diff --git a/.github/workflows/docker-build-publish.yml b/.github/workflows/docker-build-publish.yml new file mode 100644 index 0000000..9701cb6 --- /dev/null +++ b/.github/workflows/docker-build-publish.yml @@ -0,0 +1,53 @@ +# This workflow is provided via the organization template repository +# +# https://github.com/nextcloud/.github +# https://docs.github.com/en/actions/learn-github-actions/sharing-workflows-with-your-organization + +name: Docker build and publish + +on: + push: + tags: + - '**' + +env: + APP_ID: translate2 + +jobs: + build_and_publish: + runs-on: ubuntu-latest + + # Only allowed to be run on nextcloud repositories + if: ${{ github.repository_owner == 'nextcloud' }} + + steps: + - name: Checkout app + uses: actions/checkout@v4 + + - name: Get app version + id: appinfo + uses: skjnldsv/xpath-action@7e6a7c379d0e9abc8acaef43df403ab4fc4f770c # master + with: + filename: appinfo/info.xml + expression: "/info/version/text()" + + - name: Set up Docker Buildx + uses: docker/setup-buildx-action@v3 + + - name: Login to GitHub Container Registry + uses: docker/login-action@v3 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push + uses: docker/build-push-action@v6 + with: + context: . + push: true + tags: | + ghcr.io/nextcloud/${{ env.APP_ID }}:latest + ghcr.io/nextcloud/${{ env.APP_ID }}:${{ fromJson(steps.appinfo.outputs.result).version }} + cache-from: type=gha + cache-to: type=gha,mode=max diff --git a/.github/workflows/integration_test.yml b/.github/workflows/integration_test.yml index c645d65..9e4f981 100644 --- a/.github/workflows/integration_test.yml +++ b/.github/workflows/integration_test.yml @@ -41,6 +41,7 @@ jobs: APP_ID: llm2 APP_PORT: 9080 APP_SECRET: 12345 + COMPUTE_DEVICE: cpu NEXTCLOUD_URL: http://localhost:8080 services: diff --git a/Dockerfile b/Dockerfile index 33f6f46..2ce2298 100644 --- a/Dockerfile +++ b/Dockerfile @@ -3,23 +3,29 @@ FROM nvidia/cuda:12.2.2-cudnn8-devel-ubuntu22.04 ENV DEBIAN_FRONTEND=noninteractive RUN apt update -RUN apt install -y pipx build-essential +RUN apt install -y pipx build-essential git vim RUN pipx install poetry ENV DEBIAN_FRONTEND=dialog +ENV PATH="/root/.local/bin:${PATH}" +ENV CMAKE_ARGS="-DGGML_CUDA=on" + +WORKDIR /app + +# Install requirements +COPY pyproject.toml . +COPY poetry.lock . +COPY healthcheck.sh . + +RUN poetry install +RUN ln -s /usr/local/cuda/compat/libcuda.so.1 /usr/lib/x86_64-linux-gnu/ ADD li[b] /app/lib ADD model[s] /app/models ADD default_confi[g] /app/default_config -# Install requirements -COPY pyproject.toml /app -COPY poetry.lock /app -COPY init.sh /app -COPY healthcheck.sh /app - -WORKDIR /app -ENTRYPOINT ["bash", "init.sh"] +WORKDIR /app/lib +ENTRYPOINT ["poetry", "run", "python3", "main.py"] LABEL org.opencontainers.image.source=https://github.com/nextcloud/llm2 -HEALTHCHECK --interval=2s --timeout=2s --retries=300 CMD /app/healthcheck.sh \ No newline at end of file +HEALTHCHECK --interval=2s --timeout=2s --retries=300 CMD /app/healthcheck.sh diff --git a/default_config/config.json b/default_config/config.json index 6eb1efd..0f34cdd 100644 --- a/default_config/config.json +++ b/default_config/config.json @@ -1,58 +1,61 @@ { "llama-2-7b-chat.Q4_K_M": { "prompt": "<|im_start|> system\n{system_prompt}\n<|im_end|>\n<|im_start|> user\n{user_prompt}\n<|im_end|>\n<|im_start|> assistant\n", - "gpt4all_config": { - "max_tokens": 4096, - "n_predict": 2048, + "loader_config": { + "n_ctx": 4096, + "max_tokens": 2048, "stop": ["<|im_end|>"] } }, "gpt4all-falcon-q4_0": { "prompt": "### Instruction: {system_prompt}\n{user_prompt}\n### Response:", - "gpt4all_config": { - "max_tokens": 4096, - "n_predict": 2048, + "loader_config": { + "n_ctx": 4096, + "max_tokens": 2048, "stop": ["### Instruction:"] } }, "leo-hessianai-13b-chat-bilingual.Q4_K_M": { "prompt": "<|im_start|> system\n{system_prompt}\n<|im_end|>\n<|im_start|> user\n{user_prompt}\n<|im_end|>\n<|im_start|> assistant\n", - "gpt4all_config": { - "max_tokens": 