From 57c12066f393ba58dae0ba86a8c0a906b53a561b Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein Date: Tue, 2 Jul 2024 17:16:15 -0700 Subject: [PATCH 01/11] Adds LM Studio connector guide --- .../assistant/connect-to-byo-llm.mdx | 153 ++++++++++++++++++ .../images/lms-custom-logs-config.png | Bin 0 -> 298875 bytes .../images/lms-studio-arch-diagram.png | Bin 0 -> 134838 bytes .../images/lms-studio-model-loaded-msg.png | Bin 0 -> 151635 bytes .../assistant/llm-connector-guides.mdx | 1 + .../serverless-security.docnav.json | 3 + 6 files changed, 157 insertions(+) create mode 100644 docs/serverless/assistant/connect-to-byo-llm.mdx create mode 100644 docs/serverless/assistant/images/lms-custom-logs-config.png create mode 100644 docs/serverless/assistant/images/lms-studio-arch-diagram.png create mode 100644 docs/serverless/assistant/images/lms-studio-model-loaded-msg.png diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx new file mode 100644 index 0000000000..b7575523f4 --- /dev/null +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -0,0 +1,153 @@ +--- +slug: /serverless/security/connect-to-byo-llm +title: Connect to your own local LLM +description: Set up a connector to LM Studio so you can use a local model with AI Assistant. +tags: ["security", "overview", "get-started"] +status: in review +--- + +This page provides instructions for setting up a connector to a large language model (LLM) of your choice using LM Studio. This allows you to use your chosen model within ((elastic-sec)). You'll first need to set up LM Studio on a server, set up a reverse proxy to communicate with ((elastic-sec)), and finally configure the connector in your ((elastic-sec)) project. [Learn more about the benefits of using a local LLM](https://www.elastic.co/blog/ai-assistant-locally-hosted-models). + +This example uses a server hosted in GCP to run: +- LM Studio with the [Mixtral-8x7b](https://mistral.ai/technology/#models) model +- a reverse proxy using Nginx to authenticate to Elastic Cloud + + + + + +For testing, you can use alternatives to Nginx such as Azure Dev Tunnels or Ngrock, but using Nginx makes it easy to collect additional telemetry and monitor its status by using Elastic's native Nginx integration. While this example uses cloud infrastructure, it could also be replicated locally without an internet connection. + + +## Configure your reverse proxy + + +If your Elastic instance is on the same host as LM Studio, you can skip this step. + + +You need to set up a reverse proxy to enable communication between LM Studio and ((elastic-sec)). For more complete instructions, refer to a guide such as [this one](https://www.digitalocean.com/community/tutorials/how-to-configure-nginx-as-a-reverse-proxy-on-ubuntu-22-04). + +The following is an example Nginx configuration file: +``` +server { + listen 80; + listen [::]:80; + server_name yourdomainname.com; + server_tokens off; + add_header x-xss-protection "1; mode=block" always; + add_header x-frame-options "SAMEORIGIN" always; + add_header X-Content-Type-Options "nosniff" always; + return 301 https://$server_name$request_uri; +} + +server { + + listen 443 ssl http2; + listen [::]:443 ssl http2; + server_name yourdomainname.com; + server_tokens off; + ssl_certificate /etc/letsencrypt/live/yourdomainname.com/fullchain.pem; + ssl_certificate_key /etc/letsencrypt/live/yourdomainname.com/privkey.pem; + ssl_session_timeout 1d; + ssl_session_cache shared:SSL:50m; + ssl_session_tickets on; + ssl_ciphers 'ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-CHACHA20-POLY1305:ECDHE-RSA-CHACHA20-POLY1305:ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256'; + ssl_protocols TLSv1.3 TLSv1.2; + ssl_prefer_server_ciphers on; + add_header Strict-Transport-Security "max-age=31536000; includeSubDomains; preload" always; + add_header x-xss-protection "1; mode=block" always; + add_header x-frame-options "SAMEORIGIN" always; + add_header X-Content-Type-Options "nosniff" always; + add_header Referrer-Policy "strict-origin-when-cross-origin" always; + ssl_stapling on; + ssl_stapling_verify on; + ssl_trusted_certificate /etc/letsencrypt/live/yourdomainname.com/fullchain.pem; + resolver 1.1.1.1; + location / { + + if ($http_authorization != "Bearer ") { + return 401; +} + + proxy_pass http://localhost:1234/; + } + +} +``` + + +Store the bearer `secret token`, you'll need it to set up the ((elastic-sec)) connector. + + +### (Optional) set up performance monitoring for your reverse proxy +You can use Elastic's [Nginx integration](https://www.elastic.co/docs/current/integrations/nginx) to monitor performance and populate monitoring dashboards in ((kib)). + +## Configure LM Studio and download a model + +LM Studio supports the OpenAI SDK, which means that any local model listed in its marketplace can be connected to ((elastic-sec)). + + +One current limitation is that for best results you must launch the LM Studio application using its GUI before doing so using the CLI. For example, you could use the GUI to launch the application using Chrome RDP with an [X Window System](https://cloud.google.com/architecture/chrome-desktop-remote-on-compute-engine). Using `sudo lms server start` in the CLI yielded inconsistent results. + + +Once you've launched LM Studio, select a model: + +1. Go to the Search section. +2. Search for an LLM (for example, `Mixtral-8x7B-instruct`). +3. Your chosen model must include `instruct` in its name. Models with this label are capable of carrying out tasks in ((elastic-sec)). +4. Filtering your search for "Compatibility