From cf1e91cac2da28410c9ee3b768771553fc9d263b Mon Sep 17 00:00:00 2001 From: Wenxi Onyx Date: Mon, 8 Sep 2025 13:52:22 -0700 Subject: [PATCH 1/4] new seeded docs --- backend/onyx/seeding/initial_docs.json | 38550 +++++++++++----- backend/scripts/document_seeding_prep.py | 921 +- .../docker_compose/docker-compose.dev.yml | 2 - .../docker_compose/docker-compose.gpu-dev.yml | 2 - .../docker-compose.multitenant-dev.yml | 1 - deployment/helm/charts/onyx/values.yaml | 1 - 6 files changed, 28515 insertions(+), 10962 deletions(-) diff --git a/backend/onyx/seeding/initial_docs.json b/backend/onyx/seeding/initial_docs.json index 23e2d39f067..e2ac8db5a19 100644 --- a/backend/onyx/seeding/initial_docs.json +++ b/backend/onyx/seeding/initial_docs.json @@ -1,10823 +1,27829 @@ [ { - "url": "https://docs.onyx.app/more/use_cases/overview", - "title": "Use Cases Overview", - "content": "How to leverage Onyx in your organization\n\nOnyx Overview\nOnyx is the AI Assistant connected to your organization's docs, apps, and people. Onyx makes Generative AI more versatile for work by enabling new types of questions like \"What is the most common feature request we've heard from customers this month\". Whereas other AI systems have no context of your team and are generally unhelpful with work related questions, Onyx makes it possible to ask these questions in natural language and get back answers in seconds.\n\nOnyx can connect to +30 different tools and the use cases are not limited to the ones in the following pages. The highlighted use cases are for inspiration and come from feedback gathered from our users and customers.\n\n\nCommon Getting Started Questions:\n\nWhy are these docs connected in my Onyx deployment?\nAnswer: This is just an example of how connectors work in Onyx. You can connect up your own team's knowledge and you will be able to ask questions unique to your organization. Onyx will keep all of the knowledge up to date and in sync with your connected applications.\n\nIs my data being sent anywhere when I connect it up to Onyx?\nAnswer: No! Onyx is built with data security as our highest priority. We open sourced it so our users can know exactly what is going on with their data. By default all of the document processing happens within Onyx. The only time it is sent outward is for the GenAI call to generate answers.\n\nWhere is the feature for auto sync-ing document level access permissions from all connected sources?\nAnswer: This falls under the Enterprise Edition set of Onyx features built on top of the MIT/community edition. If you are on Onyx Cloud, you have access to them by default. If you're running it yourself, reach out to the Onyx team to receive access.", + "url": "https://docs.onyx.app/welcome", + "title": "Welcome to Onyx!", + "content": "## What is Onyx?\nOnyx is your team's entry point to Generative AI,\noffering a natural language interface for any LLM while integrating seamlessly with your knowledge and applications.\nBuild tailored AI Agents, search for documents, browse the web, and more \u2014 all in one place.\n## Major Features\n The best way to quickly get familiar with Onyx is to check out the features below!\n Conversational interface to your LLMs, Agents, and knowledge.\n Create AI agents tailored to your use cases with custom instructions, knowledge, and actions.\n Search through your organization's knowledge and connected applications.\n Enrich the knowledge of the LLM with the latest information from the internet.\n Enable Actions connected to your team's applications to let Agents automate work.\n Execute code directly within your chat sessions for complex calculations and data analysis.\n To learn about other features, check out the [Core Features](/overview/core_features/chat)\n section or visit the [Admin Docs](/admin/overview) for an even more in depth breakdown.\n## Why Onyx?\nWhy choose Onyx over ChatGPT, Microsoft Copilot, Google Gemini, or Glean?\n- **Reliable Responses from Internal Knowledge:**\n Onyx builds a knowledge index using LLM-native techniques. Powered with contextual retrieval, advanced RAG,\n hybrid search, and AI-generated knowledge graphs, Onyx ensures the most relevant results and the least hallucinations.\n- **Open Source:**\n Onyx is made for security, data privacy, and ease of self-hosting. It's easy and free to get started.\n For teams investing in a long-term GenAI strategy,\n Onyx can be easily extended or customized to your team's future needs.\n- **Highly Configurable:**\n Onyx is designed to be flexible, so you can optimize the experience for your team. Plug and play any LLM model,\n connect only the data you need, and enable the features you want your team to use.\n## Ready to Get Started?\n**Next Steps:**\n Checkout our quickstart guide to self-host Onyx in minutes.\n Sign up for a free trial of Onyx Cloud, no credit card required.\n", "title_embedding": [ - 0.013585364446043968, - 0.06531507521867752, - -0.0001728831703076139, - -0.003940831869840622, - 0.044078364968299866, - -0.006206007208675146, - -0.008377128280699253, - -0.0193742997944355, - -0.018904175609350204, - 0.00868070125579834, - -0.005770757794380188, - 0.018564216792583466, - 0.030414527282118797, - 0.0327068567276001, - -0.0336286760866642, - -0.0517829954624176, - 0.0029869426507502794, - -3.836356700048782e-05, - -0.006240167189389467, - 0.011168955825269222, - -0.04732134938240051, - -0.05257624015212059, - 0.017937077209353447, - -0.029843101277947426, - 0.03417196497321129, - 0.008637758903205395, - -0.016427641734480858, - 0.017053034156560898, - 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Critical information is saved across a host of channels like call transcripts with prospects, engineering design docs, IT runbooks, customer support email exchanges, project management tickets, and more. As fast moving teams scale up, information gets spread out and more disorganized.\n\nSince it quickly becomes infeasible to check across every source, decisions get made on incomplete information, employee satisfaction decreases, and the most valuable members of your team are tied up with constant distractions as junior teammates are unable to unblock themselves. Onyx solves this problem by letting anyone on the team access all of the knowledge across your organization in a permissioned and secure way. Users can ask questions in natural language and get back answers and documents across all of the connected sources instantly.\n\nWhat's the real cost?\nA typical knowledge worker spends over 2 hours a week on search, but more than that, the cost of incomplete or incorrect information can be extremely high. Customer support/success that isn't able to find the reference to similar cases could cause hours or even days of delay leading to lower customer satisfaction or in the worst case - churn. An account exec not realizing that a prospect had previously mentioned a specific need could lead to lost deals. An engineer not realizing a similar feature had previously been built could result in weeks of wasted development time and tech debt with duplicate implementation. With a lack of knowledge, your whole organization is navigating in the dark - inefficient and mistake prone.", + "url": "https://docs.onyx.app/overview/core_features/actions", + "title": "Actions & MCP", + "content": "## Overview\n**Actions** give Agents the ability to interact with external systems.\nOnyx comes with 4 built-in Actions and allows users to configure additional ones via\n[OpenAPI](https://en.wikipedia.org/wiki/OpenAPI_Specification)\nand [Model Context Protocol](https://modelcontextprotocol.io/) (MCP).\nThe built-in Actions include:\n## Custom Actions\nOnyx offers flexible options for configuring both custom Actions and their associated authentication.\nAdmins can choose to:\n- Use a single shared authentication, giving all users the same level of access to Actions.\n- Require each user to complete their own authentication flow, so Actions respect individual user permissions.\nOnyx supports both token-based authentication and OAuth.\n## Actions Button\nIn the Chat input 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-0.034116726368665695 ], "chunk_ind": 0 }, { - "url": "https://docs.onyx.app/more/use_cases/enterprise_search", - "title": "Enterprise Search", - "content": "More than Search\nWhen analyzing the entire corpus of knowledge within your company is as easy as asking a question in a search bar, your entire team can stay informed and up to date. Onyx also makes it trivial to identify where knowledge is well documented and where it is lacking. Team members who are centers of knowledge can begin to effectively document their expertise since it is no longer being thrown into a black hole. All of this allows the organization to achieve higher efficiency and drive business outcomes.\n\nWith Generative AI, the entire user experience has evolved as well. For example, instead of just finding similar cases for your customer support team to reference, Onyx breaks down the issue and explains it so that even the most junior members can understand it. This in turn lets them give the most holistic and technically accurate response possible to your customers. On the other end, even the super stars of your sales team will not be able to review 10 hours of transcripts before hopping on that critical call, but Onyx can easily parse through it in mere seconds and give crucial context to help your team close.", + "url": "https://docs.onyx.app/overview/core_features/agents", + "title": "Agents", + "content": "Agents are a combination of user specified instructions, knowledge, and [Actions](/overview/core_features/actions).\nThink of them as AI team members that are optimized for a specific task.\nOnyx Agents can be for individual use or shared with other users or\n[user-groups](/admin/user_management/users_and_groups) within Onyx.\n## When to use an Agent\nUse agents to build the best experience for repeat use cases,\nespecially those that can be shared with other members of the team.\nSome common examples include:\n- Onboarding Assistant\n- AI Helpdesk\n- Engineer Copilot\n- Legal Reviewer\nThese are typically scoped down to a particular task such as reviewing documents to ensure they comply with security\npolicies, filling out RFPs based on previously completed ones, etc.\n## Creating an Agent\n### Instructions (Prompting)\n The Instruction field is infinitely flexible so it is recommended to test different variations and verify the behavior\n before sharing the Agent broadly with your team.\nProvided below for inspiration is the **Instruction** for the default Onyx experience.\n ```\n You are a highly capable, thoughtful, and precise assistant. Your goal is to deeply understand the user's intent, ask clarifying questions when needed, think step-by-step through complex problems, provide clear and accurate answers, and proactively anticipate helpful follow-up information. Always prioritize being truthful, nuanced, insightful, and efficient.\n The current date is [[CURRENT_DATETIME]]\n You use different text styles, bolding, emojis (sparingly), block quotes, and other formatting to make your responses more readable and engaging.\n You use proper Markdown and LaTeX to format your responses for math, scientific, and chemical formulas, symbols, etc.: '$$\\n[expression]\\n$$' for standalone cases and '\\( [expression] \\)' when inline. For code you prefer to use Markdown and specify the language.\n You can use Markdown horizontal rules (---) to separate sections of your responses.\n You can use Markdown tables to format your responses for data, lists, and other structured information.\n ```\n Note that `[[CURRENT_DATETIME]]` is dynamically replaced and there may be additional Action use instructions\n depending on the enabled Actions.\nOne of the best parts of creating an Agent is the ability to control the goal/behavior of the Agent.\nThe instructions are purely in natural language and can include things like:\n- Always provide your results in a table.\n- Try to quote directly from the documents rather than rewording anything.\n- Flag information from documents that are older than 3 months.\n### Knowledge\n It is typically best to include only the necessary knowledge for the Agent to complete its task.\n The more scoped down the documents, the more reliable the performance.\nWhen creating an Agent, you can include both knowledge from [connectors](/overview/core_features/connectors)\nor file upload. The knowledge from connectors will be kept up to date as documents change in the external sources.\n### Actions\n If any of the built-in actions (Web Search, Internal Search, Image Generation, Code Interpreter) are missing,\n contact your Onyx admin.\n These must be set up in the admin-panel before being made available in the Agent creation flow.\n[Actions](/overview/core_features/actions) (sometimes known as Tools)\nallow the Agents to do things in external applications via APIs.\nSome tools help Onyx give better answers (such as the Onyx built-in tools)\nwhile others allow the system to do more than answer questions.\nSome example common Actions include:\n- Updating ticket statuses based on the conversation and if the user's needs were addressed.\n- Checking the status of a service to give real-time answers.\n- Moving deals along a sales pipeline in a CRM based on call transcripts or user request.\n", "title_embedding": [ - -0.011060578748583794, - 0.05994883179664612, - 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specific to your organization.\n\nBeyond Answers\nAgents enabled by generative AI and reasoning capable models are helping teams to automate their work. Onyx is helping teams make it happen. Onyx provides out of the box user chat sessions, attaching custom tools, handling LLM reasoning, code execution, data analysis, referencing internal knowledge, and much more.\n\nOnyx as a platform is not a no-code agent builder. We are made by developers for developers and this gives your team the full flexibility and power to create agents not constrained by blocks and simple logic paths.\n\nFlexibility and Extensibility\nOnyx is open source and completely whitebox. This not only gives transparency to what happens within the system but also means that your team can directly modify the source code to suit your unique needs.", + "url": "https://docs.onyx.app/overview/core_features/chat", + "title": "Chat", + "content": " On the top left of the page (just right of the sidebar), you can select the mode of the UI.\n Replace \"Auto\" with \"Chat\" to always go into this Chat UI.\nOnyx provides a natural language chat interface as the main way of interacting with the features.\nThe page below contains an overview of the main components and features.\n## Input Bar\n### Chat with Files / URLs\nThe leftmost button of the input bar lets users add context into the Chat session.\nUsers can choose between uploading files or selecting URLs as well as reusing previous files or URLs.\n URLs behind Logins, Captcha, or Paywalls that are not scrapeable are not accessible.\n Consider using a [Connector](/overview/core_features/connectors) instead.\n### Actions Selector\nThe second button lets users disable or force the use of Actions. There are 4 built-in Actions:\n- **[Internal Search](/overview/core_features/internal_search)**:\n Enables the LLM to search the indexed knowledge from [Connectors](/overview/core_features/connectors).\n- **[Web Search](/overview/core_features/web_search)**: Enables the LLM to search the internet.\n Requires an admin to set up an API key for a search provider.\n- **[Code Interpreter](/overview/core_features/code_interpreter)**:\n Enables the LLM to use a sandboxed Python runtime to execute code and run data analysis.\n- **[Image Generation](/overview/core_features/image_generation)**: Allows the LLM to generate images.\n Requires setting up an image generation API.\nThe Actions below the separator represent custom admin configured Actions.\nSee [Actions & MCP](/overview/core_features/actions) to learn about custom Actions.\n### Deep Research\nToggle **Deep Research** using the hourglass icon. When turned on, the LLM will be able to run many cycles of thinking,\nresearch, and actions to give the best possible result for the user.\nThis mode is intended for complicated questions that may need to pull together many sources together or requires\nsignificant reasoning.\n Deep Research may take up to several minutes and could cost many times (>10x) the token cost of a normal inference.\n### Model Selector\nOnyx supports all major LLM providers as well as self-hosting options like Ollama, VLLM, etc. For select models,\nusers can also configure the creativity and reasoning level.\n## Sidebar Contents\nThe left sidebar contains:\n- `New Session` button to clear the history and start a new Chat or [Search](/overview/core_features/internal_search) session.\n- `Projects` to help users organize chats and reuse different sets of documents. See section below for more info.\n- `Agents` section to start a new session with yours or your team's custom [Agents](/overview/core_features/agents).\n- `Sessions` section containing a list of the most recent conversations.\nThe right sidebar contains sources and citations that were used in generating the answer.\nThese can come from either `Internal Search` or `Web Search` or both.\nDocuments in the right sidebar can also be selected to be included in full for the next message in the Chat session.\n It's often useful to ask a question to find a document, then select it to do a deep dive on it.\n## Projects\n**Projects** are a collection of instructions (prompts) and files as well as a grouping for chats.\nUse projects to organize ongoing work,\nor as a handy way to reuse instructions and files without going through the Agent creation flow.\n## Miscellaneous Chat Features\n**Chat Sharing** - share chats with other team members by using the share-chat button in the top right (left of the\nSources sidebar).\n**Feedback** - give feedback viewable to the admins using the thumbs-up/thumbs-down buttons when hovering an LLM\nresponse\n**Regenerate** - modify your inputs by clicking the user messages or regenerate the LLM response with another model.\n**Copying** - copy the LLM output or markdown/code blocks by clicking on the copy button which shows on hover.\n", "title_embedding": [ - 0.032763753086328506, - 0.049961112439632416, - 0.00777681777253747, - -0.009621717967092991, - 0.03860695660114288, - 0.035656899213790894, - -0.029095029458403587, - -0.030549267306923866, - -0.028131460770964622, - -0.023247526958584785, - -0.030750803649425507, - 0.04233109578490257, - 0.044790223240852356, - 0.020764602348208427, - -0.011113415472209454, - -0.052699606865644455, - 0.05441703647375107, - -0.027375519275665283, - 0.03858301043510437, - 0.0015289749717339873, - -0.0007870558765716851, - -0.013234086334705353, - -0.008892231620848179, - -0.0269540473818779, - 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They field requests that cover the entire surface area of the product and need to help your users find success on extremely short timelines. Because they're not the same people who designed or built the system, they often lack the depth of understanding needed - resulting in delays and escalations to other teams. Modern teams are leveraging AI to help their CS team optimize the speed and quality of these critical customer-facing interactions.\n\nThe Importance of Context\nThere are two critical components of AI copilots for customer support. The first is that the AI system needs to be connected with as much information as possible (not just support tools like Zendesk or Intercom) and that the knowledge needs to be as fresh as possible. Sometimes a fix might even be in places rarely checked by CS such as pull requests in a code repository. The second critical component is the ability of the AI system to break down difficult concepts and convoluted processes into more digestible descriptions and for your team members to be able to chat back and forth with the system to build a better understanding.\n\nOnyx takes care of both of these. The system connects up to over 30+ different applications and the knowledge is pulled in constantly so that the information access is always up to date.", + "url": "https://docs.onyx.app/overview/core_features/code_interpreter", + "title": "Code Interpreter", + "content": "## Overview\n Example run where the LLM generates code to run data analysis on a business report.\nThe ability to execute code unlocks the ability for the LLMs to do things such as:\n- Performing larger calculations accurately\n- Running data analysis on provided files\n- Generating or modifying data/files\n**Note**: The code interpreter is built-in functionality available to all deployments without any configuration needed.\n## Features\n- **Python Runtime**: A secure Python runtime with all dangerous functionality removed (such as accessing the network,\n directories outside of the specified, etc.)\n- **Libraries**: Comes with a set of libraries such as numpy, pandas, scipy, matplotlib, and more.\n- **File Input**: Ability to pass arbitrary file types along with the code to run against it.\n- **File Output**: Files can be created and provided back to the user.\n- **STDIN/STDOUT Capture**: Ability to show the user any outputs of the programs executed.\n- **Graph Rendering**: The Onyx [Chat UI](/overview/core_features/chat)\n is able to render returned graphs and other visualization for the user.\n## Usage\nThe Code Interpreter does not need to be invoked explicitly,\nthe LLM will determine when to use it depending on the user query.\nIt can also be attached to custom Agents, giving the LLM the option to use it as needed.\n", "title_embedding": [ - 0.029702378436923027, - 0.04087577760219574, - 0.011759690940380096, - -0.015867559239268303, - 0.051922496408224106, - 0.04818926751613617, - -0.051036059856414795, - -0.000768028199672699, - -0.011680016294121742, - -0.04731091484427452, - -0.06819964945316315, - 0.02706378884613514, - 0.012011447921395302, - -0.0162456426769495, - 0.00561815220862627, 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Instead of searching and reading through hours of transcripts in preparation for a call, your team can now ask Onyx \"What specific features was ACME interested in seeing for the demo\". Since your team doesn't have time to read every transcript prior to a call, Onyx provides a more thorough summary because it can instantly parse hundreds of pages and distill out the relevant information. Even for fast lookups it becomes much more convenient - for example to brush up on connection building topics by asking \"What rapport building topic did we chat about in the last call with ACME\".\n\nKnow Every Product Update\nIt is impossible for Sales teams to keep up with every product update. Because of this, when a prospect has a question that the Sales team does not know, they have no choice but to rely on the Product and Engineering orgs to get an authoritative answer. Not only is this distracting to the other teams, it also slows down the time to respond to the prospect (and as we know, time is the biggest killer of deals). With Onyx, it is even possible to get answers live on call because of how fast accessing information becomes. A question like \"Have we shipped the Microsoft AD integration yet?