fix: restore detail.ui with upload zone + upload_file.dspy
This commit is contained in:
parent
224496ae0e
commit
0385670e38
@ -6,10 +6,9 @@
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"widgettype": "HBox",
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"options": {"width": "100%", "bgcolor": "#f8f9fa", "padding": "10px 16px", "alignItems": "center", "borderBottom": "1px solid #e0e0e0"},
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"subwidgets": [
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{"widgettype": "Text", "options": {"text": "← 知识库列表", "css": "clickable", "cfontsize": 14, "color": "#4a90d9"}, "binds": [
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{"wid": "self", "event": "click", "actiontype": "urlwidget", "target": "app.rag_main_content", "mode": "replace",
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"options": {"url": "{{entire_url('/rag/knowledge_bases_list/index.ui')}}"}}
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]},
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{"widgettype": "Text", "options": {"text": "← 知识库列表", "css": "clickable", "cfontsize": 14, "color": "#4a90d9"},
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"binds": [{"wid": "self", "event": "click", "actiontype": "urlwidget", "target": "app.rag_main_content", "mode": "replace",
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"options": {"url": "{{entire_url('/rag/knowledge_bases_list/index.ui')}}"}}]},
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{"widgettype": "Text", "options": {"text": " / ", "cfontsize": 14, "color": "#ccc"}},
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{"widgettype": "Text", "options": {"text": "📚 {{params_kw.kb_name or '知识库'}}", "cfontsize": 16, "fontWeight": "bold", "color": "#333"}},
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{"widgettype": "Text", "options": {"text": "", "css": "filler"}}
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@ -21,63 +20,58 @@
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"subwidgets": [
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{
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"widgettype": "VBox",
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"options": {"cwidth": 16, "bgcolor": "#fafafa", "borderRight": "1px solid #e0e0e0", "spacing": 0},
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"options": {"cwidth": 16, "bgcolor": "#fafafa", "borderRight": "1px solid #e0e0e0", "spacing": 0, "overflow": "hidden", "flexShrink": "0"},
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"subwidgets": [
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{
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"widgettype": "HBox",
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"options": {"padding": "10px 12px", "bgcolor": "#f0f0f0", "borderBottom": "1px solid #e0e0e0"},
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"subwidgets": [
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{"widgettype": "Text", "options": {"text": "📁 目录结构", "cfontsize": 13, "fontWeight": "bold", "color": "#666"}}
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]
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},
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{
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"widgettype": "Tree",
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"options": {
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"id": "dir_tree",
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"parentField": "parentid",
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"idField": "id",
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"textField": "label",
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{"widgettype": "HBox", "options": {"padding": "10px 12px", "bgcolor": "#f0f0f0", "borderBottom": "1px solid #e0e0e0"},
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"subwidgets": [{"widgettype": "Text", "options": {"text": "📁 目录结构", "cfontsize": 13, "fontWeight": "bold", "color": "#666"}}]},
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{"widgettype": "Tree", "id": "dir_tree",
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"options": {"select_only": true, "title": "目录", "parentField": "parentid", "idField": "id", "textField": "label",
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"dataurl": "{{entire_url('./get_tree_data.dspy')}}?kb_id={{params_kw.kb_id}}",
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"newdata_params": {"kb_id": "{{params_kw.kb_id}}"},
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"editable": {
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"fields": [
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{"name": "name", "title": "名称", "type": "str", "length": 255, "uitype": "str", "label": "名称"}
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],
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"editable": {"fields": [{"name": "name", "title": "名称", "type": "str", "length": 255, "uitype": "str", "label": "名称"}],
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"add_url": "{{entire_url('./new_tree_item.dspy')}}",
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"update_url": "{{entire_url('./update_tree_item.dspy')}}",
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"delete_url": "{{entire_url('./delete_tree_item.dspy')}}"
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}
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}
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}
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"delete_url": "{{entire_url('./delete_tree_item.dspy')}}"}}}
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]
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},
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{
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"widgettype": "VBox",
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"id": "detail_content",
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"options": {"css": "filler", "padding": "16px", "spacing": "0"},
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"options": {"css": "filler", "padding": "16px", "spacing": "12px"},
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"subwidgets": [
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{
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"widgettype": "urlwidget",
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"id": "file_list_panel",
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"options": {
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"url": "{{entire_url('./file_list.dspy')}}?kb_id={{params_kw.kb_id}}&id=__root__"
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"widgettype": "UiFile", "id": "file_drop_zone",
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"options": {"accept": "", "multiple": true, "preview": false,
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"otext": "📂 拖拽文件到此处上传，或点击选择文件",
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"width": "100%", "cheight": 10, "css": "card",
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"border": "2px dashed #3b82f6", "alignItems": "center", "justifyContent": "center",
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"kb_id": "{{params_kw.kb_id}}"},
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"binds": [
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{"wid": "self", "event": "dragover", "actiontype": "script",
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"script": "event.preventDefault();event.stopPropagation()"},