Guess" will optimize results for your hardware. Results will be color coded (green for "Full GPU Possible" yields the best results, while blue may work but isn't optimal for your machine, and red is not likely to work). +5. For security reasons, before downloading your chosen model, verify that it is from a trusted source and review community feedback on the model (for example on a site like Hugging Face). +6. Download one or more models. + +In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF quanitization. For more information about model names and format information, refer to the following table: + +| Model Name | Parameter Size | Tokens/Context Window | Quantization Format | +|------------|----------------|-----------------------|---------------------| +| Name of model, sometimes with a version number. | LLMs are often compared by their number of parameters — higher numbers mean more powerful models. | Tokens are small chunks of input information. Characters do not necessarily correspond to tokens 1:1. You can use [Tokenizer](https://platform.openai.com/tokenizer) to see how many tokens a given prompt might contain. | Quantization reduces overall parameters and helps the model to run faster, but reduces accuracy. | +| Examples: Llama, Mistral, Phi-3, Falcon. | The number of parameters is a measure of the size and the complexity of the model. The more parameters a model has, the more data it can process, learn from, generate, and predict. | The context window defines how much information the model can process at once. If the number of input tokens exceeds this limit, input gets truncated. | Specific formats for quantization vary, most models now support GPU rather than CPU offloading. | + + +## Load a model in LM Studio + +After downloading a model, you'll need to load it in LM Studio using the GUI or LM Studio's [CLI tool](https://lmstudio.ai/blog/lms). You can do this either using the CLI, or the GUI. + +It is a best practice to use the GUI to download at least one model from the marketplace first, and then load/unload the model(s) using the CLI. The GUI allows you to search for models, whereas the CLI only allows you to import specific paths, but the CLI provides a good interface for loading/unloading. + +Use the following commands in your CLI: + +1. Verify LM Studio: `lms` +2. Check LM Studio's status: `lms status` +3. List all downloaded models: `lms ls` +4. Load a model: `lms load` + +After the model loads, you should see a `Model loaded successfully` message in the CLI: + + + +To verify which model is loaded, use the `lms ps` command. + +If your model uses NVIDIA drivers, you can check the GPU performance with the `sudo nvidia-smi` command. + +## (Optional) Collect logs using Elastic's Custom Logs integration + +You can monitor the performance of the host running LM Studio using Elastic's [Custom Logs integration](https://www.elastic.co/docs/current/integrations/log). This can also help with troubleshooting. Note that the default path for LM Studio logs is `/tmp/lmstudio-server-log.txt`, as in the following screenshot: + + + +## Configure the connector in ((elastic-sec)) + +Finally, configure the connector in ((kib)): + +1. Log in to ((kib)). +2. Navigate to **Stack Management → Connectors → Create Connector → OpenAI**. The OpenAI connector enables this use-case because LM Studio uses the OpenAI SDK. +3. Name your connector to help keep track of the model version you are using. +4. Under **URL**, enter the domain name specified in your Nginx configuration file. +5. Under **Default model**, enter `local-model`. +6. Under **API Key**, enter the secret token specified in your Nginx configuration file. +7. Click **Save**. + +Setup is now complete. You can use the model you've loaded in LM Studio to power ((elastic-sec)) features like AI Assistant. You can test a variety of models as you interact with AI Assistant to see what works best. + + +While local models work well for if you would like to interact with we recommend you use one of . 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This allows you to use your chosen model within ((elastic-sec)). You'll first need to set up LM Studio on a server, set up a reverse proxy to communicate with ((elastic-sec)), and finally configure the connector in your ((elastic-sec)) project. [Learn more about the benefits of using a local LLM](https://www.elastic.co/blog/ai-assistant-locally-hosted-models). -This example uses a server hosted in GCP to run: +This example uses a single server hosted in GCP to run the following components: - LM Studio with the [Mixtral-8x7b](https://mistral.ai/technology/#models) model -- a reverse proxy using Nginx to authenticate to Elastic Cloud +- A reverse proxy using Nginx to authenticate to Elastic Cloud -For testing, you can use alternatives to Nginx such as Azure Dev Tunnels or Ngrock, but using Nginx makes it easy to collect additional telemetry and monitor its status by using Elastic's native Nginx integration. While this example uses cloud infrastructure, it could also be replicated locally without an internet connection. +For testing, you can use alternatives to Nginx such as [Azure Dev Tunnels](https://learn.microsoft.com/en-us/azure/developer/dev-tunnels/overview) or [Ngrock](https://ngrok.com/), but using Nginx makes it easy to collect additional telemetry and monitor its status by using Elastic's native Nginx integration. While this example uses cloud infrastructure, it could also be replicated locally without an internet connection. ## Configure your reverse proxy @@ -25,14 +25,14 @@ For testing, you can use alternatives to Nginx such as Azure Dev Tunnels or Ngro If your Elastic instance is on the same host as LM Studio, you can skip this step. -You need to set up a reverse proxy to enable communication between LM Studio and ((elastic-sec)). For more complete instructions, refer to a guide such as [this one](https://www.digitalocean.com/community/tutorials/how-to-configure-nginx-as-a-reverse-proxy-on-ubuntu-22-04). +You need to set up a reverse proxy to enable communication between LM Studio and Elastic. For more complete instructions, refer to a guide such as [this one](https://www.digitalocean.com/community/tutorials/how-to-configure-nginx-as-a-reverse-proxy-on-ubuntu-22-04). The following is an example Nginx configuration file: ``` server { listen 80; listen [::]:80; - server_name yourdomainname.com; + server_name ; server_tokens off; add_header x-xss-protection "1; mode=block" always; add_header x-frame-options "SAMEORIGIN" always; @@ -44,10 +44,10 @@ server { listen 443 ssl http2; listen [::]:443 ssl http2; - server_name yourdomainname.com; + server_name ; server_tokens off; - ssl_certificate /etc/letsencrypt/live/yourdomainname.com/fullchain.pem; - ssl_certificate_key /etc/letsencrypt/live/yourdomainname.com/privkey.pem; + ssl_certificate /etc/letsencrypt/live//fullchain.pem; + ssl_certificate_key /etc/letsencrypt/live//privkey.pem; ssl_session_timeout 1d; ssl_session_cache shared:SSL:50m; ssl_session_tickets on; @@ -61,7 +61,7 @@ server { add_header Referrer-Policy "strict-origin-when-cross-origin" always; ssl_stapling on; ssl_stapling_verify on; - ssl_trusted_certificate /etc/letsencrypt/live/yourdomainname.com/fullchain.pem; + ssl_trusted_certificate /etc/letsencrypt/live//fullchain.pem; resolver 1.1.1.1; location / { @@ -76,7 +76,7 @@ server { ``` -Store the bearer `secret token`, you'll need it to set up the ((elastic-sec)) connector. +Replace `` with your actual token, and keep it safe since you'll need it to set up the ((elastic-sec)) connector. Replace `` with your actual domain name. If you decide to change the port number in LM studio to something other than 1234, update the `proxy_pass` value at the bottom of the configuration. ### (Optional) set up performance monitoring for your reverse proxy @@ -84,22 +84,26 @@ You can use Elastic's [Nginx integration](https://www.elastic.co/docs/current/in ## Configure LM Studio and download a model -LM Studio supports the OpenAI SDK, which means that any local model listed in its marketplace can be connected to ((elastic-sec)). +First, install LM Studio. LM Studio supports the OpenAI SDK, which makes it compatible with Elastic's OpenAI connector, so you can connect Elastic AI Assistant to any model available in the LM Studio marketplace. + +One current limitation of LM Studio is that when it is installed on a server, you must launch the application using its GUI before doing so using the CLI. For example, by using Chrome RDP with an [X Window System](https://cloud.google.com/architecture/chrome-desktop-remote-on-compute-engine). After you've opened the application the first time using the GUI, you can start it by using `sudo lms server start` in the CLI. + +Once you've launched LM Studio, select a model: -One current limitation is that for best results you must launch the LM Studio application using its GUI before doing so using the CLI. For example, you could use the GUI to launch the application using Chrome RDP with an [X Window System](https://cloud.google.com/architecture/chrome-desktop-remote-on-compute-engine). Using `sudo lms server start` in the CLI yielded inconsistent results. +For security reasons, before downloading a model, verify that it is from a trusted source. It can be helpful to review community feedback on the model (for example using a site like Hugging Face). -Once you've launched LM Studio, select a model: - -1. Go to the Search section. +1. Go to LM Studio's Search window. 2. Search for an LLM (for example, `Mixtral-8x7B-instruct`). -3. Your chosen model must include `instruct` in its name. Models with this label are capable of carrying out tasks in ((elastic-sec)). -4. Filtering your search for "Compatibility Guess" will optimize results for your hardware. Results will be color coded (green for "Full GPU Possible" yields the best results, while blue may work but isn't optimal for your machine, and red is not likely to work). -5. For security reasons, before downloading your chosen model, verify that it is from a trusted source and review community feedback on the model (for example on a site like Hugging Face). -6. Download one or more models. +3. Your chosen model must include `instruct` in its name in order to work with Elastic. +4. Filter your search for "Compatibility Guess" to optimize results for your hardware. Results will be color coded: +.. Green means "Full GPU Possible", which yields the best results. +.. Blue means "Partial GPU offload possible", which may work. +.. Red for "Likely too large for this machine", which typically will not work. +5. Download one or more models. -In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF quanitization. For more information about model names and format information, refer to the following table: +In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF [quanitization](https://huggingface.co/docs/transformers/main/en/quantization/overview). For more information about model names and format information, refer to the following table: | Model Name | Parameter Size | Tokens/Context Window | Quantization