使用环境变量管理模型名称[ci][0.2.5]

.gitea/workflows/ci.yml

@@ -24,9 +24,9 @@ jobs:
       DJANGO_DEBUG: "False"
       DJANGO_ALLOWED_HOSTS: "127.0.0.1,localhost"
       IMAGE_NAME: achievement_inputing_ci
-      ALIST_URL: https://alist.spdis.top
-      ALIST_USER: ${{ secrets.ALIST_USER }}
-      ALIST_PASSWORD: ${{ secrets.ALIST_PASSWORD }}
+      ARTIFACT_DIR: artifacts
+      SERVER_DEST_DIR: /srv/ci
+      DOWNLOAD_BASE: http://139.224.69.213:8080
       GITEA_SERVER: ${{ github.server_url }}
       GITEA_REPO: ${{ github.repository }}
       RELEASE_TOKEN: ${{ secrets.token }}
@@ -74,35 +74,18 @@ jobs:
           ART="achievement_inputing_ci_${VERSION}.tar"
           docker save -o "$GITHUB_WORKSPACE/$ART" "$IMAGE_NAME:$VERSION"
           echo "$ART" > "$GITHUB_WORKSPACE/.artifact_name"
-      - name: Upload to Alist
+      - name: Publish artifact locally
+        run: |
+          ART=$(cat "$GITHUB_WORKSPACE/.artifact_name")
+          mkdir -p "$GITHUB_WORKSPACE/$ARTIFACT_DIR"
+          mv "$GITHUB_WORKSPACE/$ART" "$GITHUB_WORKSPACE/$ARTIFACT_DIR/"
+          echo "artifact: $GITHUB_WORKSPACE/$ARTIFACT_DIR/$ART"
+      - name: Publish to /srv/ci
         run: |
           set -e
           ART=$(cat "$GITHUB_WORKSPACE/.artifact_name")
-          BASE="${ALIST_URL%/}"
-          curl -sS -o "$GITHUB_WORKSPACE/login.json" -w "%{http_code}" -X POST "$BASE/api/auth/login" -H "Content-Type: application/json" -d "{\"username\":\"$ALIST_USER\",\"password\":\"$ALIST_PASSWORD\"}" > "$GITHUB_WORKSPACE/login.code"
-          if [ "$(cat "$GITHUB_WORKSPACE/login.code")" != "200" ]; then
-            echo login_failed
-            cat "$GITHUB_WORKSPACE/login.json"
-            exit 1
-          fi
-          TOKEN=$(sed -n 's/.*"token":"\([^"]*\)".*/\1/p' "$GITHUB_WORKSPACE/login.json")
-          if [ -z "$TOKEN" ]; then
-            TOKEN=$(sed -n 's/.*"auth":"\([^"]*\)".*/\1/p' "$GITHUB_WORKSPACE/login.json")
-          fi
-          if [ -z "$TOKEN" ]; then
-            echo token_not_found
-            cat "$GITHUB_WORKSPACE/login.json"
-            exit 1
-          fi
-          curl -sS -X POST "$BASE/api/fs/mkdir" -H "Authorization: $TOKEN" -H "Content-Type: application/json" -d "{\"path\":\"/ci\"}" >/dev/null 2>&1 || true
-          UPLOAD_STATUS=$(curl -sS -w "%{http_code}" -o /dev/null -X PUT "$BASE/api/fs/form" -H "Authorization: $TOKEN" -F "path=/ci" -F "file=@$GITHUB_WORKSPACE/$ART;type=application/x-tar")
-          if [ "$UPLOAD_STATUS" -ge 400 ]; then
-            UPLOAD_STATUS=$(curl -sS -w "%{http_code}" -o /dev/null -X PUT "$BASE/api/fs/form" -H "Authorization: Bearer $TOKEN" -F "path=/ci" -F "file=@$GITHUB_WORKSPACE/$ART;type=application/x-tar")
-          fi
-          if [ "$UPLOAD_STATUS" -ge 400 ]; then
-            echo upload_failed
-            exit 1
-          fi
+          cat "$GITHUB_WORKSPACE/$ARTIFACT_DIR/$ART" | docker run --rm -i -v "$SERVER_DEST_DIR:/srvci" "$IMAGE_NAME:$VERSION" sh -c "cat > /srvci/$ART && ls -l /srvci"
+          echo "published: $SERVER_DEST_DIR/$ART"
       - name: Create release with download link
         if: env.RELEASE_TOKEN != ''
         run: |
@@ -110,6 +93,9 @@ jobs:
           BRANCH=${GITHUB_REF#refs/heads/}
           TAG="$VERSION"
           NAME="$VERSION"
-          DL="${ALIST_URL%/}/ci/$ART"
+          BASE="${DOWNLOAD_BASE%/}"
+          BASE="${BASE%/ci}"
+          DL="$BASE/$ART"
+          echo "download: $DL"
           JSON=$(printf '{"tag_name":"%s","target_commitish":"%s","name":"%s","body":"%s"}' "$TAG" "$BRANCH" "$NAME" "$DL")
           curl -sS -X POST "$GITEA_SERVER/api/v1/repos/$GITEA_REPO/releases" -H "Content-Type: application/json" -H "Authorization: token $RELEASE_TOKEN" -d "$JSON"