4096, - "n_predict": 2048, + "loader_config": { + "n_ctx": 4096, + "max_tokens": 2048, "stop": ["<|im_end|>"] } }, "neuralbeagle14-7b.Q4_K_M": { "prompt": "<|im_start|> system\n{system_prompt}\n<|im_end|>\n<|im_start|> user\n{user_prompt}\n<|im_end|>\n<|im_start|> assistant\n", - "gpt4all_config": { - "max_tokens": 8000, - "n_predict": 4000, + "loader_config": { + "n_ctx": 8000, + "max_tokens": 4000, "stop": ["<|im_end|>"] } }, "Meta-Llama-3-8B-Instruct.Q4_K_M": { "prompt": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>\n{user_prompt}<|eot_id|>\n<|start_header_id|>assistant<|end_header_id|>\n", - "gpt4all_config": { - "max_tokens": 8000, - "n_predict": 4000, - "stop": ["<|eot_id|>"] + "loader_config": { + "n_ctx": 8000, + "max_tokens": 4000, + "stop": ["<|eot_id|>"], + "temperature": 0.3 } }, "Meta-Llama-3.1-8B-Instruct.Q4_K_M": { "prompt": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>\n{user_prompt}<|eot_id|>\n<|start_header_id|>assistant<|end_header_id|>\n", - "gpt4all_config": { - "max_tokens": 128000, - "n_predict": 60000, - "stop": ["<|eot_id|>"] + "loader_config": { + "n_ctx": 128000, + "max_tokens": 60000, + "stop": ["<|eot_id|>"], + "temperature": 0.3 } }, "default": { "prompt": "<|im_start|> system\n{system_prompt}\n<|im_end|>\n<|im_start|> user\n{user_prompt}\n<|im_end|>\n<|im_start|> assistant\n", - "gpt4all_config": { - "max_tokens": 4096, - "n_predict": 2048, - "stop": ["<|im_end|>"] + "loader_config": { + "n_ctx": 4096, + "max_tokens": 2048, + "stop": ["<|im_end|>"], + "temperature": 0.6 } } -} \ No newline at end of file +} diff --git a/init.sh b/init.sh deleted file mode 100755 index d6961e8..0000000 --- a/init.sh +++ /dev/null @@ -1,7 +0,0 @@ -#! /bin/bash -export PATH="/root/.local/bin/:$PATH" -export CMAKE_ARGS="-DLLAMA_CUDA=on" -source $(poetry env info --path)/bin/activate -poetry install -cd lib -poetry run python3 main.py \ No newline at end of file diff --git a/lib/chains.py b/lib/chains.py index e0118ce..3842ca1 100644 --- a/lib/chains.py +++ b/lib/chains.py @@ -2,19 +2,15 @@ """ import os +import json from free_prompt import FreePromptChain from headline import HeadlineChain from topics import TopicsChain from summarize import SummarizeChain -from contextwrite import ContextWriteChain -from reformulate import ReformulateChain -from simplify import SimplifyChain -from formalize import FormalizeChain from langchain_community.llms import LlamaCpp from langchain.chains import LLMChain from langchain.prompts import PromptTemplate -import json from nc_py_api.ex_app import persistent_storage dir_path = os.path.dirname(os.path.realpath(__file__)) @@ -42,18 +38,6 @@ def get_model_config(file_name): return model_config -config = { - "llama": { - "n_batch": 10, - "n_ctx": 4096, - "n_gpu_layers": -1, - "model_kwargs": { - "device": "cuda" - } - } -} - - def generate_llm_chain(file_name): model_config = get_model_config(file_name) @@ -62,35 +46,24 @@ def generate_llm_chain(file_name): if not os.path.exists(path): path = os.path.join(persistent_storage(), file_name) + compute_device = os.getenv("COMPUTE_DEVICE", "cuda") try: llm = LlamaCpp( model_path=path, - model_kwargs={'device': config["llama"]["model_kwargs"]["device"]}, - n_gpu_layers=config["llama"]["n_gpu_layers"], - n_ctx=model_config['gpt4all_config']["n_predict"], - max_tokens=model_config["gpt4all_config"]["max_tokens"], - stop=model_config["gpt4all_config"]["stop"], - echo=True + **{ + "n_gpu_layers": (0, -1)[compute_device != "cpu"], + **model_config["loader_config"], + }, ) - print(f'Using: {config["llama"]["model_kwargs"]["device"]}', flush=True) - except Exception as gpu_error: - try: - llm = LlamaCpp(model_path=path, device="cpu", - n_ctx=model_config['gpt4all_config']["n_predict"], - max_tokens=model_config["gpt4all_config"]["max_tokens"], - stop=model_config["gpt4all_config"]["stop"], - echo=True) - print("Using: CPU", flush=True) - except