Format | |------------|----------------|-----------------------|---------------------| @@ -111,6 +115,8 @@ In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](http After downloading a model, you'll need to load it in LM Studio using the GUI or LM Studio's [CLI tool](https://lmstudio.ai/blog/lms). You can do this either using the CLI, or the GUI. +### Option 1: load a model using the CLI (Recommended) + It is a best practice to use the GUI to download at least one model from the marketplace first, and then load/unload the model(s) using the CLI. The GUI allows you to search for models, whereas the CLI only allows you to import specific paths, but the CLI provides a good interface for loading/unloading. Use the following commands in your CLI: @@ -120,14 +126,24 @@ Use the following commands in your CLI: 3. List all downloaded models: `lms ls` 4. Load a model: `lms load` + + After the model loads, you should see a `Model loaded successfully` message in the CLI: To verify which model is loaded, use the `lms ps` command. + + If your model uses NVIDIA drivers, you can check the GPU performance with the `sudo nvidia-smi` command. +### Option 2: load a model using the GUI + +Refer to the following video to see how to load a model using LM Studio's GUI. You can change the **port** setting, which is referenced in the Nginx configuration file. Note that the **GPU offload** was set to **Max**. + + + ## (Optional) Collect logs using Elastic's Custom Logs integration You can monitor the performance of the host running LM Studio using Elastic's [Custom Logs integration](https://www.elastic.co/docs/current/integrations/log). This can also help with troubleshooting. Note that the default path for LM Studio logs is `/tmp/lmstudio-server-log.txt`, as in the following screenshot: @@ -141,12 +157,14 @@ Finally, configure the connector in ((kib)): 1. Log in to ((kib)). 2. Navigate to **Stack Management → Connectors → Create Connector → OpenAI**. The OpenAI connector enables this use-case because LM Studio uses the OpenAI SDK. 3. Name your connector to help keep track of the model version you are using. -4. Under **URL**, enter the domain name specified in your Nginx configuration file. +4. Under **URL**, enter the domain name specified in your Nginx configuration file, followed by `/v1/chat/completions`. 5. Under **Default model**, enter `local-model`. 6. Under **API Key**, enter the secret token specified in your Nginx configuration file. 7. Click **Save**. -Setup is now complete. You can use the model you've loaded in LM Studio to power ((elastic-sec)) features like AI Assistant. You can test a variety of models as you interact with AI Assistant to see what works best. + + +Setup is now complete. You can use the model you've loaded in LM Studio to power Elastic's generative AI features. You can test a variety of models as you interact with AI Assistant to see what works best without having to update your connector. While local models work well for if you would like to interact with we recommend you use one of . 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zoTNMyLaJs~Z3EiBnSiC`Xm*7=&0zt-%tz?OF8*QCV!BkL4~dqO{!t_J(tu5e1G=M$ zgs;-~r6K}!iq3Q-I^EE~QcDASuefd}T^!&YvV)sya>Xk)?1TE?X}>`r*2(4jbU2zs zI52v_cYbvqDx+sYM_XCanmKWti8%)D`Ooa1*Y366gG4QmU-T&Yc%AZULpH2Qb|7Z5 z>VjL2OQj13Awyf=rB|WyJQNE}Uae#3SNjL&w&fz>Nhg<*SnE^I-P2ZgoD_TDEvm`9 zQ`~favoZh8p@}1Ec(!3CfQjkkN*N4gWO~ZTuBRAeRO|9VH5H@+H0#RF&3ziYRqdu) zhM20bRskAiYEj}bZkz%>SiXmkMlwu;B~l-V*f?FBoxcNMe*RbQ4C1#L_7m%|lW-+t zkIunAPJXhmbEL=Sq($tK!?3QeDiHjh4HoM2+dKy=I#U#b5yW#Es-=7^(0vBCnk3aq| zk1ZSkOed++oqpV#?8@JF|A7E5IudHVf0GyR_i#;^0FLMx5EQ`mzhCCx@T7oCfZJP* zV6D1!V@&g};Yb+*Flw-AaNIEe%bNV=1}?f(DV6yzkL`r-KE)6Du0sK>tQGHqb!t~w$2clSXEdT%j literal 0 HcmV?d00001 From a34282f8f94b6260adceac9d0c1916bb580cc907 Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein Date: Thu, 4 Jul 2024 18:26:50 -0700 Subject: [PATCH 03/11] minor fixes --- docs/serverless/assistant/connect-to-byo-llm.mdx | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index 736feada4a..9f9c2dcdd5 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -94,14 +94,14 @@ Once you've launched LM Studio, select a model: For security reasons, before downloading a model, verify that it is from a trusted source. It can be helpful to review community feedback on the model (for example using a site like Hugging Face). -1. Go to LM Studio's Search window. -2. Search for an LLM (for example, `Mixtral-8x7B-instruct`). -3. Your chosen model must include `instruct` in its name in order to work with Elastic. -4. Filter your search for "Compatibility Guess" to optimize results for your hardware. Results will be color coded: +. Go to LM Studio's Search window. +. Search for an LLM (for example, `Mixtral-8x7B-instruct`). +. Your chosen model must include `instruct` in its name in order to work with Elastic. +. Filter your search for "Compatibility Guess" to optimize results for your hardware. Results will be color coded: .. Green means "Full GPU Possible", which yields the best results. .. Blue means "Partial GPU offload possible", which may work. .. Red for "Likely too large for this machine", which typically will not work. -5. Download one or more models. +. Download one or more models. In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF [quanitization](https://huggingface.co/docs/transformers/main/en/quantization/overview). For more information about model names and format information, refer to the following table: @@ -119,7 +119,7 @@ After downloading a model, you'll need to load it in LM