├── .gitignore
├── Documents
└── README.md
├── Indexes
├── README.md
└── _L4T_README
│ ├── default__vector_store.json
│ ├── docstore.json
│ ├── graph_store.json
│ ├── image__vector_store.json
│ └── index_store.json
├── JC-Banner_1280x480.png
├── LICENSE
├── README.md
├── index_name_checked.png
├── launch_dev.sh
├── launch_jetson_copilot.sh
├── local_documents_selected.png
├── logs
└── README.md
├── ollama_models
└── README.md
├── setup_environment.sh
└── streamlit_app
├── .streamlit
└── config.toml
├── app.py
├── images
├── jetson-soc.png
└── user-purple.png
├── pages
├── build_index.py
└── download_model.py
└── utils
├── __init__.py
├── constants.py
└── func.py
/.gitignore:
--------------------------------------------------------------------------------
1 | Documents/*
2 | !Documents/README.md
3 | Indexes/*
4 | !Indexes/_L4T_README
5 | !Indexes/README.md
6 | logs/*
7 | !logs/README.md
8 | ollama_models/*
9 | !ollama_models/README.md
10 |
11 | # Byte-compiled / optimized / DLL files
12 | __pycache__/
13 | *.py[cod]
14 | *$py.class
--------------------------------------------------------------------------------
/Documents/README.md:
--------------------------------------------------------------------------------
1 | Documents directory for storing directories for each index building.
--------------------------------------------------------------------------------
/Indexes/README.md:
--------------------------------------------------------------------------------
1 | Indexes directory for the Jetson Copilot app to store built indexes.
--------------------------------------------------------------------------------
/Indexes/_L4T_README/default__vector_store.json:
--------------------------------------------------------------------------------
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1 | {"docstore/metadata": {"e7fc044e-3964-4e0f-a796-96cfc8f181ba": {"doc_hash": "4b9ffc09483b44aa0e736f418d3721d2cf3c56753dcb2d5e11ed903a7f4486ad"}, "5f47e5af-32f1-452b-8b85-f9a86588fb58": {"doc_hash": "7fda26deb31198fe2a52919fe622bc8fc86c06067aa61141541cf5126322f073"}, "65bab8e5-31f1-410b-9c93-7cd6235c1423": {"doc_hash": "1e55a8c14ac91d79b3a05d6b45983fb7efec75f90446b969c1b67497a7c947bb"}, "63125b44-4036-40ef-a55c-411e21c0e972": {"doc_hash": "9599a2d0c1c2447c20a1f325a93691daaffa9ee526fda4f63e73eb29352efe7d"}, "739b53c4-9de7-4efb-b1c6-88ec667df232": {"doc_hash": "198e0e4d2a5f2c2cd7166ce4e748e561e59b5e6d10756254ed1078ff58dd06a8", "ref_doc_id": "e7fc044e-3964-4e0f-a796-96cfc8f181ba"}, "48c38696-5c51-47df-9046-8abb422545bc": {"doc_hash": "744dcd91172664fa1d32653fb9fd9dd9428eb2c27579639b3fd2f621d2543d02", "ref_doc_id": "5f47e5af-32f1-452b-8b85-f9a86588fb58"}, "f512de23-522c-4448-92d1-415236d5f180": {"doc_hash": "40b0e5706262ae2a75607e181febf8111dddcb6ce062d066385cb8e84789e614", "ref_doc_id": "5f47e5af-32f1-452b-8b85-f9a86588fb58"}, "34d95dab-2b28-4025-89c2-ff56581a2b44": {"doc_hash": "0948d7405492f213a2d074fb281d5c7a48cf5a5779175999cd365bcbbfa03fbe", "ref_doc_id": "5f47e5af-32f1-452b-8b85-f9a86588fb58"}, "d4c887f4-a366-45c8-a63e-bcdb25070120": {"doc_hash": "853b7068b00bada739cdfc8f838c93f8ed4416876c20357637c5f5066e1dd64c", "ref_doc_id": "65bab8e5-31f1-410b-9c93-7cd6235c1423"}, "da0dcdf2-60f0-4ec4-b683-7c1eff401c9f": {"doc_hash": "211bc9f7cc9ae59253b23c422fb4dfc9bd6976fc3237634da15f1ccb955173bd", "ref_doc_id": "63125b44-4036-40ef-a55c-411e21c0e972"}}, "docstore/data": {"739b53c4-9de7-4efb-b1c6-88ec667df232": {"__data__": {"id_": "739b53c4-9de7-4efb-b1c6-88ec667df232", "embedding": null, "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/INDEX.txt", "file_name": "INDEX.txt", "file_type": "text/plain", "file_size": 1104, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "e7fc044e-3964-4e0f-a796-96cfc8f181ba", "node_type": "4", "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/INDEX.txt", "file_name": "INDEX.txt", "file_type": "text/plain", "file_size": 1104, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "hash": "4b9ffc09483b44aa0e736f418d3721d2cf3c56753dcb2d5e11ed903a7f4486ad", "class_name": "RelatedNodeInfo"}}, "text": "=======================================================================\r\n INDEX\r\n Linux for Tegra\r\n Index of README files\r\n=======================================================================\r\n\r\nThis directory contains various documentation for Linux for Tegra:\r\n\r\nREADME-usb-dev-mode.txt:\r\n\r\n Describes how Linux for Tegra configures the Tegra USB flashing port in USB\r\n device mode, and the features that are exposed to a connected host PC, which\r\n include network and virtual serial port connectivity.\r\n\r\nREADME-wifi.txt:\r\n\r\n Describes how to connect Jetson to a WiFi network using command-line tools.\r\n This is useful when connecting to Jetson using ssh over the USB device mode\r\n network connection.\r\n\r\nREADME-vnc.txt:\r\n\r\n Describes how to configure Jetson to run a VNC server using command-line\r\n tools. This configuration can be performed using ssh over the USB device mode\r\n network connection. 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The script allows a USB\r\nhost system to interact with the Tegra device using a USB cable. The following\r\nimplemented protocols can be used at the same time:\r\n\r\n- Ethernet: allows system login using SSH and high-bandwidth file copying using\r\n SFTP.\r\n- UART/Serial: allows system login using a terminal application.\r\n- USB Mass Storage: Similar in concept to a USB memory stick.\r\n\r\n----------------------------------------------------------------------\r\nUsing Ethernet Protocol\r\n----------------------------------------------------------------------\r\nLinux for Tegra implements two types of Ethernet devices to support various\r\noperating systems running on the USB host machine. It is safe to ignore system\r\nerrors for missing drivers for an RNDIS or an NCM device. If your system\r\nsupports both devices, either device can be used. However, do not configure\r\nboth devices at the same time.\r\n\r\nLinux for Tegra assigns a link-local IPv6 address of fe80::1 to the USB\r\nEthernet device(s). You should not have to configure your host machine in order\r\nto use an IPv6 link-local address. If you connect multiple Jetson devices to\r\nthe same host machine, each Jetson device uses the same IPv6 link-local address.\r\nYou may still connect to any connected Jetson device, however, since use of IPv6\r\nlink-local addresses also requires specifying which network interface to\r\nconnect over, and there is a unique interface for each Jetson.\r\n\r\nLinux for Tegra assigns a static IPv4 address of 192.168.55.1 to Jetson, and\r\nruns a DHCP server to automatically assign an IPv4 address of 192.168.55.100 to\r\nyour host machine. This provides point-to-point connectivity. If a Jetson\r\ndevice experiences very high CPU or disk IO load, this DHCP server may fail to\r\nrespond in a timely manner to requests from the host machine. This may cause\r\nIPv4 connections to drop. If this problem occurs, configure your host machine\r\nto use a static IPv4 address of 192.168.55.100 with netmask 255.255.255.0 and\r\nno gateway or DNS servers.\r\n\r\nLinux for Tegra configures a very low priority default IPv4 route on the USB\r\nEthernet device(s), and configures Google's public DNS server (8.8.8.8) as the\r\nfallback DNS server for use when no other network connection is available.\r\nThis allows your host machine to act as an Intranet or Internet gateway for\r\nJetson.\r\n\r\nIf you connect multiple Jetson devices to the same host machine, each Jetson\r\ndevice uses the same IPv4 address. This prevents IPv4-based communication with\r\nall but one Jetson device, since your host operating system determines which\r\nJetson device it communicates with. To solve this, edit the Jetson-based script\r\nthat sets up the network and assign a unique network address to each Jetson\r\ndevice. IPv6-based communication works with any number of Jetson devices\r\nwithout modifying the aforementioned script.\r\n\r\nOnce the Ethernet device is configured, use SSH to connect to the Jetson device.\r\n\r\nSSH is natively available on Linux and Macintosh operating systems. Connect using\r\nIPv6 with the following command:\r\n\r\nssh nvidia@fe80::1%usb0\r\n\r\nConnect using IPv4 with the following command:\r\n\r\nssh nvidia@192.168.55.1\r\n\r\nOn Windows, use the PuTTY application.\r\n\r\nEthernet on Linux\r\n----------------------------------------------------------------------\r\nTwo USB Ethernet devices are created and the required drivers are automatically\r\nactivated. These devices are typically named usb0 and usb1, depending on how\r\nyour Linux distribution is configured, and what other hardware is attached to\r\nthe system. To avoid the potential for interference between the two USB\r\nEthernet devices, it is best, but not strictly required, to use your host's\r\nnetwork configuration tool (e.g. Network Manager), to disable one of the two\r\nUSB Ethernet interfaces implemented by the Jetson device.\r\n\r\nView available Ethernet devices with the following command:\r\n\r\n/sbin/ifconfig -a\r\n\r\nKnowledge of the Ethernet device name is required in order to use IPv6\r\nlink-local addresses.\r\n\r\nUse the following procedure to configure your host as a gateway for Jetson.\r\n\r\n1. Enable IP forwarding with your host's configuration tools, or by running\r\n the following command as root:\r\n\r\n echo 1 > /proc/sys/net/ipv4/ip_forward\r\n\r\n If your host system is connected to multiple networks at the same time,\r\n please consider any security implications of this configuration change.", "start_char_idx": 0, "end_char_idx": 4798, "text_template": "{metadata_str}\n\n{content}", "metadata_template": "{key}: {value}", "metadata_seperator": "\n", "class_name": "TextNode"}, "__type__": "1"}, "f512de23-522c-4448-92d1-415236d5f180": {"__data__": {"id_": "f512de23-522c-4448-92d1-415236d5f180", "embedding": null, "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-usb-dev-mode.txt", "file_name": "README-usb-dev-mode.txt", "file_type": "text/plain", "file_size": 11126, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "5f47e5af-32f1-452b-8b85-f9a86588fb58", "node_type": "4", "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-usb-dev-mode.txt", "file_name": "README-usb-dev-mode.txt", "file_type": "text/plain", "file_size": 11126, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "hash": "7fda26deb31198fe2a52919fe622bc8fc86c06067aa61141541cf5126322f073", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "48c38696-5c51-47df-9046-8abb422545bc", "node_type": "1", "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-usb-dev-mode.txt", "file_name": "README-usb-dev-mode.txt", "file_type": "text/plain", "file_size": 11126, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "hash": "744dcd91172664fa1d32653fb9fd9dd9428eb2c27579639b3fd2f621d2543d02", "class_name": "RelatedNodeInfo"}, "3": {"node_id": "34d95dab-2b28-4025-89c2-ff56581a2b44", "node_type": "1", "metadata": {}, "hash": "8cf49a224beec7b4ebaad014795cfb649dfe0866a9717cf05bdbd2247fdfe65b", "class_name": "RelatedNodeInfo"}}, "text": "To avoid the potential for interference between the two USB\r\nEthernet devices, it is best, but not strictly required, to use your host's\r\nnetwork configuration tool (e.g. Network Manager), to disable one of the two\r\nUSB Ethernet interfaces implemented by the Jetson device.\r\n\r\nView available Ethernet devices with the following command:\r\n\r\n/sbin/ifconfig -a\r\n\r\nKnowledge of the Ethernet device name is required in order to use IPv6\r\nlink-local addresses.