\" can now be answered in seconds meaning that prospects can get answers while on the call instead of asynchronously and sales cycles are reduced as a result.", + "url": "https://docs.onyx.app/overview/core_features/connectors", + "title": "Connectors", + "content": "## What are Connectors?\nOnyx uses Connectors to build an understanding of your documents, team,\nand higher level concepts so that answers are grounded and specific to your organization's knowledge.\nConnectors:\n- Keep all updates synced between external systems and Onyx.\n- Pull in metadata and additional signals to ensure answer relevance.\n- Respect all user permissions (Enterprise Edition only).\n## Common Connector Questions\n Click this card to see the full list of supported connectors.\n You can also push documents directly into Onyx via [API](/developers/guides/index_files_ingestion_api)\n or via File Upload.\n All processing and storage of documents and metadata happen within Onyx.\n There are options to use LLMs or third party providers during the indexing flow but by default everything is\n processing entirely locally.\n Click this card to see more about security.\n In the same way LLMs are pre-trained on massive amounts of internet data,\n Onyx builds an understanding of all of the documents, concepts, and people within your organization.\n This allows Onyx to provide more accurate answer to questions that relate to internal knowledge compared to using the\n applications' provided search APIs at query time.\n Click this card to learn more about Internal Search in Onyx.\n", "title_embedding": [ - 0.008453648537397385, - 0.049128592014312744, - 0.0009390072082169354, - -0.011420674622058868, - 0.009472657926380634, - 0.05824451148509979, - -0.04129518195986748, - -0.018892904743552208, - -0.007598293945193291, - -0.03804052621126175, - -0.003747896058484912, - 0.005537204910069704, - 0.026590371504426003, - 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which can be rendered in the\nchat and easily downloaded.\n## Configuration\nCurrently, Onyx supports two APIs for image generation, both through OpenAI. In the future,\nthere likely will be support for other options such as Google Imagen or Stability AI.\n**GPT-Image-1**: Newer model, better prompt adherence. Likely a better default for most use cases.\n**DALL-E 3**: Older model, slightly better for more imaginative and rich styles.\n## Usage\nTo use **Image Generation**,\nbe explicit in the prompting since the system is tuned to not generate images unless directly instructed.\nSee below for the instructions provided to the system for when to create images.\n Tool Description:\n ```\n Generate an image from a prompt.\n ```\n Instruction (System Prompt) Modification:\n ```\n NEVER use image_gen unless the user specifically requests an image.\n ```\n This phrase is injected into the default **Instruction** for Onyx if the **Image Generation** (image_gen)\n tool is available.\n", + "title_embedding": [ + -0.017020173370838165, + 0.03963346406817436, + 0.00490707578137517, + -0.02459554560482502, + 0.02969607338309288, + 0.05662396922707558, + -0.04315737634897232, + -0.0017788930563256145, + -0.08292493224143982, + -0.03019525669515133, + -0.00880469474941492, + 0.03487468510866165, + 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Onyx uses [Connectors](/overview/core_features/connectors)\nto index knowledge from your team's applications to build an understanding of the documents, people,\nand concepts within your organization.\nDocuments, metadata, and access permissions are all kept up to date in near real time.\n## Search UI\n On the top left of the page, you can select the mode of the UI.\n Replace \"Auto\" with \"Search\" to always go into this view.\n Onyx's context retrieval respects user level permissions which is only configurable via the Enterprise Edition.\nOnyx's knowledge connectivity can be used via both the **Search** and [Chat](/overview/core_features/chat) interface.\nThe Search interface provides a better view of documents and is better for quickly accessing documents when the intent\nis not to get an answer.\nUsers do not need to explicitly select this mode \u2014 when a query is classified by Onyx as a document search,\nit will automatically go into this UI experience.\n### Filters\nThe Search UI also provides more advanced filtering options:\nThe top bar allows users to filter by time ranges (date range / time offset), authors, and tags (e.g. `Folder:\nEngineering`).\nThe side filters allow users to filter by the source type of the documents.\n## Chat UI\nContext from your applications are also available in the Chat UI and to Onyx Agents.\nDeep Research mode is also a Chat UI feature.\nClick [here](/overview/core_features/chat) to learn more about the Chat experience.\n", + "title_embedding": [ + 0.009123370051383972, + 0.037235453724861145, + 0.013692759908735752, + -0.0010621694382280111, + 0.011468728072941303, + 0.03305310755968094, + -0.04102027416229248, + -0.011397652328014374, + -0.049812328070402145, + -0.02994588576257229, + -0.0342310406267643, + 0.03455013036727905, + -0.021528830751776695, + -0.06181608885526657, + 0.006598589476197958, + -0.05661531537771225, + 0.034404464066028595, + -0.005459312349557877, + 0.005437854211777449, + 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"chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/core_features/web_search", + "title": "Web Search", + "content": "## Overview\nOnyx can access the internet for questions that require up to date information or for niche information that the LLM may\nnot be certain about.\nUsers can toggle the **Web Search** Action on the fly to override the LLM's decision.\nIf [Internal Search](/overview/core_features/internal_search) was used during the research process,\nOnyx will seamlessly combine web sources with internal documents in both the answer generation and for displaying in the\nUI.\n## Requirements\nTo provide Web Search functionality,\nOnyx requires both the ability to get search results and to be able to parse websites for more complete context.\nThis is broken down into 1) *the search provider* and 2) *the web scraper*.\n### Search Providers\nOnyx provides multiple search providers (pricing subject to change, please double check):\n| Name | Provider | Price | Benefit |\n|------|----------|-------|---------|\n| Google PSE | Google | Free tier + $5/1000 queries | Official Google search results, high trust option for security conscious teams. |\n| Serper | Serper.dev | Free tier + $0.30/1000 queries | Fast, and cost-effective |\n| Exa | Exa.ai | $5/1000 queries | AI-optimized with better semantic capabilities|\n### Web Scraper\nAs the Search Providers only give short snippets and metadata,\na scraper is used to fetch the full site contents for more complete/reliable answers.\n| Name | Requires Config | Benefits |\n|------|----------------|----------|\n| Onyx built-in | No | No third parties get access to user queries, free to use |\n| Firecrawl | Yes, API key | More performant with better edge case handling |\n", + "title_embedding": [ + 0.027322933077812195, + 0.03801405429840088, + 0.004930360242724419, + -0.009815420024096966, + 0.025635194033384323, + 0.04190409928560257, + -0.03269384801387787, + -0.009429137222468853, + -0.03549771010875702, + 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Stay tuned for updates!\n## What's Coming\nThe Onyx Workflows feature will enable:\n- **Asynchronous Actions**: Set up Agents to run when triggered by events or on a time basis.\n- **Batch Processing**: Set up instructions to run against large sets of objects to automate repeat work.\n- **Acknowledgements**: Optionally set up notifications to give approval for more sensitive Actions.\n- **Reports**: Get breakdowns of the work that was done for you in the background.\n", + "title_embedding": [ + -0.014278704300522804, + 0.036746032536029816, + 0.011647758074104786, + -0.009314833208918571, + 0.03278018534183502, + 0.020678354427218437, + -0.03167637065052986, + -0.02099463902413845, + 0.006498174741864204, + -0.0834314376115799, + -0.05220106244087219, + 0.039377737790346146, + 0.06538623571395874, + 0.004667028784751892, + -0.010628010146319866, + -0.04738559201359749, + 0.04378253221511841, + 0.018325254321098328, + -0.005063565447926521, + 0.028310589492321014, + 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"url": "https://docs.onyx.app/overview/getting_started/faq", + "title": "FAQ", + "content": "## General Questions\n You can ask Onyx about general world knowledge known to the LLM,\n knowledge from [connected applications](/overview/core_features/internal_search),\n or things searchable on the web (if [Web Search](/overview/core_features/web_search) is configured)\n Please check the [Security](/security/architecture/system_description) tab to learn more.\n Onyx is built with security and data privacy as a core commitment.\n Onyx is built for teams of all sizes whether it's a single user looking for a local Chat UI or a global enterprise\n needing a unified GenAI solution for the entire workforce.\n Onyx emphasizes data privacy and security as well as reliable responses by connecting to knowledge whether private\n or from the web.\n Yes, however Onyx needs an LLM to function properly.\n You can air gap the entire system but you would need to run a local LLM.\n Note that we strongly recommend using a recent and non-quantized LLM for the best experience.\n## Technical Issues\n The most common culprit is under-resourcing the deployment.\n Please refer to the [Resourcing](/deployment/getting_started/resourcing) page to double check.\n No! Onyx is intended to provide a fast and snappy experience. If the responses are slow,\n it may be due to a couple issues.\n - The LLM attached to the system is slow, has low throughput, or does not support streaming.\n - You've configured locally running models that are not the default but you do not have a GPU available to the\n system. Typically this is from setting a local reranking or embedding model.\n## Knowledge and Search\n If it's an internal document,\n it may be because the indexing of the application has not completed or because the access controls are incorrectly\n set. In cases of failure, the system always defaults to least permissive.\n The most common failure is that the [connector](/admin/connectors/overview) is incorrectly configured.\n Onyx connectors will fetch updates on a set schedule (typically 30 minutes),\n this polling frequency can be configured by the admin for each connector. The documents, metadata,\n and access permissions all receive updates.\n Web Search must be configured by an admin to be usable.\n It requires setting up one of the supported Search providers and also a scraper (though this is optional as Onyx\n provides one built in).\n", + "title_embedding": [ + 0.0254424549639225, + 0.049218129366636276, + 0.01710507646203041, + 0.005409142933785915, + 0.016579264774918556, + 0.03359467536211014, + -0.047864753752946854, + 0.02212352491915226, + -0.048316486179828644, + -0.04190720617771149, + -0.05027628317475319, + 0.0302424319088459, + 0.01330624334514141, + 0.0009234970202669501, + 0.011332277208566666, + -0.03979974240064621, + 0.037258606404066086, + -0.010172175243496895, + 0.023477792739868164, + 0.036772336810827255, + -0.00788051262497902, + -0.025729751214385033, + 0.015748800709843636, + -0.017618773505091667, + 0.05499717965722084, + -0.004128564614802599, + 0.016833258792757988, + -0.0035072562750428915, + 0.0055140964686870575, + 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questions!\n## AI-Powered Team\nGive your team secure access to all major LLMs such as GPT, Claude, Gemini, Deepseek, Llama,\nand more - all with access to advanced utilities.\n Use LLMs to help quickly summarize documents, explain key concepts, or create derivative works.\n Get answers to any topic using a combination of Web Search and internal knowledge or run a deeper exploration with\n Deep Research.\n Execute code to run complex data crunching tasks, generate graphs to help visualize results,\n and chat with the LLM to interpret the results.\n Generate images, draft content from scratch, or refine existing works with AI suggestions.\n## Enterprise Search\nQuickly access knowledge across all of your team's applications from wikis to chats and everything in between.\n A single interface to find knowledge across the entire organization.\n Leverage analytics and users feedback to identify holes in your team's knowledge base.\n Reduce misinformation and downstream costs.\n Let new team members unblock themselves and reduce distractions for more senior members.\n## Sales\nHelp your sales team stay up to date and focus on closing.\n Instantly access customer history, past interactions,\n and account details before any call or ask questions against past call transcripts.\n Gather competitive intelligence and stay ahead of the market.\n Create custom Agents to run deep analysis on your pipeline based on all connected knowledge.\n## Support\nKeep customers happy with faster resolutions and more reliable support.\n AI helps your team quickly surface past tickets and runbooks to craft accurate answers for users.\n Onyx ensures that all knowledge is kept up to date with any product or documentation changes.\n Build automations on Onyx to automatically resolve up to >90% of customer tickets.\n## Engineering\nHelp your team ship with speed and confidence through access to GenAI and internal knowledge.\n Accelerate development by having an AI copilot for every developer.\n Have Onyx find and explain design docs, internal services,\n and relevant other projects to ensure devs have full context for every project.\n Quickly check against past tickets and projects to avoid duplicate work and accumulation of tech debt.\n", + "title_embedding": [ + 0.017698800191283226, + 0.04772930219769478, + -0.0016525016399100423, + -0.004517734982073307, + 0.04559320956468582, + 0.009486325085163116, + -0.043294508010149, + -0.007329623214900494, + -0.021854909136891365, + -0.0008062636479735374, + -0.017165115103125572, + 0.012082917615771294, + 0.024485474452376366, + 0.006291019730269909, + -0.023886369541287422, + -0.05377965420484543, + 0.031321123242378235, + 0.008324896916747093, + -0.031064361333847046, + 0.012075562961399555, + -0.04280267283320427, + -0.04904203861951828, + 0.0022782422602176666, + -0.03427121043205261, + 0.023973196744918823, + -0.017222542315721512, + -0.006046854890882969, + 0.025779608637094498, + -0.010676244273781776, + -0.0409131683409214, + 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Open Source?\n We believe teams should feel safe with the AI platform that they adopt. That's why Onyx is fully transparent.\n You'll have peace of mind knowing exactly how your data is processed and stored,\n and all of this happening within the Onyx deployment.\n With GenAI being such a fundamental piece of modern company strategy,\n we want to offer the most flexible and future proof option.\n We understand that every team is unique in their needs so we're building Onyx with an emphasis on customizability,\n both for building on top of the platform and directly modifying it.\n Open source also gives control over to your team. With the GenAI space rapidly evolving,\n your vendor of choice may not always be aligned with your team's direction.\n OSS combines the benefits of building in-house with getting product updates for free.\n Open source also prevents lock in so that you can leverage any LLM provider (or your own LLM).\n## Commercial Viability\nWe are a team of builders and we want to have as many people find value from our software as possible.\nThis is our singular goal and everything that we do derives from this.\nTo push the boundaries of user experience and AI innovation,\nwe've assembled a core team of world-class developers who share this vision.\nTo borrow from Sid Sijbrandij (Co-Founder, GitLab):\n> \"We need to think in the interests of the project, while tending to the realities of running a business to support it... After all, we know that to sustain the project, we need to make it commercially viable.\"\nWe believe in radical transparency\u2014both in how we build open software and in the commercial realities of competing in\nthis rapidly evolving space.\n Every organization, regardless of size or budget, will always have access to Onyx's core capabilities\u2014including RAG,\n deep research, custom agents, and more\u2014completely free.\nFor organizations with special requirements\u2014such as usage auditing, granular access controls,\nand white-labeling\u2014we offer the Enterprise Edition, available both as a self-hosted solution and through Onyx Cloud.\nThe Enterprise Edition sustains our mission,\nenabling us to keep the vast majority of Onyx's features free and open for everyone.\n## On Contributions\nOnyx is a project built in collaboration with our community and we openly welcome contributions.\nIt is a point of emphasis of our team to ensure that the Onyx project continues to be easy for teams to contribute to or\nmaintain in house. This comes down to:\n- Intentional high level architecture.\n- Strong product direction and refusal to accept bloat for niche use cases.\n- A consistent and high quality of engineering best practices across the code base.\nTo that end,\nwe ask that contributors work on smaller issues to start and get approval from the maintainers for larger feature\ncontributions.\n", + "title_embedding": [ + -0.022274143993854523, + 0.024085983633995056, + 0.004168466664850712, + -0.024897504597902298, + 0.02458733320236206, + 0.038097232580184937, + -0.05161890387535095, + -0.0017337194876745343, + -0.015355128794908524, + -0.009740414097905159, + -0.03581155836582184, + 0.04829670861363411, + 0.01667267642915249, + 0.002830896060913801, + 0.022331146523356438, + -0.030550090596079826, + 0.04312089458107948, + -0.014599364250898361, + -0.0014605469768866897, + 0.040827617049217224, + 0.009301434271037579, + -0.04362654313445091, + 0.011992799118161201, + -0.04622611403465271, + 0.03580885007977486, + 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"url": "https://docs.onyx.app/overview/onyx_anywhere/chrome_extension", + "title": "Chrome Extension", + "content": " The Chrome extension is available but is undergoing a fairly major rework,\n it is recommended to wait until the next major release prior to deploying this\nUse the Onyx extension to ask questions from anywhere. You can also replace your new-tab page with a custom Onyx page:\n- Onyx Search on new tabs\n- Favorite website bookmarks\n- Onyx as a sidebar to any page in Chrome\n In the future,\n the Onyx Chrome Extension will allow you to ask questions about the page you are currently on and optionally index the\n recent pages into the Onyx knowledge base.\n You'll be able to ask questions about recently visited pages via both the extension and the Onyx web app.\n## Getting Started\nOnce your administrator has set up the Chrome extension for your organization, you can start using it immediately.\n**For Onyx Cloud users**: Install directly from the Chrome Web Store **For self-hosted users**:\nYour administrator will provide installation instructions\n## Using the Extension\n### **Ask Questions Anywhere**\n- Click the Onyx extension icon in your browser toolbar\n- Type your question in natural language\n- Get instant answers with source citations\n### **New Tab Experience**\n- Replace your default new tab with Onyx search\n- Access your favorite website bookmarks\n- Quick search across your organization's knowledge\n### **Sidebar Mode**\n- Open Onyx as a sidebar on any webpage\n- Ask questions about your current work without leaving the page\n- Perfect for research and context-sensitive queries\n## Settings and Options\nTo customize your extension experience:\n Click the three dots (...) next to the Onyx extension\n Select **Options**\n Configure your preferences for search, bookmarks, and new tab behavior\n **Need help with setup?** Contact your Onyx administrator for installation assistance or configuration questions.\n", + "title_embedding": [ + 0.013987557031214237, + 0.0448349267244339, + 0.025651562958955765, + 0.00898982584476471, + 0.016149720177054405, + 0.02496424876153469, + -0.037455834448337555, + 0.0017749951221048832, + -0.001626145443879068, + -0.027082936838269234, + -0.04595969244837761, + 0.07458677887916565, + -0.0043261693790555, + 0.014714955352246761, + 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This way you can associate Slack Apps with Onyx Agents for specific use cases.\n- Channel level configurations. Every channel can have different default behavior based on the channel's purpose.\n- Answers using internal or web knowledge are backed by citations and link back to the original sources.\n- Works in Threads, Channels and DMs.\n Try asking Onyx to summarize Threads by tagging the Onyx Slack Bot in the Thread!\n## Try it out\nThe Onyx Slack Bot is always live and serving answers to the community in our public Slack.\nTo test it out,\njoin the [community Slack](https://join.slack.com/t/onyx-dot-app/shared_invite/zt-34lu4m7xg-TsKGO6h8PDvR5W27zTdyhA)\nand see the #ask-onyx channel or tag **@OnyxBot** from anywhere.\n", + "title_embedding": [ + 0.048718396574258804, + 0.029821865260601044, + -0.0011853596661239862, + -0.03152287378907204, + 0.06518974900245667, + 0.041628312319517136, + -0.004485032521188259, + -0.030310792848467827, + 0.012000087648630142, + -0.07471709698438644, + -0.07690177857875824, + 0.06942982226610184, + 0.013170303776860237, + -0.01825779676437378, + 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Whether it is an employee asking about benefits details or how to set up the VPN for remote work, Onyx can help your team help themselves. This frees up your team to do the real impactful work of landing star candidates or improving your internal processes.\n\nAI Aided Onboarding\nOne of the periods where your team needs the most help is when they're just ramping up. Instead of feeling lost in dozens of new tools, Onyx gives them a single place where they can ask about anything in natural language. Whether it's how to set up their work environment or what their onboarding goals are, Onyx can walk them through every step with the help of Generative AI. This lets your team feel more empowered and gives time back to the more seasoned members of your team to focus on moving the needle.", + "url": "https://docs.onyx.app/overview/onyx_anywhere/web_interface", + "title": "Web App", + "content": "The Web App is the default way to use Onyx and the recommended for the most complete experience.\nThe admin panel is also a web-app exclusive feature which is the easiest way to manage the\n[Agents](/overview/core_features/agents), [Actions](/overview/core_features/actions),\n[Connectors](/overview/core_features/connectors), users, settings and more.\n A great place to get familiar with the experience is to start with the [Chat](/overview/core_features/chat)\n overview or the [Admin](/admin/overview) tab for managing the deployment.\nIf you're deploying Onyx locally (guide [here](/deployment/getting_started/quickstart)),\nyou should be able to access the Web UI at http://localhost:3000/.