Dockerfile

# ╔══════════════════════════════════════════════════════════════════════════╗
# ║  MYTHICAL UNIVERSAL SYSTEM — Dockerfile [v7.1]                          ║
# ║  [FIX-A] RAM thresholds → 0 (auto-detect via cgroup, not hardcoded)     ║
# ║  [FIX-D] THINKING_TIMEOUT=300s added                                    ║
# ║  + all v7.0 fixes (PGO+ThinLTO, Ubuntu 22.04, whisper.cpp server)      ║
# ╚══════════════════════════════════════════════════════════════════════════╝

# ─────────────────────────────────────────────────────────────────────────────
# STAGE 1: PGO INSTRUMENTATION BUILD
# ─────────────────────────────────────────────────────────────────────────────
FROM ubuntu:22.04 AS pgo-instrument

ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && apt-get install -y --no-install-recommends \
    clang-15 lld-15 llvm-15 cmake make git \
    python3 python3-pip \
    libcurl4-openssl-dev ca-certificates curl \
    && ln -sf /usr/bin/clang-15   /usr/local/bin/clang \
    && ln -sf /usr/bin/clang++-15 /usr/local/bin/clang++ \
    && rm -rf /var/lib/apt/lists/*

# Download small profiling model (200MB, same transformer hot paths as Qwen3)
RUN pip3 install --no-cache-dir --break-system-packages huggingface_hub hf_transfer 2>/dev/null || \
    pip3 install --no-cache-dir huggingface_hub hf_transfer && \
    HF_HUB_ENABLE_HF_TRANSFER=1 python3 -c "\
from huggingface_hub import hf_hub_download; \
hf_hub_download( \
    repo_id='bartowski/SmolLM2-360M-Instruct-GGUF', \
    filename='SmolLM2-360M-Instruct-Q4_K_M.gguf', \
    local_dir='/pgo_model' \
)"

WORKDIR /llama
RUN git clone --depth=1 https://github.com/ggml-org/llama.cpp .

# Instrumented build
RUN mkdir -p /pgo-data && \
    cmake -B build-instr \
        -DCMAKE_BUILD_TYPE=Release \
        -DCMAKE_C_COMPILER=clang \
        -DCMAKE_CXX_COMPILER=clang++ \
        -DGGML_AVX2=ON -DGGML_FMA=ON -DGGML_F16C=ON \
        -DGGML_NATIVE=OFF \
        -DBUILD_SHARED_LIBS=OFF \
        -DLLAMA_CURL=ON \
        -DCMAKE_C_FLAGS="-fprofile-generate=/pgo-data -O2 -march=x86-64-v3" \
        -DCMAKE_CXX_FLAGS="-fprofile-generate=/pgo-data -O2 -march=x86-64-v3" \
        -DCMAKE_EXE_LINKER_FLAGS="-fprofile-generate=/pgo-data" \
    && cmake --build build-instr --target llama-server -j$(nproc)