Studio using the GUI or It is a best practice to use the GUI to download at least one model from the marketplace first, and then load/unload the model(s) using the CLI. The GUI allows you to search for models, whereas the CLI only allows you to import specific paths, but the CLI provides a good interface for loading/unloading. -Use the following commands in your CLI: +Use the following commands in your CLI. 1. Verify LM Studio: `lms` 2. Check LM Studio's status: `lms status` From 9d0a2e17de2853fc1baee9bba4cee2a06f8d203c Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein Date: Thu, 4 Jul 2024 19:15:11 -0700 Subject: [PATCH 04/11] reformats a list --- docs/serverless/assistant/connect-to-byo-llm.mdx | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index 9f9c2dcdd5..5f77af1a9a 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -94,14 +94,14 @@ Once you've launched LM Studio, select a model: For security reasons, before downloading a model, verify that it is from a trusted source. It can be helpful to review community feedback on the model (for example using a site like Hugging Face). -. Go to LM Studio's Search window. -. Search for an LLM (for example, `Mixtral-8x7B-instruct`). -. Your chosen model must include `instruct` in its name in order to work with Elastic. -. Filter your search for "Compatibility Guess" to optimize results for your hardware. Results will be color coded: -.. Green means "Full GPU Possible", which yields the best results. -.. Blue means "Partial GPU offload possible", which may work. -.. Red for "Likely too large for this machine", which typically will not work. -. Download one or more models. +1. Go to LM Studio's Search window. +1. Search for an LLM (for example, `Mixtral-8x7B-instruct`). +1. Your chosen model must include `instruct` in its name in order to work with Elastic. +1. Filter your search for "Compatibility Guess" to optimize results for your hardware. Results will be color coded: + 1. Green means "Full GPU Possible", which yields the best results. + 1. Blue means "Partial GPU offload possible", which may work. + 1. Red for "Likely too large for this machine", which typically will not work. +1. Download one or more models. In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF [quanitization](https://huggingface.co/docs/transformers/main/en/quantization/overview). For more information about model names and format information, refer to the following table: From 7aa4f14499514f5e393b2a7fe6d4566b63900879 Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein Date: Thu, 4 Jul 2024 19:16:25 -0700 Subject: [PATCH 05/11] updates punctuation --- docs/serverless/assistant/connect-to-byo-llm.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index 5f77af1a9a..b7980e0518 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -103,7 +103,7 @@ For security reasons, before downloading a model, verify that it is from a trust 1. Red for "Likely too large for this machine", which typically will not work. 1. Download one or more models. -In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF [quanitization](https://huggingface.co/docs/transformers/main/en/quantization/overview). For more information about model names and format information, refer to the following table: +In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF [quanitization](https://huggingface.co/docs/transformers/main/en/quantization/overview). For more information about model names and format information, refer to the following table. | Model Name | Parameter Size | Tokens/Context Window | Quantization Format | |------------|----------------|-----------------------|---------------------| @@ -128,7 +128,7 @@ Use the following commands in your CLI. -After the model loads, you should see a `Model loaded successfully` message in the CLI: +After the model loads, you should see a `Model loaded successfully` message in the CLI. 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z1$M^%jk8}*2^^**SFZxKi)}-qK@TGZ4)f&HiK&G8Oc-)$pAqT>;E2Tzpb6y zN+}p*AMdWD*=giB?4?BRUUgeO3iFUECEZyD;UUdmj{b1M=a<>XnamhxBz+)BjxYoR z`AGrWUXOO*a%Z$lZ?>Ay~eLkyG5$srtnCKrsRfl)c z)39gCK{Y;Wq!cwujya9L32wQM?8zT8ic`tteRee7ZJl5*!x6jSQMvIqXgA|E*#i*h znV_e1DF)f2YUf=<9AWi(`aK`DSpD5`sH9A{|B1}anT#4;q-hosyilFqx3XC=lRGH@ zKb7pwSn$YdYii!*s{)QvX7oTwvE3e$OR}U;B+9!SsiG@WW?*oQ4fMt!;!l!U$*3n| zc}wK>MY%<^MYIQ!WAh5g-%D~>3LsYlfy%kmbsyQYyo&K{Cw~h>Ig?ud))qlOY3B|1 z4Lja<=AQ)zjM~gf1WJNHOMm~nx&K~EqWYXb-ve;nFZ$E^@PBkggd=Yywn{|oG5`Cn NDvBBkWiMWb|383uWC{QP From 5cd23508887afb47de780443514db6d339df0f1d Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein Date: Fri, 5 Jul 2024 10:18:56 -0700 Subject: [PATCH 07/11] incorporates Charles' final review --- .../assistant/connect-to-byo-llm.mdx | 5 ++++- .../assistant/images/lms-model-select.png | Bin 0 -> 679820 bytes 2 files changed, 4 insertions(+), 1 deletion(-) create mode 100644 docs/serverless/assistant/images/lms-model-select.png diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index b7980e0518..ff7618e96e 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -84,12 +84,15 @@ You can use Elastic's [Nginx integration](https://www.elastic.co/docs/current/in ## Configure LM Studio and download a model -First, install LM Studio. LM Studio supports the OpenAI SDK, which makes it compatible with Elastic's OpenAI connector, so you can connect Elastic AI Assistant to any model available in the LM Studio marketplace. +First, install [LM Studio](https://lmstudio.ai/). LM Studio supports the OpenAI SDK, which makes it compatible with Elastic's OpenAI connector, allowing you to connect to any model available in the LM Studio marketplace. One current limitation of LM Studio is that when it is installed on a server, you must launch the application using its GUI before doing so using the CLI. For example, by using Chrome RDP with an [X Window System](https://cloud.google.com/architecture/chrome-desktop-remote-on-compute-engine). After you've opened the application the first time using the GUI, you can start it by using `sudo lms server start` in the CLI. Once you've launched LM Studio, select a model: + + + For security reasons, before downloading a model, verify that it is from a trusted source. 