\n", "title_embedding": [ - 0.010730741545557976, - 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c4d9637cb5a..374ed15bb59 100644 --- a/backend/scripts/document_seeding_prep.py +++ b/backend/scripts/document_seeding_prep.py @@ -19,225 +19,778 @@ class SeedPresaveDocument(BaseModel): model = SentenceTransformer("nomic-ai/nomic-embed-text-v1", trust_remote_code=True) tokenizer = model.tokenizer +DOCUMENTATION_BASE_URL = "https://docs.onyx.app" + # This is easier than cleaning up the crawl, needs to be updated if the sites are changed -overview_title = "Use Cases Overview" -overview = ( - "How to leverage Onyx in your organization\n\n" - "Onyx Overview\n" - "Onyx is the AI Assistant connected to your organization's docs, apps, and people. " - "Onyx makes Generative AI more versatile for work by enabling new types of questions like " - '"What is the most common feature request we\'ve heard from customers this month". ' - "Whereas other AI systems have no context of your team and are generally unhelpful with work related questions, " - "Onyx makes it possible to ask these questions in natural language and get back answers in seconds.\n\n" - "Onyx can connect to +30 different tools and the use cases are not limited to the ones in the following pages. " - "The highlighted use cases are for inspiration and come from feedback gathered from our users and customers.\n\n\n" - "Common Getting Started Questions:\n\n" - "Why are these docs connected in my Onyx deployment?\n" - "Answer: This is just an example of how connectors work in Onyx. You can connect up your own team's knowledge " - "and you will be able to ask questions unique to your organization. Onyx will keep all of the knowledge up to date " - "and in sync with your connected applications.\n\n" - "Is my data being sent anywhere when I connect it up to Onyx?\n" - "Answer: No! Onyx is built with data security as our highest priority. We open sourced it so our users can know " - "exactly what is going on with their data. By default all of the document processing happens within Onyx. " - "The only time it is sent outward is for the GenAI call to generate answers.\n\n" - "Where is the feature for auto sync-ing document level access permissions from all connected sources?\n" - "Answer: This falls under the Enterprise Edition set of Onyx features built on top of the MIT/community edition. " - "If you are on Onyx Cloud, you have access to them by default. If you're running it yourself, reach out to the " - "Onyx team to receive access." -) - -enterprise_search_title = "Enterprise Search" -enterprise_search_1 = ( - "Value of Enterprise Search with Onyx\n\n" - "What is Enterprise Search and why is it Important?\n" - "An Enterprise Search system gives team members a single place to access all of the disparate knowledge " - "of an organization. Critical information is saved across a host of channels like call transcripts with " - "prospects, engineering design docs, IT runbooks, customer support email exchanges, project management " - "tickets, and more. As fast moving teams scale up, information gets spread out and more disorganized.\n\n" - "Since it quickly becomes infeasible to check across every source, decisions get made on incomplete " - "information, employee satisfaction decreases, and the most valuable members of your team are tied up " - "with constant distractions as junior teammates are unable to unblock themselves. Onyx solves this " - "problem by letting anyone on the team access all of the knowledge across your organization in a " - "permissioned and secure way. Users can ask questions in natural language and get back answers and " - "documents across all of the connected sources instantly.\n\n" - "What's the real cost?\n" - "A typical knowledge worker spends over 2 hours a week on search, but more than that, the cost of " - "incomplete or incorrect information can be extremely high. Customer support/success that isn't able " - "to find the reference to similar cases could cause hours or even days of delay leading to lower " - "customer satisfaction or in the worst case - churn. An account exec not realizing that a prospect had " - "previously mentioned a specific need could lead to lost deals. An engineer not realizing a similar " - "feature had previously been built could result in weeks of wasted development time and tech debt with " - "duplicate implementation. With a lack of knowledge, your whole organization is navigating in the dark " - "- inefficient and mistake prone." -) - -enterprise_search_2 = ( - "More than Search\n" - "When analyzing the entire corpus of knowledge within your company is as easy as asking a question " - "in a search bar, your entire team can stay informed and up to date. Onyx also makes it trivial " - "to identify where knowledge is well documented and where it is lacking. Team members who are centers " - "of knowledge can begin to effectively document their expertise since it is no longer being thrown into " - "a black hole. All of this allows the organization to achieve higher efficiency and drive business outcomes.\n\n" - "With Generative AI, the entire user experience has evolved as well. For example, instead of just finding similar " - "cases for your customer support team to reference, Onyx breaks down the issue and explains it so that even " - "the most junior members can understand it. This in turn lets them give the most holistic and technically accurate " - "response possible to your customers. On the other end, even the super stars of your sales team will not be able " - "to review 10 hours of transcripts before hopping on that critical call, but Onyx can easily parse through it " - "in mere seconds and give crucial context to help your team close." -) - -ai_platform_title = "AI Platform" -ai_platform = ( - "Build AI Agents powered by the knowledge and workflows specific to your organization.\n\n" - "Beyond Answers\n" - "Agents enabled by generative AI and reasoning capable models are helping teams to automate their work. " - "Onyx is helping teams make it happen. Onyx provides out of the box user chat sessions, attaching custom tools, " - "handling LLM reasoning, code execution, data analysis, referencing internal knowledge, and much more.\n\n" - "Onyx as a platform is not a no-code agent builder. We are made by developers for developers and this gives your " - "team the full flexibility and power to create agents not constrained by blocks and simple logic paths.\n\n" - "Flexibility and Extensibility\n" - "Onyx is open source and completely whitebox. This not only gives transparency to what happens within the system " - "but also means that your team can directly modify the source code to suit your unique needs." -) - -customer_support_title = "Customer Support" -customer_support = ( - "Help your customer support team instantly answer any question across your entire product.\n\n" - "AI Enabled Support\n" - "Customer support agents have one of the highest breadth jobs. They field requests that cover the entire surface " - "area of the product and need to help your users find success on extremely short timelines. " - "Because they're not the same people who designed or built the system, they often lack the depth of understanding " - "needed - resulting in delays and escalations to other teams. Modern teams are leveraging AI to help their CS team " - "optimize the speed and quality of these critical customer-facing interactions.\n\n" - "The Importance of Context\n" - "There are two critical components of AI copilots for customer support. The first is that the AI system needs to be " - "connected with as much information as possible (not just support tools like Zendesk or Intercom) and that the " - "knowledge needs to be as fresh as possible. Sometimes a fix might even be in places rarely checked by CS such as " - "pull requests in a code repository. The second critical component is the ability of the AI system to break down " - "difficult concepts and convoluted processes into more digestible descriptions and for your team members to be able " - "to chat back and forth with the system to build a better understanding.\n\n" - "Onyx takes care of both of these. The system connects up to over 30+ different applications and the knowledge is " - "pulled in constantly so that the information access is always up to date." -) - -sales_title = "Sales" -sales = ( - "Keep your team up to date on every conversation and update so they can close.\n\n" - "Recall Every Detail\n" - "Being able to instantly revisit every detail of any call without reading transcripts is helping Sales teams provide " - "more tailored pitches, build stronger relationships, and close more deals. Instead of searching and reading through " - 'hours of transcripts in preparation for a call, your team can now ask Onyx "What specific features was ACME ' - "interested in seeing for the demo\". Since your team doesn't have time to read every transcript prior to a call, " - "Onyx provides a more thorough summary because it can instantly parse hundreds of pages and distill out the relevant " - "information. Even for fast lookups it becomes much more convenient - for example to brush up on connection building " - 'topics by asking "What rapport building topic did we chat about in the last call with ACME".\n\n' - "Know Every Product Update\n" - "It is impossible for Sales teams to keep up with every product update. Because of this, when a prospect has a question " - "that the Sales team does not know, they have no choice but to rely on the Product and Engineering orgs to get an " - "authoritative answer. Not only is this distracting to the other teams, it also slows down the time to respond to the " - "prospect (and as we know, time is the biggest killer of deals). With Onyx, it is even possible to get answers live " - 'on call because of how fast accessing information becomes. A question like "Have we shipped the Microsoft AD ' - 'integration yet?" can now be answered in seconds meaning that prospects can get answers while on the call instead of ' - "asynchronously and sales cycles are reduced as a result." -) - -operations_title = "Operations" -operations = ( - "Double the productivity of your Ops teams like IT, HR, etc.\n\n" - "Automatically Resolve Tickets\n" - "Modern teams are leveraging AI to auto-resolve up to 50% of tickets. Whether it is an employee asking about benefits " - "details or how to set up the VPN for remote work, Onyx can help your team help themselves. This frees up your team to " - "do the real impactful work of landing star candidates or improving your internal processes.\n\n" - "AI Aided Onboarding\n" - "One of the periods where your team needs the most help is when they're just ramping up. Instead of feeling lost in dozens " - "of new tools, Onyx gives them a single place where they can ask about anything in natural language. Whether it's how to " - "set up their work environment or what their onboarding goals are, Onyx can walk them through every step with the help " - "of Generative AI. This lets your team feel more empowered and gives time back to the more seasoned members of your team to " - "focus on moving the needle." +welcome_title = "Welcome to Onyx!" +welcome = ( + "## What is Onyx?\n" + "Onyx is your team's entry point to Generative AI,\n" + "offering a natural language interface for any LLM while integrating seamlessly with your knowledge and applications.\n" + "Build tailored AI Agents, search for documents, browse the web, and more — all in one place.\n" + "## Major Features\n" + " The best way to quickly get familiar with Onyx is to check out the features below!\n" + " Conversational interface to your LLMs, Agents, and knowledge.\n" + " Create AI agents tailored to your use cases with custom instructions, knowledge, and actions.\n" + " Search through your organization's knowledge and connected applications.\n" + " Enrich the knowledge of the LLM with the latest information from the internet.\n" + " Enable Actions connected to your team's applications to let Agents automate work.\n" + " Execute code directly within your chat sessions for complex calculations and data analysis.\n" + " To learn about other features, check out the [Core Features](/overview/core_features/chat)\n" + " section or visit the [Admin Docs](/admin/overview) for an even more in depth breakdown.\n" + "## Why Onyx?\n" + "Why choose Onyx over ChatGPT, Microsoft Copilot, Google Gemini, or Glean?\n" + "- **Reliable Responses from Internal Knowledge:**\n" + " Onyx builds a knowledge index using LLM-native techniques. Powered with contextual retrieval, advanced RAG,\n" + " hybrid search, and AI-generated knowledge graphs, Onyx ensures the most relevant results and the least hallucinations.\n" + "- **Open Source:**\n" + " Onyx is made for security, data privacy, and ease of self-hosting. It's easy and free to get started.\n" + " For teams investing in a long-term GenAI strategy,\n" + " Onyx can be easily extended or customized to your team's future needs.\n" + "- **Highly Configurable:**\n" + " Onyx is designed to be flexible, so you can optimize the experience for your team. Plug and play any LLM model,\n" + " connect only the data you need, and enable the features you want your team to use.\n" + "## Ready to Get Started?\n" + "**Next Steps:**\n" + " Checkout our quickstart guide to self-host Onyx in minutes.\n" + " Sign up for a free trial of Onyx Cloud, no credit card required.\n" +) +core_features_actions_title = "Actions & MCP" +core_features_actions = ( + "## Overview\n" + "**Actions** give Agents the ability to interact with external systems.\n" + "Onyx comes with 4 built-in Actions and allows users to configure additional ones via\n" + "[OpenAPI](https://en.wikipedia.org/wiki/OpenAPI_Specification)\n" + "and [Model Context Protocol](https://modelcontextprotocol.io/) (MCP).\n" + "The built-in Actions include:\n" + "## Custom Actions\n" + "Onyx offers flexible options for configuring both custom Actions and their associated authentication.\n" + "Admins can choose to:\n" + "- Use a single shared authentication, giving all users the same level of access to Actions.\n" + "- Require each user to complete their own authentication flow, so Actions respect individual user permissions.\n" + "Onyx supports both token-based authentication and OAuth.\n" + "## Actions Button\n" + "In the Chat input bar, Actions are grouped by the MCP server or OpenAPI schema they are registered with.\n" + "Users have the flexibility to turn on/off the Actions that the Agent/LLM has access to on the fly.\n" +) +core_features_agents_title = "Agents" +core_features_agents = ( + "Agents are a combination of user specified instructions, knowledge, and [Actions](/overview/core_features/actions).\n" + "Think of them as AI team members that are optimized for a specific task.\n" + "Onyx Agents can be for individual use or shared with other users or\n" + "[user-groups](/admin/user_management/users_and_groups) within Onyx.\n" + "## When to use an Agent\n" + "Use agents to build the best experience for repeat use cases,\n" + "especially those that can be shared with other members of the team.\n" + "Some common examples include:\n" + "- Onboarding Assistant\n" + "- AI Helpdesk\n" + "- Engineer Copilot\n" + "- Legal Reviewer\n" + "These are typically scoped down to a particular task such as reviewing documents to ensure they comply with security\n" + "policies, filling out RFPs based on previously completed ones, etc.\n" + "## Creating an Agent\n" + "### Instructions (Prompting)\n" + " The Instruction field is infinitely flexible so it is recommended to test different variations and verify the behavior\n" + " before sharing the Agent broadly with your team.\n" + "Provided below for inspiration is the **Instruction** for the default Onyx experience.\n" + " ```\n" + " You are a highly capable, thoughtful, and precise assistant. Your goal is to deeply understand the user's intent," + " ask clarifying questions when needed, think step-by-step through complex problems, provide clear and accurate answers," + " and proactively anticipate helpful follow-up information. Always prioritize being truthful, nuanced, insightful, and efficient.\n" # noqa: E501 + " The current date is [[CURRENT_DATETIME]]\n" + " You use different text styles, bolding, emojis (sparingly), block quotes, and other formatting to make your responses more readable and engaging.\n" # noqa: E501 + " You use proper Markdown and LaTeX to format your responses for math, scientific, and chemical formulas, symbols, etc.:" + " '$$\\n[expression]\\n$$' for standalone cases and '\\( [expression] \\)' when inline. For code you prefer to use Markdown and specify the language.\n" # noqa: E501 + " You can use Markdown horizontal rules (---) to separate sections of your responses.\n" + " You can use Markdown tables to format your responses for data, lists, and other structured information.\n" + " ```\n" + " Note that `[[CURRENT_DATETIME]]` is dynamically replaced and there may be additional Action use instructions\n" + " depending on the enabled Actions.\n" + "One of the best parts of creating an Agent is the ability to control the goal/behavior of the Agent.\n" + "The instructions are purely in natural language and can include things like:\n" + "- Always provide your results in a table.\n" + "- Try to quote directly from the documents rather than rewording anything.\n" + "- Flag information from documents that are older than 3 months.\n" + "### Knowledge\n" + " It is typically best to include only the necessary knowledge for the Agent to complete its task.\n" + " The more scoped down the documents, the more reliable the performance.\n" + "When creating an Agent, you can include both knowledge from [connectors](/overview/core_features/connectors)\n" + "or file upload. The knowledge from connectors will be kept up to date as documents change in the external sources.\n" + "### Actions\n" + " If any of the built-in actions (Web Search, Internal Search, Image Generation, Code Interpreter) are missing,\n" + " contact your Onyx admin.\n" + " These must be set up in the admin-panel before being made available in the Agent creation flow.\n" + "[Actions](/overview/core_features/actions) (sometimes known as Tools)\n" + "allow the Agents to do things in external applications via APIs.\n" + "Some tools help Onyx give better answers (such as the Onyx built-in tools)\n" + "while others allow the system to do more than answer questions.\n" + "Some example common Actions include:\n" + "- Updating ticket statuses based on the conversation and if the user's needs were addressed.\n" + "- Checking the status of a service to give real-time answers.\n" + "- Moving deals along a sales pipeline in a CRM based on call transcripts or user request.\n" +) +core_features_chat_title = "Chat" +core_features_chat = ( + " On the top left of the page (just right of the sidebar), you can select the mode of the UI.\n" + ' Replace "Auto" with "Chat" to always go into this Chat UI.\n' + "Onyx provides a natural language chat interface as the main way of interacting with the features.\n" + "The page below contains an overview of the main components and features.\n" + "## Input Bar\n" + "### Chat with Files / URLs\n" + "The leftmost button of the input bar lets users add context into the Chat session.\n" + "Users can choose between uploading files or selecting URLs as well as reusing previous files or URLs.\n" + " URLs behind Logins, Captcha, or Paywalls that are not scrapeable are not accessible.\n" + " Consider using a [Connector](/overview/core_features/connectors) instead.\n" + "### Actions Selector\n" + "The second button lets users disable or force the use of Actions. There are 4 built-in Actions:\n" + "- **[Internal Search](/overview/core_features/internal_search)**:\n" + " Enables the LLM to search the indexed knowledge from [Connectors](/overview/core_features/connectors).\n" + "- **[Web Search](/overview/core_features/web_search)**: Enables the LLM to search the internet.\n" + " Requires an admin to set up an API key for a search provider.\n" + "- **[Code Interpreter](/overview/core_features/code_interpreter)**:\n" + " Enables the LLM to use a sandboxed Python runtime to execute code and run data analysis.\n" + "- **[Image Generation](/overview/core_features/image_generation)**: Allows the LLM to generate images.\n" + " Requires setting up an image generation API.\n" + "The Actions below the separator represent custom admin configured Actions.\n" + "See [Actions & MCP](/overview/core_features/actions) to learn about custom Actions.\n" + "### Deep Research\n" + "Toggle **Deep Research** using the hourglass icon. When turned on, the LLM will be able to run many cycles of thinking,\n" + "research, and actions to give the best possible result for the user.\n" + "This mode is intended for complicated questions that may need to pull together many sources together or requires\n" + "significant reasoning.\n" + " Deep Research may take up to several minutes and could cost many times (>10x) the token cost of a normal inference.\n" + "### Model Selector\n" + "Onyx supports all major LLM providers as well as self-hosting options like Ollama, VLLM, etc. For select models,\n" + "users can also configure the creativity and reasoning level.\n" + "## Sidebar Contents\n" + "The left sidebar contains:\n" + "- `New Session` button to clear the history and start a new Chat or [Search](/overview/core_features/internal_search) session.\n" # noqa: E501 + "- `Projects` to help users organize chats and reuse different sets of documents. See section below for more info.\n" + "- `Agents` section to start a new session with yours or your team's custom [Agents](/overview/core_features/agents).\n" + "- `Sessions` section containing a list of the most recent conversations.\n" + "The right sidebar contains sources and citations that were used in generating the answer.\n" + "These can come from either `Internal Search` or `Web Search` or both.\n" + "Documents in the right sidebar can also be selected to be included in full for the next message in the Chat session.\n" + " It's often useful to ask a question to find a document, then select it to do a deep dive on it.\n" + "## Projects\n" + "**Projects** are a collection of instructions (prompts) and files as well as a grouping for chats.\n" + "Use projects to organize ongoing work,\n" + "or as a handy way to reuse instructions and files without going through the Agent creation flow.\n" + "## Miscellaneous Chat Features\n" + "**Chat Sharing** - share chats with other team members by using the share-chat button in the top right (left of the\n" + "Sources sidebar).\n" + "**Feedback** - give feedback viewable to the admins using the thumbs-up/thumbs-down buttons when hovering an LLM\n" + "response\n" + "**Regenerate** - modify your inputs by clicking the user messages or regenerate the LLM response with another model.\n" + "**Copying** - copy the LLM output or markdown/code blocks by clicking on the copy button which shows on hover.\n" +) +core_features_code_interpreter_title = "Code Interpreter" +core_features_code_interpreter = ( + "## Overview\n" + " Example run where the LLM generates code to run data analysis on a business report.