Exception as cpu_error: - raise RuntimeError(f"Error: Failed to initialize the LLM model on both GPU and CPU.", f"{cpu_error}") from cpu_error + except Exception as e: + print(f"Failed to load model '{path}' with compute device '{compute_device}'") + raise e prompt = PromptTemplate.from_template(model_config['prompt']) return LLMChain(llm=llm, prompt=prompt) - - def generate_chains(): chains = {} for file in os.scandir(models_folder_path): @@ -104,6 +77,7 @@ def generate_chains(): return chains + def generate_chain_for_model(file_name, chains): model_name = file_name.split('.gguf')[0] diff --git a/lib/main.py b/lib/main.py index eb2b563..cf3b015 100644 --- a/lib/main.py +++ b/lib/main.py @@ -1,130 +1,150 @@ """Tha main module of the llm2 app """ -import threading -from contextlib import asynccontextmanager, suppress +import os +from contextlib import asynccontextmanager from time import perf_counter, sleep +from threading import Event, Thread import httpx from fastapi import FastAPI from nc_py_api import AsyncNextcloudApp, NextcloudApp, NextcloudException -from nc_py_api.ex_app import LogLvl, run_app, set_handlers +from nc_py_api.ex_app import LogLvl, persistent_storage, run_app, set_handlers from nc_py_api.ex_app.providers.task_processing import TaskProcessingProvider from chains import generate_chains -chains = generate_chains() +models_to_fetch = { + "https://huggingface.co/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/resolve/4f0c246f125fc7594238ebe7beb1435a8335f519/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf": { "save_path": os.path.join(persistent_storage(), "Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf") }, +} +app_enabled = Event() @asynccontextmanager async def lifespan(_app: FastAPI): set_handlers( APP, - enabled_handler, + enabled_handler, # type: ignore + models_to_fetch=models_to_fetch, ) - t = BackgroundProcessTask() - t.start() + try: + nc = NextcloudApp() + enabled_flag = nc.ocs("GET", "/ocs/v1.php/apps/app_api/ex-app/state") + if enabled_flag: + app_enabled.set() + start_bg_task() + except Exception as e: + print(f"Failed to check the enabled state on startup, background task did not start: {e}", flush=True) yield APP = FastAPI(lifespan=lifespan) -class BackgroundProcessTask(threading.Thread): - def run(self, *args, **kwargs): # pylint: disable=unused-argument - nc = NextcloudApp() +def background_thread_task(chains: dict): + nc = NextcloudApp() - provider_ids = set() - task_type_ids = set() - for chain_name, _ in chains.items(): - provider_ids.add("llm2:" + chain_name) - (model, task) = chain_name.split(":", 1) - task_type_ids.add(task) + provider_ids = set() + task_type_ids = set() + for chain_name, _ in chains.items(): + provider_ids.add("llm2:" + chain_name) + (model, task) = chain_name.split(":", 1) + task_type_ids.add(task) - while True: - try: - enabled_flag = nc.ocs("GET", "/ocs/v1.php/apps/app_api/ex-app/state") - if not enabled_flag: - sleep(5) - continue - - response = nc.providers.task_processing.next_task(list(provider_ids), list(task_type_ids)) - if not response: - sleep(5) - continue - - except (NextcloudException, httpx.RequestError) as e: - print("Network error fetching the next task", e, flush=True) + while True: + if not app_enabled.is_set(): + sleep(5) + break + + try: + response = nc.providers.task_processing.next_task(list(provider_ids), list(task_type_ids)) + if not response: sleep(5) continue - - task = response["task"] - provider = response["provider"] - - try: - chain_name = provider["name"][5:] - print(f"chain: {chain_name}", flush=True) - chain_load = chains.get(chain_name) - if chain_load is None: - NextcloudApp().providers.task_processing.report_result( - task["id"], error_message="Requested model is not available" - ) - continue - - chain = chain_load() - print("Generating reply", flush=True) - time_start = perf_counter() - print(task.get("input").get("input"), flush=True) - result = chain.invoke(task.get("input")).get("text") - del chain - print(f"reply generated: {round(float(perf_counter() - time_start), 2)}s", flush=True) - print(result, flush=True) + except (NextcloudException, httpx.RequestError) as e: + print("Network error fetching the next task", e, flush=True) + sleep(5) + continue + + task = response["task"] + provider = response["provider"] + + try: + chain_name = provider["name"][5:] + print(f"chain: {chain_name}", flush=True) + chain_load = chains.get(chain_name) + if chain_load is None: NextcloudApp().providers.task_processing.report_result( - task["id"], - {"output": str(result)}, + task["id"], error_message="Requested model is not available" ) - except (NextcloudException, httpx.RequestError) as e: - print("Network error:", e, flush=True) - sleep(5) - except Exception as e: # noqa - print("Error:", e, flush=True) - try: - nc = NextcloudApp() - nc.log(LogLvl.ERROR, str(e)) - nc.providers.task_processing.report_result(task["id"], error_message=str(e)) - except (NextcloudException, httpx.RequestError) as net_err: - print("Network error in reporting the error:", net_err, flush=True) + continue + + chain = chain_load() + print("Generating reply", flush=True) + time_start = perf_counter() + print(task.get("input").get("input"), flush=True) + result = chain.invoke(task.get("input")).get("text") + del chain + print(f"reply generated: {round(float(perf_counter() - time_start), 2)}s", flush=True) + print(result, flush=True) + NextcloudApp().providers.task_processing.report_result( + task["id"], + {"output": str(result)}, + ) + except (NextcloudException, httpx.RequestError) as e: + print("Network error:", e, flush=True) + sleep(5) + except Exception as e: # noqa + print("Error:", e, flush=True) + try: + nc = NextcloudApp() + nc.log(LogLvl.ERROR, str(e)) + nc.providers.task_processing.report_result(task["id"], error_message=str(e)) + except (NextcloudException, httpx.RequestError) as net_err: + print("Network error in reporting the error:", net_err, flush=True) + + sleep(5) - sleep(5) + +def start_bg_task(): + app_enabled.set() + t = Thread(target=background_thread_task, args=(generate_chains(),)) + t.start() async def enabled_handler(enabled: bool, nc: AsyncNextcloudApp) -> str: + global app_enabled print(f"enabled={enabled}", flush=True) + + chains = generate_chains() + if enabled is True: - for chain_name, _ in chains.items(): + for chain_name in chains: (model, task) = chain_name.split(":", 1) try: - await nc.providers.task_processing.register({ - "id": "llm2:" + chain_name, - "name": "Local Large language Model: " + model, - "task_type": task, - "expected_runtime": 30, - "optional_input_shape": [], - "optional_output_shape": [], - "input_shape_enum_values": {}, - "input_shape_defaults": {}, - "optional_input_shape_enum_values": {}, - "optional_input_shape_defaults": {}, - "output_shape_enum_values": {}, - "optional_output_shape_enum_values": {}, - }) - print(f"Registering {chain_name}", flush=True) + provider = TaskProcessingProvider( + id="llm2:" + chain_name, + name="Local Large language Model: " + model, + task_type=task, + expected_runtime=30, + ) + await nc.providers.task_processing.register(provider) + print(f"Registered {chain_name}", flush=True) + start_bg_task() except Exception as e: print(f"Failed to register", f"{model} - {task}", f"Error:", f"{e}\n", flush=True) + break else: - for chain_name, chain in chains.items(): - await nc.providers.task_processing.unregister("llm2:" + chain_name) - print(f"Unregistering {chain_name}", flush=True) + for chain_name in chains: + try: + await nc.providers.task_processing.unregister("llm2:" + chain_name) + print(f"Unregistered {chain_name}", flush=True) + except Exception as e: + print(f"Failed to unregister", f"{chain_name}", f"Error:", f"{e}\n", flush=True) + break + + app_enabled.clear() + return "" @@ -134,6 +154,7 @@ async def 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