254 lines
11 KiB
Python
254 lines
11 KiB
Python
# -*- coding:utf-8 -*-
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"""
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RagServer DSPY Handlers - RAG 核心业务逻辑 + 文件上传/删除
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"""
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from traceback import format_exc
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from ahserver.serverenv import ServerEnv
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from appPublic.registerfunction import RegisterFunction
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from appPublic.log import debug, exception
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from sqlor.dbpools import get_sor_context
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import json, os, uuid, time
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async def status_handler(request, params_kw, *args, **kwargs):
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return json.dumps({
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"service": "ragserver", "version": "0.1.0",
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"endpoints": ["/api/status", "/api/kb/list", "/api/doc/upload",
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"/api/doc/delete", "/api/search", "/api/engines"]
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}, indent=2, ensure_ascii=False)
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async def kb_list_handler(request, params_kw, *args, **kwargs):
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env = request._run_ns
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try:
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userorgid = await env.get_userorgid()
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async with get_sor_context(env, 'rag') as sor:
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recs = await sor.R("knowledge_bases", {"org_id": userorgid})
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rows = [dict(r) for r in recs]
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return json.dumps({"status": "SUCCEEDED", "data": {"rows": rows, "total": len(rows)}}, ensure_ascii=False, default=str)
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except Exception as e:
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exception(f"kb_list: {e}, {format_exc()}")
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return json.dumps({"error": str(e)})
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async def engines_handler(request, params_kw, *args, **kwargs):
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env = request._run_ns
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try:
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userorgid = await env.get_userorgid()
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async with get_sor_context(env, 'rag') as sor:
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sql = "SELECT * FROM engine_configs WHERE status='active' AND (org_id IS NULL OR org_id=${org_id}$) ORDER BY engine_type, priority DESC"
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recs = await sor.sqlExe(sql, {"org_id": userorgid})
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rows = [dict(r) for r in recs]
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return json.dumps({"status": "SUCCEEDED", "data": {"rows": rows, "total": len(rows)}}, ensure_ascii=False, default=str)
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except Exception as e:
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exception(f"engines: {e}, {format_exc()}")
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return json.dumps({"error": str(e)})
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async def search_handler(request, params_kw, *args, **kwargs):
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env = request._run_ns
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try:
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query = params_kw.get("query", "")
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kb_id = params_kw.get("kb_id", "")
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top_k = int(params_kw.get("top_k", 5))
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if not query:
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return json.dumps({"error": "query required"})
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try:
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from pipeline import search as pipeline_search
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result = pipeline_search(query, pipeline_name="kg-rag-standard",
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collection=kb_id or "knowledge",
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graph_name=kb_id or "knowledge",
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top_k=top_k, llm_func=None)
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return json.dumps(result, ensure_ascii=False)
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except ImportError:
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return json.dumps({"status": "FALLBACK", "message": "pipeline not available"})
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except Exception as e:
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exception(f"search: {e}, {format_exc()}")
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return json.dumps({"error": str(e)})
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async def doc_upload_handler(request, params_kw, *args, **kwargs):
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"""文件上传 → 保存 → DB记录 → 触发RAG入库"""
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env = request._run_ns
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try:
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userorgid = await env.get_userorgid()
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kb_id = params_kw.get("kb_id", "")
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file_name = params_kw.get("file_name", "upload.bin")
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if not kb_id:
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return json.dumps({"error": "kb_id required"})
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# Read raw file data from request body
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file_data = await request.read()
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if not file_data:
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return json.dumps({"error": "no file data"})
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# Save file
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doc_id = uuid.uuid4().hex[:16]
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ext = os.path.splitext(file_name)[1] or ".bin"
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saved_name = f"{doc_id}{ext}"
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files_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files")
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os.makedirs(files_dir, exist_ok=True)
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file_path = os.path.join(files_dir, saved_name)
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with open(file_path, "wb") as f:
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f.write(file_data)
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file_size = len(file_data)
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file_type = _detect_file_type(file_name, "application/octet-stream")
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# Create document record
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async with get_sor_context(env, 'rag') as sor:
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await sor.sqlExe(
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"INSERT INTO documents (id, kb_id, file_name, file_type, file_size, file_path, mime_type, status, org_id, created_at, updated_at) "
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"VALUES (${id}$, ${kb_id}$, ${file_name}$, ${file_type}$, ${file_size}$, ${file_path}$, ${mime_type}$, 'pending', ${org_id}$, NOW(), NOW())",
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{"id": doc_id, "kb_id": kb_id, "file_name": file_name, "file_type": file_type,
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"file_size": file_size, "file_path": "/idfile/files/" + saved_name,
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"mime_type": "application/octet-stream", "org_id": userorgid})
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# Update KB stats
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await sor.sqlExe(
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"UPDATE knowledge_bases SET doc_count=doc_count+1, total_size=total_size+${size}$ WHERE id=${kb_id}$",
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{"size": file_size, "kb_id": kb_id})
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# Trigger async ingest for text-based files
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ingest_result = None
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if file_type == "text":
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try:
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text = file_data.decode("utf-8", errors="replace")
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from pipeline import ingest as pipeline_ingest
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ingest_result = pipeline_ingest(
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text, pipeline_name="kg-rag-standard",
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collection=kb_id, graph_name=kb_id, llm_func=None)
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# Update status to done
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async with get_sor_context(env, 'rag') as sor:
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await sor.sqlExe(
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"UPDATE documents SET status='done', chunk_count=${chunks}$ WHERE id=${id}$",
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{"chunks": ingest_result.get("chunks", 0) if ingest_result else 0, "id": doc_id})
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if ingest_result:
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await sor.sqlExe(
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"UPDATE knowledge_bases SET chunk_count=chunk_count+${n}$ WHERE id=${kb_id}$",
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{"n": ingest_result.get("chunks", 0), "kb_id": kb_id})
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except Exception as e:
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exception(f"async ingest failed: {e}")
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return json.dumps({
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"status": "SUCCEEDED",
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"doc_id": doc_id,
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"file_name": file_name,
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"file_size": file_size,
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"file_type": file_type,
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"ingest": ingest_result
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}, ensure_ascii=False, default=str)
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except Exception as e:
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exception(f"doc_upload: {e}, {format_exc()}")
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return json.dumps({"error": str(e)})
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async def doc_delete_handler(request, params_kw, *args, **kwargs):
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"""文件删除 → 清理VDB → 清理图 → 清理DB → 删文件"""
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env = request._run_ns
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try:
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doc_id = params_kw.get("doc_id", "")
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if not doc_id:
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return json.dumps({"error": "doc_id required"})
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async with get_sor_context(env, 'rag') as sor:
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# Get document info
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recs = await sor.R("documents", {"id": doc_id})
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if not recs:
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return json.dumps({"error": "document not found"})
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doc = recs[0]
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# Get chunks to clean VDB
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chunks = await sor.R("document_chunks", {"doc_id": doc_id})
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# Delete from VDB
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if chunks:
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vector_ids = [c.vector_id for c in chunks if c.vector_id]
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if vector_ids:
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try:
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_call_vdb("/v1/delete", {"colname": doc.kb_id, "ids": vector_ids})
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except Exception as e:
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exception(f"vdb delete failed: {e}")
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# Delete from graph
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entities = await sor.R("entities", {"kb_id": doc.kb_id})
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if entities:
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try:
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_call_graph("/api/graph/save", {"graph": doc.kb_id})
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except Exception as e:
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exception(f"graph cleanup failed: {e}")
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# Delete DB records
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await sor.sqlExe("DELETE FROM document_chunks WHERE doc_id=${id}$", {"id": doc_id})
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await sor.sqlExe("DELETE FROM entities WHERE kb_id=${kb_id}$", {"kb_id": doc.kb_id})
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await sor.sqlExe("DELETE FROM entity_relations WHERE kb_id=${kb_id}$", {"kb_id": doc.kb_id})
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await sor.sqlExe("DELETE FROM documents WHERE id=${id}$", {"id": doc_id})
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# Update KB stats
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await sor.sqlExe(
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"UPDATE knowledge_bases SET doc_count=GREATEST(doc_count-1,0), total_size=GREATEST(total_size-${size}$,0), chunk_count=GREATEST(chunk_count-${n}$,0) WHERE id=${kb_id}$",
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{"size": doc.file_size, "n": len(chunks), "kb_id": doc.kb_id})
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# Delete file from disk
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file_path = doc.file_path
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if file_path and file_path.startswith("/idfile/"):
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real_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "files",
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os.path.basename(file_path))
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if os.path.exists(real_path):
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os.remove(real_path)
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return json.dumps({"status": "SUCCEEDED", "doc_id": doc_id, "chunks_deleted": len(chunks)})
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except Exception as e:
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exception(f"doc_delete: {e}, {format_exc()}")
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return json.dumps({"error": str(e)})
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def _detect_file_type(name, mime):
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"""Detect file type from name and MIME"""
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ext = os.path.splitext(name)[1].lower()
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if ext in ('.txt', '.md', '.json', '.csv', '.xml', '.html', '.py', '.js', '.css', '.yaml', '.yml'):
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return "text"
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if ext in ('.jpg', '.jpeg', '.png', '.gif', '.bmp', '.webp', '.svg'):
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return "image"
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if ext in ('.mp3', '.wav', '.flac', '.ogg', '.m4a', '.aac'):
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return "audio"
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if ext in ('.mp4', '.avi', '.mov', '.mkv', '.webm'):
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return "video"
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if ext == '.pdf':
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return "text"
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return "other"
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def _call_vdb(path, data, timeout=10):
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"""Call VDB service"""
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import urllib.request
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url = f"http://localhost:8886{path}"
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req = urllib.request.Request(url, data=json.dumps(data).encode(),
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headers={"Content-Type": "application/json"})
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with urllib.request.urlopen(req, timeout=timeout) as resp:
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return json.loads(resp.read())
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def _call_graph(path, data, timeout=10):
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"""Call Graph service"""
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import urllib.request
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url = f"http://localhost:9092{path}"
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req = urllib.request.Request(url, data=json.dumps(data).encode(),
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headers={"Content-Type": "application/json"})
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with urllib.request.urlopen(req, timeout=timeout) as resp:
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return json.loads(resp.read())
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def init_ragserver():
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env = ServerEnv()
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rf = RegisterFunction()
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rf.register("status", status_handler)
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rf.register("kb_list", kb_list_handler)
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rf.register("engines", engines_handler)
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rf.register("search", search_handler)
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rf.register("doc_upload", doc_upload_handler)
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rf.register("doc_delete", doc_delete_handler)
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