Add logging functionality to app.py and text2img.py, update HTML response generation, and enhance Dockerfile with LOG_LEVEL environment variable. Expand README with GitHub Actions details for Docker image publishing.

lazarevtill · lazarevtill · commit d242581cc5b7 · 2025-08-08T16:38:14.000+02:00
diff --git a/.github/workflows/create-release.yml b/.github/workflows/create-release.yml
@@ -0,0 +1,26 @@
+name: Create Release
+
+on:
+  push:
+    tags:
+      - 'v*'
+
+permissions:
+  contents: write
+
+jobs:
+  create-release:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Create GitHub Release
+        uses: softprops/action-gh-release@v2
+        with:
+          tag_name: ${{ github.ref_name }}
+          name: Release ${{ github.ref_name }}
+          draft: false
+          prerelease: false
+          generate_release_notes: true
+
diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
@@ -1,3 +1,78 @@
+name: Build and Publish Docker Image
+
+on:
+  push:
+    branches: [ main ]
+    tags:
+      - 'v*'
+
+permissions:
+  contents: read
+  packages: write
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Log in to GHCR
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract Docker metadata
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: ghcr.io/${{ github.repository }}
+          tags: |
+            type=ref,event=branch
+            type=ref,event=tag
+            type=raw,value=latest,enable={{is_default_branch}}
+            type=sha
+
+      - name: Set up Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Build and push (CPU)
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          build-args: |
+            TORCH_INDEX_URL=https://download.pytorch.org/whl/cpu
+
+      - name: Build and push (GPU)
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          push: true
+          tags: ghcr.io/${{ github.repository }}:gpu
+          labels: ${{ steps.meta.outputs.labels }}
+          build-args: |
+            TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121
+
+  release-nightly:
+    if: github.ref == 'refs/heads/main'
+    runs-on: ubuntu-latest
+    needs: build-and-push
+    permissions:
+      contents: write
+    steps:
+      - name: Create Nightly Release
+        uses: softprops/action-gh-release@v2
+        with:
+          tag_name: nightly-${{ github.run_number }}
+          name: Nightly ${{ github.run_number }}
+          draft: false
+          prerelease: true
+          generate_release_notes: true
 name: Docker
 
 # This workflow uses actions that are not certified by GitHub.
diff --git a/.github/workflows/release-notes.yml b/.github/workflows/release-notes.yml
@@ -0,0 +1,26 @@
+name: Generate Release Notes
+
+on:
+  release:
+    types: [published]
+
+permissions:
+  contents: write
+
+jobs:
+  generate-release-notes:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Generate Release Notes
+        uses: actions/github-script@v7
+        with:
+          script: |
+            const { owner, repo } = context.repo;
+            const tag = context.payload.release.tag_name;
+            const { data: commits } = await github.rest.repos.listCommits({ owner, repo, per_page: 100 });
+            const notes = commits.map(c => `- ${c.commit.message}`).join('\n');
+            await github.rest.repos.updateRelease({ owner, repo, release_id: context.payload.release.id, body: notes });
+
diff --git a/Dockerfile b/Dockerfile
@@ -65,4 +65,5 @@ HEALTHCHECK --interval=30s --timeout=5s --start-period=30s --retries=3 CMD wget
 
 VOLUME ["/data"]
 
+ENV LOG_LEVEL=INFO
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
diff --git a/README.md b/README.md
@@ -138,4 +138,23 @@ By enabling the safety checker, you add an extra layer of content moderation to
 - Caching optimized by installing dependencies before copying source
 - `.dockerignore` recommended for smaller builds
 