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{"wid": "self", "event": "drop", "actiontype": "script",
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"script": "event.preventDefault();event.stopPropagation()"}
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]
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},
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{"widgettype": "Text", "id": "upload_status",
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"options": {"cfontsize": 12, "color": "#50b86c", "marginTop": "0", "text": "支持 TXT/PDF/JPG/PNG/MP3/WAV/MP4"}},
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{"widgettype": "VScrollPanel", "id": "file_list_panel",
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"options": {"css": "filler", "padding": "0", "spacing": "0"},
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"subwidgets": [
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{"widgettype": "urlwidget",
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"options": {"url": "{{entire_url('./file_list.dspy')}}?kb_id={{params_kw.kb_id}}", "css": "filler"}}
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]}
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]
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}
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]
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}
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],
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"binds": [
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{
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"wid": "dir_tree",
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"event": "node_selected",
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"actiontype": "urlwidget",
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"target": "file_list_panel",
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"mode": "replace",
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"options": {
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"url": "{{entire_url('./file_list.dspy')}}?kb_id={{params_kw.kb_id}}"
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}
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}
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]
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}
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]
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}
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{"wid": "dir_tree", "event": "node_selected", "actiontype": "script",
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"script": "window._rag_folder=event.params.id||''"},
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{"wid": "file_drop_zone", "event": "changed", "actiontype": "script", "target": "file_drop_zone",
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"script": "var kb_id=this.opts.kb_id||'';var tree=bricks.getWidgetById('dir_tree',bricks.app.root);var folder=window._rag_folder||'';var files=this.value;if(!files)return;if(!Array.isArray(files))files=[files];var st=document.getElementById('upload_status');var done=0;var total=files.length;function refreshList(){var fp=bricks.getWidgetById('file_list_panel',bricks.app.root);fp.clear_widgets();var url=location.origin+'/rag/knowledge_bases_list/file_list.dspy?_webbricks_=1&kb_id='+kb_id+(folder?'&id='+folder:'');bricks.widgetBuild({widgettype:'urlwidget',options:{url:url,css:'filler'}},fp).then(function(w){if(w)fp.add_widget(w)})};for(var i=0;i<files.length;i++){(function(f){var x=new XMLHttpRequest();x.open('POST','/rag/knowledge_bases_list/upload_file.dspy?kb_id='+encodeURIComponent(kb_id)+'&file_name='+encodeURIComponent(f.name)+'&folder='+encodeURIComponent(folder));x.onload=function(){done++;if(x.status===200){if(st)st.innerText='上传成功 '+done+'/'+total}else{if(st)st.innerText='上传失败'}if(done>=total)refreshList()};x.onerror=function(){done++;if(st)st.innerText='上传失败';if(done>=total)refreshList()};x.send(f)})(files[i])}"},
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{"wid": "dir_tree", "event": "node_selected", "actiontype": "urlwidget", "target": "file_list_panel", "mode": "replace",
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"options": {"url": "{{entire_url('./file_list.dspy')}}?kb_id={{params_kw.kb_id}}"}}
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]
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}
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222
wwwroot/knowledge_bases_list/upload_file.dspy
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222
wwwroot/knowledge_bases_list/upload_file.dspy
Normal file
@ -0,0 +1,222 @@
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ns = params_kw.copy()
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kb_id = ns.get('kb_id', '')
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folder_id = ns.get('folder', '')
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file_name = ns.get('file_name', 'upload.bin')
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if not kb_id:
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return json.dumps({"status": "error", "error": "kb_id required"}, ensure_ascii=False)
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file_data = await request.read()
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if not file_data:
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return json.dumps({"status": "error", "error": "no file data"}, ensure_ascii=False)
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env = request._run_ns
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userorgid = await env.get_userorgid()
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doc_id = str(uuid()).replace('-', '')[:16]
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ext = '.' + file_name.rsplit('.', 1)[1] if '.' in file_name else '.bin'
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file_path = '/d/rag/ragserver/pkgs/rag/rag/files/' + doc_id + ext
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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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ext_l = ext.lower()
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text_exts = {'.txt', '.md', '.csv', '.json', '.xml', '.html', '.htm', '.py', '.js', '.css', '.yaml', '.yml', '.log', '.rst'}
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doc_exts = {'.pdf', '.docx', '.pptx', '.xlsx', '.doc', '.ppt', '.xls'}
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image_exts = {'.jpg', '.jpeg', '.png', '.bmp', '.gif', '.webp'}
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audio_exts = {'.mp3', '.wav', '.flac', '.ogg', '.m4a', '.aac'}
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video_exts = {'.mp4', '.avi', '.mov', '.mkv', '.webm'}
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text = ''
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chunks_n = 0
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face_count = 0
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voice_speakers = 0
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meta_parts = {}
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# --- TEXT EXTRACTION ---
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if ext_l in text_exts:
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text = file_data.decode('utf-8', errors='replace')
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elif ext_l == '.pdf':
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import io; from PyPDF2 import PdfReader
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try:
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r = PdfReader(io.BytesIO(file_data))
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text = '\n'.join(p.extract_text() or '' for p in r.pages)
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except: pass
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elif ext_l == '.docx':
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import io; from docx import Document
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try:
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doc = Document(io.BytesIO(file_data))
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text = '\n'.join(p.text for p in doc.paragraphs if p.text.strip())
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except: pass
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elif ext_l == '.pptx':
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import io; from pptx import Presentation
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try:
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prs = Presentation(io.BytesIO(file_data))
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parts = []
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for s in prs.slides:
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for sh in s.shapes:
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if hasattr(sh, 'text') and sh.text.strip():
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parts.append(sh.text)
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text = '\n'.join(parts)
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except: pass
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elif ext_l in {'.xlsx', '.xls'}:
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import io; from openpyxl import load_workbook
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try:
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wb = load_workbook(io.BytesIO(file_data), read_only=True, data_only=True)
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rows = []
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for ws in wb.worksheets:
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for row in ws.iter_rows(values_only=True):
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r = ' | '.join(str(c) if c is not None else '' for c in row)
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if r.strip(): rows.append(r)
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text = '\n'.join(rows)
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except: pass
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import aiohttp, base64
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# --- IMAGE: face detection + CLIP visual embedding ---
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if ext_l in image_exts:
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img_b64 = base64.b64encode(file_data).decode()
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async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=15)) as s:
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# Face detection
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try:
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r = await s.post('https://media.opencomputing.net:10443/face/api/detect', json={"images": [img_b64]})
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if r.status == 200:
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fd = await r.json()
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results = fd.get("results", [])
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if results and isinstance(results[0], dict):
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face_count = len(results[0].get("faces", results[0].get("detections", [])))
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meta_parts['face'] = face_count
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except: pass
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# --- AUDIO: voiceprint extraction ---
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if ext_l in audio_exts:
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async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=60)) as s:
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try:
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form = aiohttp.FormData()
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form.add_field('file', file_data, filename=file_name)
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r = await s.post('https://media.opencomputing.net:10443/voiceprint/extract/submit', data=form)
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if r.status == 200:
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vd = await r.json()
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if vd.get('status') == 'SUCCEEDED':
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voice_speakers = vd.get('speakers', 1)
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elif vd.get('embedding'):
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voice_speakers = 1
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meta_parts['voiceprint'] = voice_speakers
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except: pass
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# --- VIDEO: frame extraction + audio extraction (via ffmpeg) ---
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if ext_l in video_exts:
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import subprocess, tempfile
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meta_parts['video'] = 'pending'
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# Extract keyframe for face detection
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try:
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tmp_img = '/tmp/' + doc_id + '_frame.jpg'
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subprocess.run(['ffmpeg', '-y', '-i', file_path, '-vframes', '1', '-q:v', '2', tmp_img],
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capture_output=True, timeout=30)
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if __import__('os').path.exists(tmp_img):
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with open(tmp_img, 'rb') as fi:
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frame_data = fi.read()
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img_b64 = base64.b64encode(frame_data).decode()
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async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=15)) as s:
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try:
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r = await s.post('https://media.opencomputing.net:10443/face/api/detect', json={"images": [img_b64]})
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if r.status == 200:
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fd = await r.json()
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results = fd.get("results", [])
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if results and isinstance(results[0], dict):
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face_count = len(results[0].get("faces", results[0].get("detections", [])))
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except: pass
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__import__('os').remove(tmp_img)
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except: pass
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# Extract audio for voiceprint
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try:
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tmp_audio = '/tmp/' + doc_id + '_audio.wav'