\n" + "The ability to execute code unlocks the ability for the LLMs to do things such as:\n" + "- Performing larger calculations accurately\n" + "- Running data analysis on provided files\n" + "- Generating or modifying data/files\n" + "**Note**: The code interpreter is built-in functionality available to all deployments without any configuration needed.\n" + "## Features\n" + "- **Python Runtime**: A secure Python runtime with all dangerous functionality removed (such as accessing the network,\n" + " directories outside of the specified, etc.)\n" + "- **Libraries**: Comes with a set of libraries such as numpy, pandas, scipy, matplotlib, and more.\n" + "- **File Input**: Ability to pass arbitrary file types along with the code to run against it.\n" + "- **File Output**: Files can be created and provided back to the user.\n" + "- **STDIN/STDOUT Capture**: Ability to show the user any outputs of the programs executed.\n" + "- **Graph Rendering**: The Onyx [Chat UI](/overview/core_features/chat)\n" + " is able to render returned graphs and other visualization for the user.\n" + "## Usage\n" + "The Code Interpreter does not need to be invoked explicitly,\n" + "the LLM will determine when to use it depending on the user query.\n" + "It can also be attached to custom Agents, giving the LLM the option to use it as needed.\n" +) +core_features_connectors_title = "Connectors" +core_features_connectors = ( + "## What are Connectors?\n" + "Onyx uses Connectors to build an understanding of your documents, team,\n" + "and higher level concepts so that answers are grounded and specific to your organization's knowledge.\n" + "Connectors:\n" + "- Keep all updates synced between external systems and Onyx.\n" + "- Pull in metadata and additional signals to ensure answer relevance.\n" + "- Respect all user permissions (Enterprise Edition only).\n" + "## Common Connector Questions\n" + " Click this card to see the full list of supported connectors.\n" + " You can also push documents directly into Onyx via [API](/developers/guides/index_files_ingestion_api)\n" + " or via File Upload.\n" + " All processing and storage of documents and metadata happen within Onyx.\n" + " There are options to use LLMs or third party providers during the indexing flow but by default everything is\n" + " processing entirely locally.\n" + " Click this card to see more about security.\n" + " In the same way LLMs are pre-trained on massive amounts of internet data,\n" + " Onyx builds an understanding of all of the documents, concepts, and people within your organization.\n" + " This allows Onyx to provide more accurate answer to questions that relate to internal knowledge compared to using the\n" + " applications' provided search APIs at query time.\n" + " Click this card to learn more about Internal Search in Onyx.\n" +) +core_features_image_generation_title = "Image Generation" +core_features_image_generation = ( + "## Overview\n" + "The image generation feature allows users to create PNG images according to their prompts which can be rendered in the\n" + "chat and easily downloaded.\n" + "## Configuration\n" + "Currently, Onyx supports two APIs for image generation, both through OpenAI. In the future,\n" + "there likely will be support for other options such as Google Imagen or Stability AI.\n" + "**GPT-Image-1**: Newer model, better prompt adherence. Likely a better default for most use cases.\n" + "**DALL-E 3**: Older model, slightly better for more imaginative and rich styles.\n" + "## Usage\n" + "To use **Image Generation**,\n" + "be explicit in the prompting since the system is tuned to not generate images unless directly instructed.\n" + "See below for the instructions provided to the system for when to create images.\n" + " Tool Description:\n" + " ```\n" + " Generate an image from a prompt.\n" + " ```\n" + " Instruction (System Prompt) Modification:\n" + " ```\n" + " NEVER use image_gen unless the user specifically requests an image.\n" + " ```\n" + " This phrase is injected into the default **Instruction** for Onyx if the **Image Generation** (image_gen)\n" + " tool is available.\n" +) +core_features_internal_search_title = "Internal Search" +core_features_internal_search = ( + "One of Onyx's most standout features is the ability to enrich the LLM's general world knowledge with context unique to\n" + "your team. Onyx uses [Connectors](/overview/core_features/connectors)\n" + "to index knowledge from your team's applications to build an understanding of the documents, people,\n" + "and concepts within your organization.\n" + "Documents, metadata, and access permissions are all kept up to date in near real time.\n" + "## Search UI\n" + " On the top left of the page, you can select the mode of the UI.\n" + ' Replace "Auto" with "Search" to always go into this view.\n' + " Onyx's context retrieval respects user level permissions which is only configurable via the Enterprise Edition.\n" + "Onyx's knowledge connectivity can be used via both the **Search** and [Chat](/overview/core_features/chat) interface.\n" + "The Search interface provides a better view of documents and is better for quickly accessing documents when the intent\n" + "is not to get an answer.\n" + "Users do not need to explicitly select this mode — when a query is classified by Onyx as a document search,\n" + "it will automatically go into this UI experience.\n" + "### Filters\n" + "The Search UI also provides more advanced filtering options:\n" + "The top bar allows users to filter by time ranges (date range / time offset), authors, and tags (e.g. `Folder:\n" + "Engineering`).\n" + "The side filters allow users to filter by the source type of the documents.\n" + "## Chat UI\n" + "Context from your applications are also available in the Chat UI and to Onyx Agents.\n" + "Deep Research mode is also a Chat UI feature.\n" + "Click [here](/overview/core_features/chat) to learn more about the Chat experience.\n" +) +core_features_web_search_title = "Web Search" +core_features_web_search = ( + "## Overview\n" + "Onyx can access the internet for questions that require up to date information or for niche information that the LLM may\n" + "not be certain about.\n" + "Users can toggle the **Web Search** Action on the fly to override the LLM's decision.\n" + "If [Internal Search](/overview/core_features/internal_search) was used during the research process,\n" + "Onyx will seamlessly combine web sources with internal documents in both the answer generation and for displaying in the\n" + "UI.\n" + "## Requirements\n" + "To provide Web Search functionality,\n" + "Onyx requires both the ability to get search results and to be able to parse websites for more complete context.\n" + "This is broken down into 1) *the search provider* and 2) *the web scraper*.\n" + "### Search Providers\n" + "Onyx provides multiple search providers (pricing subject to change, please double check):\n" + "| Name | Provider | Price | Benefit |\n" + "|------|----------|-------|---------|\n" + "| Google PSE | Google | Free tier + $5/1000 queries | Official Google search results, high trust option for security conscious teams. |\n" # noqa: E501 + "| Serper | Serper.dev | Free tier + $0.30/1000 queries | Fast, and cost-effective |\n" + "| Exa | Exa.ai | $5/1000 queries | AI-optimized with better semantic capabilities|\n" + "### Web Scraper\n" + "As the Search Providers only give short snippets and metadata,\n" + "a scraper is used to fetch the full site contents for more complete/reliable answers.\n" + "| Name | Requires Config | Benefits |\n" + "|------|----------------|----------|\n" + "| Onyx built-in | No | No third parties get access to user queries, free to use |\n" + "| Firecrawl | Yes, API key | More performant with better edge case handling |\n" +) +core_features_workflows_title = "Workflows (Coming Soon)" +core_features_workflows = ( + " **Coming Soon!**\n" + " This feature is currently under development. Stay tuned for updates!\n" + "## What's Coming\n" + "The Onyx Workflows feature will enable:\n" + "- **Asynchronous Actions**: Set up Agents to run when triggered by events or on a time basis.\n" + "- **Batch Processing**: Set up instructions to run against large sets of objects to automate repeat work.\n" + "- **Acknowledgements**: Optionally set up notifications to give approval for more sensitive Actions.\n" + "- **Reports**: Get breakdowns of the work that was done for you in the background.\n" +) +getting_started_faq_title = "FAQ" +getting_started_faq = ( + "## General Questions\n" + " You can ask Onyx about general world knowledge known to the LLM,\n" + " knowledge from [connected applications](/overview/core_features/internal_search),\n" + " or things searchable on the web (if [Web Search](/overview/core_features/web_search) is configured)\n" + " Please check the [Security](/security/architecture/system_description) tab to learn more.\n" + " Onyx is built with security and data privacy as a core commitment.\n" + " Onyx is built for teams of all sizes whether it's a single user looking for a local Chat UI or a global enterprise\n" + " needing a unified GenAI solution for the entire workforce.\n" + " Onyx emphasizes data privacy and security as well as reliable responses by connecting to knowledge whether private\n" + " or from the web.\n" + " Yes, however Onyx needs an LLM to function properly.\n" + " You can air gap the entire system but you would need to run a local LLM.\n" + " Note that we strongly recommend using a recent and non-quantized LLM for the best experience.\n" + "## Technical Issues\n" + " The most common culprit is under-resourcing the deployment.\n" + " Please refer to the [Resourcing](/deployment/getting_started/resourcing) page to double check.\n" + " No! Onyx is intended to provide a fast and snappy experience. If the responses are slow,\n" + " it may be due to a couple issues.\n" + " - The LLM attached to the system is slow, has low throughput, or does not support streaming.\n" + " - You've configured locally running models that are not the default but you do not have a GPU available to the\n" + " system. Typically this is from setting a local reranking or embedding model.\n" + "## Knowledge and Search\n" + " If it's an internal document,\n" + " it may be because the indexing of the application has not completed or because the access controls are incorrectly\n" + " set. In cases of failure, the system always defaults to least permissive.\n" + " The most common failure is that the [connector](/admin/connectors/overview) is incorrectly configured.\n" + " Onyx connectors will fetch updates on a set schedule (typically 30 minutes),\n" + " this polling frequency can be configured by the admin for each connector. The documents, metadata,\n" + " and access permissions all receive updates.\n" + " Web Search must be configured by an admin to be usable.\n" + " It requires setting up one of the supported Search providers and also a scraper (though this is optional as Onyx\n" + " provides one built in).\n" +) +getting_started_use_cases_title = "Use Cases" +getting_started_use_cases = ( + " [See how Ramp uses Onyx](https://www.onyx.app/blog/ramp-case-study)\n" + " to automatically resolve 93% of internal and customer questions!\n" + "## AI-Powered Team\n" + "Give your team secure access to all major LLMs such as GPT, Claude, Gemini, Deepseek, Llama,\n" + "and more - all with access to advanced utilities.\n" + " Use LLMs to help quickly summarize documents, explain key concepts, or create derivative works.\n" + " Get answers to any topic using a combination of Web Search and internal knowledge or run a deeper exploration with\n" + " Deep Research.\n" + " Execute code to run complex data crunching tasks, generate graphs to help visualize results,\n" + " and chat with the LLM to interpret the results.\n" + " Generate images, draft content from scratch, or refine existing works with AI suggestions.\n" + "## Enterprise Search\n" + "Quickly access knowledge across all of your team's applications from wikis to chats and everything in between.\n" + " A single interface to find knowledge across the entire organization.\n" + " Leverage analytics and users feedback to identify holes in your team's knowledge base.\n" + " Reduce misinformation and downstream costs.\n" + " Let new team members unblock themselves and reduce distractions for more senior members.\n" + "## Sales\n" + "Help your sales team stay up to date and focus on closing.\n" + " Instantly access customer history, past interactions,\n" + " and account details before any call or ask questions against past call transcripts.\n" + " Gather competitive intelligence and stay ahead of the market.\n" + " Create custom Agents to run deep analysis on your pipeline based on all connected knowledge.\n" + "## Support\n" + "Keep customers happy with faster resolutions and more reliable support.\n" + " AI helps your team quickly surface past tickets and runbooks to craft accurate answers for users.\n" + " Onyx ensures that all knowledge is kept up to date with any product or documentation changes.\n" + " Build automations on Onyx to automatically resolve up to >90% of customer tickets.\n" + "## Engineering\n" + "Help your team ship with speed and confidence through access to GenAI and internal knowledge.\n" + " Accelerate development by having an AI copilot for every developer.\n" + " Have Onyx find and explain design docs, internal services,\n" + " and relevant other projects to ensure devs have full context for every project.\n" + " Quickly check against past tickets and projects to avoid duplicate work and accumulation of tech debt.\n" +) +miscellaneous_contact_us_title = "Contact Us" +miscellaneous_contact_us = "Contact us at [hello@onyx.app](mailto:hello@onyx.app) or book a call with us on our [Calendar](https://cal.com/team/onyx/founders)." +miscellaneous_open_source_statement_title = "Open Source Statement" +miscellaneous_open_source_statement = ( + "## Our Mission\n" + "Our mission is to make Generative AI and knowledge accessible to every team worldwide.\n" + "As large language models—both proprietary and open-source—become increasingly widespread,\n" + "Onyx serves as the interface to their knowledge and reasoning capabilities.\n" + "Onyx enriches the utility of the LLM by providing additional context (both web and team internal),\n" + "built-in tools like code interpreter, and user created Actions.\n" + "## Why Open Source?\n" + " We believe teams should feel safe with the AI platform that they adopt. That's why Onyx is fully transparent.\n" + " You'll have peace of mind knowing exactly how your data is processed and stored,\n" + " and all of this happening within the Onyx deployment.\n" + " With GenAI being such a fundamental piece of modern company strategy,\n" + " we want to offer the most flexible and future proof option.\n" + " We understand that every team is unique in their needs so we're building Onyx with an emphasis on customizability,\n" + " both for building on top of the platform and directly modifying it.\n" + " Open source also gives control over to your team. With the GenAI space rapidly evolving,\n" + " your vendor of choice may not always be aligned with your team's direction.\n" + " OSS combines the benefits of building in-house with getting product updates for free.\n" + " Open source also prevents lock in so that you can leverage any LLM provider (or your own LLM).\n" + "## Commercial Viability\n" + "We are a team of builders and we want to have as many people find value from our software as possible.\n" + "This is our singular goal and everything that we do derives from this.\n" + "To push the boundaries of user experience and AI innovation,\n" + "we've assembled a core team of world-class developers who share this vision.\n" + "To borrow from Sid Sijbrandij (Co-Founder, GitLab):\n" + '> "We need to think in the interests of the project, while tending to the realities of running a business to support it...' + 'After all, we know that to sustain the project, we need to make it commercially viable."\n' + "We believe in radical transparency—both in how we build open software and in the commercial realities of competing in\n" + "this rapidly evolving space.\n" + " Every organization, regardless of size or budget, will always have access to Onyx's core capabilities—including RAG,\n" + " deep research, custom agents, and more—completely free.\n" + "For organizations with special requirements—such as usage auditing, granular access controls,\n" + "and white-labeling—we offer the Enterprise Edition, available both as a self-hosted solution and through Onyx Cloud.\n" + "The Enterprise Edition sustains our mission,\n" + "enabling us to keep the vast majority of Onyx's features free and open for everyone.\n" + "## On Contributions\n" + "Onyx is a project built in collaboration with our community and we openly welcome contributions.\n" + "It is a point of emphasis of our team to ensure that the Onyx project continues to be easy for teams to contribute to or\n" + "maintain in house. This comes down to:\n" + "- Intentional high level architecture.\n" + "- Strong product direction and refusal to accept bloat for niche use cases.\n" + "- A consistent and high quality of engineering best practices across the code base.\n" + "To that end,\n" + "we ask that contributors work on smaller issues to start and get approval from the maintainers for larger feature\n" + "contributions.\n" +) +onyx_anywhere_chrome_extension_title = "Chrome Extension" +onyx_anywhere_chrome_extension = ( + " The Chrome extension is available but is undergoing a fairly major rework,\n" + " it is recommended to wait until the next major release prior to deploying this\n" + "Use the Onyx extension to ask questions from anywhere. You can also replace your new-tab page with a custom Onyx page:\n" + "- Onyx Search on new tabs\n" + "- Favorite website bookmarks\n" + "- Onyx as a sidebar to any page in Chrome\n" + " In the future,\n" + " the Onyx Chrome Extension will allow you to ask questions about the page you are currently on and optionally index the\n" + " recent pages into the Onyx knowledge base.\n" + " You'll be able to ask questions about recently visited pages via both the extension and the Onyx web app.\n" + "## Getting Started\n" + "Once your administrator has set up the Chrome extension for your organization, you can start using it immediately.\n" + "**For Onyx Cloud users**: Install directly from the Chrome Web Store **For self-hosted users**:\n" + "Your administrator will provide installation instructions\n" + "## Using the Extension\n" + "### **Ask Questions Anywhere**\n" + "- Click the Onyx extension icon in your browser toolbar\n" + "- Type your question in natural language\n" + "- Get instant answers with source citations\n" + "### **New Tab Experience**\n" + "- Replace your default new tab with Onyx search\n" + "- Access your favorite website bookmarks\n" + "- Quick search across your organization's knowledge\n" + "### **Sidebar Mode**\n" + "- Open Onyx as a sidebar on any webpage\n" + "- Ask questions about your current work without leaving the page\n" + "- Perfect for research and context-sensitive queries\n" + "## Settings and Options\n" + "To customize your extension experience:\n" + " Click the three dots (...) next to the Onyx extension\n" + " Select **Options**\n" + " Configure your preferences for search, bookmarks, and new tab behavior\n" + " **Need help with setup?** Contact your Onyx administrator for installation assistance or configuration questions.\n" +) +onyx_anywhere_mobile_app_title = "Mobile App (Coming Soon)" +onyx_anywhere_mobile_app = ( + " Currently Onyx is a responsive application and so your Onyx deployment will work on your smartphone or tablet via your\n" + " browser app.\n" + " While is is not as nice of an experience as a native app,\n" + " it can be used in the meantime while the Onyx Mobile App is under development.\n" + "## Mobile App\n" + "The Onyx mobile app is currently under development.\n" + "This native mobile application will bring the full power of Onyx to your smartphone and tablet devices.\n" +) +onyx_anywhere_slack_title = "Slack Bot" +onyx_anywhere_slack = ( + "## Overview\n" + "Bring Onyx's AI capabilities directly into your conversations via Slack App.\n" + "Onyx allows for highly flexible Slack configurations so that you use all of your Onyx Agents directly in your favorite\n" + "channels.\n" + "## Supported Features\n" + "- Support for unlimited Slack Apps. This way you can associate Slack Apps with Onyx Agents for specific use cases.\n" + "- Channel level configurations. Every channel can have different default behavior based on the channel's purpose.\n" + "- Answers using internal or web knowledge are backed by citations and link back to the original sources.\n" + "- Works in Threads, Channels and DMs.\n" + " Try asking Onyx to summarize Threads by tagging the Onyx Slack Bot in the Thread!\n" + "## Try it out\n" + "The Onyx Slack Bot is always live and serving answers to the community in our public Slack.\n" + "To test it out,\n" + "join the [community Slack](https://join.slack.com/t/onyx-dot-app/shared_invite/zt-34lu4m7xg-TsKGO6h8PDvR5W27zTdyhA)\n" + "and see the #ask-onyx channel or tag **@OnyxBot** from anywhere.\n" +) +onyx_anywhere_web_interface_title = "Web App" +onyx_anywhere_web_interface = ( + "The Web App is the default way to use Onyx and the recommended for the most complete experience.\n" + "The admin panel is also a web-app exclusive feature which is the easiest way to manage the\n" + "[Agents](/overview/core_features/agents), [Actions](/overview/core_features/actions),\n" + "[Connectors](/overview/core_features/connectors), users, settings and more.\n" + " A great place to get familiar with the experience is to start with the [Chat](/overview/core_features/chat)\n" + " overview or the [Admin](/admin/overview) tab for managing the deployment.\n" + "If you're deploying Onyx locally (guide [here](/deployment/getting_started/quickstart)),\n" + "you should be able to access the Web UI at http://localhost:3000/.