完成 EDL 的构建，完成 QA 的拒答流

bot/services/digital-ide.ts

@@ -0,0 +1,46 @@
+import '../plugins/image';
+
+import { mapper, plugins, LagrangeContext, PrivateMessage, GroupMessage, Send } from 'lagrange.onebot'
+
+import { apiGetIntentRecogition, apiQueryVecdb } from '../api/vecdb';
+
+import { handleGroupIntent } from './intent';
+
+let lastCall = undefined;
+
+export class Impl {
+    @mapper.onGroup(932987873, { at: false })
+    async handleDigitalGroup(c: LagrangeContext<GroupMessage>) {
+        const texts = [];
+        const message = c.message;
+        for (const msg of message.message) {
+            if (msg.type === 'text') {
+                texts.push(msg.data.text);
+            }
+        }
+        const reply: Send.Default[] = [];
+        const axiosRes = await apiGetIntentRecogition({ query: texts.join('\n') });
+        const res = axiosRes.data;
+
+        if (res.code == 200) {
+            const intentResult = res.data;
+            // 如果 不确定性 太高，就将意图修改为 
+            if (intentResult.uncertainty >= 0.33) {
+                intentResult.name = 'others';
+            }
+            const uncertainty = Math.round(intentResult.uncertainty * 1000) / 1000;
+            const intentDebug = `【意图: ${intentResult.name} 不确定度: ${uncertainty}】`;
+            const anwser = await handleGroupIntent(c, intentResult);
+            if (anwser !== undefined) {
+                c.sendMessage(anwser + '\n' + intentDebug);
+            }
+
+        } else {
+            const now = Date.now();
+            if (lastCall === undefined || (now - lastCall) >= 60 * 10 * 1000) {
+                c.sendMessage('RAG 系统目前离线');
+            }
+            lastCall = Date.now();
+        }
+    }
+}

bot/services/intent.ts

@@ -23,13 +23,15 @@ async function useRagLLM(c: LagrangeContext<GroupMessage>, intentResult: IntentR
             texts.push(msg.data.text);
         }
     }
-
+    const query = texts.join(' ').trim();
-
+    if (query.length === 0) {
-    const { data } = await apiQueryVecdb({ query: texts.join(' '), k: 3 });
+        return undefined;
+    }
+    const { data } = await apiQueryVecdb({ query, k: 3 });
     if (data.code === 200) {
-        const messages: apiQueryVecdbDataItem[] = data.data.filter(m => m.score <= 0.8);
+        const messages: apiQueryVecdbDataItem[] = data.data.filter(m => m.score <= 0.7);
         if (messages.length === 0) {
-            c.sendMessage('未在数据库中检索到相关内容。');
+            return '未在数据库中检索到相关内容。';
         } else {
             const query = makePrompt(messages);
             const res = await llm.answer([
@@ -40,16 +42,16 @@ async function useRagLLM(c: LagrangeContext<GroupMessage>, intentResult: IntentR
             ]);
             if (typeof res === 'string') {
                 const links = messages.map(m => m.source);
-                
+                const linkSet = new Set<string>(links);
-                const reference = ['参考链接：', ...links].join('\n');
+                const reference = ['参考链接：', ...linkSet].join('\n');
                 const anwser = res + '\n\n' + reference;
-                c.sendMessage(anwser);
+                return anwser;
             }
         }
 
     } else {
         logger.error('apiQueryVecdb 接口访问失败: ' + JSON.stringify(data));
-        return false;
+        return undefined;
     }
 }
 

bot/services/test.ts

@@ -1,6 +1,6 @@
 import '../plugins/image';
 
-import { mapper, plugins, LagrangeContext, PrivateMessage, GroupMessage, Send } from 'lagrange.onebot'
+import { mapper, plugins, LagrangeContext, PrivateMessage, GroupMessage, Send, logger } from 'lagrange.onebot'
 
 import { apiGetIntentRecogition, apiQueryVecdb } from '../api/vecdb';
 
@@ -41,9 +41,16 @@ export class Impl {
             if (intentResult.uncertainty >= 0.33) {
                 intentResult.name = 'others';
             }
+            
             const uncertainty = Math.round(intentResult.uncertainty * 1000) / 1000;
-            c.sendMessage(`【意图: ${intentResult.name} 不确定度: ${uncertainty}】`);
+            const intentDebug = `【意图: ${intentResult.name} 不确定度: ${uncertainty}】`;
-            handleGroupIntent(c, intentResult);
+            const anwser = await handleGroupIntent(c, intentResult);
+            if (anwser === undefined) {
+                c.sendMessage('拒答' + '\n' + intentDebug);
+            } else {
+                c.sendMessage(anwser + '\n' + intentDebug);
+            }
+
         } else {
             c.sendMessage('RAG 系统目前离线');
         }

config/push-to-server.sh

@@ -0,0 +1 @@
+scp -r config ubuntu@101.43.239.71:/home/ubuntu/files/data/llm-rag