# Profile run — covers all real production use cases
RUN /llama/build-instr/bin/llama-server \
        --model /pgo_model/SmolLM2-360M-Instruct-Q4_K_M.gguf \
        --host 127.0.0.1 --port 18080 \
        --ctx-size 2048 --threads 2 --parallel 1 \
        --log-disable > /tmp/pgo.log 2>&1 & \
    SERVER_PID=$! && \
    for i in $(seq 1 30); do \
        sleep 3; curl -sf http://127.0.0.1:18080/health >/dev/null 2>&1 && break; \
    done && \
    # Profile 1: Arabic text completion
    curl -sf http://127.0.0.1:18080/v1/chat/completions \
        -H "Content-Type: application/json" \
        -d '{"model":"p","messages":[{"role":"system","content":"You are a universal AI assistant."},{"role":"user","content":"اشرح مفهوم التعلم الآلي بطريقة بسيطة مع أمثلة عملية."}],"max_tokens":250}' >/dev/null 2>&1 || true && \
    # Profile 2: English reasoning
    curl -sf http://127.0.0.1:18080/v1/chat/completions \
        -H "Content-Type: application/json" \
        -d '{"model":"p","messages":[{"role":"user","content":"Explain the difference between supervised and unsupervised learning."}],"max_tokens":300}' >/dev/null 2>&1 || true && \
    # Profile 3: Tool calling (MCP)
    curl -sf http://127.0.0.1:18080/v1/chat/completions \
        -H "Content-Type: application/json" \
        -d '{"model":"p","messages":[{"role":"user","content":"Search for latest AI research papers."}],"max_tokens":100,"tools":[{"type":"function","function":{"name":"web_search","description":"Search the web","parameters":{"type":"object","properties":{"query":{"type":"string"}},"required":["query"]}}}],"tool_choice":"auto"}' >/dev/null 2>&1 || true && \
    # Profile 4: Streaming
    curl -sf http://127.0.0.1:18080/v1/chat/completions \
        -H "Content-Type: application/json" \
        -d '{"model":"p","messages":[{"role":"user","content":"Write a Python function to download files asynchronously."}],"max_tokens":200,"stream":true}' >/dev/null 2>&1 || true && \
    # Profile 5: Code generation
    curl -sf http://127.0.0.1:18080/v1/chat/completions \
        -H "Content-Type: application/json" \
        -d '{"model":"p","messages":[{"role":"user","content":"Write a complete React component for a chat interface."}],"max_tokens":400}' >/dev/null 2>&1 || true && \
    # Repeated short requests (cache path)
    for i in $(seq 1 8); do \
        curl -sf http://127.0.0.1:18080/v1/chat/completions \
            -H "Content-Type: application/json" \
            -d '{"model":"p","messages":[{"role":"user","content":"Hello"}],"max_tokens":10}' >/dev/null 2>&1 || true; \
    done && \
    kill "${SERVER_PID}" && wait "${SERVER_PID}" 2>/dev/null || true && \
    llvm-profdata-15 merge --output=/pgo-data/merged.profdata /pgo-data/ && \
    echo "[PGO] Profile data ready: $(ls -lh /pgo-data/merged.profdata)"


# ─────────────────────────────────────────────────────────────────────────────
# STAGE 2: PGO + ThinLTO OPTIMISED llama-server
# ─────────────────────────────────────────────────────────────────────────────
FROM ubuntu:22.04 AS llama-builder

ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && apt-get install -y --no-install-recommends \
    clang-15 lld-15 llvm-15 cmake make libcurl4-openssl-dev ca-certificates \
    && ln -sf /usr/bin/clang-15   /usr/local/bin/clang \
    && ln -sf /usr/bin/clang++-15 /usr/local/bin/clang++ \
    && rm -rf /var/lib/apt/lists/*

COPY --from=pgo-instrument /llama    /llama
COPY --from=pgo-instrument /pgo-data /pgo-data

WORKDIR /llama
RUN cmake -B build-final \
        -DCMAKE_BUILD_TYPE=Release \
        -DCMAKE_C_COMPILER=clang \
        -DCMAKE_CXX_COMPILER=clang++ \
        -DGGML_AVX2=ON -DGGML_FMA=ON -DGGML_F16C=ON \
        -DGGML_NATIVE=OFF \
        -DBUILD_SHARED_LIBS=OFF \
        -DLLAMA_CURL=ON \
        -DCMAKE_C_FLAGS="-fprofile-use=/pgo-data/merged.profdata \
                         -fprofile-correction -flto=thin \
                         -O3 -march=x86-64-v3 -DNDEBUG" \
        -DCMAKE_CXX_FLAGS="-fprofile-use=/pgo-data/merged.profdata \
                           -fprofile-correction -flto=thin \
                           -O3 -march=x86-64-v3 -DNDEBUG" \
        -DCMAKE_EXE_LINKER_FLAGS="-flto=thin -fuse-ld=lld-15" \
    && cmake --build build-final --target llama-server -j$(nproc) \
    && strip --strip-unneeded build-final/bin/llama-server \
    && echo "[llama-builder] Binary: $(du -sh build-final/bin/llama-server)"


# ─────────────────────────────────────────────────────────────────────────────
# STAGE 3: WHISPER.CPP SERVER
# Separate stage to avoid ggml version conflicts with llama.cpp
# ─────────────────────────────────────────────────────────────────────────────
FROM ubuntu:22.04 AS whisper-builder

ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && apt-get install -y --no-install-recommends \
    clang-15 lld-15 cmake make git ca-certificates \
    && ln -sf /usr/bin/clang-15   /usr/local/bin/clang \
    && ln -sf /usr/bin/clang++-15 /usr/local/bin/clang++ \
    && rm -rf /var/lib/apt/lists/*

WORKDIR /whisper
RUN git clone --depth=1 https://github.com/ggml-org/whisper.cpp .