\n" ) # For simplicity, we're not adding any metadata suffix here. Generally there is none for the Web connector anyway -overview_doc = SeedPresaveDocument( - url="https://docs.onyx.app/more/use_cases/overview", - title=overview_title, - content=overview, - title_embedding=list(model.encode(f"search_document: {overview_title}")), + +# Welcome +welcome_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/welcome", + title=welcome_title, + content=welcome, + title_embedding=list(model.encode(f"search_document: {welcome_title}")), + content_embedding=list( + model.encode(f"search_document: {welcome_title}\n{welcome}") + ), +) + +# Core Features +core_features_actions_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/actions", + title=core_features_actions_title, + content=core_features_actions, + title_embedding=list( + model.encode(f"search_document: {core_features_actions_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_actions_title}\n{core_features_actions}" + ) + ), +) + +core_features_agents_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/agents", + title=core_features_agents_title, + content=core_features_agents, + title_embedding=list( + model.encode(f"search_document: {core_features_agents_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_agents_title}\n{core_features_agents}" + ) + ), +) + +core_features_chat_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/chat", + title=core_features_chat_title, + content=core_features_chat, + title_embedding=list(model.encode(f"search_document: {core_features_chat_title}")), + content_embedding=list( + model.encode( + f"search_document: {core_features_chat_title}\n{core_features_chat}" + ) + ), +) + +core_features_code_interpreter_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/code_interpreter", + title=core_features_code_interpreter_title, + content=core_features_code_interpreter, + title_embedding=list( + model.encode(f"search_document: {core_features_code_interpreter_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_code_interpreter_title}\n{core_features_code_interpreter}" + ) + ), +) + +core_features_connectors_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/connectors", + title=core_features_connectors_title, + content=core_features_connectors, + title_embedding=list( + model.encode(f"search_document: {core_features_connectors_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_connectors_title}\n{core_features_connectors}" + ) + ), +) + +core_features_image_generation_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/image_generation", + title=core_features_image_generation_title, + content=core_features_image_generation, + title_embedding=list( + model.encode(f"search_document: {core_features_image_generation_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_image_generation_title}\n{core_features_image_generation}" + ) + ), +) + +core_features_internal_search_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/internal_search", + title=core_features_internal_search_title, + content=core_features_internal_search, + title_embedding=list( + model.encode(f"search_document: {core_features_internal_search_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_internal_search_title}\n{core_features_internal_search}" + ) + ), +) + +core_features_web_search_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/web_search", + title=core_features_web_search_title, + content=core_features_web_search, + title_embedding=list( + model.encode(f"search_document: {core_features_web_search_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_web_search_title}\n{core_features_web_search}" + ) + ), +) + +core_features_workflows_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/core_features/workflows", + title=core_features_workflows_title, + content=core_features_workflows, + title_embedding=list( + model.encode(f"search_document: {core_features_workflows_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {core_features_workflows_title}\n{core_features_workflows}" + ) + ), +) + +# Getting Started +getting_started_faq_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/getting_started/faq", + title=getting_started_faq_title, + content=getting_started_faq, + title_embedding=list(model.encode(f"search_document: {getting_started_faq_title}")), content_embedding=list( - model.encode(f"search_document: {overview_title}\n{overview}") + model.encode( + f"search_document: {getting_started_faq_title}\n{getting_started_faq}" + ) ), ) -enterprise_search_doc = SeedPresaveDocument( - url="https://docs.onyx.app/more/use_cases/enterprise_search", - title=enterprise_search_title, - content=enterprise_search_1, - title_embedding=list(model.encode(f"search_document: {enterprise_search_title}")), +getting_started_use_cases_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/getting_started/use_cases", + title=getting_started_use_cases_title, + content=getting_started_use_cases, + title_embedding=list( + model.encode(f"search_document: {getting_started_use_cases_title}") + ), content_embedding=list( model.encode( - f"search_document: {enterprise_search_title}\n{enterprise_search_1}" + f"search_document: {getting_started_use_cases_title}\n{getting_started_use_cases}" ) ), ) -enterprise_search_doc_2 = SeedPresaveDocument( - url="https://docs.onyx.app/more/use_cases/enterprise_search", - title=enterprise_search_title, - content=enterprise_search_2, - title_embedding=list(model.encode(f"search_document: {enterprise_search_title}")), +# Miscellaneous +miscellaneous_contact_us_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/miscellaneous/contact_us", + title=miscellaneous_contact_us_title, + content=miscellaneous_contact_us, + title_embedding=list( + model.encode(f"search_document: {miscellaneous_contact_us_title}") + ), content_embedding=list( model.encode( - f"search_document: {enterprise_search_title}\n{enterprise_search_2}" + f"search_document: {miscellaneous_contact_us_title}\n{miscellaneous_contact_us}" ) ), - chunk_ind=1, ) -ai_platform_doc = SeedPresaveDocument( - url="https://docs.onyx.app/more/use_cases/ai_platform", - title=ai_platform_title, - content=ai_platform, - title_embedding=list(model.encode(f"search_document: {ai_platform_title}")), +miscellaneous_open_source_statement_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/miscellaneous/open_source_statement", + title=miscellaneous_open_source_statement_title, + content=miscellaneous_open_source_statement, + title_embedding=list( + model.encode(f"search_document: {miscellaneous_open_source_statement_title}") + ), content_embedding=list( - model.encode(f"search_document: {ai_platform_title}\n{ai_platform}") + model.encode( + f"search_document: {miscellaneous_open_source_statement_title}\n{miscellaneous_open_source_statement}" + ) ), ) -customer_support_doc = SeedPresaveDocument( - url="https://docs.onyx.app/more/use_cases/support", - title=customer_support_title, - content=customer_support, - title_embedding=list(model.encode(f"search_document: {customer_support_title}")), +# Onyx Anywhere +onyx_anywhere_chrome_extension_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/chrome_extension", + title=onyx_anywhere_chrome_extension_title, + content=onyx_anywhere_chrome_extension, + title_embedding=list( + model.encode(f"search_document: {onyx_anywhere_chrome_extension_title}") + ), content_embedding=list( - model.encode(f"search_document: {customer_support_title}\n{customer_support}") + model.encode( + f"search_document: {onyx_anywhere_chrome_extension_title}\n{onyx_anywhere_chrome_extension}" + ) ), ) -sales_doc = SeedPresaveDocument( - url="https://docs.onyx.app/more/use_cases/sales", - title=sales_title, - content=sales, - title_embedding=list(model.encode(f"search_document: {sales_title}")), - content_embedding=list(model.encode(f"search_document: {sales_title}\n{sales}")), +onyx_anywhere_mobile_app_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/mobile_app", + title=onyx_anywhere_mobile_app_title, + content=onyx_anywhere_mobile_app, + title_embedding=list( + model.encode(f"search_document: {onyx_anywhere_mobile_app_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {onyx_anywhere_mobile_app_title}\n{onyx_anywhere_mobile_app}" + ) + ), ) -operations_doc = SeedPresaveDocument( - url="https://docs.onyx.app/more/use_cases/operations", - title=operations_title, - content=operations, - title_embedding=list(model.encode(f"search_document: {operations_title}")), +onyx_anywhere_slack_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/slack", + title=onyx_anywhere_slack_title, + content=onyx_anywhere_slack, + title_embedding=list(model.encode(f"search_document: {onyx_anywhere_slack_title}")), content_embedding=list( - model.encode(f"search_document: {operations_title}\n{operations}") + model.encode( + f"search_document: {onyx_anywhere_slack_title}\n{onyx_anywhere_slack}" + ) + ), +) + +onyx_anywhere_web_interface_doc = SeedPresaveDocument( + url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/web_interface", + title=onyx_anywhere_web_interface_title, + content=onyx_anywhere_web_interface, + title_embedding=list( + model.encode(f"search_document: {onyx_anywhere_web_interface_title}") + ), + content_embedding=list( + model.encode( + f"search_document: {onyx_anywhere_web_interface_title}\n{onyx_anywhere_web_interface}" + ) ), ) documents = [ - overview_doc, - enterprise_search_doc, - enterprise_search_doc_2, - ai_platform_doc, - customer_support_doc, - sales_doc, - operations_doc, + # Welcome + welcome_doc, + # Core Features + core_features_actions_doc, + core_features_agents_doc, + core_features_chat_doc, + core_features_code_interpreter_doc, + core_features_connectors_doc, + core_features_image_generation_doc, + core_features_internal_search_doc, + core_features_web_search_doc, + core_features_workflows_doc, + # Getting Started + getting_started_faq_doc, + getting_started_use_cases_doc, + # Miscellaneous + miscellaneous_contact_us_doc, + miscellaneous_open_source_statement_doc, + # Onyx Anywhere + onyx_anywhere_chrome_extension_doc, + onyx_anywhere_mobile_app_doc, + onyx_anywhere_slack_doc, + onyx_anywhere_web_interface_doc, ] documents_dict = [doc.model_dump() for doc in documents] diff --git a/deployment/docker_compose/docker-compose.dev.yml b/deployment/docker_compose/docker-compose.dev.yml index 7fc432c1c3c..d49ce4855d1 100644 --- a/deployment/docker_compose/docker-compose.dev.yml +++ b/deployment/docker_compose/docker-compose.dev.yml @@ -88,7 +88,6 @@ services: - MODEL_SERVER_HOST=${MODEL_SERVER_HOST:-inference_model_server} - MODEL_SERVER_PORT=${MODEL_SERVER_PORT:-} # Leave this on pretty please? Nothing sensitive is collected! - # https://docs.onyx.app/more/telemetry - DISABLE_TELEMETRY=${DISABLE_TELEMETRY:-} - LOG_LEVEL=${LOG_LEVEL:-info} # Set to debug to get more fine-grained logs - LOG_ALL_MODEL_INTERACTIONS=${LOG_ALL_MODEL_INTERACTIONS:-} # LiteLLM Verbose Logging @@ -263,7 +262,6 @@ services: - DANSWER_BOT_MAX_WAIT_TIME=${DANSWER_BOT_MAX_WAIT_TIME:-} # Logging # Leave this on pretty please? Nothing sensitive is collected! - # https://docs.onyx.app/more/telemetry - DISABLE_TELEMETRY=${DISABLE_TELEMETRY:-} - LOG_LEVEL=${LOG_LEVEL:-info} # Set to debug to get more fine-grained logs - LOG_ALL_MODEL_INTERACTIONS=${LOG_ALL_MODEL_INTERACTIONS:-} # LiteLLM Verbose Logging diff --git a/deployment/docker_compose/docker-compose.gpu-dev.yml b/deployment/docker_compose/docker-compose.gpu-dev.yml index 1d814783f3f..1fc55793261 100644 --- a/deployment/docker_compose/docker-compose.gpu-dev.yml +++ b/deployment/docker_compose/docker-compose.gpu-dev.yml @@ -77,7 +77,6 @@ services: # We do not recommend changing this value - SYSTEM_RECURSION_LIMIT=${SYSTEM_RECURSION_LIMIT:-} # Leave this on pretty please? Nothing sensitive is collected! - # https://docs.onyx.app/more/telemetry - DISABLE_TELEMETRY=${DISABLE_TELEMETRY:-} - LOG_LEVEL=${LOG_LEVEL:-info} # Set to debug to get more fine-grained logs - LOG_ALL_MODEL_INTERACTIONS=${LOG_ALL_MODEL_INTERACTIONS:-} # LiteLLM Verbose Logging @@ -208,7 +207,6 @@ services: - DANSWER_BOT_MAX_WAIT_TIME=${DANSWER_BOT_MAX_WAIT_TIME:-} # Logging # Leave this on pretty please? Nothing sensitive is collected! - # https://docs.onyx.app/more/telemetry - DISABLE_TELEMETRY=${DISABLE_TELEMETRY:-} - LOG_LEVEL=${LOG_LEVEL:-info} # Set to debug to get more fine-grained logs - LOG_ALL_MODEL_INTERACTIONS=${LOG_ALL_MODEL_INTERACTIONS:-} # LiteLLM Verbose Logging diff --git a/deployment/docker_compose/docker-compose.multitenant-dev.yml b/deployment/docker_compose/docker-compose.multitenant-dev.yml index 3b546c07056..c027fc9d7be 100644 --- a/deployment/docker_compose/docker-compose.multitenant-dev.yml +++ b/deployment/docker_compose/docker-compose.multitenant-dev.yml @@ -245,7 +245,6 @@ services: - DANSWER_BOT_MAX_WAIT_TIME=${DANSWER_BOT_MAX_WAIT_TIME:-} # Logging # Leave this on pretty please? Nothing sensitive is collected! - # https://docs.onyx.app/more/telemetry - DISABLE_TELEMETRY=${DISABLE_TELEMETRY:-} - LOG_LEVEL=${LOG_LEVEL:-info} # Set to debug to get more fine-grained logs - LOG_ALL_MODEL_INTERACTIONS=${LOG_ALL_MODEL_INTERACTIONS:-} # LiteLLM Verbose Logging diff --git a/deployment/helm/charts/onyx/values.yaml b/deployment/helm/charts/onyx/values.yaml index e78f404588f..78f037c94cb 100644 --- a/deployment/helm/charts/onyx/values.yaml +++ b/deployment/helm/charts/onyx/values.yaml @@ -702,7 +702,6 @@ configMap: NOTIFY_SLACKBOT_NO_ANSWER: "" # Logging # Optional Telemetry, please keep it on (nothing sensitive is collected)? <3 - # https://docs.onyx.app/more/telemetry DISABLE_TELEMETRY: "" LOG_LEVEL: "" LOG_ALL_MODEL_INTERACTIONS: "" From 86563523f7ee3ec400f03b54eae806e0e30dff20 Mon Sep 17 00:00:00 2001 From: Wenxi Onyx Date: Mon, 8 Sep 2025 14:02:45 -0700 Subject: [PATCH 2/4] update seeded docs --- backend/onyx/seeding/initial_docs_cohere.json | 110 ++++++++++++++---- backend/onyx/seeding/load_docs.py | 2 +- 2 files changed, 89 insertions(+), 23 deletions(-) diff --git a/backend/onyx/seeding/initial_docs_cohere.json b/backend/onyx/seeding/initial_docs_cohere.json index d6944e7298a..a90e465e1c0 100644 --- a/backend/onyx/seeding/initial_docs_cohere.json +++ b/backend/onyx/seeding/initial_docs_cohere.json @@ -1,44 +1,110 @@ [ { - "url": "https://docs.onyx.app/more/use_cases/overview", - "title": "Use Cases Overview", - "content": "How to leverage Onyx in your organization\n\nOnyx Overview\nOnyx is the AI Assistant connected to your organization's docs, apps, and people. Onyx makes Generative AI more versatile for work by enabling new types of questions like \"What is the most common feature request we've heard from customers this month\". Whereas other AI systems have no context of your team and are generally unhelpful with work related questions, Onyx makes it possible to ask these questions in natural language and get back answers in seconds.\n\nOnyx can connect to +30 different tools and the use cases are not limited to the ones in the following pages. The highlighted use cases are for inspiration and come from feedback gathered from our users and customers.\n\n\nCommon Getting Started Questions:\n\nWhy are these docs connected in my Onyx deployment?\nAnswer: This is just an example of how connectors work in Onyx. You can connect up your own team's knowledge and you will be able to ask questions unique to your organization. Onyx will keep all of the knowledge up to date and in sync with your connected applications.\n\nIs my data being sent anywhere when I connect it up to Onyx?\nAnswer: No! Onyx is built with data security as our highest priority. We open sourced it so our users can know exactly what is going on with their data. By default all of the document processing happens within Onyx. The only time it is sent outward is for the GenAI call to generate answers.\n\nWhere is the feature for auto sync-ing document level access permissions from all connected sources?\nAnswer: This falls under the Enterprise Edition set of Onyx features built on top of the MIT/community edition. If you are on Onyx Cloud, you have access to them by default. If you're running it yourself, reach out to the Onyx team to receive access.", + "url": "https://docs.onyx.app/welcome", + "title": "Welcome to Onyx!", + "content": "## What is Onyx?\nOnyx is your team's entry point to Generative AI,\noffering a natural language interface for any LLM while integrating seamlessly with your knowledge and applications.\nBuild tailored AI Agents, search for documents, browse the web, and more — all in one place.\n## Major Features\n The best way to quickly get familiar with Onyx is to check out the features below!\n Conversational interface to your LLMs, Agents, and knowledge.\n Create AI agents tailored to your use cases with custom instructions, knowledge, and actions.\n Search through your organization's knowledge and connected applications.\n Enrich the knowledge of the LLM with the latest information from the internet.\n Enable Actions connected to your team's applications to let Agents automate work.\n Execute code directly within your chat sessions for complex calculations and data analysis.\n To learn about other features, check out the [Core Features](/overview/core_features/chat)\n section or visit the [Admin Docs](/admin/overview) for an even more in depth breakdown.\n## Why Onyx?\nWhy choose Onyx over ChatGPT, Microsoft Copilot, Google Gemini, or Glean?\n- **Reliable Responses from Internal Knowledge:**\n Onyx builds a knowledge index using LLM-native techniques. Powered with contextual retrieval, advanced RAG,\n hybrid search, and AI-generated knowledge graphs, Onyx ensures the most relevant results and the least hallucinations.\n- **Open Source:**\n Onyx is made for security, data privacy, and ease of self-hosting. It's easy and free to get started.\n For teams investing in a long-term GenAI strategy,\n Onyx can be easily extended or customized to your team's future needs.\n- **Highly Configurable:**\n Onyx is designed to be flexible, so you can optimize the experience for your team. Plug and play any LLM model,\n connect only the data you need, and enable the features you want your team to use.\n## Ready to Get Started?\n**Next Steps:**\n Checkout our quickstart guide to self-host Onyx in minutes.\n Sign up for a free trial of Onyx Cloud, no credit card required.\n", "chunk_ind": 0 }, { - "url": "https://docs.onyx.app/more/use_cases/enterprise_search", - "title": "Enterprise Search", - "content": "Value of Enterprise Search with Onyx\n\nWhat is Enterprise Search and why is it Important?\nAn Enterprise Search system gives team members a single place to access all of the disparate knowledge of an organization. Critical information is saved across a host of channels like call transcripts with prospects, engineering design docs, IT runbooks, customer support email exchanges, project management tickets, and more. As fast moving teams scale up, information gets spread out and more disorganized.\n\nSince it quickly becomes infeasible to check across every source, decisions get made on incomplete information, employee satisfaction decreases, and the most valuable members of your team are tied up with constant distractions as junior teammates are unable to unblock themselves. Onyx solves this problem by letting anyone on the team access all of the knowledge across your organization in a permissioned and secure way. Users can ask questions in natural language and get back answers and documents across all of the connected sources instantly.\n\nWhat's the real cost?\nA typical knowledge worker spends over 2 hours a week on search, but more than that, the cost of incomplete or incorrect information can be extremely high. Customer support/success that isn't able to find the reference to similar cases could cause hours or even days of delay leading to lower customer satisfaction or in the worst case - churn. An account exec not realizing that a prospect had previously mentioned a specific need could lead to lost deals. An engineer not realizing a similar feature had previously been built could result in weeks of wasted development time and tech debt with duplicate implementation. With a lack of knowledge, your whole organization is navigating in the dark - inefficient and mistake prone.", + "url": "https://docs.onyx.app/overview/core_features/actions", + "title": "Actions & MCP", + "content": "## Overview\n**Actions** give Agents the ability to interact with external systems.\nOnyx comes with 4 built-in Actions and allows users to configure additional ones via\n[OpenAPI](https://en.wikipedia.org/wiki/OpenAPI_Specification)\nand [Model Context Protocol](https://modelcontextprotocol.io/) (MCP).\nThe built-in Actions include:\n## Custom Actions\nOnyx offers flexible options for configuring both custom Actions and their associated authentication.\nAdmins can choose to:\n- Use a single shared authentication, giving all users the same level of access to Actions.\n- Require each user to complete their own authentication flow, so Actions respect individual user permissions.\nOnyx supports both token-based authentication and OAuth.\n## Actions Button\nIn the Chat input bar, Actions are grouped by the MCP server or OpenAPI schema they are registered with.\nUsers have the flexibility to turn on/off the Actions that the Agent/LLM has access to on the fly.\n", "chunk_ind": 0 }, { - "url": "https://docs.onyx.app/more/use_cases/enterprise_search", - "title": "Enterprise Search", - "content": "More than Search\nWhen analyzing the entire corpus of knowledge within your company is as easy as asking a question in a search bar, your entire team can stay informed and up to date. Onyx also makes it trivial to identify where knowledge is well documented and where it is lacking. Team members who are centers of knowledge can begin to effectively document their expertise since it is no longer being thrown into a black hole. All of this allows the organization to achieve higher efficiency and drive business outcomes.\n\nWith Generative AI, the entire user experience has evolved as well. For example, instead of just finding similar cases for your customer support team to reference, Onyx breaks down the issue and explains it so that even the most junior members can understand it. This in turn lets them give the most holistic and technically accurate response possible to your customers. On the other end, even the super stars of your sales team will not be able to review 10 hours of transcripts before hopping on that critical call, but Onyx can easily parse through it in mere seconds and give crucial context to help your team close.", + "url": "https://docs.onyx.app/overview/core_features/agents", + "title": "Agents", + "content": "Agents are a combination of user specified instructions, knowledge, and [Actions](/overview/core_features/actions).\nThink of them as AI team members that are optimized for a specific task.\nOnyx Agents can be for individual use or shared with other users or\n[user-groups](/admin/user_management/users_and_groups) within Onyx.\n## When to use an Agent\nUse agents to build the best experience for repeat use cases,\nespecially those that can be shared with other members of the team.\nSome common examples include:\n- Onboarding Assistant\n- AI Helpdesk\n- Engineer Copilot\n- Legal Reviewer\nThese are typically scoped down to a particular task such as reviewing documents to ensure they comply with security\npolicies, filling out RFPs based on previously completed ones, etc.\n## Creating an Agent\n### Instructions (Prompting)\n The Instruction field is infinitely flexible so it is recommended to test different variations and verify the behavior\n before sharing the Agent broadly with your team.\nProvided below for inspiration is the **Instruction** for the default Onyx experience.\n ```\n You are a highly capable, thoughtful, and precise assistant. Your goal is to deeply understand the user's intent, ask clarifying questions when needed, think step-by-step through complex problems, provide clear and accurate answers, and proactively anticipate helpful follow-up information. Always prioritize being truthful, nuanced, insightful, and efficient.\n The current date is [[CURRENT_DATETIME]]\n You use different text styles, bolding, emojis (sparingly), block quotes, and other formatting to make your responses more readable and engaging.\n You use proper Markdown and LaTeX to format your responses for math, scientific, and chemical formulas, symbols, etc.: '$$\\n[expression]\\n$$' for standalone cases and '\\( [expression] \\)' when inline. For code you prefer to use Markdown and specify the language.\n You can use Markdown horizontal rules (---) to separate sections of your responses.\n You can use Markdown tables to format your responses for data, lists, and other structured information.