\r\n\r\nUse the following procedure to configure your host as a gateway for Jetson.\r\n\r\n1. Enable IP forwarding with your host's configuration tools, or by running\r\n the following command as root:\r\n\r\n echo 1 > /proc/sys/net/ipv4/ip_forward\r\n\r\n If your host system is connected to multiple networks at the same time,\r\n please consider any security implications of this configuration change.\r\n\r\n Depending on your Linux distribution, you may be able to make this change\r\n permanent by editing /etc/sysctl.conf.\r\n\r\n2. Enable Network Address Translation (NAT) using your host's configuration\r\n tools to do this, or by running the following command as root:\r\n\r\n iptables -t nat -A POSTROUTING -o eth0 -j SNAT --to 192.168.1.100\r\n\r\n where:\r\n eth0 is the name of your host's upstream Ethernet interface.\r\n 192.168.1.100 is your host's IP address on that interface.\r\n\r\nDepending on your Linux distribution, you may have to run this command every\r\ntime your host is rebooted.\r\n\r\nEthernet on Windows\r\n----------------------------------------------------------------------\r\nAn RNDIS USB Ethernet device is created, and the required driver is\r\nautomatically installed. You can safely ignore the message that the NCM device\r\nis unknown. Depending on the Windows version you have, you might need to\r\ndisable the NCM device.\r\n\r\nTo configure your host as a gateway for Jetson:\r\n\r\n1. Click Control Panel -> Network and Internet -> Network Connections.\r\n\r\n2. Edit the \"Remote NDIS Compatible Device\" interface and configure \"Property\".\r\n\r\n3. Ensure that the IP address is 192.168.55.100. If Windows always gives you\r\n another IP address, for example, 192.168.137, you might need to configure a\r\n static IP address.\r\n\r\n4. Click Control Panel -> Network and Internet -> Network Connections.\r\n\r\n5. Edit the interface of your public interface and configure \"Property\".\r\n\r\n6. On the Sharing tab, enable the \"Allow other network users to connect through\r\n this computer's internet connection\" option.\r\n\r\n7. In the \"Home networking connection\" menu, select the RNDIS interface.\r\n\r\nEthernet on Mac\r\n----------------------------------------------------------------------\r\nAn NCM USB Ethernet device is created, and the required driver is automatically\r\nactivated. Since the Mac operating system does not support the RNDIS device,\r\nthe device is not activated by default.\r\n\r\nChanging the IPv4 Address\r\n----------------------------------------------------------------------\r\nEdit /opt/nvidia/l4t-usb-device-mode/nv-l4t-usb-device-mode-config.sh on Jetson\r\nto change the IPv4 network parameters. The following variables must be changed,\r\nand must maintain consistent values:\r\n- net_ip\r\n- net_mask\r\n- net_net\r\n- net_dhcp_start\r\n- net_dhcp_end\r\n\r\n----------------------------------------------------------------------\r\nUsing the Serial Port\r\n----------------------------------------------------------------------\r\nLinux for Tegra implements a single USB serial port, and presents a login\r\nprompt on the port. You may log into the system and run shell commands over\r\nthis port.\r\n\r\nAny standard serial terminal application may be used with the port. For\r\nexample:\r\n- Screen (Linux/Mac)\r\n- Picocom (Linux)\r\n- Tera Term (Windows)\r\n- HyperTerminal (Windows)\r\n\r\nSince this is an emulated serial port, any baud rate will work. The port must\r\nbe configured for 8N1 (8-bits per character, no stop bit, 1 parity bit).\r\n\r\nSerial Port on Linux\r\n----------------------------------------------------------------------\r\nLinux creates a device such as /dev/ttyACM0 for the serial port. To locate the\r\nexact name:\r\n1. Launch a shell prompt.\r\n2. Run the command: ls /dev.\r\n3. Search for \"ACM\".\r\n\r\nSerial Port on Windows\r\n----------------------------------------------------------------------\r\nWindows creates a standard COM port device for the serial port.\r\n\r\nOn systems using an operating system prior to Windows 10, you must manually\r\ninstall the driver for the serial port. To install the driver:\r\n1. Open Device Manager.\r\n2. Locate the \"CDC Serial\" device.\r\n3. Right-click the device and select \"update Driver Software\".\r\n4. Select to Browse for the driver software.\r\n5. Set the path to the USB disk drive that is implemented by your Linux for\r\n Tegra device.", "start_char_idx": 3952, "end_char_idx": 8646, "text_template": "{metadata_str}\n\n{content}", "metadata_template": "{key}: {value}", "metadata_seperator": "\n", "class_name": "TextNode"}, "__type__": "1"}, "34d95dab-2b28-4025-89c2-ff56581a2b44": {"__data__": {"id_": "34d95dab-2b28-4025-89c2-ff56581a2b44", "embedding": null, "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-usb-dev-mode.txt", "file_name": "README-usb-dev-mode.txt", "file_type": "text/plain", "file_size": 11126, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "5f47e5af-32f1-452b-8b85-f9a86588fb58", "node_type": "4", "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-usb-dev-mode.txt", "file_name": "README-usb-dev-mode.txt", "file_type": "text/plain", "file_size": 11126, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "hash": "7fda26deb31198fe2a52919fe622bc8fc86c06067aa61141541cf5126322f073", "class_name": "RelatedNodeInfo"}, "2": {"node_id": "f512de23-522c-4448-92d1-415236d5f180", "node_type": "1", "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-usb-dev-mode.txt", "file_name": "README-usb-dev-mode.txt", "file_type": "text/plain", "file_size": 11126, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "hash": "40b0e5706262ae2a75607e181febf8111dddcb6ce062d066385cb8e84789e614", "class_name": "RelatedNodeInfo"}}, "text": "Serial Port on Linux\r\n----------------------------------------------------------------------\r\nLinux creates a device such as /dev/ttyACM0 for the serial port. To locate the\r\nexact name:\r\n1. Launch a shell prompt.\r\n2. Run the command: ls /dev.\r\n3. Search for \"ACM\".\r\n\r\nSerial Port on Windows\r\n----------------------------------------------------------------------\r\nWindows creates a standard COM port device for the serial port.\r\n\r\nOn systems using an operating system prior to Windows 10, you must manually\r\ninstall the driver for the serial port. To install the driver:\r\n1. Open Device Manager.\r\n2. Locate the \"CDC Serial\" device.\r\n3. Right-click the device and select \"update Driver Software\".\r\n4. Select to Browse for the driver software.\r\n5. Set the path to the USB disk drive that is implemented by your Linux for\r\n Tegra device.\r\n\r\nWindows will locate the required .inf file and install the relevant drivers for\r\nthe serial port.\r\n\r\nSerial Port on Mac\r\n----------------------------------------------------------------------\r\nMac OS creates a device such as /dev/tty.usbmodem1232 for the serial port. To\r\nlocate the exact name:\r\n1. Launch a shell prompt.\r\n2. Run the command: ls /dev.\r\n3. Search for \"tty.usbmodem\".\r\n\r\n----------------------------------------------------------------------\r\nUsing USB Mass Storage\r\n----------------------------------------------------------------------\r\nLinux for Tegra implements a USB Mass Storage device, known as a USB disk or\r\nUSB memory stick, that is natively supported by all operating systems. The USB\r\ndisk automatically appears in the graphical filesystem browser such as:\r\n- Linux desktop\r\n- Windows Explorer\r\n- Mac Finder\r\n\r\nOn Linux or Mac, you can manually mount the disk from the command line, just\r\nlike a USB storage device.\r\n\r\nThe USB storage device is read-only and contains various driver files and Linux\r\nfor Tegra documentation.\r\n\r\n----------------------------------------------------------------------\r\nDisabling USB Device Mode Temporarily\r\n----------------------------------------------------------------------\r\n\r\nTo disable USB device mode temporarily:\r\n1. On the Linux for Tegra system, launch a shell prompt.\r\n2. Log in as root.\r\n3. Execute the command:\r\n service nv-l4t-usb-device-mode stop\r\n\r\nTo re-enable USB device mode:\r\n1. On the Linux for Tegra system, launch a shell prompt.\r\n2. Log in as root.\r\n3. Execute the command:\r\n service nv-l4t-usb-device-mode start\r\n\r\nUSB device mode will be re-enabled automatically the next time the system is\r\nrebooted.\r\n\r\n----------------------------------------------------------------------\r\nDisabling USB Device Mode Permanently\r\n----------------------------------------------------------------------\r\nTo disable USB device mode permanently:\r\n1. On the Linux for Tegra system, launch a shell prompt.\r\n2. Log in as root.\r\n3. Execute the commands:\r\n service nv-l4t-usb-device-mode stop\r\n systemctl disable nv-l4t-usb-device-mode.service\r\n\r\nThis is equivalent to deleting the following files:\r\n\r\n/etc/systemd/system/nv-l4t-usb-device-mode.service\r\n/etc/systemd/system/multi-user.target.wants/nv-l4t-usb-device-mode.service\r\n\r\nTo re-enable USB device mode, execute the commands:\r\n\r\nsystemctl enable /opt/nvidia/l4t-usb-device-mode/nv-l4t-usb-device-mode.service\r\nservice nv-l4t-usb-device-mode start", "start_char_idx": 7810, "end_char_idx": 11124, "text_template": "{metadata_str}\n\n{content}", "metadata_template": "{key}: {value}", "metadata_seperator": "\n", "class_name": "TextNode"}, "__type__": "1"}, "d4c887f4-a366-45c8-a63e-bcdb25070120": {"__data__": {"id_": "d4c887f4-a366-45c8-a63e-bcdb25070120", "embedding": null, "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-vnc.txt", "file_name": "README-vnc.txt", "file_type": "text/plain", "file_size": 3590, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "65bab8e5-31f1-410b-9c93-7cd6235c1423", "node_type": "4", "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-vnc.txt", "file_name": "README-vnc.txt", "file_type": "text/plain", "file_size": 3590, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "hash": "1e55a8c14ac91d79b3a05d6b45983fb7efec75f90446b969c1b67497a7c947bb", "class_name": "RelatedNodeInfo"}}, "text": "=======================================================================\r\n README-vnc\r\n Linux for Tegra\r\n Configuring VNC from the command-line\r\n=======================================================================\r\n\r\nA VNC server allows access to the graphical display of a Linux for Tegra system\r\nover the network. This allows you to work physically remote from the Linux for\r\nTegra system, and avoids the need to connect an HDMI display, USB keyboard, or\r\nmouse.\r\n\r\nAll commands specified below should be executed from a terminal on the Linux\r\nfor Tegra system. This could be a serial port, an SSH session, or a graphical\r\nterminal application running on the HDMI display.\r\n\r\n----------------------------------------------------------------------\r\nInstalling the VNC Server\r\n----------------------------------------------------------------------\r\n\r\nIt is expected that the VNC server software is pre-installed. Execute the\r\nfollowing commands to ensure that it is:\r\n\r\nsudo apt update\r\nsudo apt install vino\r\n\r\n----------------------------------------------------------------------\r\nEnabling the VNC Server\r\n----------------------------------------------------------------------\r\n\r\nExecute the following commands to enable the VNC server:\r\n\r\n# Enable the VNC server to start each time you log in\r\nmkdir -p ~/.config/autostart\r\ncp /usr/share/applications/vino-server.desktop ~/.config/autostart\r\n\r\n# Configure the VNC server\r\ngsettings set org.gnome.Vino prompt-enabled false\r\ngsettings set org.gnome.Vino require-encryption false\r\n\r\n# Set a password to access the VNC server\r\n# Replace thepassword with your desired password\r\ngsettings set org.gnome.Vino authentication-methods \"['vnc']\"\r\ngsettings set org.gnome.Vino vnc-password $(echo -n 'thepassword'|base64)\r\n\r\n# Reboot the system so that the settings take effect\r\nsudo reboot\r\n\r\nThe VNC server is only available after you have logged in to Jetson locally. If\r\nyou wish VNC to be available automatically, use the system settings application\r\nto enable automatic login.