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<79124755+nastasha-solomon@users.noreply.github.com> --- docs/serverless/assistant/connect-to-byo-llm.mdx | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index ff7618e96e..77414912fa 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -6,7 +6,7 @@ tags: ["security", "overview", "get-started"] status: in review --- -This page provides instructions for setting up a connector to a large language model (LLM) of your choice using LM Studio. This allows you to use your chosen model within ((elastic-sec)). You'll first need to set up LM Studio on a server, set up a reverse proxy to communicate with ((elastic-sec)), and finally configure the connector in your ((elastic-sec)) project. [Learn more about the benefits of using a local LLM](https://www.elastic.co/blog/ai-assistant-locally-hosted-models). +This page provides instructions for setting up a connector to a large language model (LLM) of your choice using LM Studio. This allows you to use your chosen model within ((elastic-sec)). You'll first need to set up LM Studio on a server, then set up a reverse proxy to communicate with ((elastic-sec)), and finally configure the connector in your ((elastic-sec)) project. [Learn more about the benefits of using a local LLM](https://www.elastic.co/blog/ai-assistant-locally-hosted-models). This example uses a single server hosted in GCP to run the following components: - LM Studio with the [Mixtral-8x7b](https://mistral.ai/technology/#models) model @@ -76,7 +76,9 @@ server { ``` -Replace `` with your actual token, and keep it safe since you'll need it to set up the ((elastic-sec)) connector. Replace `` with your actual domain name. If you decide to change the port number in LM studio to something other than 1234, update the `proxy_pass` value at the bottom of the configuration. +* Replace `` with your actual token, and keep it safe since you'll need it to set up the ((elastic-sec)) connector. +* Replace `` with your actual domain name. +* Update the `proxy_pass` value at the bottom of the configuration if you decide to change the port number in LM studio to something other than 1234. ### (Optional) set up performance monitoring for your reverse proxy @@ -101,22 +103,22 @@ For security reasons, before downloading a model, verify that it is from a trust 1. Search for an LLM (for example, `Mixtral-8x7B-instruct`). 1. Your chosen model must include `instruct` in its name in order to work with Elastic. 1. Filter your search for "Compatibility Guess" to optimize results for your hardware. Results will be color coded: - 1. Green means "Full GPU Possible", which yields the best results. - 1. Blue means "Partial GPU offload possible", which may work. - 1. Red for "Likely too large for this machine", which typically will not work. + * Green means "Full GPU Possible", which yields the best results. + * Blue means "Partial GPU offload possible", which may work. + * Red for "Likely too large for this machine", which typically will not work. 1. Download one or more models. In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF [quanitization](https://huggingface.co/docs/transformers/main/en/quantization/overview). For more information about model names and format information, refer to the following table. | Model Name | Parameter Size | Tokens/Context Window | Quantization Format | |------------|----------------|-----------------------|---------------------| -| Name of model, sometimes with a version number. | LLMs are often compared by their number of parameters — higher numbers mean more powerful models. | Tokens are small chunks of input information. Characters do not necessarily correspond to tokens 1:1. You can use [Tokenizer](https://platform.openai.com/tokenizer) to see how many tokens a given prompt might contain. | Quantization reduces overall parameters and helps the model to run faster, but reduces accuracy. | +| Name of model, sometimes with a version number. | LLMs are often compared by their number of parameters — higher numbers mean more powerful models. | Tokens are small chunks of input information. Tokens do not necessarily correspond to characters. You can use [Tokenizer](https://platform.openai.com/tokenizer) to see how many tokens a given prompt might contain. | Quantization reduces overall parameters and helps the model to run faster, but reduces accuracy. | | Examples: Llama, Mistral, Phi-3, Falcon. | The number of parameters is a measure of the size and the complexity of the model. The more parameters a model has, the more data it can process, learn from, generate, and predict. | The context window defines how much information the model can process at once. If the number of input tokens exceeds this limit, input gets truncated. | Specific formats for quantization vary, most models now support GPU rather than CPU offloading. | ## Load a model in LM Studio -After downloading a model, you'll need to