\n ```\n Note that `[[CURRENT_DATETIME]]` is dynamically replaced and there may be additional Action use instructions\n depending on the enabled Actions.\nOne of the best parts of creating an Agent is the ability to control the goal/behavior of the Agent.\nThe instructions are purely in natural language and can include things like:\n- Always provide your results in a table.\n- Try to quote directly from the documents rather than rewording anything.\n- Flag information from documents that are older than 3 months.\n### Knowledge\n It is typically best to include only the necessary knowledge for the Agent to complete its task.\n The more scoped down the documents, the more reliable the performance.\nWhen creating an Agent, you can include both knowledge from [connectors](/overview/core_features/connectors)\nor file upload. The knowledge from connectors will be kept up to date as documents change in the external sources.\n### Actions\n If any of the built-in actions (Web Search, Internal Search, Image Generation, Code Interpreter) are missing,\n contact your Onyx admin.\n These must be set up in the admin-panel before being made available in the Agent creation flow.\n[Actions](/overview/core_features/actions) (sometimes known as Tools)\nallow the Agents to do things in external applications via APIs.\nSome tools help Onyx give better answers (such as the Onyx built-in tools)\nwhile others allow the system to do more than answer questions.\nSome example common Actions include:\n- Updating ticket statuses based on the conversation and if the user's needs were addressed.\n- Checking the status of a service to give real-time answers.\n- Moving deals along a sales pipeline in a CRM based on call transcripts or user request.\n", "chunk_ind": 0 }, { - "url": "https://docs.onyx.app/more/use_cases/ai_platform", - "title": "AI Platform", - "content": "Build AI Agents powered by the knowledge and workflows specific to your organization.\n\nBeyond Answers\nAgents enabled by generative AI and reasoning capable models are helping teams to automate their work. Onyx is helping teams make it happen. Onyx provides out of the box user chat sessions, attaching custom tools, handling LLM reasoning, code execution, data analysis, referencing internal knowledge, and much more.\n\nOnyx as a platform is not a no-code agent builder. We are made by developers for developers and this gives your team the full flexibility and power to create agents not constrained by blocks and simple logic paths.\n\nFlexibility and Extensibility\nOnyx is open source and completely whitebox. This not only gives transparency to what happens within the system but also means that your team can directly modify the source code to suit your unique needs.", + "url": "https://docs.onyx.app/overview/core_features/chat", + "title": "Chat", + "content": " On the top left of the page (just right of the sidebar), you can select the mode of the UI.\n Replace \"Auto\" with \"Chat\" to always go into this Chat UI.\nOnyx provides a natural language chat interface as the main way of interacting with the features.\nThe page below contains an overview of the main components and features.\n## Input Bar\n### Chat with Files / URLs\nThe leftmost button of the input bar lets users add context into the Chat session.\nUsers can choose between uploading files or selecting URLs as well as reusing previous files or URLs.\n URLs behind Logins, Captcha, or Paywalls that are not scrapeable are not accessible.\n Consider using a [Connector](/overview/core_features/connectors) instead.\n### Actions Selector\nThe second button lets users disable or force the use of Actions. There are 4 built-in Actions:\n- **[Internal Search](/overview/core_features/internal_search)**:\n Enables the LLM to search the indexed knowledge from [Connectors](/overview/core_features/connectors).\n- **[Web Search](/overview/core_features/web_search)**: Enables the LLM to search the internet.\n Requires an admin to set up an API key for a search provider.\n- **[Code Interpreter](/overview/core_features/code_interpreter)**:\n Enables the LLM to use a sandboxed Python runtime to execute code and run data analysis.\n- **[Image Generation](/overview/core_features/image_generation)**: Allows the LLM to generate images.\n Requires setting up an image generation API.\nThe Actions below the separator represent custom admin configured Actions.\nSee [Actions & MCP](/overview/core_features/actions) to learn about custom Actions.\n### Deep Research\nToggle **Deep Research** using the hourglass icon. When turned on, the LLM will be able to run many cycles of thinking,\nresearch, and actions to give the best possible result for the user.\nThis mode is intended for complicated questions that may need to pull together many sources together or requires\nsignificant reasoning.\n Deep Research may take up to several minutes and could cost many times (>10x) the token cost of a normal inference.\n### Model Selector\nOnyx supports all major LLM providers as well as self-hosting options like Ollama, VLLM, etc. For select models,\nusers can also configure the creativity and reasoning level.\n## Sidebar Contents\nThe left sidebar contains:\n- `New Session` button to clear the history and start a new Chat or [Search](/overview/core_features/internal_search) session.\n- `Projects` to help users organize chats and reuse different sets of documents. See section below for more info.\n- `Agents` section to start a new session with yours or your team's custom [Agents](/overview/core_features/agents).\n- `Sessions` section containing a list of the most recent conversations.\nThe right sidebar contains sources and citations that were used in generating the answer.\nThese can come from either `Internal Search` or `Web Search` or both.\nDocuments in the right sidebar can also be selected to be included in full for the next message in the Chat session.\n It's often useful to ask a question to find a document, then select it to do a deep dive on it.\n## Projects\n**Projects** are a collection of instructions (prompts) and files as well as a grouping for chats.\nUse projects to organize ongoing work,\nor as a handy way to reuse instructions and files without going through the Agent creation flow.\n## Miscellaneous Chat Features\n**Chat Sharing** - share chats with other team members by using the share-chat button in the top right (left of the\nSources sidebar).\n**Feedback** - give feedback viewable to the admins using the thumbs-up/thumbs-down buttons when hovering an LLM\nresponse\n**Regenerate** - modify your inputs by clicking the user messages or regenerate the LLM response with another model.\n**Copying** - copy the LLM output or markdown/code blocks by clicking on the copy button which shows on hover.\n", "chunk_ind": 0 }, { - "url": "https://docs.onyx.app/more/use_cases/support", - "title": "Customer Support", - "content": "Help your customer support team instantly answer any question across your entire product.\n\nAI Enabled Support\nCustomer support agents have one of the highest breadth jobs. They field requests that cover the entire surface area of the product and need to help your users find success on extremely short timelines. Because they're not the same people who designed or built the system, they often lack the depth of understanding needed - resulting in delays and escalations to other teams. Modern teams are leveraging AI to help their CS team optimize the speed and quality of these critical customer-facing interactions.\n\nThe Importance of Context\nThere are two critical components of AI copilots for customer support. The first is that the AI system needs to be connected with as much information as possible (not just support tools like Zendesk or Intercom) and that the knowledge needs to be as fresh as possible. Sometimes a fix might even be in places rarely checked by CS such as pull requests in a code repository. The second critical component is the ability of the AI system to break down difficult concepts and convoluted processes into more digestible descriptions and for your team members to be able to chat back and forth with the system to build a better understanding.\n\nOnyx takes care of both of these. The system connects up to over 30+ different applications and the knowledge is pulled in constantly so that the information access is always up to date.", + "url": "https://docs.onyx.app/overview/core_features/code_interpreter", + "title": "Code Interpreter", + "content": "## Overview\n Example run where the LLM generates code to run data analysis on a business report.\nThe ability to execute code unlocks the ability for the LLMs to do things such as:\n- Performing larger calculations accurately\n- Running data analysis on provided files\n- Generating or modifying data/files\n**Note**: The code interpreter is built-in functionality available to all deployments without any configuration needed.\n## Features\n- **Python Runtime**: A secure Python runtime with all dangerous functionality removed (such as accessing the network,\n directories outside of the specified, etc.)\n- **Libraries**: Comes with a set of libraries such as numpy, pandas, scipy, matplotlib, and more.\n- **File Input**: Ability to pass arbitrary file types along with the code to run against it.\n- **File Output**: Files can be created and provided back to the user.\n- **STDIN/STDOUT Capture**: Ability to show the user any outputs of the programs executed.\n- **Graph Rendering**: The Onyx [Chat UI](/overview/core_features/chat)\n is able to render returned graphs and other visualization for the user.\n## Usage\nThe Code Interpreter does not need to be invoked explicitly,\nthe LLM will determine when to use it depending on the user query.\nIt can also be attached to custom Agents, giving the LLM the option to use it as needed.\n", "chunk_ind": 0 }, { - "url": "https://docs.onyx.app/more/use_cases/sales", - "title": "Sales", - "content": "Keep your team up to date on every conversation and update so they can close.\n\nRecall Every Detail\nBeing able to instantly revisit every detail of any call without reading transcripts is helping Sales teams provide more tailored pitches, build stronger relationships, and close more deals. Instead of searching and reading through hours of transcripts in preparation for a call, your team can now ask Onyx \"What specific features was ACME interested in seeing for the demo\". Since your team doesn't have time to read every transcript prior to a call, Onyx provides a more thorough summary because it can instantly parse hundreds of pages and distill out the relevant information. Even for fast lookups it becomes much more convenient - for example to brush up on connection building topics by asking \"What rapport building topic did we chat about in the last call with ACME\".\n\nKnow Every Product Update\nIt is impossible for Sales teams to keep up with every product update. Because of this, when a prospect has a question that the Sales team does not know, they have no choice but to rely on the Product and Engineering orgs to get an authoritative answer. Not only is this distracting to the other teams, it also slows down the time to respond to the prospect (and as we know, time is the biggest killer of deals). With Onyx, it is even possible to get answers live on call because of how fast accessing information becomes. A question like \"Have we shipped the Microsoft AD integration yet?\" can now be answered in seconds meaning that prospects can get answers while on the call instead of asynchronously and sales cycles are reduced as a result.", + "url": "https://docs.onyx.app/overview/core_features/connectors", + "title": "Connectors", + "content": "## What are Connectors?\nOnyx uses Connectors to build an understanding of your documents, team,\nand higher level concepts so that answers are grounded and specific to your organization's knowledge.\nConnectors:\n- Keep all updates synced between external systems and Onyx.\n- Pull in metadata and additional signals to ensure answer relevance.\n- Respect all user permissions (Enterprise Edition only).\n## Common Connector Questions\n Click this card to see the full list of supported connectors.\n You can also push documents directly into Onyx via [API](/developers/guides/index_files_ingestion_api)\n or via File Upload.\n All processing and storage of documents and metadata happen within Onyx.\n There are options to use LLMs or third party providers during the indexing flow but by default everything is\n processing entirely locally.\n Click this card to see more about security.\n In the same way LLMs are pre-trained on massive amounts of internet data,\n Onyx builds an understanding of all of the documents, concepts, and people within your organization.\n This allows Onyx to provide more accurate answer to questions that relate to internal knowledge compared to using the\n applications' provided search APIs at query time.\n Click this card to learn more about Internal Search in Onyx.\n", "chunk_ind": 0 }, { - "url": "https://docs.onyx.app/more/use_cases/operations", - "title": "Operations", - "content": "Double the productivity of your Ops teams like IT, HR, etc.\n\nAutomatically Resolve Tickets\nModern teams are leveraging AI to auto-resolve up to 50% of tickets. Whether it is an employee asking about benefits details or how to set up the VPN for remote work, Onyx can help your team help themselves. This frees up your team to do the real impactful work of landing star candidates or improving your internal processes.\n\nAI Aided Onboarding\nOne of the periods where your team needs the most help is when they're just ramping up. Instead of feeling lost in dozens of new tools, Onyx gives them a single place where they can ask about anything in natural language. Whether it's how to set up their work environment or what their onboarding goals are, Onyx can walk them through every step with the help of Generative AI. This lets your team feel more empowered and gives time back to the more seasoned members of your team to focus on moving the needle.", + "url": "https://docs.onyx.app/overview/core_features/image_generation", + "title": "Image Generation", + "content": "## Overview\nThe image generation feature allows users to create PNG images according to their prompts which can be rendered in the\nchat and easily downloaded.\n## Configuration\nCurrently, Onyx supports two APIs for image generation, both through OpenAI. In the future,\nthere likely will be support for other options such as Google Imagen or Stability AI.\n**GPT-Image-1**: Newer model, better prompt adherence. Likely a better default for most use cases.\n**DALL-E 3**: Older model, slightly better for more imaginative and rich styles.\n## Usage\nTo use **Image Generation**,\nbe explicit in the prompting since the system is tuned to not generate images unless directly instructed.\nSee below for the instructions provided to the system for when to create images.\n Tool Description:\n ```\n Generate an image from a prompt.\n ```\n Instruction (System Prompt) Modification:\n ```\n NEVER use image_gen unless the user specifically requests an image.\n ```\n This phrase is injected into the default **Instruction** for Onyx if the **Image Generation** (image_gen)\n tool is available.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/core_features/internal_search", + "title": "Internal Search", + "content": "One of Onyx's most standout features is the ability to enrich the LLM's general world knowledge with context unique to\nyour team. Onyx uses [Connectors](/overview/core_features/connectors)\nto index knowledge from your team's applications to build an understanding of the documents, people,\nand concepts within your organization.\nDocuments, metadata, and access permissions are all kept up to date in near real time.\n## Search UI\n On the top left of the page, you can select the mode of the UI.\n Replace \"Auto\" with \"Search\" to always go into this view.\n Onyx's context retrieval respects user level permissions which is only configurable via the Enterprise Edition.\nOnyx's knowledge connectivity can be used via both the **Search** and [Chat](/overview/core_features/chat) interface.\nThe Search interface provides a better view of documents and is better for quickly accessing documents when the intent\nis not to get an answer.\nUsers do not need to explicitly select this mode — when a query is classified by Onyx as a document search,\nit will automatically go into this UI experience.\n### Filters\nThe Search UI also provides more advanced filtering options:\nThe top bar allows users to filter by time ranges (date range / time offset), authors, and tags (e.g. `Folder:\nEngineering`).\nThe side filters allow users to filter by the source type of the documents.\n## Chat UI\nContext from your applications are also available in the Chat UI and to Onyx Agents.\nDeep Research mode is also a Chat UI feature.\nClick [here](/overview/core_features/chat) to learn more about the Chat experience.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/core_features/web_search", + "title": "Web Search", + "content": "## Overview\nOnyx can access the internet for questions that require up to date information or for niche information that the LLM may\nnot be certain about.\nUsers can toggle the **Web Search** Action on the fly to override the LLM's decision.\nIf [Internal Search](/overview/core_features/internal_search) was used during the research process,\nOnyx will seamlessly combine web sources with internal documents in both the answer generation and for displaying in the\nUI.\n## Requirements\nTo provide Web Search functionality,\nOnyx requires both the ability to get search results and to be able to parse websites for more complete context.\nThis is broken down into 1) *the search provider* and 2) *the web scraper*.\n### Search Providers\nOnyx provides multiple search providers (pricing subject to change, please double check):\n| Name | Provider | Price | Benefit |\n|------|----------|-------|---------|\n| Google PSE | Google | Free tier + $5/1000 queries | Official Google search results, high trust option for security conscious teams. |\n| Serper | Serper.dev | Free tier + $0.30/1000 queries | Fast, and cost-effective |\n| Exa | Exa.ai | $5/1000 queries | AI-optimized with better semantic capabilities|\n### Web Scraper\nAs the Search Providers only give short snippets and metadata,\na scraper is used to fetch the full site contents for more complete/reliable answers.\n| Name | Requires Config | Benefits |\n|------|----------------|----------|\n| Onyx built-in | No | No third parties get access to user queries, free to use |\n| Firecrawl | Yes, API key | More performant with better edge case handling |\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/core_features/workflows", + "title": "Workflows (Coming Soon)", + "content": " **Coming Soon!**\n This feature is currently under development. Stay tuned for updates!\n## What's Coming\nThe Onyx Workflows feature will enable:\n- **Asynchronous Actions**: Set up Agents to run when triggered by events or on a time basis.\n- **Batch Processing**: Set up instructions to run against large sets of objects to automate repeat work.\n- **Acknowledgements**: Optionally set up notifications to give approval for more sensitive Actions.\n- **Reports**: Get breakdowns of the work that was done for you in the background.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/getting_started/faq", + "title": "FAQ", + "content": "## General Questions\n You can ask Onyx about general world knowledge known to the LLM,\n knowledge from [connected applications](/overview/core_features/internal_search),\n or things searchable on the web (if [Web Search](/overview/core_features/web_search) is configured)\n Please check the [Security](/security/architecture/system_description) tab to learn more.\n Onyx is built with security and data privacy as a core commitment.\n Onyx is built for teams of all sizes whether it's a single user looking for a local Chat UI or a global enterprise\n needing a unified GenAI solution for the entire workforce.\n Onyx emphasizes data privacy and security as well as reliable responses by connecting to knowledge whether private\n or from the web.\n Yes, however Onyx needs an LLM to function properly.\n You can air gap the entire system but you would need to run a local LLM.\n Note that we strongly recommend using a recent and non-quantized LLM for the best experience.\n## Technical Issues\n The most common culprit is under-resourcing the deployment.\n Please refer to the [Resourcing](/deployment/getting_started/resourcing) page to double check.\n No! Onyx is intended to provide a fast and snappy experience. If the responses are slow,\n it may be due to a couple issues.\n - The LLM attached to the system is slow, has low throughput, or does not support streaming.\n - You've configured locally running models that are not the default but you do not have a GPU available to the\n system. Typically this is from setting a local reranking or embedding model.\n## Knowledge and Search\n If it's an internal document,\n it may be because the indexing of the application has not completed or because the access controls are incorrectly\n set. In cases of failure, the system always defaults to least permissive.\n The most common failure is that the [connector](/admin/connectors/overview) is incorrectly configured.\n Onyx connectors will fetch updates on a set schedule (typically 30 minutes),\n this polling frequency can be configured by the admin for each connector. The documents, metadata,\n and access permissions all receive updates.\n Web Search must be configured by an admin to be usable.\n It requires setting up one of the supported Search providers and also a scraper (though this is optional as Onyx\n provides one built in).\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/getting_started/use_cases", + "title": "Use Cases", + "content": " [See how Ramp uses Onyx](https://www.onyx.app/blog/ramp-case-study)\n to automatically resolve 93% of internal and customer questions!\n## AI-Powered Team\nGive your team secure access to all major LLMs such as GPT, Claude, Gemini, Deepseek, Llama,\nand more - all with access to advanced utilities.\n Use LLMs to help quickly summarize documents, explain key concepts, or create derivative works.\n Get answers to any topic using a combination of Web Search and internal knowledge or run a deeper exploration with\n Deep Research.\n Execute code to run complex data crunching tasks, generate graphs to help visualize results,\n and chat with the LLM to interpret the results.\n Generate images, draft content from scratch, or refine existing works with AI suggestions.\n## Enterprise Search\nQuickly access knowledge across all of your team's applications from wikis to chats and everything in between.\n A single interface to find knowledge across the entire organization.\n Leverage analytics and users feedback to identify holes in your team's knowledge base.\n Reduce misinformation and downstream costs.\n Let new team members unblock themselves and reduce distractions for more senior members.\n## Sales\nHelp your sales team stay up to date and focus on closing.\n Instantly access customer history, past interactions,\n and account details before any call or ask questions against past call transcripts.\n Gather competitive intelligence and stay ahead of the market.