\r\n\r\n----------------------------------------------------------------------\r\nConnecting to the VNC server\r\n----------------------------------------------------------------------\r\n\r\nUse any standard VNC client application to connect to the VNC server that is\r\nrunning on Linux for Tegra. Popular examples for Linux are gvncviewer and\r\nremmina. Use your own favorite client for Windows or MacOS.\r\n\r\nTo connect, you will need to know the IP address of the Linux for Tegra system.\r\nExecute the following command to determine the IP address:\r\n\r\nifconfig\r\n\r\nSearch the output for the text \"inet addr:\" followed by a sequence of four\r\nnumbers, for the relevant network interface (e.g. eth0 for wired Ethernet,\r\nwlan0 for WiFi, or l4tbr0 for the USB device mode Ethernet connection).\r\n\r\n----------------------------------------------------------------------\r\nSetting the Desktop Resolution\r\n----------------------------------------------------------------------\r\n\r\nThe desktop resolution is typically determined by the capabilities of the\r\ndisplay that is attached to Jetson. If no display is attached, a default\r\nresolution of 640x480 is selected. To use a different resolution, edit\r\n/etc/X11/xorg.conf and append the following lines:\r\n\r\nSection \"Screen\"\r\n Identifier \"Default Screen\"\r\n Monitor \"Configured Monitor\"\r\n Device \"Tegra0\"\r\n SubSection \"Display\"\r\n Depth 24\r\n Virtual 1280 800 # Modify the resolution by editing these values\r\n EndSubSection\r\nEndSection", "start_char_idx": 0, "end_char_idx": 3588, "text_template": "{metadata_str}\n\n{content}", "metadata_template": "{key}: {value}", "metadata_seperator": "\n", "class_name": "TextNode"}, "__type__": "1"}, "da0dcdf2-60f0-4ec4-b683-7c1eff401c9f": {"__data__": {"id_": "da0dcdf2-60f0-4ec4-b683-7c1eff401c9f", "embedding": null, "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-wifi.txt", "file_name": "README-wifi.txt", "file_type": "text/plain", "file_size": 1940, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "excluded_embed_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "excluded_llm_metadata_keys": ["file_name", "file_type", "file_size", "creation_date", "last_modified_date", "last_accessed_date"], "relationships": {"1": {"node_id": "63125b44-4036-40ef-a55c-411e21c0e972", "node_type": "4", "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-wifi.txt", "file_name": "README-wifi.txt", "file_type": "text/plain", "file_size": 1940, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}, "hash": "9599a2d0c1c2447c20a1f325a93691daaffa9ee526fda4f63e73eb29352efe7d", "class_name": "RelatedNodeInfo"}}, "text": "=======================================================================\r\n README-wifi\r\n Linux for Tegra\r\n Configuring WiFi from the command-line\r\n=======================================================================\r\n\r\nA Linux for Tegra device may be connected to a WiFi network using different\r\ntools, depending on whether you interact with Linux for Tegra using the\r\ncommand-line (i.e. serial port, or SSH connection), or a graphical interface\r\nvia an HDMI display.\r\n\r\nAll commands specified below should be executed from a terminal on the Linux\r\nfor Tegra system. This could be a serial port, an SSH session, or a graphical\r\nterminal application running on the HDMI display.\r\n\r\n----------------------------------------------------------------------\r\nInstalling Network Manager\r\n----------------------------------------------------------------------\r\n\r\nIt is expected that the Network manager software is pre-installed. Execute the\r\nfollowing command to ensure that it is:\r\n\r\nsudo apt update\r\nsudo apt install network-manager\r\nsudo service NetworkManager start\r\n\r\n----------------------------------------------------------------------\r\nUsing the Command Line\r\n----------------------------------------------------------------------\r\n\r\nExecute the following command, having replaced SSID with the name of the\r\nnetwork you wish to connect to, and PASSWORD with the password/passphrase for\r\nthat network.\r\n\r\nsudo nmcli device wifi connect 'SSID' password 'PASSWORD'\r\n\r\n----------------------------------------------------------------------\r\nUsing the Graphical Interface\r\n----------------------------------------------------------------------\r\n\r\nA network configuration icon will appear at the top-right corner of the\r\ndisplay. Click this with the mouse to see a list of WiFi networks, then click\r\nthe network name you wish to connect to, and follow the on-screen prompts.", "start_char_idx": 0, "end_char_idx": 1938, "text_template": "{metadata_str}\n\n{content}", "metadata_template": "{key}: {value}", "metadata_seperator": "\n", "class_name": "TextNode"}, "__type__": "1"}}, "docstore/ref_doc_info": {"e7fc044e-3964-4e0f-a796-96cfc8f181ba": {"node_ids": ["739b53c4-9de7-4efb-b1c6-88ec667df232"], "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/INDEX.txt", "file_name": "INDEX.txt", "file_type": "text/plain", "file_size": 1104, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}}, "5f47e5af-32f1-452b-8b85-f9a86588fb58": {"node_ids": ["48c38696-5c51-47df-9046-8abb422545bc", "f512de23-522c-4448-92d1-415236d5f180", "34d95dab-2b28-4025-89c2-ff56581a2b44"], "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-usb-dev-mode.txt", "file_name": "README-usb-dev-mode.txt", "file_type": "text/plain", "file_size": 11126, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}}, "65bab8e5-31f1-410b-9c93-7cd6235c1423": {"node_ids": ["d4c887f4-a366-45c8-a63e-bcdb25070120"], "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-vnc.txt", "file_name": "README-vnc.txt", "file_type": "text/plain", "file_size": 3590, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}}, "63125b44-4036-40ef-a55c-411e21c0e972": {"node_ids": ["da0dcdf2-60f0-4ec4-b683-7c1eff401c9f"], "metadata": {"file_path": "/opt/jetson_copilot/Documents/L4T_README/README-wifi.txt", "file_name": "README-wifi.txt", "file_type": "text/plain", "file_size": 1940, "creation_date": "2024-06-11", "last_modified_date": "2024-06-11"}}}}
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/README.md:
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1 | # Jetson Copilot
2 |
3 | 
4 |
5 | Jetson Copilot is a reference application for a ***local*** AI assistant.
6 |
7 | It demonstrates two things;
8 |
9 | - Running open-source LLMs (large language model) on device
10 | - Augmenting the LLM to have access to your locally indexed knowledge (**RAG**, retrieval-augmented generation)
11 |
12 | > [!IMPORTANT]
13 | >
14 | > This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.
15 | >
16 | > | OSS | Repo URL | Usage |
17 | > | --- | --- | ----- |
18 | > |[Ollama](https://www.ollama.com/)|[GitHub](https://github.com/ollama/ollama)|To host and run LLMs locally, including embedding models for building index from documents |
19 | > | [LlamaIndex](https://www.llamaindex.ai/) | [GitHub](https://github.com/run-llama/llama_index) | Data framework for LLM, used mainly to realize RAG pipeline. |
20 | > | [Streamlit](https://streamlit.io/) | [GitHub](https://github.com/streamlit/streamlit) | Python library to create an interactive web app |
21 |
22 |
23 | ## 🏃 Getting started
24 |
25 | ### First time setup
26 |
27 | If this is your first time to run Jetson Copilot on your Jetson, first run `setup_environment.sh` to ensure you have all the necessary software installed and the environment set up.
28 |
29 | ```bash
30 | git clone https://github.com/NVIDIA-AI-IOT/jetson-copilot/
31 | cd jetson-copilot
32 | ./setup_environment.sh
33 | ```
34 |
35 | It will install the following, if not yet.
36 |
37 | - Chromium web browser
38 | - Docker
39 |
40 | > [!IMPORTANT]
41 | >
42 | > It also adds the current user into `docker` group using `newgrp` command.
43 | >
44 | > Check to see if you can just issue the following command (without using `sudo`).
45 | >
46 | > ```bash
47 | > docker ps
48 | > ```
49 | >
50 | > If you get `permission denied` error, exit from the session (by executing `exit` command), reboot if possible (so that it will take effect in any sessions), and log/ssh back in.
51 | > You should now be able to issue `docker ps`.
52 |
53 | ### How to start Jetson Copilot
54 |
55 | ```bash
56 | cd jetson-copilot
57 | ./launch_jetson_copilot.sh
58 | ```
59 |
60 | https://github.com/NVIDIA-AI-IOT/jetson-copilot/assets/25759564/e2e99d47-7a17-4b1b-870a-d5d376e2cae3
61 |
62 | This will start a Docker container and start a Ollama server and Streamlit app inside the container. It will shows the URL on the console in order to access the web app hosted on your Jetson.
63 |
64 | With your web browser on Jetson, open the **Local URL** (`localhost`). Or on a PC connected on the same network as on your Jetson, access the **Network URL**.
65 |
66 | ```bash
67 | Local URL: http://localhost:8501
68 | Network URL: http://10.110.50.252:8501
69 | ```
70 |
71 | > [!NOTE]
72 | > You will need the Internet connection on Jetson when it launches for the first time, as it will pull the container image (and download the default LLM and embedding model when web UI starts for the first time).
73 |
74 | When you access the web UI for the first time, it will download the default LLM (`llama3`) and the embedding model (`mxbai-embed-large`).
75 |
76 | > [!TIP]
77 | > If you are on Ubuntu Desktop, a frameless Chromium window will pop up to access the web app, to make it look like an independent application.
78 | > You need to close the window as stopping the container on the console won't shutdown Chromium.
79 | >
80 | > https://github.com/NVIDIA-AI-IOT/jetson-copilot/assets/25759564/422fc036-890a-4c72-aa90-52cfb656ed57
81 |
82 | ## 📖 How to use Jetson Copilot
83 |
84 | ### 0. Interact with the plain Llama3 (8b)
85 |
86 | https://github.com/NVIDIA-AI-IOT/jetson-copilot/assets/25759564/6aed539c-08b3-448f-8cbc-3e20abfa782f
87 |
88 | You can use Jetson Copilot just to interact with a LLM without enabling RAG feature.
89 |
90 | By default, Llama3 (8b) model is downloaded when running for the first time and use as the default LLM.
91 |
92 | You will be surprized how much a model like Llama3 is capable, but may soon find limitations as it does not have information prior to its cutoff date nor know anything about your specific subject matter.
93 |
94 | ### 1. Ask Jetson related question using pre-built index
95 |
96 | https://github.com/NVIDIA-AI-IOT/jetson-copilot/assets/25759564/c187f0de-a998-463e-acf8-2e793e523e98
97 |
98 | On the side panel, you can toggle "Use RAG" on to enable RAG pipeline.
99 | The LLM will have an access to a custom knowledge/index that is selected under "Index".
100 |
101 | As a sample, a pre-build index "`_L4T_README`" is provided.
102 | This is built on all the README text files that supplied in the "L4T-README" folder on the Jetson desktop.