Achievement_Inputing/settings.py

@@ -166,3 +166,4 @@ ELASTICSEARCH_INDEX_NAMES = {
 # AI Studio/OpenAI client settings
 AISTUDIO_API_KEY = os.environ.get('AISTUDIO_API_KEY', '')
 OPENAI_BASE_URL = os.environ.get('OPENAI_BASE_URL', 'https://aistudio.baidu.com/llm/lmapi/v3')
+OPENAI_MODEL_NAME = os.environ.get('OPENAI_MODEL_NAME', 'ernie-4.5-turbo-vl-32k')

elastic/templates/elastic/upload.html

@@ -54,6 +54,10 @@
   .status-message.success { background-color: #d4edda; color: #155724; border: 1px solid #c3e6cb; }
   .status-message.error { background-color: #f8d7da;color: #721c24; border: 1px solid #f5c6cb; }
   .action-buttons { margin-top: 16px; display: flex; gap: 8px; flex-wrap: wrap; }
+  .progress {position: relative; height: 12px; background: #e2e8f0; border-radius: 8px; overflow: hidden;}
+  .progress-bar {height: 100%; width: 0; background: linear-gradient(90deg, #4f46e5 0%, #60a5fa 100%); transition: width .2s ease;}
+  .progress-wrap {display:none; margin-top: 8px;}
+  .progress-text {margin-top: 6px; font-size: 12px; color: #334155;}
   </style>
 </head>
 <body>
@@ -90,6 +94,10 @@
         <button type="submit" class="btn btn-primary">上传并识别</button>
       </form>
       <div class="status-message" id="uploadMsg"></div>
+      <div class="progress-wrap" id="progressWrap">
+        <div class="progress"><div class="progress-bar" id="progressBar"></div></div>
+        <div class="progress-text" id="progressText"></div>
+      </div>
     </div>
 
     <div class="preview-container">
@@ -136,9 +144,51 @@ const kvForm = document.getElementById('kvForm');
 const addFieldBtn = document.getElementById('addFieldBtn');
 const syncFromTextBtn = document.getElementById('syncFromTextBtn');
 const dropArea = document.getElementById('dropArea');
+const progressWrap = document.getElementById('progressWrap');
+const progressBar = document.getElementById('progressBar');
+const progressText = document.getElementById('progressText');
 
 let currentImageRel = '';
 
