Merge branch 'fix/embedder-model-preload' into feat/helm-setup

Author: root

chat_service/models/__init__.py

@@ -32,6 +32,14 @@ services:
     container_name: docling_translation_service
     env_file:
       - ./docling_translation_service/.env
+  
+  pdf_renderer_service:
+    build:
+      context: .
+      dockerfile: ./pdf_renderer_service/Dockerfile
+    container_name: pdf_renderer_service
+    env_file:
+      - ./pdf_renderer_service/.env
 
   embedder_service:
     build:

docker-compose.gpu.yml

@@ -44,7 +44,15 @@ services:
     container_name: docling_translation_service
     env_file:
       - ./docling_translation_service/.env
-      
+  
+  pdf_renderer_service:
+    build:
+      context: .
+      dockerfile: ./pdf_renderer_service/Dockerfile
+    container_name: pdf_renderer_service
+    env_file:
+      - ./pdf_renderer_service/.env
+
   embedder_service:
     build:
       context: .
@@ -69,6 +77,7 @@ services:
       - pdf_processor_service
       - chat_service
       - docling_translation_service
+      - pdf_renderer_service
       - embedder_service
       - minio
 

docker-compose.yml

@@ -11,6 +11,18 @@ COPY embedder_service/requirements.txt .
 
 RUN pip install --no-cache-dir -r requirements.txt
 
+# Allow model to be configured at build time
+ARG EMBEDDING_MODEL="all-MiniLM-L6-v2"
+ENV EMBEDDING_MODEL=${EMBEDDING_MODEL}
+
+# Set a predictable cache directory for sentence-transformers models
+ENV SENTENCE_TRANSFORMERS_HOME=/opt/models_cache
+
+# Pre-download the sentence transformers model to avoid runtime download and cache permission issues
+RUN echo 'import os\nfrom sentence_transformers import SentenceTransformer\nSentenceTransformer(os.environ["EMBEDDING_MODEL"])' > download_model.py && \
+    python download_model.py && \
+    rm download_model.py
+
 # Copy utils folder from root context into /app/utils
 COPY shared_utils ./shared_utils
 

embedder_service/Dockerfile

@@ -3,4 +3,5 @@ PDF_EXTRACTOR_URL=http://pdf_extraction_service:8000
 CHAT_URL=http://chat_service:8000
 DOCLING_TRANSLATION_URL=http://docling_translation_service:8000
 EMBEDDER_URL=http://embedder_service:8000
+PDF_RENDERER_URL=http://pdf_renderer_service:8000
 MINIO_ENDPOINT=http://minio:9000

embedder_service/models/__init__.py

@@ -29,6 +29,15 @@ server {
         proxy_read_timeout 300;
         send_timeout 300;
     }
+
+    location /pdf_renderer/ {
+        proxy_pass ${PDF_RENDERER_URL}/;
+
+        proxy_connect_timeout 300;
+        proxy_send_timeout 300;
+        proxy_read_timeout 300;
+        send_timeout 300;
+    }
 
     location /embedder/ {
         proxy_pass ${EMBEDDER_URL}/;

nginx/example.env

@@ -0,0 +1,20 @@
+FROM python:3.13-slim
+
+WORKDIR /app
+
+ENV PYTHONPATH=/app/pdf_renderer_service:/app/shared_utils
+
+RUN apt-get update && apt-get install -y build-essential && rm -rf /var/lib/apt/lists/*
+
+COPY pdf_renderer_service/requirements.txt .
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY shared_utils ./shared_utils
+
+COPY pdf_renderer_service ./pdf_renderer_service
+
+EXPOSE 8000
+
+# Start the FastAPI server
+CMD ["sh", "-c", "PYTHONPATH=/app/pdf_renderer_service uvicorn pdf_renderer_service.main:app --host 0.0.0.0 --port 8000"]

nginx/nginx.conf.template

@@ -0,0 +1,6 @@
+# MinIO / S3-compatible storage
+MINIO_ENDPOINT=http://minio:9000
+MINIO_BUCKET=omnifiles
+MINIO_ACCESS_KEY=minioadmin
+MINIO_SECRET_KEY=minioadmin
+REDIS_URL="redis://redis:6379/0?decode_responses=True&protocol=3"

pdf_renderer_service/Dockerfile

@@ -0,0 +1,15 @@
+from fastapi import FastAPI
+from routers import health, render, bypass
+import logging
+
+# Set up logger
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(name)s: %(message)s"
+)
+
+app = FastAPI(root_path="/pdf_renderer")
+
+app.include_router(health.router)
+app.include_router(render.router)
+app.include_router(bypass.router)