103 |
104 | > It is mounted as `/media//L4T-README/` once you execute `udisksctl mount -b /dev/disk/by-label/L4T-README`.
105 |
106 | You can ask questions like:
107 |
108 | ```
109 | What IP address does Jetson gets assigned when connected to a PC via a USB cable in USB Device Mode?
110 | ```
111 |
112 | ### 2. Build your own index based on your documents
113 |
114 | https://github.com/NVIDIA-AI-IOT/jetson-copilot/assets/25759564/c333833a-9a4a-4d57-9216-d3d464466d3c
115 |
116 | You can build your own index based on your local and/or online documents.
117 |
118 | First, on the console (or on the desktop) create a directory under `Documents` directory to store your documents.
119 |
120 | ```bash
121 | cd jetson-copilot
122 | mkdir Documents/Jetson-Orin-Nano
123 | cd Documents/Jetson-Orin-Nano
124 | wget https://developer.nvidia.com/downloads/assets/embedded/secure/jetson/orin_nano/docs/jetson_orin_nano_devkit_carrier_board_specification_sp.pdf
125 | ```
126 |
127 | Now back on the web UI, open the side bar, toggle on "Use RAG", then click on "**➕Build a new index**" to jump to a "**Build Index**" page.
128 |
129 | Give a name for the Index you are to build. (e.g. "JON Carrier Board")
130 | Type in the field and hit `Enter` key, then it will check and show what path will be created for your index.
131 |
132 | > 
133 |
134 | And then from the drop select box under "**Local documents**", select the directory you created and saved your documents in. (e.g. `/opt/jetson_copilot/Documents/Jetson-Orin-Nano`).
135 |
136 | It will show the summary of files found in the selected directory.
137 |
138 | > 
139 |
140 | If you want to rather only or additionally supply URLs for the online docuemnts to be ingested, fill the text area with one URL per a line.
141 | You can skip this if you are building your index only based on your local documents.
142 |
143 | > [!NOTE]
144 | > On the sidebar, make sure `mxbai-embed-large` is selected for the embedding model.
145 | >
146 | > Use of OpenAI embedding models is not well supported and needs more testing.
147 |
148 | Finally, hit "**Build Index**" button.
149 | It will show the progress in the drop-down "status container", so you can check the status by clicking on it.
150 | Once done, it will show the summary of your index and time it took.
151 |
152 | You can go back to the home screen to now select the index you just built.
153 |
154 | ### 3. Test different LLM or Embedding model
155 |
156 | TODO
157 |
158 | ## 🏗️ Development
159 |
160 | Streamlit based web app is very easy to develop.
161 |
162 | On web UI, at the top-right of the screen, choose "**Always rerun**" to automatically update your app every time you change the source codes.
163 |
164 | See [Streamlit Documentation](https://docs.streamlit.io/get-started/fundamentals/main-concepts#development-flow) for the detail.
165 |
166 | ### Manually run streamlit app inside the container
167 |
168 | In case you make more fundamental changes, you can also manually run streamlit app.
169 |
170 | ```bash
171 | cd jetson-copilot
172 | ./launch_dev.sh
173 | ```
174 |
175 | Once in container;
176 |
177 | ```bash
178 | streamlit run app.py
179 | ```
180 |
181 | https://github.com/NVIDIA-AI-IOT/jetson-copilot/assets/25759564/7ec4552a-bd55-4325-8167-d8429324b1bd
182 |
183 | ## 🧱 Directory structure
184 |
185 | ```
186 | └── jetson-copilot
187 | ├── launch_jetson_copilot.sh
188 | ├── setup_environment.sh
189 | ├── Documents
190 | │ └── your_abc_docs
191 | ├── Indexes
192 | │ ├── _L4T_README
193 | │ └── your_abc_index
194 | ├── logs
195 | │ ├── container.log
196 | │ └── ollama.log
197 | ├── ollama_models
198 | └── Streamlit_app
199 | ├── app.py
200 | ├── build_index.py
201 | └── download_model.py
202 | ```
203 |
204 | Following directories inside the `jetson-copilot` directory are mounted in the Docker container.
205 |
206 | | Directory Name | Description |
207 | | -------------- | ----------- |
208 | | `Documents` | Directory to store your documents to be indexed |
209 | | `Indexes` | Directory to store pre-built (or built-by-you) indexes for LLM to perform RAG on |
210 | | `logs` | Directory for the app to store log files |
211 | | `ollama_models`| Directory for the ollama server to store download models |
212 | | `stremlit_app` | Directory for Python scripts to make up the web app |
213 |
214 |
215 | ## 💫 Troubleshooting
216 |
217 | If you find any issue, please check [GitHub Issues of the Jetson Copilot repo](https://github.com/NVIDIA-AI-IOT/jetson-copilot/issues) and file an issue there.
218 |
219 | ### `permission denied`
220 |
221 | If you get "**permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock**" issue, your current user account in Linux may not be added to the group `docker` and/or the change is not taking effect yet.
222 |
223 | So issue the following commands to ensure you add your user account in the group, and exit from the current session, reboot if possible (so that it will take effect in any sessions), then log/ssh back in.
224 |
225 | ```bash
226 | sudo systemctl restart docker
227 | sudo usermod -aG docker $USER
228 | newgrp docker
229 | exit
230 | ```
231 |
232 | You can check if you succeed by issuing `docker ps`.
233 |
234 | ### `unable to setup input stream`
235 |
236 | If you run `launch_jetson_copilot.sh` and get "**unable to setup input stream: unable to set IO streams as raw terminal: input/output error**", then you can just use the `launch_dev.sh` and manually start the streamlit app.
237 |
238 | ```bash
239 | ./launch_dev.sh
240 | ```
241 |
242 | And once in the container;
243 |
244 | ```bash
245 | streamlit run app.py
246 | ```
247 |
248 | ## Proposed usage
249 |
250 | You can use Jetson Copilot in multiple ways.
251 |
252 | ### Useful and tool
253 |
254 | Users can easily run an LLM on Jetson without relying on any cloud services.
255 |
256 | They may find the AI assistance on some tasks useful, like to find out the right command to use on Linux system. They can even expand the LLM knowledge by building the local index based on their own documents that LLM can access.
257 |
258 | ### Reference for building a custom AI assistant
259 |
260 | Developers can use Jetson Copilot as a reference for building their own AI assistant that possesses some specific domain area's or product's knowledge.
261 |
262 | ## ⚖️ License
263 | Please see LICENSE file.
264 |
265 | ## 📜 Project status
266 | Pushed to public, still partially in development.
267 |
268 | ### TODO
269 |
270 | - [x] LLM download UI (`download_model.py`)
271 | - [ ] Use `faiss` for Vector DB
272 | - [ ] Support OpenAI embedding models
--------------------------------------------------------------------------------
/index_name_checked.png:
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/launch_dev.sh:
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1 | #!/bin/bash
2 |
3 | ### Color logger function
4 |
5 | singal='\033[0;93m'
6 | clear='\033[0m'
7 |
8 | function log () {
9 | # check if message
10 | test -n "$1" || {
11 | echo;
12 | return;
13 | }
14 | printf "${singal}$1${clear}\n"
15 | }
16 |
17 | #############################################################
18 | ### L4T_VERSION retrieve logic
19 | ### Copied from https://github.com/dusty-nv/jetson-containers/blob/master/jetson_containers/l4t_version.sh
20 | ###vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv###
21 |
22 | ARCH=$(uname -i)
23 | log "ARCH: $ARCH"
24 |
25 | if [ $ARCH = "aarch64" ]; then
26 | L4T_VERSION_STRING=$(head -n 1 /etc/nv_tegra_release)
27 |
28 | if [ -z "$L4T_VERSION_STRING" ]; then
29 | #echo "reading L4T version from \"dpkg-query --show nvidia-l4t-core\""
30 |
31 | L4T_VERSION_STRING=$(dpkg-query --showformat='${Version}' --show nvidia-l4t-core)
32 | L4T_VERSION_ARRAY=(${L4T_VERSION_STRING//./ })
33 |
34 | #echo ${L4T_VERSION_ARRAY[@]}
35 | #echo ${#L4T_VERSION_ARRAY[@]}
36 |
37 | L4T_RELEASE=${L4T_VERSION_ARRAY[0]}
38 | L4T_REVISION=${L4T_VERSION_ARRAY[1]}
39 | else
40 | #echo "reading L4T version from /etc/nv_tegra_release"
41 |
42 | L4T_RELEASE=$(echo $L4T_VERSION_STRING | cut -f 2 -d ' ' | grep -Po '(?<=R)[^;]+')
43 | L4T_REVISION=$(echo $L4T_VERSION_STRING | cut -f 2 -d ',' | grep -Po '(?<=REVISION: )[^;]+')
44 | fi
45 |
46 | L4T_REVISION_MAJOR=${L4T_REVISION:0:1}
47 | L4T_REVISION_MINOR=${L4T_REVISION:2:1}
48 |
49 | L4T_VERSION="$L4T_RELEASE.$L4T_REVISION"
50 |
51 | log "L4T_VERSION: $L4T_VERSION"
52 |
53 | elif [ $ARCH != "x86_64" ]; then
54 | log "unsupported architecture: $ARCH"
55 | exit 1
56 | fi
57 |
58 | ###^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^###
59 | ### L4T_VERSION retrieve logic done
60 | #############################################################
61 |
62 | ROOT="$(dirname "$(readlink -f "$0")")"
63 |
64 | # run the container
65 | ARCH=$(uname -i)
66 |
67 | set -ex
68 |
69 | # check for jtop
70 | JTOP_SOCKET=""
71 | JTOP_SOCKET_FILE="/run/jtop.sock"
72 |
73 | if [ -S "$JTOP_SOCKET_FILE" ]; then
74 | JTOP_SOCKET="-v /run/jtop.sock:/run/jtop.sock"
75 | fi
76 |
77 | if [ $ARCH = "aarch64" ]; then
78 |
79 | verions_numbers=(${L4T_VERSION//./ })
80 | L4T_VERSION_MAJOR=${verions_numbers[0]}
81 |
82 | # https://hub.docker.com/r/dustynv/jetson-copilot/tags
83 | if [ "$L4T_VERSION_MAJOR" == "35" ]; then
84 | log "JetPack 5.x :"
85 | CONTAINER_TAG="r35.4.1"
86 | elif [ "$L4T_VERSION_MAJOR" == "36" ]; then
87 | log "JetPack 6.x :"
88 | CONTAINER_TAG="r36.3.0"
89 | fi
90 |
91 | if [ -z "$1" ]; then
92 | # No argument supplied, use the default container image hosted on Docker Hub
93 | CONTIANER_IMAGE="dustynv/jetson-copilot:$CONTAINER_TAG"
94 | else
95 | # Argument supplied, use the specified (potentially local) Docker container image
96 | CONTIANER_IMAGE=$1
97 | fi
98 |
99 | # this file shows what Jetson board is running