RUN cmake -B build \
        -DCMAKE_BUILD_TYPE=Release \
        -DCMAKE_C_COMPILER=clang \
        -DCMAKE_CXX_COMPILER=clang++ \
        -DGGML_AVX2=ON -DGGML_FMA=ON -DGGML_F16C=ON \
        -DGGML_NATIVE=OFF \
        -DWHISPER_BUILD_SERVER=ON \
        -DWHISPER_NO_OPENVINO=ON \
        -DCMAKE_C_FLAGS="-O3 -march=x86-64-v3 -DNDEBUG" \
        -DCMAKE_CXX_FLAGS="-O3 -march=x86-64-v3 -DNDEBUG" \
    && cmake --build build --target whisper-server -j$(nproc) \
    && strip --strip-unneeded build/bin/whisper-server \
    && echo "[whisper-builder] Binary: $(du -sh build/bin/whisper-server)"


# ─────────────────────────────────────────────────────────────────────────────
# STAGE 4: RUNTIME — minimal, production-ready
# ─────────────────────────────────────────────────────────────────────────────
FROM python:3.11-slim AS runtime

ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && apt-get install -y --no-install-recommends \
    ffmpeg \
    libcurl4 \
    libjemalloc2 \
    curl tini ca-certificates \
    && rm -rf /var/lib/apt/lists/*

# Copy optimised binaries
COPY --from=llama-builder  /llama/build-final/bin/llama-server  /usr/local/bin/llama-server
COPY --from=whisper-builder /whisper/build/bin/whisper-server   /usr/local/bin/whisper-server
RUN chmod +x /usr/local/bin/llama-server /usr/local/bin/whisper-server

# Python dependencies
RUN pip install --no-cache-dir \
    "fastapi==0.115.12" \
    "uvicorn[standard]==0.34.3" \
    "uvloop==0.21.0" \
    "httpx==0.28.1" \
    "orjson==3.10.18" \
    "psutil==7.0.0" \
    "pillow==11.2.1" \
    "pypdf==5.4.0" \
    "beautifulsoup4==4.13.4" \
    "youtube-transcript-api==0.6.3" \
    "aiohttp==3.11.18" \
    "huggingface_hub==0.31.4" \
    "hf_transfer==0.1.9" \
    "python-multipart==0.0.20"

WORKDIR /app
COPY app.py          /app/app.py
COPY model_manager.py /app/model_manager.py
COPY startup.sh      /app/startup.sh
RUN chmod +x /app/startup.sh

RUN mkdir -p /data/models /data/slot_cache /data/whisper /tmp/media /var/log /var/run
VOLUME ["/data"]

# ── Environment defaults ──────────────────────────────────────────────────────
ENV \
    # Model selection managed by model_manager.py
    MODEL_DIR="/data/models" \
    SLOT_CACHE_DIR="/data/slot_cache" \
    WHISPER_DIR="/data/whisper" \
    WHISPER_MODEL_SIZE="base" \
    # Server
    LLAMA_HOST="127.0.0.1" LLAMA_PORT="8080" \
    WHISPER_HOST="127.0.0.1" WHISPER_PORT="8081" \
    API_HOST="0.0.0.0" API_PORT="7860" \
    # Inference
    CTX_SIZE="16384" \
    MAX_NEW_TOKENS="2048" \
    MAX_CTX_TOKENS="14000" \
    # Safety — 0 = auto-detect container RAM via cgroup, then 82/90/95%
    RAM_WARN_GB="0" RAM_REJECT_GB="0" RAM_FLUSH_GB="0" \
    RAM_LIMIT_GB="14.0" \
    REQUEST_TIMEOUT="90.0" THINKING_TIMEOUT="600.0" GENERATE_TIMEOUT="600.0" \
    QUEUE_TIMEOUT="30.0" ENRICH_TIMEOUT="12.0" DOWNLOAD_TIMEOUT="30.0" \
    # API
    API_KEY="change-this-to-a-strong-secret" \
    RATE_LIMIT_RPM="60" CACHE_TTL="60" \
    # Media
    IMAGE_MAX_PX="1120" VIDEO_MAX_FRAMES="8" MAX_FILE_MB="50" \
    # HF
    HF_HUB_ENABLE_HF_TRANSFER="1" \
    PYTHONUNBUFFERED="1" PYTHONDONTWRITEBYTECODE="1"

EXPOSE 7860
ENTRYPOINT ["/usr/bin/tini", "--"]
CMD ["/app/startup.sh"]