99 lines
4.5 KiB
Plaintext
99 lines
4.5 KiB
Plaintext
ns = params_kw.copy()
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kb_id = ns.get('kb_id', '')
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env = request._run_ns
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query = ns.get("query") or ns.get("value") or ns.get("keyword") or ns.get("text") or ""
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file_data = None
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file_name = None
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try:
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reader = await request.multipart()
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while True:
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part = await reader.next()
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if part is None: break
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if part.name == "file": file_data = await part.read(); file_name = part.filename; break
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except: pass
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if not file_data:
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try: file_data = await request.read();
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except: pass
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if file_data and len(file_data) < 10: file_data = None
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import base64, io
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top_k = int(ns.get('top_k', 5))
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if not query:
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return json.dumps({
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"widgettype": "VBox", "options": {"padding": "20px", "spacing": "16px"},
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"subwidgets": [
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{"widgettype": "Text", "options": {"text": "🔍 知识检索", "cfontsize": 20, "fontWeight": "bold"}},
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{"widgettype": "Text", "options": {"text": "请输入检索内容", "color": "#666", "marginTop": "20px"}}
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]
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}, ensure_ascii=False)
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import aiohttp
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async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=20)) as s:
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# 1. Embed
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r = await s.post('https://embedding.opencomputing.net:10443/api/embed',
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json={"texts": [query], "model": "CLIP-ViT-H-14"})
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emb = await r.json() if r.status == 200 else {}
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vec = emb.get("text_embeddings", emb.get("embeddings", [[]]))[0]
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if not vec:
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return json.dumps({"widgettype": "Text", "options": {"text": "向量化失败", "cfontsize": 14, "color": "#e74c3c"}}, ensure_ascii=False)
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# 2. VDB search
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recall_n = top_k * 3
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r2 = await s.post('https://vectordb.opencomputing.net:10443/v1/query',
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json={"colname": kb_id, "vector": vec, "pagerows": recall_n, "output_fields": ["*"]})
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vdb = await r2.json() if r2.status == 200 else {}
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raw_rows = vdb.get("data", {}).get("rows", [])
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if not isinstance(raw_rows, list):
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raw_rows = []
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hits = []
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for row in raw_rows:
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rid = str(row.get("id", ""))
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score = row.get("score", 0)
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# Resolve doc_id from chunk id pattern "xxxx_c0"
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doc_id = rid.rsplit('_c', 1)[0] if '_c' in rid else rid
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# Look up chunk text from DB
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chunk_text = ''
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doc_name = ''
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async with get_sor_context(env, 'rag') as sor:
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recs = await sor.sqlExe(
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"SELECT content, doc_id FROM document_chunks WHERE id=${id}$",
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{"id": rid})
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if recs:
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chunk_text = recs[0].content or ''
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doc_id = recs[0].doc_id or doc_id
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if chunk_text:
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hits.append({"id": rid, "doc_id": doc_id, "score": score, "text": chunk_text})
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hits.sort(key=lambda x: x.get("score", 0), reverse=True)
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hits = hits[:top_k]
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subwidgets = [
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{"widgettype": "Text", "options": {"text": f"🔍 检索: {query}", "cfontsize": 18, "fontWeight": "bold", "marginBottom": "8px"}},
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{"widgettype": "Text", "options": {"text": f"共 {len(hits)} 条结果 (召回 {len(raw_rows)} 条)", "cfontsize": 13, "color": "#888", "marginBottom": "16px"}}
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]
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if not hits:
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subwidgets.append({"widgettype": "Text", "options": {"text": "😔 未找到相关内容", "cfontsize": 14, "color": "#aaa", "halign": "center", "marginTop": "40px"}})
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else:
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for i, h in enumerate(hits):
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score_pct = round(float(h["score"]) * 100, 1)
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color = "#3b82f6" if score_pct > 60 else ("#10b981" if score_pct > 30 else "#f59e0b")
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subwidgets.append({
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"widgettype": "VBox",
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"options": {"padding": "12px 16px", "marginBottom": "8px", "border": "1px solid #e0e0e0", "borderLeft": f"3px solid {color}", "bgcolor": "#fafafa", "borderRadius": "4px"},
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"subwidgets": [
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{"widgettype": "HBox", "options": {"alignItems": "center", "marginBottom": "6px"}, "subwidgets": [
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{"widgettype": "Text", "options": {"text": f"#{i+1}", "cfontsize": 12, "fontWeight": "bold", "color": color, "marginRight": "8px"}},
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{"widgettype": "Text", "options": {"text": f"{score_pct}%", "cfontsize": 11, "bgcolor": color, "color": "#fff", "padding": "2px 8px", "borderRadius": "10px"}},
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{"widgettype": "Text", "options": {"text": f" {h['id'][:16]}", "cfontsize": 11, "color": "#999", "marginLeft": "8px"}}
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]},
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{"widgettype": "Text", "options": {"text": h["text"][:300], "cfontsize": 13, "color": "#333", "lineHeight": "1.6"}}
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]
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})
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return json.dumps({"widgettype": "VBox", "options": {"padding": "20px", "spacing": "4px"}, "subwidgets": subwidgets}, ensure_ascii=False, default=str)
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