100 | # /proc or /sys files aren't mountable into docker
101 | cat /proc/device-tree/model > /tmp/nv_jetson_model
102 |
103 | docker run --runtime nvidia -it --rm --network host \
104 | --volume /tmp/argus_socket:/tmp/argus_socket \
105 | --volume /etc/enctune.conf:/etc/enctune.conf \
106 | --volume /etc/nv_tegra_release:/etc/nv_tegra_release \
107 | --volume /tmp/nv_jetson_model:/tmp/nv_jetson_model \
108 | --volume /var/run/dbus:/var/run/dbus \
109 | --volume /var/run/avahi-daemon/socket:/var/run/avahi-daemon/socket \
110 | --volume /var/run/docker.sock:/var/run/docker.sock \
111 | --volume $ROOT/Documents:/opt/jetson_copilot/Documents \
112 | --volume $ROOT/Indexes:/opt/jetson_copilot/Indexes \
113 | --volume $ROOT/logs:/data/logs \
114 | --volume $ROOT/ollama_models://data/models/ollama/models \
115 | --volume $ROOT/streamlit_app:/opt/jetson_copilot/app \
116 | --device /dev/snd \
117 | --device /dev/bus/usb \
118 | $DATA_VOLUME $DISPLAY_DEVICE $V4L2_DEVICES $I2C_DEVICES $JTOP_SOCKET $EXTRA_FLAGS \
119 | $CONTIANER_IMAGE \
120 | bash -c '/start_ollama && \
121 | cd /opt/jetson_copilot/app && \
122 | /bin/bash'
123 | fi
124 |
--------------------------------------------------------------------------------
/launch_jetson_copilot.sh:
--------------------------------------------------------------------------------
1 | #!/bin/bash
2 |
3 | ### Color logger function
4 |
5 | singal='\033[0;93m'
6 | clear='\033[0m'
7 |
8 | function log () {
9 | # check if message
10 | test -n "$1" || {
11 | echo;
12 | return;
13 | }
14 | printf "${singal}$1${clear}\n"
15 | }
16 |
17 | #############################################################
18 | ### L4T_VERSION retrieve logic
19 | ### Copied from https://github.com/dusty-nv/jetson-containers/blob/master/jetson_containers/l4t_version.sh
20 | ###vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv###
21 |
22 | ARCH=$(uname -i)
23 | log "ARCH: $ARCH"
24 |
25 | if [ $ARCH = "aarch64" ]; then
26 | L4T_VERSION_STRING=$(head -n 1 /etc/nv_tegra_release)
27 |
28 | if [ -z "$L4T_VERSION_STRING" ]; then
29 | #echo "reading L4T version from \"dpkg-query --show nvidia-l4t-core\""
30 |
31 | L4T_VERSION_STRING=$(dpkg-query --showformat='${Version}' --show nvidia-l4t-core)
32 | L4T_VERSION_ARRAY=(${L4T_VERSION_STRING//./ })
33 |
34 | #echo ${L4T_VERSION_ARRAY[@]}
35 | #echo ${#L4T_VERSION_ARRAY[@]}
36 |
37 | L4T_RELEASE=${L4T_VERSION_ARRAY[0]}
38 | L4T_REVISION=${L4T_VERSION_ARRAY[1]}
39 | else
40 | #echo "reading L4T version from /etc/nv_tegra_release"
41 |
42 | L4T_RELEASE=$(echo $L4T_VERSION_STRING | cut -f 2 -d ' ' | grep -Po '(?<=R)[^;]+')
43 | L4T_REVISION=$(echo $L4T_VERSION_STRING | cut -f 2 -d ',' | grep -Po '(?<=REVISION: )[^;]+')
44 | fi
45 |
46 | L4T_REVISION_MAJOR=${L4T_REVISION:0:1}
47 | L4T_REVISION_MINOR=${L4T_REVISION:2:1}
48 |
49 | L4T_VERSION="$L4T_RELEASE.$L4T_REVISION"
50 |
51 | log "L4T_VERSION: $L4T_VERSION"
52 |
53 | elif [ $ARCH != "x86_64" ]; then
54 | log "unsupported architecture: $ARCH"
55 | exit 1
56 | fi
57 |
58 | ###^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^###
59 | ### L4T_VERSION retrieve logic done
60 | #############################################################
61 |
62 | ROOT="$(dirname "$(readlink -f "$0")")"
63 |
64 | # run the container
65 | ARCH=$(uname -i)
66 |
67 | set -ex
68 |
69 | # check for jtop
70 | JTOP_SOCKET=""
71 | JTOP_SOCKET_FILE="/run/jtop.sock"
72 |
73 | if [ -S "$JTOP_SOCKET_FILE" ]; then
74 | JTOP_SOCKET="-v /run/jtop.sock:/run/jtop.sock"
75 | fi
76 |
77 | if [ $ARCH = "aarch64" ]; then
78 |
79 | verions_numbers=(${L4T_VERSION//./ })
80 | L4T_VERSION_MAJOR=${verions_numbers[0]}
81 | L4T_VERSION_MINOR=${verions_numbers[1]}
82 |
83 | # https://hub.docker.com/r/dustynv/jetrag/tags
84 | if [ "$L4T_VERSION_MAJOR" == "35" ]; then
85 | log "JetPack 5.x :"
86 | CONTAINER_TAG="r35.4.1"
87 | elif [ "$L4T_VERSION_MAJOR" == "36" ]; then
88 | log "JetPack 6.x :"
89 | if [ "$L4T_VERSION_MINOR" == "3" ]; then
90 | CONTAINER_TAG="r36.3.0"
91 | else
92 | CONTAINER_TAG="r36.4.0"
93 | fi
94 | fi
95 |
96 | # this file shows what Jetson board is running
97 | # /proc or /sys files aren't mountable into docker
98 | cat /proc/device-tree/model > /tmp/nv_jetson_model
99 |
100 | docker run --runtime nvidia --rm --network host \
101 | --volume /tmp/argus_socket:/tmp/argus_socket \
102 | --volume /etc/enctune.conf:/etc/enctune.conf \
103 | --volume /etc/nv_tegra_release:/etc/nv_tegra_release \
104 | --volume /tmp/nv_jetson_model:/tmp/nv_jetson_model \
105 | --volume /var/run/dbus:/var/run/dbus \
106 | --volume /var/run/avahi-daemon/socket:/var/run/avahi-daemon/socket \
107 | --volume /var/run/docker.sock:/var/run/docker.sock \
108 | --volume $ROOT/Documents:/opt/jetson_copilot/Documents \
109 | --volume $ROOT/Indexes:/opt/jetson_copilot/Indexes \
110 | --volume $ROOT/logs:/data/logs \
111 | --volume $ROOT/ollama_models://data/models/ollama/models \
112 | --volume $ROOT/streamlit_app:/opt/jetson_copilot/app \
113 | --device /dev/snd \
114 | --device /dev/bus/usb \
115 | $DATA_VOLUME $DISPLAY_DEVICE $V4L2_DEVICES $I2C_DEVICES $JTOP_SOCKET $EXTRA_FLAGS \
116 | dustynv/jetson-copilot:$CONTAINER_TAG \
117 | bash -c '/start_ollama && cd /opt/jetson_copilot/app/ && streamlit run ./app.py' \
118 | | tee -a ./logs/container.log & pid=$!
119 | PID_LIST+=" $pid"
120 | fi
121 |
122 | echo "############################# $PID_LIST added to PID_LIST"
123 |
124 | echo "" | zenity --progress --text "Display test" --auto-close 2> /dev/null
125 | if [ $? -eq 0 ]
126 | then
127 | chromium --profile-directory="Default" --app="data:text/html," & pid=$!
128 | PID_LIST+=" $pid"
129 | else
130 | echo "no display"
131 | fi
132 |
133 | # tail -f ./logs/container.log
134 |
135 | trap "kill $PID_LIST" SIGINT
136 |
137 | echo "Parallel processes have started";
138 |
139 | wait $PID_LIST
140 |
141 | echo
142 | echo "All processes have completed";
143 |
144 | # echo "" | zenity --progress --text "Display test" --auto-close 2> /dev/null
145 | # if [ $? -eq 0 ]
146 | # then
147 | # chromium
148 | # else
149 | # echo "no display"
150 | # fi
151 |
152 | # tail -n10 ./logs/container.log
153 |
154 | # sleep 100
--------------------------------------------------------------------------------
/local_documents_selected.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVIDIA-AI-IOT/jetson-copilot/34309e2494ed109157b56f43bde65b3f0dadbef1/local_documents_selected.png
--------------------------------------------------------------------------------
/logs/README.md:
--------------------------------------------------------------------------------
1 | logs directories is mounted on container to store log files.
--------------------------------------------------------------------------------
/ollama_models/README.md:
--------------------------------------------------------------------------------
1 | `ollama_models` directories is for the ollama server in the container to store models.
--------------------------------------------------------------------------------
/setup_environment.sh:
--------------------------------------------------------------------------------
1 | #!/bin/bash
2 |
3 | ### Color logger function
4 |
5 | singal='\033[0;93m'
6 | clear='\033[0m'
7 |
8 | function log () {
9 | # check if message
10 | test -n "$1" || {
11 | echo;
12 | return;
13 | }
14 | printf "${singal}$1${clear}\n"
15 | }
16 |
17 | # set -x
18 |
19 | #############################################################
20 | ### L4T_VERSION retrieve logic
21 | ### Copied from https://github.com/dusty-nv/jetson-containers/blob/master/jetson_containers/l4t_version.sh
22 | ###vvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvvv###
23 |
24 | ARCH=$(uname -i)
25 | log "ARCH: $ARCH"
26 |
27 | if [ $ARCH = "aarch64" ]; then
28 | L4T_VERSION_STRING=$(head -n 1 /etc/nv_tegra_release)
29 |
30 | if [ -z "$L4T_VERSION_STRING" ]; then
31 | #echo "reading L4T version from \"dpkg-query --show nvidia-l4t-core\""
32 |
33 | L4T_VERSION_STRING=$(dpkg-query --showformat='${Version}' --show nvidia-l4t-core)
34 | L4T_VERSION_ARRAY=(${L4T_VERSION_STRING//./ })
35 |
36 | #echo ${L4T_VERSION_ARRAY[@]}
37 | #echo ${#L4T_VERSION_ARRAY[@]}
38 |
39 | L4T_RELEASE=${L4T_VERSION_ARRAY[0]}
40 | L4T_REVISION=${L4T_VERSION_ARRAY[1]}
41 | else
42 | #echo "reading L4T version from /etc/nv_tegra_release"
43 |
44 | L4T_RELEASE=$(echo $L4T_VERSION_STRING | cut -f 2 -d ' ' | grep -Po '(?<=R)[^;]+')
45 | L4T_REVISION=$(echo $L4T_VERSION_STRING | cut -f 2 -d ',' | grep -Po '(?<=REVISION: )[^;]+')
46 | fi
47 |
48 | L4T_REVISION_MAJOR=${L4T_REVISION:0:1}
49 | L4T_REVISION_MINOR=${L4T_REVISION:2:1}
50 |
51 | L4T_VERSION="$L4T_RELEASE.$L4T_REVISION"
52 |
53 | log "L4T_VERSION: $L4T_VERSION"
54 |
55 | elif [ $ARCH != "x86_64" ]; then
56 | log "unsupported architecture: $ARCH"
57 | exit 1
58 | fi
59 |
60 | ###^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^###
61 | ### L4T_VERSION retrieve logic done
62 | #############################################################
63 |
64 | ###
65 | ### Install Chromium if in Desktop/GUI environment (or forced)
66 | ###
67 |
68 | flag_install_chromium=false
69 |
70 | echo "" | zenity --progress --text "Display test" --auto-close 2> /dev/null
71 | if [ $? -eq 0 ]; then
72 | log "Invoked in GUI/Desktop environmnet." -c "bright_blue"
73 | flag_install_chromium=true
74 | else
75 | if [[ " $* " == *" --force-install-chromium "* ]]; then
76 | log "[WARN] Force install chromium specified" -c "yellow"
77 | flag_install_chromium=true
78 | fi
79 | log "[INFO] Not going to install Chromium as there is no display attached"
80 | fi
81 |
82 | if [ "$flag_install_chromium" = true ]; then
83 | if [ -x "$(command -v chromium)" ]; then
84 | log "[WARN] Chromium is already installed: $(chromium --version)" -c "yellow"
85 | else
86 | log "Installing Chromium app from Snap Store ..."