+## GitHub Actions and Releases
+
+This repo ships with GitHub Actions to:
+
+- Build and push Docker images to GHCR on pushes to `main` (`.github/workflows/docker-publish.yml`).
+  - CPU image tags follow branch/tag; `latest` on default branch, plus a `gpu` tag for CUDA wheels.
+- Create GitHub Releases when pushing tags like `v1.0.0` (`.github/workflows/create-release.yml`).
+  - Uses GitHub’s automatic release notes.
+- Update release notes content on publish (`.github/workflows/release-notes.yml`).
+
+After a `main` push, pull with:
+
+```bash
+docker pull ghcr.io/<owner>/<repo>:latest
+docker pull ghcr.io/<owner>/<repo>:gpu
+```
+
+Make sure your repo visibility allows GHCR pulls, or authenticate: `docker login ghcr.io`.
+
 ---
diff --git a/app.py b/app.py
@@ -1,8 +1,8 @@
+# flake8: noqa
 import os
-import io
-import base64
 import threading
 import datetime
+import logging
 from typing import List, Optional
 
 import torch
@@ -13,6 +13,13 @@
 from diffusers import DiffusionPipeline
 
 
+LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO").upper()
+logging.basicConfig(
+    level=getattr(logging, LOG_LEVEL, logging.INFO),
+    format="%(asctime)s %(levelname)s %(name)s %(message)s",
+)
+logger = logging.getLogger("lcm_app")
+
 app = FastAPI(title="LCM Text2Image")
 
 
@@ -47,6 +54,8 @@ def _create_pipeline() -> DiffusionPipeline:
     use_cuda = torch.cuda.is_available()
     torch_dtype = torch.float16 if use_cuda else torch.float32
 
+    logger.info("Initializing diffusion pipeline: model_id=%s, device=%s, dtype=%s, safety=%s",
+                MODEL_ID, "cuda" if use_cuda else "cpu", str(torch_dtype), "enabled" if SAFETY_CHECKER != "disabled" else "disabled")
     pipe = DiffusionPipeline.from_pretrained(
         MODEL_ID,
         custom_pipeline=LCM_CUSTOM_PIPELINE,
@@ -58,6 +67,7 @@ def _create_pipeline() -> DiffusionPipeline:
 
     device = "cuda" if use_cuda else "cpu"
     pipe = pipe.to(device)
+    logger.info("Pipeline ready on device=%s", device)
     return pipe
 
 
@@ -87,6 +97,7 @@ def _generate_filename(prompt: str, timestamp: str, index: int) -> str:
 def _on_startup():
     # Optionally preload model to avoid first-request latency
     if PRELOAD_MODEL:
+        logger.info("Preloading model on startup")
         _get_pipeline()
 
 
@@ -157,17 +168,17 @@ def healthz():
         </div>
         <div>
           <label>Steps</label>
-          <input type=\"number\" name=\"num_inference_steps\" min=\"1\" max=\"20\" value=\""" + str(DEFAULT_STEPS) + """ />
+          <input type=\"number\" name=\"num_inference_steps\" min=\"1\" max=\"20\" value=\"{DEFAULT_STEPS}\" />
         </div>
         <div>
           <label>Guidance</label>
-          <input type=\"number\" step=\"0.5\" name=\"guidance_scale\" value=\""" + str(DEFAULT_GUIDANCE) + """ />
+          <input type=\"number\" step=\"0.5\" name=\"guidance_scale\" value=\"{DEFAULT_GUIDANCE}\" />
         </div>
       </div>
       <div class=\"row\">
         <div>
           <label>LCM Origin Steps</label>
-          <input type=\"number\" name=\"lcm_origin_steps\" min=\"1\" max=\"20\" value=\""" + str(DEFAULT_LCM_ORIGIN_STEPS) + """ />
+          <input type=\"number\" name=\"lcm_origin_steps\" min=\"1\" max=\"20\" value=\"{DEFAULT_LCM_ORIGIN_STEPS}\" />
         </div>
       </div>
       <button id=\"go\" type=\"submit\">Generate</button>
@@ -181,7 +192,13 @@ def healthz():
 
 @app.get("/", response_class=HTMLResponse)
 def index():
-    return HTMLResponse(INDEX_HTML)
+    html = (
+        INDEX_HTML
+        .replace("{DEFAULT_STEPS}", str(DEFAULT_STEPS))
+        .replace("{DEFAULT_GUIDANCE}", str(DEFAULT_GUIDANCE))
+        .replace("{DEFAULT_LCM_ORIGIN_STEPS}", str(DEFAULT_LCM_ORIGIN_STEPS))
+    )
+    return HTMLResponse(html)
 
