation? Happy to share details.",
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"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]",
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"key_points": ["产品质量有保障", "价格有竞争力", "可定制"],
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"tips": ["发送前先了解对方背景", "LinkedIn 消息要简短"],
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"provider": "template",
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}
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