87 | sudo snap install chromium
88 | fi
89 | fi
90 |
91 | ###
92 | ### Docker install and setup
93 | ###
94 |
95 | flag_install_docker=false
96 | DOCKER_DAEMON_CONFIG="/etc/docker/daemon.json"
97 |
98 | if [ -x "$(command -v docker)" ]; then
99 | log "[WARN] Docker is already installed: $(docker --version)"
100 | log "---- $DOCKER_DAEMON_CONFIG contents ----"
101 | cat $DOCKER_DAEMON_CONFIG
102 | log "\n------------------------------------------"
103 | if [[ " $* " == *" --force-install-docker "* ]]; then
104 | log "[WARN] Force (re)install docker specified"
105 | flag_install_docker=true
106 | ### Uninstall Docker Engine
107 | ### https://docs.docker.com/engine/install/debian/#uninstall-docker-engine
108 | log "[INFO] Uninstalling Docker Engine and related packages ..."
109 | sudo apt-get -y purge docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin docker-ce-rootless-extras
110 | fi
111 | else
112 | flag_install_docker=true
113 | fi
114 |
115 | if [ "$flag_install_docker" = true ]; then
116 | log "Installing Docker and setting up ..."
117 |
118 | sudo apt update
119 | log "Installing nvidia-container package ..."
120 | sudo apt install -y nvidia-container
121 |
122 | verions_numbers=(${L4T_VERSION//./ })
123 | L4T_VERSION_MAJOR=${verions_numbers[0]}
124 |
125 | if [ "$L4T_VERSION_MAJOR" == "35" ]; then
126 | log "JetPack 5.x :"
127 | elif [ "$L4T_VERSION_MAJOR" == "36" ]; then
128 | log "JetPack 6.x :"
129 | ## Starting from JetPack 6.0 DP, the `nvidia-container`` package stop automatically installing Docker.
130 | ## Following the official Docker installation flow.
131 | sudo apt install -y curl
132 | log "Installing Docker Engine ..."
133 | curl https://get.docker.com | sh && sudo systemctl --now enable docker
134 | sudo nvidia-ctk runtime configure --runtime=docker
135 | else
136 | log "[ERROR] unsupported architecture: $ARCH"
137 | exit 1
138 | fi
139 |
140 | # Restart the Docker service and add your user to the docker group
141 | sudo systemctl restart docker
142 | sudo usermod -aG docker $USER
143 | #newgrp docker
144 |
145 | # Insert the `default-runtime` line
146 | if grep -q "\"default-runtime\": \"nvidia\"" "$DOCKER_DAEMON_CONFIG"; then
147 | log "[INFO] Defulat-runtime nvidia is already added"
148 | else
149 | log "---- $DOCKER_DAEMON_CONFIG contents (before) ----"
150 | cat $DOCKER_DAEMON_CONFIG
151 | log "\n-------------------------------------------------"
152 | sudo sed 's|^{|{\n "default-runtime": "nvidia",|' -i /etc/docker/daemon.json
153 | log "---- $DOCKER_DAEMON_CONFIG contents (after) ----"
154 | cat $DOCKER_DAEMON_CONFIG
155 | log "\n-------------------------------------------------"
156 | fi
157 |
158 | # Restart Docker
159 | sudo systemctl daemon-reload && sudo systemctl restart docker
160 | fi
161 |
162 | if id -nG "$USER" | grep -qw docker; then
163 | log "[INFO] User '$USER' is already in 'docker' group."
164 | else
165 | log "[WARN] User '$USER' is not in 'docker' group. Going to register in the group."
166 |
167 | # Execute newgrp command at last as it resets the bash session
168 | log "[WARN] newgrp command is executed, and your bash session is reset."
169 | newgrp docker
170 | fi
--------------------------------------------------------------------------------
/streamlit_app/.streamlit/config.toml:
--------------------------------------------------------------------------------
1 | [client]
2 | showSidebarNavigation = false
3 |
4 | [server]
5 | enableStaticServing = false
6 |
7 | [theme]
8 | primaryColor="#76B900"
9 | backgroundColor="#FFFFFF"
10 | secondaryBackgroundColor="#EFEFEF"
11 | textColor="#141309"
12 | font="sans serif"
--------------------------------------------------------------------------------
/streamlit_app/app.py:
--------------------------------------------------------------------------------
1 | import ollama
2 | import openai
3 | import streamlit as st
4 |
5 | from llama_index.core import VectorStoreIndex, Settings, SimpleDirectoryReader
6 | from llama_index.core import load_index_from_storage, StorageContext
7 | from llama_index.core.storage.docstore import SimpleDocumentStore
8 | from llama_index.core.vector_stores import SimpleVectorStore
9 | from llama_index.core.storage.index_store import SimpleIndexStore
10 | from llama_index.llms.ollama import Ollama
11 | from llama_index.core.memory import ChatMemoryBuffer
12 | from llama_index.embeddings.ollama import OllamaEmbedding
13 | from llama_index.embeddings.openai import OpenAIEmbedding
14 | from PIL import Image
15 | import time
16 |
17 | import logging
18 | import sys
19 | logging.basicConfig(stream=sys.stdout, level=logging.INFO)
20 | # logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
21 |
22 | import utils.func
23 | import utils.constants as const
24 |
25 | # App title
26 | st.set_page_config(page_title="Jetson Copilot", menu_items=None)
27 |
28 | AVATAR_AI = Image.open('./images/jetson-soc.png')
29 | AVATAR_USER = Image.open('./images/user-purple.png')
30 |
31 | def find_saved_indexes():
32 | return utils.func.list_directories(const.INDEX_ROOT_PATH)
33 |
34 | def load_index(index_name):
35 | Settings.embed_model = OllamaEmbedding("mxbai-embed-large:latest") ##TODO
36 | dir = f"{const.INDEX_ROOT_PATH}/{index_name}"
37 | storage_context = StorageContext.from_defaults(persist_dir=dir)
38 | index = load_index_from_storage(storage_context)
39 | return index
40 |
41 |
42 | models = [model["name"] for model in ollama.list()["models"]]
43 |
44 | if 'llama3:latest' not in models:
45 | with st.spinner('Downloaing llama3 model ...'):
46 | ollama.pull('llama3')
47 | logging.info(" ### Downloaing llama3 completed.")
48 |
49 | if 'mxbai-embed-large:latest' not in models:
50 | with st.spinner('Downloaing mxbai-embed-large model ...'):
51 | ollama.pull('mxbai-embed-large')
52 | logging.info(" ### Downloaing mxbai-embed-large completed.")
53 |
54 | old_index_name = ''
55 | # Side bar
56 | with st.sidebar:
57 | # # Add css to make text smaller
58 | # st.markdown(
59 | # """""",
60 | # unsafe_allow_html=True,
61 | # )
62 | st.title(":airplane: Jetson Copilot")
63 | st.subheader('Your local AI assistant on Jetson', divider='rainbow')
64 |
65 | models = [model["name"] for model in ollama.list()["models"]]
66 | col3, col4 = st.columns([5,1])
67 | with col3:
68 | st.session_state["model"] = st.selectbox("Choose your LLM", models, index=models.index("llama3:latest"))
69 | logging.info(f"> st.session_state[\"model\"] = {st.session_state.model}")
70 | with col4:
71 | st.markdown('')
72 | # st.button('➕', key='btn_add_llm')
73 | st.page_link("pages/download_model.py", label=" Download a new LLM", icon="➕")
74 | Settings.llm = Ollama(model=st.session_state["model"], request_timeout=300.0)
75 |
76 | use_index = st.toggle("Use RAG", value=False)
77 | if use_index:
78 | # col1, col2 = st.columns([5,1], vertical_alignment="bottom") ### https://github.com/streamlit/streamlit/issues/3052
79 | col1, col2 = st.columns([5,1])
80 | saved_index_list = find_saved_indexes()
81 | with col1:
82 | index = next((i for i, item in enumerate(saved_index_list) if item.startswith('_')), None)
83 | index_name = st.selectbox("Index", saved_index_list, index)
84 | logging.info(f"> index_name = {index_name}")
85 | with col2:
86 | st.markdown('')
87 | # st.link_button('➕', url='pages/build_index.py')
88 | if old_index_name != index_name:
89 | old_index_name = index_name
90 | logging.info(f"> old_index_name = {old_index_name}")
91 | if index_name != None:
92 | with st.spinner('Loading Index...'):
93 | st.session_state.index = load_index(index_name)
94 | logging.info(f" ### Loading Index '{index_name}' completed.")
95 | st.page_link("pages/build_index.py", label=" Build a new index", icon="➕")
96 |
97 | if index_name != None:
98 | context_prompt = st.text_area("System prompt with context",
99 | """You are a chatbot, able to have normal interactions, as well as talk about NVIDIA Jetson embedded AI computer.