load it in LM Studio using the GUI or LM Studio's [CLI tool](https://lmstudio.ai/blog/lms). You can do this either using the CLI, or the GUI. +After downloading a model, load it in LM Studio using the GUI or LM Studio's [CLI tool](https://lmstudio.ai/blog/lms). You can do this using the CLI or the GUI. ### Option 1: load a model using the CLI (Recommended) From 61ba4a2a70642bd9a58535d20ff582e835e2282a Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein Date: Fri, 5 Jul 2024 13:34:21 -0700 Subject: [PATCH 09/11] Incorporates Nastasha's review --- docs/serverless/assistant/connect-to-byo-llm.mdx | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index 77414912fa..ca4aa9e05c 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -90,14 +90,7 @@ First, install [LM Studio](https://lmstudio.ai/). LM Studio supports the OpenAI One current limitation of LM Studio is that when it is installed on a server, you must launch the application using its GUI before doing so using the CLI. For example, by using Chrome RDP with an [X Window System](https://cloud.google.com/architecture/chrome-desktop-remote-on-compute-engine). After you've opened the application the first time using the GUI, you can start it by using `sudo lms server start` in the CLI. -Once you've launched LM Studio, select a model: - - - - - -For security reasons, before downloading a model, verify that it is from a trusted source. It can be helpful to review community feedback on the model (for example using a site like Hugging Face). - +Once you've launched LM Studio: 1. Go to LM Studio's Search window. 1. Search for an LLM (for example, `Mixtral-8x7B-instruct`). @@ -108,6 +101,12 @@ For security reasons, before downloading a model, verify that it is from a trust * Red for "Likely too large for this machine", which typically will not work. 1. Download one or more models. + +For security reasons, before downloading a model, verify that it is from a trusted source. It can be helpful to review community feedback on the model (for example using a site like Hugging Face). + + + + In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF). It has 46.7B total parameters, a 32,000 token context window, and uses GGUF [quanitization](https://huggingface.co/docs/transformers/main/en/quantization/overview). For more information about model names and format information, refer to the following table. | Model Name | Parameter Size | Tokens/Context Window | Quantization Format | From 9c1b0af6457023052bd48603620cfd35d092eff4 Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein <91905639+benironside@users.noreply.github.com> Date: Mon, 8 Jul 2024 08:11:02 -0700 Subject: [PATCH 10/11] Apply suggestions from code review Incorporates Nat's review Co-authored-by: natasha-moore-elastic <137783811+natasha-moore-elastic@users.noreply.github.com> --- .../assistant/connect-to-byo-llm.mdx | 27 +++++++++---------- 1 file changed, 13 insertions(+), 14 deletions(-) diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index ca4aa9e05c..54d0b03310 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -82,7 +82,7 @@ server { ### (Optional) set up performance monitoring for your reverse proxy -You can use Elastic's [Nginx integration](https://www.elastic.co/docs/current/integrations/nginx) to monitor performance and populate monitoring dashboards in ((kib)). +You can use Elastic's [Nginx integration](https://www.elastic.co/docs/current/integrations/nginx) to monitor performance and populate monitoring dashboards in the ((security-app)). ## Configure LM Studio and download a model @@ -93,10 +93,9 @@ One current limitation of LM Studio is that when it is installed on a server, yo Once you've launched LM Studio: 1. Go to LM Studio's Search window. -1. Search for an LLM (for example, `Mixtral-8x7B-instruct`). -1. Your chosen model must include `instruct` in its name in order to work with Elastic. +1. Search for an LLM (for example, `Mixtral-8x7B-instruct`). Your chosen model must include `instruct` in its name in order to work with Elastic. 1. Filter your search for "Compatibility Guess" to optimize results for your hardware. Results will be color coded: - * Green means "Full GPU Possible", which yields the best results. + * Green means "Full GPU offload possible", which yields the best results. * Blue means "Partial GPU offload possible", which may work. * Red for "Likely too large for this machine", which typically will not work. 1. Download one or more models. @@ -117,15 +116,15 @@ In this example we used [`TheBloke/Mixtral-8x7B-Instruct-v0.1.Q3_K_M.gguf`](http ## Load a model in LM Studio -After downloading a model, load it in LM Studio using the GUI or LM Studio's [CLI tool](https://lmstudio.ai/blog/lms). You can do this using the CLI or the GUI. +After downloading a model, load it in LM Studio using the GUI or LM Studio's [CLI tool](https://lmstudio.ai/blog/lms). ### Option 1: load a model using the CLI (Recommended) -It is a best practice to use the GUI to download at least one model from the marketplace first, and then load/unload the model(s) using the CLI. The GUI allows you to search for models, whereas the CLI only allows you to import specific paths, but the CLI provides a good interface for loading/unloading. +It is a best practice to download models from the marketplace using the GUI, and then load or unload them using the CLI. The GUI allows you to search for models, whereas the CLI only allows you to import specific paths, but the CLI provides a good interface for loading and unloading. -Use the following commands in your