Initial project import

core/deploy/docker-gpu/embeddings/.env.example

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+# CPU-only OpenAI-compatible embedding endpoint for 1C code search.
+# The model cache is persistent on docker-gpu; no credentials are required.
+
+EMBEDDING_CONTAINER_NAME=llm-qwen3-embedding
+EMBEDDING_IMAGE=ghcr.io/ggml-org/llama.cpp@sha256:3e8914c1aab600a330ada97c10fb5fb02ff1c15ac39f2ece218db125cf54594e
+EMBEDDING_HOST_PORT=8082
+EMBEDDING_HF_REPO=Qwen/Qwen3-Embedding-0.6B-GGUF:Q8_0
+EMBEDDING_SERVED_MODEL_NAME=qwen3-embedding-0.6b
+EMBEDDING_CTX_SIZE=8192
+EMBEDDING_BATCH_SIZE=1024
+EMBEDDING_UBATCH_SIZE=1024
+EMBEDDING_THREADS=12
+EMBEDDING_PARALLEL=1
+EMBEDDING_CPU_LIMIT=8.0
+EMBEDDING_MEMORY_LIMIT=4G
+
+# Windows path on docker-gpu.cin.su, mounted into the Linux container.
+HOST_LLAMA_CACHE_DIR=Z:/LLM/models/cache/llama.cpp