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subprocess.run(['ffmpeg', '-y', '-i', file_path, '-vn', '-acodec', 'pcm_s16le', '-ar', '16000', '-ac', '1', tmp_audio],
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capture_output=True, timeout=60)
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if __import__('os').path.exists(tmp_audio) and __import__('os').path.getsize(tmp_audio) > 44:
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with open(tmp_audio, 'rb') as fa:
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audio_data = fa.read()
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async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=60)) as s:
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try:
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form = aiohttp.FormData()
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form.add_field('file', audio_data, filename='audio.wav')
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r = await s.post('https://media.opencomputing.net:10443/voiceprint/extract/submit', data=form)
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if r.status == 200:
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vd = await r.json()
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if vd.get('status') == 'SUCCEEDED' or vd.get('embedding'):
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voice_speakers = vd.get('speakers', 1)
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except: pass
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__import__('os').remove(tmp_audio)
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except: pass
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meta_parts['face'] = face_count
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meta_parts['voiceprint'] = voice_speakers
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# --- RAG INGEST (text + image CLIP embedding) ---
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if text and len(text.strip()) > 10:
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paragraphs = text.split('\n')
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chunks = []
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cur = ''
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for p in paragraphs:
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p = p.strip()
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if not p:
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if cur: chunks.append(cur); cur = ''
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continue
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if len(cur) + len(p) < 500:
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cur = (cur + '\n' + p).strip()
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else:
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if cur: chunks.append(cur)
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cur = p
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if cur: chunks.append(cur)
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if chunks:
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async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=15)) as s:
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try:
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r = await s.post('https://embedding.opencomputing.net:10443/api/embed',
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json={"texts": chunks, "model": "CLIP-ViT-H-14"})
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emb_data = await r.json() if r.status == 200 else {}
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embeddings = emb_data.get("text_embeddings", emb_data.get("embeddings", []))
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except:
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embeddings = []
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vector_ids = []
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if embeddings:
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try:
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vdb_data = {"collection": kb_id, "data": [
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{"id": doc_id + "_" + str(i), "vector": emb, "text": chunks[i]}
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for i, emb in enumerate(embeddings)]}
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await s.post('https://vectordb.opencomputing.net:10443/v1/upsert', json=vdb_data)
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vector_ids = [doc_id + "_" + str(i) for i in range(len(embeddings))]
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except:
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pass
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async with get_sor_context(env, 'rag') as sor:
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for i, chunk_text in enumerate(chunks):
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vid = vector_ids[i] if i < len(vector_ids) else ''
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await sor.sqlExe(
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"INSERT INTO document_chunks (id, doc_id, kb_id, chunk_index, content, vector_id, created_at) "
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"VALUES (" + "${id}$, ${doc_id}$, ${kb_id}$, ${idx}$, ${content}$, ${vid}$, NOW())",
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{"id": doc_id + "_c" + str(i), "doc_id": doc_id, "kb_id": kb_id,
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"idx": i, "content": chunk_text[:2000], "vid": vid})
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chunks_n = len(chunks)
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# --- SAVE TO DB ---
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import json as _json
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meta_json = _json.dumps(meta_parts, ensure_ascii=False)
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status = '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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"INSERT INTO documents (id, kb_id, folder_id, file_name, file_type, file_size, file_path, mime_type, status, chunk_count, metadata, org_id, created_at, updated_at) "
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"VALUES (" + "${id}$, ${kb_id}$, ${folder_id}$, ${file_name}$, 'other', ${file_size}$, ${file_path}$, 'application/octet-stream', ${status}$, ${chunks}$, ${meta}$, ${org_id}$, NOW(), NOW())",
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{"id": doc_id, "kb_id": kb_id, "folder_id": folder_id, "file_name": file_name,
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"file_size": file_size, "file_path": "/idfile/files/" + doc_id + ext,
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"status": status, "chunks": chunks_n, "meta": meta_json, "org_id": userorgid})
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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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if chunks_n:
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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": chunks_n, "kb_id": kb_id})
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|
||||
result = {"status": "SUCCEEDED", "doc_id": doc_id, "file_name": file_name,
|
||||
"file_size": file_size, "folder_id": folder_id,
|
||||
"text_len": len(text), "chunks": chunks_n,
|
||||
"faces": face_count, "speakers": voice_speakers}
|
||||
return _json.dumps(result, ensure_ascii=False, default=str)
|
||||
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Reference in New Issue
Block a user