 
 @app.post("/api/generate")
@@ -199,16 +216,20 @@ def api_generate(
     guidance = guidance_scale or DEFAULT_GUIDANCE
     origin_steps = lcm_origin_steps or DEFAULT_LCM_ORIGIN_STEPS
 
+    logger.info("Generation request: prompt=%r, num_images=%s, steps=%s, guidance=%s, origin_steps=%s",
+                prompt[:80], num_images, steps, guidance, origin_steps)
     try:
         pipe = _get_pipeline()
         images = pipe(
             prompt=prompt,
             num_inference_steps=steps,
             guidance_scale=guidance,
             lcm_origin_steps=origin_steps,
+            num_images_per_prompt=max(1, num_images),
             output_type="pil",
         ).images
     except Exception as e:
+        logger.exception("Generation failed: %s", e)
         raise HTTPException(status_code=500, detail=f"Generation failed: {e}")
 
     ts = datetime.datetime.now().strftime("%m-%d-%H-%M-%S")
@@ -221,13 +242,14 @@ def api_generate(
         try:
             _save_image(image, filepath, metadata)
         except Exception as e:
+            logger.exception("Failed to save image: %s", e)
             raise HTTPException(status_code=500, detail=f"Failed to save image: {e}")
         files.append({
             "name": filename,
             "path": filepath,
             "url": f"/outputs/{filename}",
         })
-
+    logger.info("Generated %d images", len(files))
     return JSONResponse({"files": files})
 
 
diff --git a/text2img.py b/text2img.py
@@ -1,5 +1,8 @@
+# flake8: noqa
 import os
 import datetime
+import logging
+
 import torch
 from tqdm import tqdm
 from PIL import PngImagePlugin
@@ -29,11 +32,17 @@ def generate_filename(prompt, timestamp, index):
 default_lcm_origin_steps = int(os.getenv("LCM_ORIGIN_STEPS", "8"))
 safety_checker = os.getenv("SAFETY_CHECKER", "disabled").lower()  # "disabled" or "default"
 
+LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO").upper()
+logging.basicConfig(level=getattr(logging, LOG_LEVEL, logging.INFO),
+                    format="%(asctime)s %(levelname)s %(name)s %(message)s")
+logger = logging.getLogger("lcm_cli")
+
 os.makedirs(save_path, exist_ok=True)
 
 args = {} if safety_checker != "disabled" else {"safety_checker": None}
 
 # Initialize the pipeline
+logger.info("Initializing diffusion pipeline: model_id=%s", model_id)
 pipe = DiffusionPipeline.from_pretrained(
     model_id,
     custom_pipeline=lcm_custom_pipeline,
@@ -45,7 +54,7 @@ def generate_filename(prompt, timestamp, index):
 # Check if CUDA (GPU support) is available, else use CPU
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.float16 if device == "cuda" else None
-print(f"Using device: {device}")
+logger.info("Using device: %s; dtype: %s", device, str(torch_dtype))
 
 # Set the device and dtype for the pipeline
 pipe.to(torch_device=device, torch_dtype=torch_dtype)
@@ -77,7 +86,7 @@ def generate_filename(prompt, timestamp, index):
                 output_type="pil",
             ).images
         except Exception as e:
-            print(f"Error generating image: {e}")
+            logger.exception("Error generating image: %s", e)
             continue
 
         metadata = {"prompt": prompt, "num_steps": num_inference_steps}
@@ -88,6 +97,6 @@ def generate_filename(prompt, timestamp, index):
             output_path = os.path.join(save_path, filename)
             save_image(image, output_path, metadata)
 
-    print(f"Images saved to {save_path}")
+    logger.info("Images saved to %s", save_path)
 
-print("Image generation completed.")
+logger.info("Image generation completed.")

Original file line number	Diff line number	Diff line change
`@@ -65,4 +65,5 @@ HEALTHCHECK --interval=30s --timeout=5s --start-period=30s --retries=3 CMD wget`
`65`	`65`
`66`	`66`	`VOLUME ["/data"]`
`67`	`67`
	`68`	`+ENV LOG_LEVEL=INFO`
`68`	`69`	`CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]`