notebook/clear-logs.ipynb

@@ -0,0 +1,99 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import zipfile\n",
+    "from typing import *\n",
+    "import os\n",
+    "import json\n",
+    "import yaml\n",
+    "\n",
+    "log_home = '../logs'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_log_file_line(file: str, level='DEBUG') -> Generator:\n",
+    "    if file.endswith('.log'):\n",
+    "        for line in open(file, 'r', encoding='utf-8'):\n",
+    "            if level in line:\n",
+    "                yield line\n",
+    "    elif file.endswith('.zip'):\n",
+    "        with zipfile.ZipFile(file, 'r') as zip:\n",
+    "            for zip_file in zip.namelist():\n",
+    "                file_bytes = zip.read(zip_file)\n",
+    "                for line in file_bytes.decode('utf-8').split('\\n'):\n",
+    "                    if level in line:\n",
+    "                        yield line\n",
+    "                "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rag_log_files = [os.path.join(log_home, file) for file in os.listdir(log_home) if file.startswith('rag')]\n",
+    "\n",
+    "interesting_data = []\n",
+    "\n",
+    "for rag_file in rag_log_files:\n",
+    "    for line in get_log_file_line(rag_file, level='DEBUG'):\n",
+    "        try:\n",
+    "            data = line.split('|')[-1].strip()\n",
+    "            data = eval(data)\n",
+    "            if data['intent']['name'] != 'others':\n",
+    "                interesting_data.append(data)\n",
+    "        except Exception:\n",
+    "            pass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "story = {'stories': []}\n",
+    "for d in interesting_data:\n",
+    "    story['stories'].append({\n",
+    "        'message': d['query'],\n",
+    "        'intent': d['intent']['name']\n",
+    "    })\n",
+    "\n",
+    "with open('../config/qq.story.yml', 'w', encoding='utf-8') as fp:\n",
+    "    yaml.dump(story, fp, allow_unicode=True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

rag/services/intent.py

@@ -8,6 +8,7 @@ import torch
 from rag.db.embedding import embedding
 from rag.api.constant import StatusCode, MsgCode
 from rag.api.admin import app
+from rag.api.admin import logger
 from rag.api.config import necessary_files
 from rag.model.enn import LinearEnn, train_enn
 
@@ -60,30 +61,31 @@ def reload_embedding_mapping():
     response.status_code = StatusCode.success.value
     return response
 
+# TODO: 删除该接口
 @app.route('/intent/retrain-embedding-mapping', methods=['post'])
 def retrain_embedding_mapping():
-    engine = PromptEngine(necessary_files['intent-story'])
+    # engine = PromptEngine(necessary_files['intent-story'])
-    engine.merge_stories_from_yml(necessary_files['issue-story'])
+    # engine.merge_stories_from_yml(necessary_files['issue-story'])
-    sentences = []
+    # sentences = []
-    labels = []
+    # labels = []
-    for story in engine.stories:
+    # for story in engine.stories:
-        sentences.append(story.message)
+    #     sentences.append(story.message)
-        labels.append(engine.intent2id[story.intent])
+    #     labels.append(engine.intent2id[story.intent])
-    try:
+    # try:
-        labels = np.array(labels)
+    #     labels = np.array(labels)
-        embed = embedding.embed_documents(sentences)
+    #     embed = embedding.embed_documents(sentences)
-        enn_model = intent_recogition.classifier
+    #     enn_model = intent_recogition.classifier
-        train_enn(enn_model, embed, labels, bs=64, lr=1e-3, epoch=100)
+    #     train_enn(enn_model, embed, labels, bs=64, lr=1e-3, epoch=100)
-        torch.save(enn_model.state_dict(), necessary_files['intent-classifier'])
+    #     torch.save(enn_model.state_dict(), necessary_files['intent-classifier'])
         
-    except Exception as e:
+    # except Exception as e:
-        response = jsonify({
+    #     response = jsonify({
-            'code': StatusCode.process_error.value,
+    #         'code': StatusCode.process_error.value,
-            'data': str(e),
+    #         'data': str(e),
-            'msg': MsgCode.query_not_empty.value
+    #         'msg': MsgCode.query_not_empty.value
-        })
+    #     })
-        response.status_code = StatusCode.success.value
+    #     response.status_code = StatusCode.success.value
-        return response
+    #     return response
 
     response = jsonify({
         'code': StatusCode.success.value,
@@ -113,6 +115,12 @@ def get_intent_recogition():
         
     result = intent_recogition.get_intent_recogition(query)
     
+    logger_chunk = json.dumps({
+        'query': query,
+        'intent': result
+    }, ensure_ascii=False)
+    logger.debug(logger_chunk)
+    
     response = jsonify({
         'code': StatusCode.success.value,
         'data': result,

test/suite/rag.test.js

@@ -42,6 +42,12 @@ suite('test intent recogition', () => {
         { input: '因为这是养蛊的虚拟机，放了些国产垃圾软件，得用国产流氓之王才能镇得住他们', expect: 'others' },
         { input: '你咋装了个360', expect: 'others' },
         { input: '？？？', expect: 'expression,others' },
+        { input: '有点怪，这里没有和竖线对齐', expect: 'others' },
+        { input: '调试时候下载bit流和ltx，固化需要在xdc约束里面添加spi或bpi相关约束后生成bit流。建议一开始xdc约束当中就添加相关约束，后续生成mcs文件需要先添加flash型号，根据相关型号生成对应的mcs文件后再固化到flash当中。', expect: 'advice,others' },
+        { input: 'at 触发不够人性化，很多用户不知道 Tip 的存在就不会去使用它', expect: 'expression,others' },
+        { input: '非问句会触发吗', expect: 'expression,others' },
+        { input: 'zlib', expect: 'expression,others' },
+        { input: 'https://github.com/Digital-EDA/Digital-IDE/discussions', expect: 'others' },
     ];
 
     for (const s of intent_suites) {