CLI. +Use the following commands in your CLI: -1. Verify LM Studio: `lms` +1. Verify LM Studio is installed: `lms` 2. Check LM Studio's status: `lms status` 3. List all downloaded models: `lms ls` 4. Load a model: `lms load` @@ -156,20 +155,20 @@ You can monitor the performance of the host running LM Studio using Elastic's [C ## Configure the connector in ((elastic-sec)) -Finally, configure the connector in ((kib)): +Finally, configure the connector in your Security project: -1. Log in to ((kib)). -2. Navigate to **Stack Management → Connectors → Create Connector → OpenAI**. The OpenAI connector enables this use-case because LM Studio uses the OpenAI SDK. +1. Log in to your Security project. +2. Navigate to **Stack Management → Connectors → Create Connector → OpenAI**. The OpenAI connector enables this use case because LM Studio uses the OpenAI SDK. 3. Name your connector to help keep track of the model version you are using. 4. Under **URL**, enter the domain name specified in your Nginx configuration file, followed by `/v1/chat/completions`. 5. Under **Default model**, enter `local-model`. -6. Under **API Key**, enter the secret token specified in your Nginx configuration file. +6. Under **API key**, enter the secret token specified in your Nginx configuration file. 7. Click **Save**. - + Setup is now complete. You can use the model you've loaded in LM Studio to power Elastic's generative AI features. You can test a variety of models as you interact with AI Assistant to see what works best without having to update your connector. -While local models work well for if you would like to interact with we recommend you use one of . As local models become more performant over time, this is likely to change. +While local models work well for , we recommend you use one of for interacting with . As local models become more performant over time, this is likely to change. \ No newline at end of file From 96ae390e06a6c83bed8ea32d7078ca92f40a537e Mon Sep 17 00:00:00 2001 From: Benjamin Ironside Goldstein Date: Mon, 8 Jul 2024 08:11:47 -0700 Subject: [PATCH 11/11] Incorporates Nat's review --- docs/serverless/assistant/connect-to-byo-llm.mdx | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/serverless/assistant/connect-to-byo-llm.mdx b/docs/serverless/assistant/connect-to-byo-llm.mdx index ca4aa9e05c..6bf8ef8c2d 100644 --- a/docs/serverless/assistant/connect-to-byo-llm.mdx +++ b/docs/serverless/assistant/connect-to-byo-llm.mdx @@ -6,7 +6,7 @@ tags: ["security", "overview", "get-started"] status: in review --- -This page provides instructions for setting up a connector to a large language model (LLM) of your choice using LM Studio. This allows you to use your chosen model within ((elastic-sec)). You'll first need to set up LM Studio on a server, then set up a reverse proxy to communicate with ((elastic-sec)), and finally configure the connector in your ((elastic-sec)) project. [Learn more about the benefits of using a local LLM](https://www.elastic.co/blog/ai-assistant-locally-hosted-models). +This page provides instructions for setting up a connector to a large language model (LLM) of your choice using LM Studio. This allows you to use your chosen model within ((elastic-sec)). You'll first need to set up a reverse proxy to communicate with ((elastic-sec)), then set up LM Studio on a server, and finally configure the connector in your ((elastic-sec)) project. [Learn more about the benefits of using a local LLM](https://www.elastic.co/blog/ai-assistant-locally-hosted-models). This example uses a single server hosted in GCP to run the following components: - LM Studio with the [Mixtral-8x7b](https://mistral.ai/technology/#models) model @@ -16,7 +16,7 @@ This example uses a single server hosted in GCP to run the following components: -For testing, you can use alternatives to Nginx such as [Azure Dev Tunnels](https://learn.microsoft.com/en-us/azure/developer/dev-tunnels/overview) or [Ngrock](https://ngrok.com/), but using Nginx makes it easy to collect additional telemetry and monitor its status by using Elastic's native Nginx integration. While this example uses cloud infrastructure, it could also be replicated locally without an internet connection. +For testing, you can use alternatives to Nginx such as [Azure Dev Tunnels](https://learn.microsoft.com/en-us/azure/developer/dev-tunnels/overview) or [Ngrok](https://ngrok.com/), but using Nginx makes it easy to collect additional telemetry and monitor its status by using Elastic's native Nginx integration. While this example uses cloud infrastructure, it could also be replicated locally without an internet connection. ## Configure your reverse proxy @@ -78,10 +78,10 @@ server { * Replace `` with your actual token, and keep it safe since you'll need it to set up the ((elastic-sec)) connector. * Replace `` with your actual domain name. -* Update the `proxy_pass` value at the bottom of the configuration if you decide to change the port number in LM studio to something other than 1234. +* Update the `proxy_pass` value at the bottom of the configuration if you decide to change the port number in LM Studio to something other than 1234. -### (Optional) set up performance monitoring for your reverse proxy +### (Optional) Set up performance monitoring for your reverse proxy You can use Elastic's [Nginx integration](https://www.elastic.co/docs/current/integrations/nginx) to monitor performance and populate monitoring dashboards in ((kib)). ## Configure LM Studio and download a model

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