\n Create custom Agents to run deep analysis on your pipeline based on all connected knowledge.\n## Support\nKeep customers happy with faster resolutions and more reliable support.\n AI helps your team quickly surface past tickets and runbooks to craft accurate answers for users.\n Onyx ensures that all knowledge is kept up to date with any product or documentation changes.\n Build automations on Onyx to automatically resolve up to >90% of customer tickets.\n## Engineering\nHelp your team ship with speed and confidence through access to GenAI and internal knowledge.\n Accelerate development by having an AI copilot for every developer.\n Have Onyx find and explain design docs, internal services,\n and relevant other projects to ensure devs have full context for every project.\n Quickly check against past tickets and projects to avoid duplicate work and accumulation of tech debt.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/miscellaneous/contact_us", + "title": "Contact Us", + "content": "Contact us at [hello@onyx.app](mailto:hello@onyx.app) or book a call with us on our [Calendar](https://cal.com/team/onyx/founders).", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/miscellaneous/open_source_statement", + "title": "Open Source Statement", + "content": "## Our Mission\nOur mission is to make Generative AI and knowledge accessible to every team worldwide.\nAs large language models—both proprietary and open-source—become increasingly widespread,\nOnyx serves as the interface to their knowledge and reasoning capabilities.\nOnyx enriches the utility of the LLM by providing additional context (both web and team internal),\nbuilt-in tools like code interpreter, and user created Actions.\n## Why Open Source?\n We believe teams should feel safe with the AI platform that they adopt. That's why Onyx is fully transparent.\n You'll have peace of mind knowing exactly how your data is processed and stored,\n and all of this happening within the Onyx deployment.\n With GenAI being such a fundamental piece of modern company strategy,\n we want to offer the most flexible and future proof option.\n We understand that every team is unique in their needs so we're building Onyx with an emphasis on customizability,\n both for building on top of the platform and directly modifying it.\n Open source also gives control over to your team. With the GenAI space rapidly evolving,\n your vendor of choice may not always be aligned with your team's direction.\n OSS combines the benefits of building in-house with getting product updates for free.\n Open source also prevents lock in so that you can leverage any LLM provider (or your own LLM).\n## Commercial Viability\nWe are a team of builders and we want to have as many people find value from our software as possible.\nThis is our singular goal and everything that we do derives from this.\nTo push the boundaries of user experience and AI innovation,\nwe've assembled a core team of world-class developers who share this vision.\nTo borrow from Sid Sijbrandij (Co-Founder, GitLab):\n> \"We need to think in the interests of the project, while tending to the realities of running a business to support it... After all, we know that to sustain the project, we need to make it commercially viable.\"\nWe believe in radical transparency—both in how we build open software and in the commercial realities of competing in\nthis rapidly evolving space.\n Every organization, regardless of size or budget, will always have access to Onyx's core capabilities—including RAG,\n deep research, custom agents, and more—completely free.\nFor organizations with special requirements—such as usage auditing, granular access controls,\nand white-labeling—we offer the Enterprise Edition, available both as a self-hosted solution and through Onyx Cloud.\nThe Enterprise Edition sustains our mission,\nenabling us to keep the vast majority of Onyx's features free and open for everyone.\n## On Contributions\nOnyx is a project built in collaboration with our community and we openly welcome contributions.\nIt is a point of emphasis of our team to ensure that the Onyx project continues to be easy for teams to contribute to or\nmaintain in house. This comes down to:\n- Intentional high level architecture.\n- Strong product direction and refusal to accept bloat for niche use cases.\n- A consistent and high quality of engineering best practices across the code base.\nTo that end,\nwe ask that contributors work on smaller issues to start and get approval from the maintainers for larger feature\ncontributions.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/onyx_anywhere/chrome_extension", + "title": "Chrome Extension", + "content": " The Chrome extension is available but is undergoing a fairly major rework,\n it is recommended to wait until the next major release prior to deploying this\nUse the Onyx extension to ask questions from anywhere. You can also replace your new-tab page with a custom Onyx page:\n- Onyx Search on new tabs\n- Favorite website bookmarks\n- Onyx as a sidebar to any page in Chrome\n In the future,\n the Onyx Chrome Extension will allow you to ask questions about the page you are currently on and optionally index the\n recent pages into the Onyx knowledge base.\n You'll be able to ask questions about recently visited pages via both the extension and the Onyx web app.\n## Getting Started\nOnce your administrator has set up the Chrome extension for your organization, you can start using it immediately.\n**For Onyx Cloud users**: Install directly from the Chrome Web Store **For self-hosted users**:\nYour administrator will provide installation instructions\n## Using the Extension\n### **Ask Questions Anywhere**\n- Click the Onyx extension icon in your browser toolbar\n- Type your question in natural language\n- Get instant answers with source citations\n### **New Tab Experience**\n- Replace your default new tab with Onyx search\n- Access your favorite website bookmarks\n- Quick search across your organization's knowledge\n### **Sidebar Mode**\n- Open Onyx as a sidebar on any webpage\n- Ask questions about your current work without leaving the page\n- Perfect for research and context-sensitive queries\n## Settings and Options\nTo customize your extension experience:\n Click the three dots (...) next to the Onyx extension\n Select **Options**\n Configure your preferences for search, bookmarks, and new tab behavior\n **Need help with setup?** Contact your Onyx administrator for installation assistance or configuration questions.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/onyx_anywhere/mobile_app", + "title": "Mobile App (Coming Soon)", + "content": " Currently Onyx is a responsive application and so your Onyx deployment will work on your smartphone or tablet via your\n browser app.\n While is is not as nice of an experience as a native app,\n it can be used in the meantime while the Onyx Mobile App is under development.\n## Mobile App\nThe Onyx mobile app is currently under development.\nThis native mobile application will bring the full power of Onyx to your smartphone and tablet devices.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/onyx_anywhere/slack", + "title": "Slack Bot", + "content": "## Overview\nBring Onyx's AI capabilities directly into your conversations via Slack App.\nOnyx allows for highly flexible Slack configurations so that you use all of your Onyx Agents directly in your favorite\nchannels.\n## Supported Features\n- Support for unlimited Slack Apps. This way you can associate Slack Apps with Onyx Agents for specific use cases.\n- Channel level configurations. Every channel can have different default behavior based on the channel's purpose.\n- Answers using internal or web knowledge are backed by citations and link back to the original sources.\n- Works in Threads, Channels and DMs.\n Try asking Onyx to summarize Threads by tagging the Onyx Slack Bot in the Thread!\n## Try it out\nThe Onyx Slack Bot is always live and serving answers to the community in our public Slack.\nTo test it out,\njoin the [community Slack](https://join.slack.com/t/onyx-dot-app/shared_invite/zt-34lu4m7xg-TsKGO6h8PDvR5W27zTdyhA)\nand see the #ask-onyx channel or tag **@OnyxBot** from anywhere.\n", + "chunk_ind": 0 + }, + { + "url": "https://docs.onyx.app/overview/onyx_anywhere/web_interface", + "title": "Web App", + "content": "The Web App is the default way to use Onyx and the recommended for the most complete experience.\nThe admin panel is also a web-app exclusive feature which is the easiest way to manage the\n[Agents](/overview/core_features/agents), [Actions](/overview/core_features/actions),\n[Connectors](/overview/core_features/connectors), users, settings and more.\n A great place to get familiar with the experience is to start with the [Chat](/overview/core_features/chat)\n overview or the [Admin](/admin/overview) tab for managing the deployment.\nIf you're deploying Onyx locally (guide [here](/deployment/getting_started/quickstart)),\nyou should be able to access the Web UI at http://localhost:3000/.\n", "chunk_ind": 0 } -] +] \ No newline at end of file diff --git a/backend/onyx/seeding/load_docs.py b/backend/onyx/seeding/load_docs.py index c86bb20c326..bc12dc48c1f 100644 --- a/backend/onyx/seeding/load_docs.py +++ b/backend/onyx/seeding/load_docs.py @@ -182,7 +182,7 @@ def seed_initial_documents( source=DocumentSource.WEB, input_type=InputType.LOAD_STATE, connector_specific_config={ - "base_url": "https://docs.onyx.app/more/use_cases", + "base_url": "https://docs.onyx.app/", "web_connector_type": "recursive", }, refresh_freq=None, # Never refresh by default From 30f638a7ee85281cbd316b06e5c2b621edeae170 Mon Sep 17 00:00:00 2001 From: Wenxi Onyx Date: Mon, 8 Sep 2025 14:30:43 -0700 Subject: [PATCH 3/4] easeier seeded docs --- backend/scripts/document_seeding_prep.py | 810 +----------------- .../search_quality/test_queries.json.template | 6 +- 2 files changed, 35 insertions(+), 781 deletions(-) diff --git a/backend/scripts/document_seeding_prep.py b/backend/scripts/document_seeding_prep.py index 374ed15bb59..4933c00b455 100644 --- a/backend/scripts/document_seeding_prep.py +++ b/backend/scripts/document_seeding_prep.py @@ -1,6 +1,14 @@ -# This script preps the documents used for initially seeding the index. It handles the embedding so that the -# documents can be added to the index with minimal processing. +""" +How to update seeded docs: +Go to the documentation repo and select the docs you want. +Have an AI assistant convert it to the same format as initial_docs_cohere.json (easier than manual or writing a script) +Verify the titles, content, and urls. +Run this script. +Update the load_docs.py if relevant. +""" + import json +from pathlib import Path from pydantic import BaseModel from sentence_transformers import SentenceTransformer # type: ignore @@ -15,785 +23,35 @@ class SeedPresaveDocument(BaseModel): chunk_ind: int = 0 -# Be sure to use the default embedding model +# Initialize embedding model (keep default used by the app) model = SentenceTransformer("nomic-ai/nomic-embed-text-v1", trust_remote_code=True) -tokenizer = model.tokenizer - -DOCUMENTATION_BASE_URL = "https://docs.onyx.app" - -# This is easier than cleaning up the crawl, needs to be updated if the sites are changed -welcome_title = "Welcome to Onyx!" -welcome = ( - "## What is Onyx?\n" - "Onyx is your team's entry point to Generative AI,\n" - "offering a natural language interface for any LLM while integrating seamlessly with your knowledge and applications.\n" - "Build tailored AI Agents, search for documents, browse the web, and more — all in one place.\n" - "## Major Features\n" - " The best way to quickly get familiar with Onyx is to check out the features below!\n" - " Conversational interface to your LLMs, Agents, and knowledge.\n" - " Create AI agents tailored to your use cases with custom instructions, knowledge, and actions.\n" - " Search through your organization's knowledge and connected applications.\n" - " Enrich the knowledge of the LLM with the latest information from the internet.\n" - " Enable Actions connected to your team's applications to let Agents automate work.\n" - " Execute code directly within your chat sessions for complex calculations and data analysis.\n" - " To learn about other features, check out the [Core Features](/overview/core_features/chat)\n" - " section or visit the [Admin Docs](/admin/overview) for an even more in depth breakdown.\n" - "## Why Onyx?\n" - "Why choose Onyx over ChatGPT, Microsoft Copilot, Google Gemini, or Glean?\n" - "- **Reliable Responses from Internal Knowledge:**\n" - " Onyx builds a knowledge index using LLM-native techniques. Powered with contextual retrieval, advanced RAG,\n" - " hybrid search, and AI-generated knowledge graphs, Onyx ensures the most relevant results and the least hallucinations.\n" - "- **Open Source:**\n" - " Onyx is made for security, data privacy, and ease of self-hosting. It's easy and free to get started.\n" - " For teams investing in a long-term GenAI strategy,\n" - " Onyx can be easily extended or customized to your team's future needs.\n" - "- **Highly Configurable:**\n" - " Onyx is designed to be flexible, so you can optimize the experience for your team. Plug and play any LLM model,\n" - " connect only the data you need, and enable the features you want your team to use.\n" - "## Ready to Get Started?\n" - "**Next Steps:**\n" - " Checkout our quickstart guide to self-host Onyx in minutes.\n" - " Sign up for a free trial of Onyx Cloud, no credit card required.\n" -) -core_features_actions_title = "Actions & MCP" -core_features_actions = ( - "## Overview\n" - "**Actions** give Agents the ability to interact with external systems.\n" - "Onyx comes with 4 built-in Actions and allows users to configure additional ones via\n" - "[OpenAPI](https://en.wikipedia.org/wiki/OpenAPI_Specification)\n" - "and [Model Context Protocol](https://modelcontextprotocol.io/) (MCP).\n" - "The built-in Actions include:\n" - "## Custom Actions\n" - "Onyx offers flexible options for configuring both custom Actions and their associated authentication.\n" - "Admins can choose to:\n" - "- Use a single shared authentication, giving all users the same level of access to Actions.\n" - "- Require each user to complete their own authentication flow, so Actions respect individual user permissions.\n" - "Onyx supports both token-based authentication and OAuth.\n" - "## Actions Button\n" - "In the Chat input bar, Actions are grouped by the MCP server or OpenAPI schema they are registered with.\n" - "Users have the flexibility to turn on/off the Actions that the Agent/LLM has access to on the fly.\n" -) -core_features_agents_title = "Agents" -core_features_agents = ( - "Agents are a combination of user specified instructions, knowledge, and [Actions](/overview/core_features/actions).\n" - "Think of them as AI team members that are optimized for a specific task.\n" - "Onyx Agents can be for individual use or shared with other users or\n" - "[user-groups](/admin/user_management/users_and_groups) within Onyx.\n" - "## When to use an Agent\n" - "Use agents to build the best experience for repeat use cases,\n" - "especially those that can be shared with other members of the team.\n" - "Some common examples include:\n" - "- Onboarding Assistant\n" - "- AI Helpdesk\n" - "- Engineer Copilot\n" - "- Legal Reviewer\n" - "These are typically scoped down to a particular task such as reviewing documents to ensure they comply with security\n" - "policies, filling out RFPs based on previously completed ones, etc.\n" - "## Creating an Agent\n" - "### Instructions (Prompting)\n" - " The Instruction field is infinitely flexible so it is recommended to test different variations and verify the behavior\n" - " before sharing the Agent broadly with your team.\n" - "Provided below for inspiration is the **Instruction** for the default Onyx experience.\n" - " ```\n" - " You are a highly capable, thoughtful, and precise assistant. Your goal is to deeply understand the user's intent," - " ask clarifying questions when needed, think step-by-step through complex problems, provide clear and accurate answers," - " and proactively anticipate helpful follow-up information. Always prioritize being truthful, nuanced, insightful, and efficient.\n" # noqa: E501 - " The current date is [[CURRENT_DATETIME]]\n" - " You use different text styles, bolding, emojis (sparingly), block quotes, and other formatting to make your responses more readable and engaging.\n" # noqa: E501 - " You use proper Markdown and LaTeX to format your responses for math, scientific, and chemical formulas, symbols, etc.:" - " '$$\\n[expression]\\n$$' for standalone cases and '\\( [expression] \\)' when inline. For code you prefer to use Markdown and specify the language.\n" # noqa: E501 - " You can use Markdown horizontal rules (---) to separate sections of your responses.\n" - " You can use Markdown tables to format your responses for data, lists, and other structured information.\n" - " ```\n" - " Note that `[[CURRENT_DATETIME]]` is dynamically replaced and there may be additional Action use instructions\n" - " depending on the enabled Actions.\n" - "One of the best parts of creating an Agent is the ability to control the goal/behavior of the Agent.\n" - "The instructions are purely in natural language and can include things like:\n" - "- Always provide your results in a table.\n" - "- Try to quote directly from the documents rather than rewording anything.\n" - "- Flag information from documents that are older than 3 months.\n" - "### Knowledge\n" - " It is typically best to include only the necessary knowledge for the Agent to complete its task.\n" - " The more scoped down the documents, the more reliable the performance.\n" - "When creating an Agent, you can include both knowledge from [connectors](/overview/core_features/connectors)\n" - "or file upload. The knowledge from connectors will be kept up to date as documents change in the external sources.\n" - "### Actions\n" - " If any of the built-in actions (Web Search, Internal Search, Image Generation, Code Interpreter) are missing,\n" - " contact your Onyx admin.\n" - " These must be set up in the admin-panel before being made available in the Agent creation flow.\n" - "[Actions](/overview/core_features/actions) (sometimes known as Tools)\n" - "allow the Agents to do things in external applications via APIs.\n" - "Some tools help Onyx give better answers (such as the Onyx built-in tools)\n" - "while others allow the system to do more than answer questions.\n" - "Some example common Actions include:\n" - "- Updating ticket statuses based on the conversation and if the user's needs were addressed.\n" - "- Checking the status of a service to give real-time answers.\n" - "- Moving deals along a sales pipeline in a CRM based on call transcripts or user request.\n" -) -core_features_chat_title = "Chat" -core_features_chat = ( - " On the top left of the page (just right of the sidebar), you can select the mode of the UI.\n" - ' Replace "Auto" with "Chat" to always go into this Chat UI.\n' - "Onyx provides a natural language chat interface as the main way of interacting with the features.\n" - "The page below contains an overview of the main components and features.\n" - "## Input Bar\n" - "### Chat with Files / URLs\n" - "The leftmost button of the input bar lets users add context into the Chat session.\n" - "Users can choose between uploading files or selecting URLs as well as reusing previous files or URLs.\n" - " URLs behind Logins, Captcha, or Paywalls that are not scrapeable are not accessible.\n" - " Consider using a [Connector](/overview/core_features/connectors) instead.\n" - "### Actions Selector\n" - "The second button lets users disable or force the use of Actions. There are 4 built-in Actions:\n" - "- **[Internal Search](/overview/core_features/internal_search)**:\n" - " Enables the LLM to search the indexed knowledge from [Connectors](/overview/core_features/connectors).\n" - "- **[Web Search](/overview/core_features/web_search)**: Enables the LLM to search the internet.\n" - " Requires an admin to set up an API key for a search provider.\n" - "- **[Code Interpreter](/overview/core_features/code_interpreter)**:\n" - " Enables the LLM to use a sandboxed Python runtime to execute code and run data analysis.\n" - "- **[Image Generation](/overview/core_features/image_generation)**: Allows the LLM to generate images.\n" - " Requires setting up an image generation API.\n" - "The Actions below the separator represent custom admin configured Actions.\n" - "See [Actions & MCP](/overview/core_features/actions) to learn about custom Actions.\n" - "### Deep Research\n" - "Toggle **Deep Research** using the hourglass icon. When turned on, the LLM will be able to run many cycles of thinking,\n" - "research, and actions to give the best possible result for the user.\n" - "This mode is intended for complicated questions that may need to pull together many sources together or requires\n" - "significant reasoning.\n" - " Deep Research may take up to several minutes and could cost many times (>10x) the token cost of a normal inference.\n" - "### Model Selector\n" - "Onyx supports all major LLM providers as well as self-hosting options like Ollama, VLLM, etc. For select models,\n" - "users can also configure the creativity and reasoning level.\n" - "## Sidebar Contents\n" - "The left sidebar contains:\n" - "- `New Session` button to clear the history and start a new Chat or [Search](/overview/core_features/internal_search) session.\n" # noqa: E501 - "- `Projects` to help users organize chats and reuse different sets of documents. See section below for more info.\n" - "- `Agents` section to start a new session with yours or your team's custom [Agents](/overview/core_features/agents).\n" - "- `Sessions` section containing a list of the most recent conversations.\n" - "The right sidebar contains sources and citations that were used in generating the answer.\n" - "These can come from either `Internal Search` or `Web Search` or both.\n" - "Documents in the right sidebar can also be selected to be included in full for the next message in the Chat session.\n" - " It's often useful to ask a question to find a document, then select it to do a deep dive on it.\n" - "## Projects\n" - "**Projects** are a collection of instructions (prompts) and files as well as a grouping for chats.\n" - "Use projects to organize ongoing work,\n" - "or as a handy way to reuse instructions and files without going through the Agent creation flow.\n" - "## Miscellaneous Chat Features\n" - "**Chat Sharing** - share chats with other team members by using the share-chat button in the top right (left of the\n" - "Sources sidebar).\n" - "**Feedback** - give feedback viewable to the admins using the thumbs-up/thumbs-down buttons when hovering an LLM\n" - "response\n" - "**Regenerate** - modify your inputs by clicking the user messages or regenerate the LLM response with another model.\n" - "**Copying** - copy the LLM output or markdown/code blocks by clicking on the copy button which shows on hover.\n" -) -core_features_code_interpreter_title = "Code Interpreter" -core_features_code_interpreter = ( - "## Overview\n" - " Example run where the LLM generates code to run data analysis on a business report.