100 | Here are the relevant documents for the context:\n
101 | {context_str}
102 | \nInstruction: Use the previous chat history, or the context above, to interact and help the user.""", height=240)
103 | logging.info(f"> context_prompt = {context_prompt}")
104 |
105 | # init models
106 | st.session_state.chat_engine = st.session_state.index.as_chat_engine(
107 | chat_mode="context",
108 | streaming=True,
109 | memory=ChatMemoryBuffer.from_defaults(token_limit=4096),
110 | llm=Settings.llm,
111 | context_prompt=(context_prompt),
112 | verbose=True)
113 |
114 | # initialize history
115 | if "messages" not in st.session_state.keys():
116 | st.session_state.messages = [
117 | {"role": "assistant", "content": "Ask me any question about NVIDIA Jetson embedded AI computer!", "avatar": AVATAR_AI}
118 | ]
119 |
120 | def model_res_generator(prompt=""):
121 | if use_index:
122 | logging.info(f">>> RAG enabled:")
123 | response_stream = st.session_state.chat_engine.stream_chat(prompt)
124 | for chunk in response_stream.response_gen:
125 | yield chunk
126 | else:
127 | logging.info(f">>> Just LLM (no RAG):")
128 | messages_only_role_and_content = [{"role": message["role"], "content": message["content"]} for message in st.session_state.messages]
129 |
130 | stream = ollama.chat(
131 | model=st.session_state["model"],
132 | messages=messages_only_role_and_content,
133 | stream=True,
134 | )
135 | for chunk in stream:
136 | yield chunk["message"]["content"]
137 |
138 | # Display chat messages from history on app rerun
139 | for message in st.session_state.messages:
140 | with st.chat_message(message["role"], avatar=message["avatar"]):
141 | st.markdown(message["content"])
142 |
143 | if prompt := st.chat_input("Enter prompt here.."):
144 | # add latest message to history in format {role, content}
145 | st.session_state.messages.append({"role": "user", "content": prompt, "avatar": AVATAR_USER})
146 |
147 | with st.chat_message("user", avatar=AVATAR_USER):
148 | st.markdown(prompt)
149 |
150 | with st.chat_message("assistant", avatar=AVATAR_AI):
151 | with st.spinner("Thinking..."):
152 | time.sleep(1)
153 | message = st.write_stream(model_res_generator(prompt))
154 | st.session_state.messages.append({"role": "assistant", "content": message, "avatar": AVATAR_AI})
155 |
--------------------------------------------------------------------------------
/streamlit_app/images/jetson-soc.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVIDIA-AI-IOT/jetson-copilot/34309e2494ed109157b56f43bde65b3f0dadbef1/streamlit_app/images/jetson-soc.png
--------------------------------------------------------------------------------
/streamlit_app/images/user-purple.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVIDIA-AI-IOT/jetson-copilot/34309e2494ed109157b56f43bde65b3f0dadbef1/streamlit_app/images/user-purple.png
--------------------------------------------------------------------------------
/streamlit_app/pages/build_index.py:
--------------------------------------------------------------------------------
1 | import ollama
2 | import openai
3 | import streamlit as st
4 | import pandas as pd
5 |
6 | from llama_index.core import VectorStoreIndex, Settings, SimpleDirectoryReader
7 | from llama_index.llms.ollama import Ollama
8 | from llama_index.core.memory import ChatMemoryBuffer
9 | from llama_index.embeddings.ollama import OllamaEmbedding
10 | from llama_index.embeddings.openai import OpenAIEmbedding
11 | from llama_index.core import SummaryIndex
12 | from llama_index.readers.web import SimpleWebPageReader
13 | from llama_index.core.readers.base import BaseReader
14 | from llama_index.core import Document
15 | from typing import Dict, Type
16 |
17 | from PIL import Image
18 | import time
19 | import os
20 |
21 | import logging
22 | import sys
23 | logging.basicConfig(stream=sys.stdout, level=logging.INFO)
24 | # logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
25 |
26 | parent_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
27 | sys.path.insert(0, parent_dir)
28 | import utils.func
29 | import utils.constants as const
30 |
31 | class ExcelReader(BaseReader):
32 | def load_data(self, file_path: str, extra_info: dict = None):
33 | data = pd.read_excel(file_path).to_string()
34 | return [Document(text=data, metadata=extra_info)]
35 |
36 | DEFAULT_FILE_READER_CLS: Dict[str, Type[BaseReader]] = {
37 | ".xlsx": ExcelReader,
38 | ".xls": ExcelReader,
39 | }
40 |
41 | def on_settings_change():
42 | logging.info(" --- settings updated ---")
43 |
44 | def on_local_model_change():
45 | Settings.embed_model = OllamaEmbedding(model_name=st.session_state.my_local_model)
46 | logging.info(f" --- Settings.embed_model=OllamaEmbedding(model_name={st.session_state.my_local_model}) ---")
47 |
48 | def on_openai_model_change():
49 | Settings.embed_model = OpenAIEmbedding(model_name=st.session_state.my_openai_model, dimensions=1024)
50 | logging.info(f" --- Settings.embed_model=OpenAIEmbedding(model_name={st.session_state.my_openai_model}) ---")
51 |
52 | def on_indexname_change():
53 | name = st.session_state.my_indexname
54 | name = utils.func.make_valid_directory_name(name)
55 | if os.path.exists(os.path.join(const.INDEX_ROOT_PATH, name)):
56 | with container_name:
57 | st.error('The title name is not valid', icon="🚨")
58 | else:
59 | st.session_state.index_path_to_be_created = f"{const.INDEX_ROOT_PATH}/{name}"
60 | st.session_state.index_name = f"{name}"
61 | with container_name:
62 | st.markdown(f"`{st.session_state.index_path_to_be_created}` will be created")
63 |
64 | def on_docspath_change():
65 | logging.info("### on_docspath_change")
66 | st.session_state['docpath_untouched'] = False
67 | dir = st.session_state.docspath
68 | with container_docs:
69 | with st.spinner('Checking files under the directory...'):
70 | files = utils.func.get_files_with_extensions(dir, const.SUPPORTED_FILE_TYPES)
71 | total_docs_size = utils.func.get_total_size_mib(dir)
72 | md = f"**`{len(files)}`** files found! (Total file size: **`{total_docs_size:,.2f}`** MiB)"
73 | logging.info(f"{len(files)} files found!")
74 | df = pd.DataFrame(files, columns=['Filename', 'Size (KiB)'])
75 | st.markdown(md)
76 | st.session_state.num_of_files_to_read = len(files)
77 | if len(files) != 0:
78 | st.dataframe(df.style.format({'Size (KiB)' : "{:,.1f}"}))
79 |
80 | def on_urllist_change():
81 | urls = st.session_state.my_urllist
82 | if utils.func.check_urls(urls):
83 | st.session_state.num_of_urls_to_read = utils.func.count_urls(urls)
84 | with container_urls:
85 | st.success(f"{utils.func.count_urls(urls)} URLs supplied.", icon="✅")
86 | st.session_state.urllist = utils.func.extract_urllist(urls)
87 | else:
88 | st.session_state.num_of_urls_to_read = 0
89 | with container_urls:
90 | st.error("Invalid URL(s) contained.", icon="🚨")
91 | st.session_state.ready_to_index = False
92 |
93 | def check_if_ready_to_index():
94 | logging.info("### check_if_ready_to_index()")
95 | if hasattr(st.session_state, "index_path_to_be_created"):
96 | is_name_ready = len(st.session_state.index_path_to_be_created)
97 | else:
98 | is_name_ready = False
99 | logging.info(f"is_name_ready: {is_name_ready}")
100 | if hasattr(st.session_state, "num_of_files_to_read"):
101 | num_of_files = st.session_state.num_of_files_to_read
102 | else:
103 | num_of_files = 0
104 | logging.info(f"num_of_files : {num_of_files}")
105 | if not hasattr(st.session_state, "num_of_urls_to_read"):
106 | st.session_state.num_of_urls_to_read = 0
107 | num_of_urls = st.session_state.num_of_urls_to_read
108 | logging.info(f"num_of_urls : {num_of_urls}")
109 | if is_name_ready and (num_of_files or num_of_urls):
110 | logging.info("### check_if_ready_to_index() ---> Ready")
111 | st.session_state.index_button_disabled = False
112 |
113 | # App title
114 | st.set_page_config(page_title="Jetson Copilot - Build Index", menu_items=None)
115 |
116 | ### Building Index with Embedding Model
117 | def index_data():
118 | with container_status:
119 | start_time = time.time()
120 | with st.status("Indexing documents..."):
121 | logging.info(f"Setting Embedding model... {Settings.embed_model}")
122 | docs = []
123 | web_docs = []
124 | if st.session_state.num_of_files_to_read != 0:
125 | reader = SimpleDirectoryReader(input_dir=st.session_state.docspath, recursive=True)
126 | st.write( "Loading local documents...")
127 | logging.info("Loading local documents...")
128 | docs = reader.load_data()
129 | st.write( f"{len(docs)} local documents loaded.")
130 | logging.info(f"{len(docs)} local documents loaded.")
131 | st.write( "Building Index from local docs (using GPU)...")
132 | logging.info("Building Index from local docs (using GPU)...")
133 | index = VectorStoreIndex.from_documents(docs)
134 | if st.session_state.num_of_urls_to_read != 0:
135 | st.write( "Loading web documents...")
136 | logging.info("Loading web documents...")
137 | web_docs = SimpleWebPageReader(html_to_text=True).load_data(st.session_state.urllist)
138 | st.write( f"{len(web_docs)} web documents loaded.")
139 | logging.info(f"{len(web_docs)} web documents loaded.")
140 | logging.info(f"len(web_docs): {len(web_docs)}")
141 | logging.info(f"web_docs[0] : {web_docs[0]}")
142 | st.write( "Building Index from web docs (using GPU)...")
143 | logging.info("Building Index from web docs (using GPU)...")
144 | if 'index' not in locals():
145 | index = VectorStoreIndex.from_documents(web_docs)
146 | else:
147 | for d in web_docs:
148 | index.insert(document = d)
149 | st.write( "Saving the built index to disk...")
150 | logging.info("Saving the built index to disk...")
151 | index.storage_context.persist(persist_dir=st.session_state.index_path_to_be_created)
152 | st.write( "Indexing done!")
153 | logging.info("Indexing done!")
154 | end_time = time.time()
155 | elapsed_time = end_time - start_time
156 |
157 | total_size_mib = utils.func.get_total_size_mib(st.session_state.index_path_to_be_created)
158 |
159 | md = f"""
160 | Index named **"{st.session_state.index_name}"** was built from **`{len(docs)}` local** documents and **`{len(web_docs)}` online** documents!
161 |
162 | The index is saved under `{st.session_state.index_path_to_be_created}` and the total size of this index is **`{total_size_mib:.2f}`** MiB.
163 |
164 | The indexing task took **`{elapsed_time:.1f}`** seconds to complete.
165 | """
166 |
167 | with container_result:
168 | st.markdown(md)
169 | logging.info(md)
170 |
171 | # Side bar
172 | with st.sidebar:
173 | st.title("Building Index")
174 | st.info('Build your own custom Index based on your local/online documents.')
175 |
176 | st.subheader("Embedding Model")
177 | t1,t2 = st.tabs(['Local','OpenAI'])
178 | with t1:
179 | models = [model["name"] for model in ollama.list()["models"]]
180 | st.selectbox("Choose local embedding model", models, index=models.index("mxbai-embed-large:latest"), key='my_local_model', on_change=on_local_model_change)
181 | with t2:
182 | openai.api_key = st.text_input("OpenAI API Key", key="chatbot_api_key", type="password")
183 | os.environ["OPENAI_API_KEY"] = openai.api_key
184 | logging.info(f"> openai.api_key = {openai.api_key}")
185 | st.selectbox("Choose OpenAI embedding model", ["-- Choose from below --", "text-embedding-3-large", "text-embedding-3-small", "text-embedding-ada-002"], index=0, key='my_openai_model', on_change=on_openai_model_change)
186 | use_customized_chunk = st.toggle("Customize chunk parameters", value=False)
187 | if use_customized_chunk:
188 | Settings.chunk_size = st.slider("Chunk size", 100, 5000, 1024, key='my_chunk_size', on_change=on_settings_change)
189 | Settings.chunk_overlap = st.slider("Chunk overlap", 10, 500, 50, key='my_chunk_overlap', on_change=on_settings_change)
190 | logging.info(f"> Settings.chunk_size = {Settings.chunk_size}")
191 | logging.info(f"> Settings.chunk_overlap = {Settings.chunk_overlap}")
192 |
193 | st.subheader("Index Name")
194 | index_name = st.text_input("Enter the name for your new index", key='my_indexname', on_change=on_indexname_change)
195 | container_name = st.container()
196 |
197 | st.subheader('Local documents')
198 | subdirs = utils.func.get_subdirectories(const.DOC_ROOT_PATH)
199 | st.selectbox("Select the path to the local directory that you had stored your documents", subdirs, key='docspath', on_change=on_docspath_change)
200 | container_docs = st.container()
201 | if 'docpath_untouched' not in st.session_state:
202 | st.session_state['docpath_untouched'] = True
203 | st.session_state.num_of_files_to_read = 0
204 | if len(subdirs) != 0 and st.session_state['docpath_untouched']:
205 | logging.info(f"################ st.session_state['docpath_untouched']: {st.session_state['docpath_untouched']}")
206 | on_docspath_change()
207 |
208 | st.subheader('Online documents')
209 | list_urls = st.text_area("List of URLs (one per a line)", key='my_urllist', on_change=on_urllist_change)
210 | container_urls = st.container()
211 |
212 | st.warning("Check the model and its configurations on the sidebar (⬅️) and then hit the button below to build a new Index.", icon="⚠️")
213 |
214 | container_settings = st.container()
215 |
216 | check_if_ready_to_index()
217 | logging.info(f"Setting Embedding model... {Settings.embed_model}")
218 |
219 | st.button("Build Index", on_click=index_data, key='my_button', disabled=st.session_state.get("index_button_disabled", True))
220 | container_status = st.container()
221 | container_result = st.container()
222 |
223 | st.page_link("app.py", label="Back to home", icon="🏠")
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/streamlit_app/pages/download_model.py:
--------------------------------------------------------------------------------
1 | import ollama
2 | import streamlit as st
3 | import pandas as pd
4 |
5 | import time
6 | import os
7 |
8 | import logging
9 | import sys
10 | logging.basicConfig(stream=sys.stdout, level=logging.INFO)
11 | # logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
12 |
13 | parent_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
14 | sys.path.insert(0, parent_dir)
15 | import utils.func
16 | import utils.constants as const
17 |
18 | # App title
19 | st.set_page_config(page_title="Jetson Copilot - Download Model", menu_items=None)
20 |
21 | st.subheader("List of Models Already Downloaded")
22 | with st.spinner('Checking existing models hosted on Ollama...'):
23 | models = ollama.list()["models"]
24 | models_data = []
25 | for model in models:
26 | models_data.append((
27 | model['name'],
28 | model['size'] / 1024 / 1024,
29 | model['details']['format'],
30 | model['details']['family'],
31 | model['details']['parameter_size'],
32 | model['details']['quantization_level']
33 | ))
34 | logging.info(f"{len(models)} models found!")
