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Inc."},"license":"Apache-2.0","homepage":"https://picovoice.ai/products/picollm/","keywords":["node","ai","offline","llm"],"repository":{"type":"git","url":"git+https://github.com/Picovoice/picollm.git","directory":"demo/nodejs"},"description":"Picovoice PicoLLM Node.js chat and completion demos","maintainers":[{"name":"kyeo","email":"kyeo@picovoice.ai"},{"name":"kenarsa","email":"alireza@picovoice.ai"},{"name":"ilavery","email":"ian@picovoice.ai"},{"name":"erismikpico","email":"eric@picovoice.ai"},{"name":"matt200-ok","email":"matthew@picovoice.ai"},{"name":"gabe-picovoice","email":"gabriel@picovoice.ai"}],"readme":"# picoLLM Inference Engine Node.js Demos\n\nMade in Vancouver, Canada by [Picovoice](https://picovoice.ai)\n\n## picoLLM Inference Engine\n\npicoLLM Inference Engine is a highly accurate and cross-platform SDK optimized for running compressed large language\nmodels. picoLLM Inference Engine is:\n\n- Accurate; picoLLM Compression improves GPTQ by [significant margins](https://picovoice.ai/blog/picollm-towards-optimal-llm-quantization/)\n- Private; LLM inference runs 100% locally\n- Cross-Platform\n- Runs on CPU and GPU\n- Free for open-weight models\n\n## Compatibility\n\n- Node.js 18+\n- Runs on Linux (x86_64), macOS (arm64, x86_64), Windows (x86_64, arm64), and Raspberry Pi (3, 4, 5).\n\n## Installation\n\nUsing `Yarn`:\n\n```console\nyarn global add @picovoice/picollm-node-demo\n```\n\nor using `npm`:\n\n```console\nnpm install --save @picovoice/picollm-node-demo\n```\n\n## Models\n\npicoLLM Inference Engine supports the following open-weight models. The models are on\n[Picovoice Console](https://console.picovoice.ai/).\n\n- DeepSeek-OCR-2\n  - `deepseek-ocr-2`\n- EmbeddingGemma\n  - `embeddinggemma-300m`\n- Gemma\n  - `gemma-2b`\n  - `gemma-2b-it`\n  - `gemma-7b`\n  - `gemma-7b-it`\n- Gemma3\n  - `gemma-3-270m`\n  - `gemma-3-270m-it`\n- Llama-2\n  - `llama-2-7b`\n  - `llama-2-7b-chat`\n  - `llama-2-13b`\n  - `llama-2-13b-chat`\n  - `llama-2-70b`\n  - `llama-2-70b-chat`\n- Llama-3\n  - `llama-3-8b`\n  - `llama-3-8b-instruct`\n  - `llama-3-70b`\n  - `llama-3-70b-instruct`\n- Llama-3.2\n  - `llama3.2-1b-instruct`\n  - `llama3.2-3b-instruct`\n- Mistral\n  - `mistral-7b-v0.1`\n  - `mistral-7b-instruct-v0.1`\n  - `mistral-7b-instruct-v0.2`\n- Mixtral\n  - `mixtral-8x7b-v0.1`\n  - `mixtral-8x7b-instruct-v0.1`\n- Phi-2\n  - `phi2`\n- Phi-3\n  - `phi3`\n- Phi-3.5\n  - `phi3.5`\n- Qwen3-VL\n  - `qwen3-vl-2b-it`\n\n## AccessKey\n\nAccessKey is your authentication and authorization token for deploying Picovoice SDKs, including picoLLM. Anyone who is\nusing Picovoice needs to have a valid AccessKey. You must keep your AccessKey secret. You would need internet\nconnectivity to validate your AccessKey with Picovoice license servers even though the LLM inference is running 100%\noffline and completely free for open-weight models. Everyone who signs up for\n[Picovoice Console](https://console.picovoice.ai/) receives a unique AccessKey.\n\n## Usage\n\nThere are three demos available: **completion**, **chat**, and **ocr**. The **completion** demo accepts a prompt, an optional\nimage, and a set of optional parameters and generates a single completion. It can run all models (including non-instruction-tuned),\nunless an image is provided, in which case only vision models can be used. The **chat** demo can run instruction-tuned (chat)\nmodels such as `llama-3-8b-instruct`, `phi2`, etc. The chat demo enables a back-and-forth conversation with the LLM, similar\nto ChatGPT. The **optical character recognition** (ocr) demo can be run on ocr models, such as `deepseek-ocr-2`. This demo\nextracts text from a provided image.\n\n### Completion Demo\n\nRun the demo by entering the following in the terminal:\n\n```console\npicollm-completion-demo --access_key ${ACCESS_KEY} --model_path ${MODEL_PATH} --prompt ${PROMPT}\n```\n\nReplace `${ACCESS_KEY}` with yours obtained from Picovoice Console, `${MODEL_PATH}` with the path to a model file\ndownloaded from Picovoice Console, and `${PROMPT}` with a prompt string.\n\nTo get information about all the available options in the demo, run the following:\n\n```console\npicollm-completion-demo --help\n```\n\n### Chat Demo\n\nTo run an instruction-tuned model for chat, run the following in the terminal:\n\n```console\npicollm-chat-demo --access_key ${ACCESS_KEY} --model_path ${MODEL_PATH}\n```\n\nReplace `${ACCESS_KEY}` with yours obtained from Picovoice Console and `${MODEL_PATH}` with the path to a model file\ndownloaded from Picovoice Console.\n\nTo get information about all the available options in the demo, run the following:\n\n```console\npicollm-chat-demo --help\n```\n\n### OCR Demo\n\nTo extract text from an image, run the following in the terminal:\n\n```console\npicollm-ocr-demo --access_key ${ACCESS_KEY} --model_path ${MODEL_PATH} --image_path ${IMAGE_PATH}\n```\n\nReplace `${ACCESS_KEY}` with yours obtained from Picovoice Console, `${MODEL_PATH}` with the path to an ocr model file\ndownloaded from Picovoice Console, and `${IMAGE_PATH}` with the absolute path to an image file you wish to extract text from.\n\nTo get information about all the available options in the demo, run the following:\n\n```console\npicollm-ocr-demo --help\n```\n","readmeFilename":"README.md"}