+function setProgress(p, text){
+  const v = Math.max(0, Math.min(100, Math.round(p||0)));
+  progressBar.style.width = v + '%';
+  progressText.textContent = (text||'') + (text? ' ' : '') + v + '%';
+}
+function showProgress(){
+  progressWrap.style.display = 'block';
+}
+function hideProgress(){
+  progressWrap.style.display = 'none';
+  setProgress(0, '');
+}
+
+async function convertToJpeg(file){
+  const url = URL.createObjectURL(file);
+  let img;
+  try{
+    const blob = await fetch(url).then(r=>r.blob());
+    img = await createImageBitmap(blob);
+  }catch(e){
+    img = await new Promise((resolve,reject)=>{const i=new Image();i.onload=()=>resolve(i);i.onerror=reject;i.src=url;});
+  }
+  URL.revokeObjectURL(url);
+  const maxDim = 2000;
+  const w = img.width;
+  const h = img.height;
+  const scale = Math.min(1, maxDim/Math.max(w,h));
+  const nw = Math.round(w*scale);
+  const nh = Math.round(h*scale);
+  const canvas = document.createElement('canvas');
+  canvas.width = nw;
+  canvas.height = nh;
+  const ctx = canvas.getContext('2d');
+  ctx.drawImage(img, 0, 0, nw, nh);
+  const blob = await new Promise(resolve=>canvas.toBlob(resolve,'image/jpeg',0.82));
+  const name = (file.name||'image').replace(/\.[^/.]+$/, '') + '.jpg';
+  return new File([blob], name, {type:'image/jpeg'});
+}
+
 // 拖拽上传功能
 ['dragenter', 'dragover', 'dragleave', 'drop'].forEach(eventName => {
   dropArea.addEventListener(eventName, preventDefaults, false);
@@ -289,20 +339,39 @@ uploadForm.addEventListener('submit', async (e) => {
     return;
   }
 
+  showProgress();
+  setProgress(5, '转换为JPG');
+  let jpegFile = file;
+  try {
+    jpegFile = await convertToJpeg(file);
+    setProgress(50, '转换为JPG');
+    preview.src = URL.createObjectURL(jpegFile);
+  } catch (_) {
+    jpegFile = file;
+    setProgress(50, '转换为JPG');
+  }
   const formData = new FormData();
-  formData.append('file', file);
+  formData.append('file', jpegFile);
 
   try {
+    let prog = 50;
+    setProgress(prog, '识别中');
+    const timer = setInterval(() => {
+      prog = Math.min(95, prog + 1);
+      setProgress(prog, '识别中');
+    }, 120);
     const resp = await fetch('/elastic/upload/', {
       method: 'POST',
       credentials: 'same-origin',
       headers: { 'X-CSRFToken': getCookie('csrftoken') || '' },
       body: formData,
     });
+    clearInterval(timer);
     const data = await resp.json();
     if (!resp.ok || data.status !== 'success') {
       throw new Error(data.message || '上传识别失败');
     }
+    setProgress(100, '识别完成');
     uploadMsg.textContent = data.message || '识别成功';
     uploadMsg.className = 'status-message success';
     uploadMsg.style.display = 'block';
@@ -310,10 +379,12 @@ uploadForm.addEventListener('submit', async (e) => {
     renderFormFromObject(data.data || {});
     currentImageRel = data.image;
     confirmBtn.disabled = false;
+    setTimeout(hideProgress, 800);
   } catch (e) {
     uploadMsg.textContent = e.message || '发生错误';
     uploadMsg.className = 'status-message error';
     uploadMsg.style.display = 'block';
+    progressText.textContent = '识别失败';
   }
 });
 

elastic/views.py

@@ -357,7 +357,7 @@ def ocr_and_extract_info(image_path: str):
                 ],
             },
         ],
-        model="ernie-4.5-turbo-vl-32k",
+        model=getattr(settings, "OPENAI_MODEL_NAME", "ernie-4.5-turbo-vl-32k"),
     )
 
     response_text = chat_completion.choices[0].message.content