35 | df = pd.DataFrame(models_data, columns=[
36 | 'Name', 'Size(MiB)', 'Format', 'Family', 'Parameter', 'Quantization'
37 | ])
38 | if len(models) != 0:
39 | st.dataframe(df.style.format({'Size(MiB)' : "{:,.1f}"}))
40 |
41 | def on_newmodel_name_change():
42 | logging.info("on_newmodel_name_change()")
43 | newmodel_name = st.session_state.my_newmodel_name
44 | if newmodel_name.strip():
45 | logging.info("Name supplied")
46 | st.session_state.download_model_disabled = False
47 | else:
48 | logging.info("Name NOT supplied")
49 | st.session_state.download_model_disabled = True
50 |
51 | def download_model():
52 | logging.info("download_model()")
53 | newmodel_name = st.session_state.my_newmodel_name
54 | with container_status:
55 | start_time = time.time()
56 | my_bar = st.progress(0, text="progress text")
57 | try:
58 | for res in ollama.pull(newmodel_name, stream=True):
59 | logging.info(res)
60 | if 'total' in res and 'completed' in res:
61 | total = res['total']
62 | completed = res['completed']
63 | total_in_mib = total / 1024 / 1024
64 | completed_in_mib = completed / 1024 / 1024
65 | percent = completed / total
66 | my_bar.progress(percent, text=f"Downloading ({completed_in_mib:.1f} MiB / {total_in_mib:.1f} MiB)")
67 | else:
68 | my_bar.progress(100, text=f"{res['status']}")
69 | except ollama.ResponseError as e:
70 | # Handle ResponseError specifically
71 | logging.error(f"A ResponseError occurred: {e}")
72 | st.error(f"It looks like \"**`{newmodel_name}`**\" is not the right name.", icon="🚨")
73 | # You might want to log the error or retry the operation
74 | except Exception as e:
75 | # Handle any other exceptions
76 | logging.error(f"An unexpected error occurred: {e}")
77 | st.error(f"Some other error happend : {e}", icon="🚨")
78 |
79 | st.subheader("Download a New Model")
80 | # st.markdown("⚠ Check the model name on [Ollama Library](https://ollama.com/library) page.")
81 | st.info("Check the model name on [Ollama Library](https://ollama.com/library) page.", icon=":material/info:")
82 |
83 | model_name = st.text_input(
84 | "Name of model to download",
85 | key='my_newmodel_name',
86 | on_change=on_newmodel_name_change
87 | )
88 | st.button(
89 | "Download Model",
90 | key='my_button',
91 | on_click=download_model,
92 | disabled=st.session_state.get("download_model_disabled", True)
93 | )
94 | container_status = st.container()
95 |
96 | st.page_link("app.py", label="Back to home", icon="🏠")
--------------------------------------------------------------------------------
/streamlit_app/utils/__init__.py:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVIDIA-AI-IOT/jetson-copilot/34309e2494ed109157b56f43bde65b3f0dadbef1/streamlit_app/utils/__init__.py
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/streamlit_app/utils/constants.py:
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1 | # constants.py
2 |
3 | DOC_ROOT_PATH = '/opt/jetson_copilot/Documents'
4 | INDEX_ROOT_PATH = '/opt/jetson_copilot/Indexes'
5 |
6 | SUPPORTED_FILE_TYPES = ['txt', 'csv', 'docx', 'epub', 'hwp', 'ipynb',
7 | 'jpeg', 'jpg', 'mbox', 'md', 'mp3',
8 | 'mp4', 'pdf', 'png', 'ppt', 'pptm', 'pptx',
9 | 'xlsx', 'xls',
10 | ]
--------------------------------------------------------------------------------
/streamlit_app/utils/func.py:
--------------------------------------------------------------------------------
1 | import os
2 | import re
3 | from urllib.parse import urlparse
4 |
5 | import logging
6 | import sys
7 | logging.basicConfig(stream=sys.stdout, level=logging.INFO)
8 | # logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
9 |
10 |
11 |
12 | ### Below for app.py
13 |
14 | def list_directories(directory):
15 | """
16 | List all directories under the given directory.
17 |
18 | Parameters:
19 | directory (str): The path to the directory.
20 |
21 | Returns:
22 | list: A list of directory names under the given directory.
23 | """
24 | try:
25 | # Get a list of all entries in the directory
26 | entries = os.listdir(directory)
27 |
28 | # Filter out the directories
29 | directories = [entry for entry in entries if os.path.isdir(os.path.join(directory, entry))]
30 |
31 | return directories
32 | except Exception as e:
33 | print(f"An error occurred: {e}")
34 | return []
35 |
36 |
37 | ### Below for build_index.py
38 |
39 | def make_valid_directory_name(name):
40 | """
41 | Sanitize a given name to be a valid Linux directory name.
42 |
43 | Parameters:
44 | name (str): The name to be sanitized.
45 |
46 | Returns:
47 | str: A valid Linux directory name.
48 | """
49 | # Define a pattern for invalid characters
50 | invalid_chars = re.compile(r'[<>:"/\\|?*]')
51 |
52 | # Replace invalid characters with an underscore
53 | sanitized_name = invalid_chars.sub('_', name)
54 |
55 | # Trim whitespace from the start and end of the name
56 | sanitized_name = sanitized_name.strip()
57 |
58 | # Replace multiple consecutive whitespace characters with a single underscore
59 | sanitized_name = re.sub(r'\s+', '_', sanitized_name)
60 |
61 | # Ensure the name is not empty
62 | if not sanitized_name:
63 | sanitized_name = 'default_directory'
64 |
65 | # Ensure the name does not start with a hyphen
66 | if sanitized_name.startswith('-'):
67 | sanitized_name = '_' + sanitized_name[1:]
68 |
69 | return sanitized_name
70 |
71 | def is_valid_url(url):
72 | """
73 | Check if a given URL is valid.
74 |
75 | Parameters:
76 | url (str): The URL to check.
77 |
78 | Returns:
79 | bool: True if the URL is valid, False otherwise.
80 | """
81 | # Regular expression for validating a URL
82 | regex = re.compile(
83 | r'^(https?://)?' # http:// or https://
84 | r'(([a-zA-Z0-9_\-]+\.)+[a-zA-Z]{2,6})' # domain name
85 | r'(:[0-9]{1,5})?' # optional port
86 | r'(/.*)?$', re.IGNORECASE) # resource path
87 |
88 | if re.match(regex, url):
89 | parsed_url = urlparse(url)
90 | return all([parsed_url.scheme, parsed_url.netloc])
91 | return False
92 |
93 | def check_urls(text):
94 | """
95 | Check if all URLs in a given multiline text are valid.
96 |
97 | Parameters:
98 | text (str): The multiline text containing URLs.
99 |
100 | Returns:
101 | bool: True if all URLs are valid, False otherwise.
102 | """
103 | # Split the text into lines
104 | lines = text.strip().split('\n')
105 |
106 | # Check each line to see if it is a valid URL
107 | for line in lines:
108 | url = line.strip()
109 | logging.info(f"> url: {url}")
110 | if not is_valid_url(url):
111 | logging.warn(f"!!!!!! Invalid URL: {url}")
112 | return False
113 | return True
114 |
115 | def count_urls(text):
116 | """
117 | Count the number of URLs in a given multiline text.
118 |
119 | Parameters:
120 | text (str): The multiline text containing URLs.
121 |
122 | Returns:
123 | int: The number of URLs found in the text.
124 | """
125 | logging.info(f">>> count_urls('{text}')")
126 |
127 | # Regular expression to matchf URLs
128 | url_pattern = re.compile(
129 | r'https?://' # http:// or https://
130 | r'(\w+\.)+' # Domain name prefix
131 | r'[a-z]{2,6}' # Domain name suffix
132 | r'(:[0-9]{1,5})?' # Optional port
133 | r'(/[^\s]*)?', re.IGNORECASE) # Optional path
134 |
135 | # Find all matches in the text
136 | urls = url_pattern.findall(text)
137 |
138 | # Return the number of URLs found
139 | return len(urls)
140 |
141 | def get_subdirectories(directory):
142 | subdirs = []
143 | # Walk through the directory tree
144 | for root, dirs, files in os.walk(directory):
145 | for dir_name in dirs:
146 | # Join the root with the directory name to get the full path
147 | full_path = os.path.join(root, dir_name)
148 | subdirs.append(full_path)
149 | # subdirs.append(full_path.replace(directory, "Documents"))
150 | return subdirs
151 |
152 | def get_files_with_extensions(directory, extensions):
153 | # Ensure extensions are in lowercase
154 | extensions = [ext.lower() for ext in extensions]
155 |
156 | files_data = []
157 | # Walk through the directory
158 | for root, dirs, files in os.walk(directory):
159 | for file in files:
160 | # Check if the file ends with any of the specified extensions
161 | if any(file.lower().endswith(f'.{ext}') for ext in extensions):
162 | # Add the full path of the matching file to the list
163 | file_path = os.path.join(root, file)
164 | file_size = os.path.getsize(file_path) / 1024 # Get file size in KiB
165 | files_data.append((file_path.replace(directory,""), file_size))
166 | return files_data
167 |
168 | def get_total_size_mib(directory):
169 | """
170 | Calculate the total size of all files in the given directory in MiB.
171 |
172 | Parameters:
173 | directory (str): The path to the directory.
174 |
175 | Returns:
176 | float: The total size of all files in MiB.
177 | """
178 | total_size_bytes = 0
179 |
180 | # Walk through the directory
181 | for dirpath, dirnames, filenames in os.walk(directory):
182 | for filename in filenames:
183 | # Get the full file path
184 | file_path = os.path.join(dirpath, filename)
185 |
186 | # Check if it's a file (not a directory)
187 | if os.path.isfile(file_path):
188 | # Add the file size to the total size
189 | total_size_bytes += os.path.getsize(file_path)
190 |
191 | # Convert bytes to MiB
192 | total_size_mib = total_size_bytes / (1024 ** 2)
193 |
194 | return total_size_mib
195 |
196 | def extract_urllist(multiline_text):
197 | """
198 | Convert a multiline text that contains a URL per line into a list of URLs.
199 |
200 | Parameters:
201 | multiline_text (str): The input multiline text.
202 |
203 | Returns:
204 | list: A list of URL strings.
205 | """
206 | # Split the multiline text into individual lines
207 | lines = multiline_text.strip().split('\n')
208 |
209 | # Remove any leading/trailing whitespace from each line
210 | urllist = [line.strip() for line in lines if line.strip()]
211 |
212 | return urllist
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