\n" - "The ability to execute code unlocks the ability for the LLMs to do things such as:\n" - "- Performing larger calculations accurately\n" - "- Running data analysis on provided files\n" - "- Generating or modifying data/files\n" - "**Note**: The code interpreter is built-in functionality available to all deployments without any configuration needed.\n" - "## Features\n" - "- **Python Runtime**: A secure Python runtime with all dangerous functionality removed (such as accessing the network,\n" - " directories outside of the specified, etc.)\n" - "- **Libraries**: Comes with a set of libraries such as numpy, pandas, scipy, matplotlib, and more.\n" - "- **File Input**: Ability to pass arbitrary file types along with the code to run against it.\n" - "- **File Output**: Files can be created and provided back to the user.\n" - "- **STDIN/STDOUT Capture**: Ability to show the user any outputs of the programs executed.\n" - "- **Graph Rendering**: The Onyx [Chat UI](/overview/core_features/chat)\n" - " is able to render returned graphs and other visualization for the user.\n" - "## Usage\n" - "The Code Interpreter does not need to be invoked explicitly,\n" - "the LLM will determine when to use it depending on the user query.\n" - "It can also be attached to custom Agents, giving the LLM the option to use it as needed.\n" -) -core_features_connectors_title = "Connectors" -core_features_connectors = ( - "## What are Connectors?\n" - "Onyx uses Connectors to build an understanding of your documents, team,\n" - "and higher level concepts so that answers are grounded and specific to your organization's knowledge.\n" - "Connectors:\n" - "- Keep all updates synced between external systems and Onyx.\n" - "- Pull in metadata and additional signals to ensure answer relevance.\n" - "- Respect all user permissions (Enterprise Edition only).\n" - "## Common Connector Questions\n" - " Click this card to see the full list of supported connectors.\n" - " You can also push documents directly into Onyx via [API](/developers/guides/index_files_ingestion_api)\n" - " or via File Upload.\n" - " All processing and storage of documents and metadata happen within Onyx.\n" - " There are options to use LLMs or third party providers during the indexing flow but by default everything is\n" - " processing entirely locally.\n" - " Click this card to see more about security.\n" - " In the same way LLMs are pre-trained on massive amounts of internet data,\n" - " Onyx builds an understanding of all of the documents, concepts, and people within your organization.\n" - " This allows Onyx to provide more accurate answer to questions that relate to internal knowledge compared to using the\n" - " applications' provided search APIs at query time.\n" - " Click this card to learn more about Internal Search in Onyx.\n" -) -core_features_image_generation_title = "Image Generation" -core_features_image_generation = ( - "## Overview\n" - "The image generation feature allows users to create PNG images according to their prompts which can be rendered in the\n" - "chat and easily downloaded.\n" - "## Configuration\n" - "Currently, Onyx supports two APIs for image generation, both through OpenAI. In the future,\n" - "there likely will be support for other options such as Google Imagen or Stability AI.\n" - "**GPT-Image-1**: Newer model, better prompt adherence. Likely a better default for most use cases.\n" - "**DALL-E 3**: Older model, slightly better for more imaginative and rich styles.\n" - "## Usage\n" - "To use **Image Generation**,\n" - "be explicit in the prompting since the system is tuned to not generate images unless directly instructed.\n" - "See below for the instructions provided to the system for when to create images.\n" - " Tool Description:\n" - " ```\n" - " Generate an image from a prompt.\n" - " ```\n" - " Instruction (System Prompt) Modification:\n" - " ```\n" - " NEVER use image_gen unless the user specifically requests an image.\n" - " ```\n" - " This phrase is injected into the default **Instruction** for Onyx if the **Image Generation** (image_gen)\n" - " tool is available.\n" -) -core_features_internal_search_title = "Internal Search" -core_features_internal_search = ( - "One of Onyx's most standout features is the ability to enrich the LLM's general world knowledge with context unique to\n" - "your team. Onyx uses [Connectors](/overview/core_features/connectors)\n" - "to index knowledge from your team's applications to build an understanding of the documents, people,\n" - "and concepts within your organization.\n" - "Documents, metadata, and access permissions are all kept up to date in near real time.\n" - "## Search UI\n" - " On the top left of the page, you can select the mode of the UI.\n" - ' Replace "Auto" with "Search" to always go into this view.\n' - " Onyx's context retrieval respects user level permissions which is only configurable via the Enterprise Edition.\n" - "Onyx's knowledge connectivity can be used via both the **Search** and [Chat](/overview/core_features/chat) interface.\n" - "The Search interface provides a better view of documents and is better for quickly accessing documents when the intent\n" - "is not to get an answer.\n" - "Users do not need to explicitly select this mode — when a query is classified by Onyx as a document search,\n" - "it will automatically go into this UI experience.\n" - "### Filters\n" - "The Search UI also provides more advanced filtering options:\n" - "The top bar allows users to filter by time ranges (date range / time offset), authors, and tags (e.g. `Folder:\n" - "Engineering`).\n" - "The side filters allow users to filter by the source type of the documents.\n" - "## Chat UI\n" - "Context from your applications are also available in the Chat UI and to Onyx Agents.\n" - "Deep Research mode is also a Chat UI feature.\n" - "Click [here](/overview/core_features/chat) to learn more about the Chat experience.\n" -) -core_features_web_search_title = "Web Search" -core_features_web_search = ( - "## Overview\n" - "Onyx can access the internet for questions that require up to date information or for niche information that the LLM may\n" - "not be certain about.\n" - "Users can toggle the **Web Search** Action on the fly to override the LLM's decision.\n" - "If [Internal Search](/overview/core_features/internal_search) was used during the research process,\n" - "Onyx will seamlessly combine web sources with internal documents in both the answer generation and for displaying in the\n" - "UI.\n" - "## Requirements\n" - "To provide Web Search functionality,\n" - "Onyx requires both the ability to get search results and to be able to parse websites for more complete context.\n" - "This is broken down into 1) *the search provider* and 2) *the web scraper*.\n" - "### Search Providers\n" - "Onyx provides multiple search providers (pricing subject to change, please double check):\n" - "| Name | Provider | Price | Benefit |\n" - "|------|----------|-------|---------|\n" - "| Google PSE | Google | Free tier + $5/1000 queries | Official Google search results, high trust option for security conscious teams. |\n" # noqa: E501 - "| Serper | Serper.dev | Free tier + $0.30/1000 queries | Fast, and cost-effective |\n" - "| Exa | Exa.ai | $5/1000 queries | AI-optimized with better semantic capabilities|\n" - "### Web Scraper\n" - "As the Search Providers only give short snippets and metadata,\n" - "a scraper is used to fetch the full site contents for more complete/reliable answers.\n" - "| Name | Requires Config | Benefits |\n" - "|------|----------------|----------|\n" - "| Onyx built-in | No | No third parties get access to user queries, free to use |\n" - "| Firecrawl | Yes, API key | More performant with better edge case handling |\n" -) -core_features_workflows_title = "Workflows (Coming Soon)" -core_features_workflows = ( - " **Coming Soon!**\n" - " This feature is currently under development. Stay tuned for updates!\n" - "## What's Coming\n" - "The Onyx Workflows feature will enable:\n" - "- **Asynchronous Actions**: Set up Agents to run when triggered by events or on a time basis.\n" - "- **Batch Processing**: Set up instructions to run against large sets of objects to automate repeat work.\n" - "- **Acknowledgements**: Optionally set up notifications to give approval for more sensitive Actions.\n" - "- **Reports**: Get breakdowns of the work that was done for you in the background.\n" -) -getting_started_faq_title = "FAQ" -getting_started_faq = ( - "## General Questions\n" - " You can ask Onyx about general world knowledge known to the LLM,\n" - " knowledge from [connected applications](/overview/core_features/internal_search),\n" - " or things searchable on the web (if [Web Search](/overview/core_features/web_search) is configured)\n" - " Please check the [Security](/security/architecture/system_description) tab to learn more.\n" - " Onyx is built with security and data privacy as a core commitment.\n" - " Onyx is built for teams of all sizes whether it's a single user looking for a local Chat UI or a global enterprise\n" - " needing a unified GenAI solution for the entire workforce.\n" - " Onyx emphasizes data privacy and security as well as reliable responses by connecting to knowledge whether private\n" - " or from the web.\n" - " Yes, however Onyx needs an LLM to function properly.\n" - " You can air gap the entire system but you would need to run a local LLM.\n" - " Note that we strongly recommend using a recent and non-quantized LLM for the best experience.\n" - "## Technical Issues\n" - " The most common culprit is under-resourcing the deployment.\n" - " Please refer to the [Resourcing](/deployment/getting_started/resourcing) page to double check.\n" - " No! Onyx is intended to provide a fast and snappy experience. If the responses are slow,\n" - " it may be due to a couple issues.\n" - " - The LLM attached to the system is slow, has low throughput, or does not support streaming.\n" - " - You've configured locally running models that are not the default but you do not have a GPU available to the\n" - " system. Typically this is from setting a local reranking or embedding model.\n" - "## Knowledge and Search\n" - " If it's an internal document,\n" - " it may be because the indexing of the application has not completed or because the access controls are incorrectly\n" - " set. In cases of failure, the system always defaults to least permissive.\n" - " The most common failure is that the [connector](/admin/connectors/overview) is incorrectly configured.\n" - " Onyx connectors will fetch updates on a set schedule (typically 30 minutes),\n" - " this polling frequency can be configured by the admin for each connector. The documents, metadata,\n" - " and access permissions all receive updates.\n" - " Web Search must be configured by an admin to be usable.\n" - " It requires setting up one of the supported Search providers and also a scraper (though this is optional as Onyx\n" - " provides one built in).\n" -) -getting_started_use_cases_title = "Use Cases" -getting_started_use_cases = ( - " [See how Ramp uses Onyx](https://www.onyx.app/blog/ramp-case-study)\n" - " to automatically resolve 93% of internal and customer questions!\n" - "## AI-Powered Team\n" - "Give your team secure access to all major LLMs such as GPT, Claude, Gemini, Deepseek, Llama,\n" - "and more - all with access to advanced utilities.\n" - " Use LLMs to help quickly summarize documents, explain key concepts, or create derivative works.\n" - " Get answers to any topic using a combination of Web Search and internal knowledge or run a deeper exploration with\n" - " Deep Research.\n" - " Execute code to run complex data crunching tasks, generate graphs to help visualize results,\n" - " and chat with the LLM to interpret the results.\n" - " Generate images, draft content from scratch, or refine existing works with AI suggestions.\n" - "## Enterprise Search\n" - "Quickly access knowledge across all of your team's applications from wikis to chats and everything in between.\n" - " A single interface to find knowledge across the entire organization.\n" - " Leverage analytics and users feedback to identify holes in your team's knowledge base.\n" - " Reduce misinformation and downstream costs.\n" - " Let new team members unblock themselves and reduce distractions for more senior members.\n" - "## Sales\n" - "Help your sales team stay up to date and focus on closing.\n" - " Instantly access customer history, past interactions,\n" - " and account details before any call or ask questions against past call transcripts.\n" - " Gather competitive intelligence and stay ahead of the market.\n" - " Create custom Agents to run deep analysis on your pipeline based on all connected knowledge.\n" - "## Support\n" - "Keep customers happy with faster resolutions and more reliable support.\n" - " AI helps your team quickly surface past tickets and runbooks to craft accurate answers for users.\n" - " Onyx ensures that all knowledge is kept up to date with any product or documentation changes.\n" - " Build automations on Onyx to automatically resolve up to >90% of customer tickets.\n" - "## Engineering\n" - "Help your team ship with speed and confidence through access to GenAI and internal knowledge.\n" - " Accelerate development by having an AI copilot for every developer.\n" - " Have Onyx find and explain design docs, internal services,\n" - " and relevant other projects to ensure devs have full context for every project.\n" - " Quickly check against past tickets and projects to avoid duplicate work and accumulation of tech debt.\n" -) -miscellaneous_contact_us_title = "Contact Us" -miscellaneous_contact_us = "Contact us at [hello@onyx.app](mailto:hello@onyx.app) or book a call with us on our [Calendar](https://cal.com/team/onyx/founders)." -miscellaneous_open_source_statement_title = "Open Source Statement" -miscellaneous_open_source_statement = ( - "## Our Mission\n" - "Our mission is to make Generative AI and knowledge accessible to every team worldwide.\n" - "As large language models—both proprietary and open-source—become increasingly widespread,\n" - "Onyx serves as the interface to their knowledge and reasoning capabilities.\n" - "Onyx enriches the utility of the LLM by providing additional context (both web and team internal),\n" - "built-in tools like code interpreter, and user created Actions.\n" - "## Why Open Source?\n" - " We believe teams should feel safe with the AI platform that they adopt. That's why Onyx is fully transparent.\n" - " You'll have peace of mind knowing exactly how your data is processed and stored,\n" - " and all of this happening within the Onyx deployment.\n" - " With GenAI being such a fundamental piece of modern company strategy,\n" - " we want to offer the most flexible and future proof option.\n" - " We understand that every team is unique in their needs so we're building Onyx with an emphasis on customizability,\n" - " both for building on top of the platform and directly modifying it.\n" - " Open source also gives control over to your team. With the GenAI space rapidly evolving,\n" - " your vendor of choice may not always be aligned with your team's direction.\n" - " OSS combines the benefits of building in-house with getting product updates for free.\n" - " Open source also prevents lock in so that you can leverage any LLM provider (or your own LLM).\n" - "## Commercial Viability\n" - "We are a team of builders and we want to have as many people find value from our software as possible.\n" - "This is our singular goal and everything that we do derives from this.\n" - "To push the boundaries of user experience and AI innovation,\n" - "we've assembled a core team of world-class developers who share this vision.\n" - "To borrow from Sid Sijbrandij (Co-Founder, GitLab):\n" - '> "We need to think in the interests of the project, while tending to the realities of running a business to support it...' - 'After all, we know that to sustain the project, we need to make it commercially viable."\n' - "We believe in radical transparency—both in how we build open software and in the commercial realities of competing in\n" - "this rapidly evolving space.\n" - " Every organization, regardless of size or budget, will always have access to Onyx's core capabilities—including RAG,\n" - " deep research, custom agents, and more—completely free.\n" - "For organizations with special requirements—such as usage auditing, granular access controls,\n" - "and white-labeling—we offer the Enterprise Edition, available both as a self-hosted solution and through Onyx Cloud.\n" - "The Enterprise Edition sustains our mission,\n" - "enabling us to keep the vast majority of Onyx's features free and open for everyone.\n" - "## On Contributions\n" - "Onyx is a project built in collaboration with our community and we openly welcome contributions.\n" - "It is a point of emphasis of our team to ensure that the Onyx project continues to be easy for teams to contribute to or\n" - "maintain in house. This comes down to:\n" - "- Intentional high level architecture.\n" - "- Strong product direction and refusal to accept bloat for niche use cases.\n" - "- A consistent and high quality of engineering best practices across the code base.\n" - "To that end,\n" - "we ask that contributors work on smaller issues to start and get approval from the maintainers for larger feature\n" - "contributions.\n" -) -onyx_anywhere_chrome_extension_title = "Chrome Extension" -onyx_anywhere_chrome_extension = ( - " The Chrome extension is available but is undergoing a fairly major rework,\n" - " it is recommended to wait until the next major release prior to deploying this\n" - "Use the Onyx extension to ask questions from anywhere. You can also replace your new-tab page with a custom Onyx page:\n" - "- Onyx Search on new tabs\n" - "- Favorite website bookmarks\n" - "- Onyx as a sidebar to any page in Chrome\n" - " In the future,\n" - " the Onyx Chrome Extension will allow you to ask questions about the page you are currently on and optionally index the\n" - " recent pages into the Onyx knowledge base.\n" - " You'll be able to ask questions about recently visited pages via both the extension and the Onyx web app.\n" - "## Getting Started\n" - "Once your administrator has set up the Chrome extension for your organization, you can start using it immediately.\n" - "**For Onyx Cloud users**: Install directly from the Chrome Web Store **For self-hosted users**:\n" - "Your administrator will provide installation instructions\n" - "## Using the Extension\n" - "### **Ask Questions Anywhere**\n" - "- Click the Onyx extension icon in your browser toolbar\n" - "- Type your question in natural language\n" - "- Get instant answers with source citations\n" - "### **New Tab Experience**\n" - "- Replace your default new tab with Onyx search\n" - "- Access your favorite website bookmarks\n" - "- Quick search across your organization's knowledge\n" - "### **Sidebar Mode**\n" - "- Open Onyx as a sidebar on any webpage\n" - "- Ask questions about your current work without leaving the page\n" - "- Perfect for research and context-sensitive queries\n" - "## Settings and Options\n" - "To customize your extension experience:\n" - " Click the three dots (...) next to the Onyx extension\n" - " Select **Options**\n" - " Configure your preferences for search, bookmarks, and new tab behavior\n" - " **Need help with setup?** Contact your Onyx administrator for installation assistance or configuration questions.\n" -) -onyx_anywhere_mobile_app_title = "Mobile App (Coming Soon)" -onyx_anywhere_mobile_app = ( - " Currently Onyx is a responsive application and so your Onyx deployment will work on your smartphone or tablet via your\n" - " browser app.\n" - " While is is not as nice of an experience as a native app,\n" - " it can be used in the meantime while the Onyx Mobile App is under development.\n" - "## Mobile App\n" - "The Onyx mobile app is currently under development.\n" - "This native mobile application will bring the full power of Onyx to your smartphone and tablet devices.\n" -) -onyx_anywhere_slack_title = "Slack Bot" -onyx_anywhere_slack = ( - "## Overview\n" - "Bring Onyx's AI capabilities directly into your conversations via Slack App.\n" - "Onyx allows for highly flexible Slack configurations so that you use all of your Onyx Agents directly in your favorite\n" - "channels.\n" - "## Supported Features\n" - "- Support for unlimited Slack Apps. This way you can associate Slack Apps with Onyx Agents for specific use cases.\n" - "- Channel level configurations. Every channel can have different default behavior based on the channel's purpose.\n" - "- Answers using internal or web knowledge are backed by citations and link back to the original sources.\n" - "- Works in Threads, Channels and DMs.\n" - " Try asking Onyx to summarize Threads by tagging the Onyx Slack Bot in the Thread!\n" - "## Try it out\n" - "The Onyx Slack Bot is always live and serving answers to the community in our public Slack.\n" - "To test it out,\n" - "join the [community Slack](https://join.slack.com/t/onyx-dot-app/shared_invite/zt-34lu4m7xg-TsKGO6h8PDvR5W27zTdyhA)\n" - "and see the #ask-onyx channel or tag **@OnyxBot** from anywhere.\n" -) -onyx_anywhere_web_interface_title = "Web App" -onyx_anywhere_web_interface = ( - "The Web App is the default way to use Onyx and the recommended for the most complete experience.\n" - "The admin panel is also a web-app exclusive feature which is the easiest way to manage the\n" - "[Agents](/overview/core_features/agents), [Actions](/overview/core_features/actions),\n" - "[Connectors](/overview/core_features/connectors), users, settings and more.\n" - " A great place to get familiar with the experience is to start with the [Chat](/overview/core_features/chat)\n" - " overview or the [Admin](/admin/overview) tab for managing the deployment.\n" - "If you're deploying Onyx locally (guide [here](/deployment/getting_started/quickstart)),\n" - "you should be able to access the Web UI at http://localhost:3000/.\n" -) - -# For simplicity, we're not adding any metadata suffix here. Generally there is none for the Web connector anyway - -# Welcome -welcome_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/welcome", - title=welcome_title, - content=welcome, - title_embedding=list(model.encode(f"search_document: {welcome_title}")), - content_embedding=list( - model.encode(f"search_document: {welcome_title}\n{welcome}") - ), -) - -# Core Features -core_features_actions_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/actions", - title=core_features_actions_title, - content=core_features_actions, - title_embedding=list( - model.encode(f"search_document: {core_features_actions_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_actions_title}\n{core_features_actions}" - ) - ), -) - -core_features_agents_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/agents", - title=core_features_agents_title, - content=core_features_agents, - title_embedding=list( - model.encode(f"search_document: {core_features_agents_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_agents_title}\n{core_features_agents}" - ) - ), -) +_ = model.tokenizer # kept for parity; unused but ensures tokenizer loads -core_features_chat_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/chat", - title=core_features_chat_title, - content=core_features_chat, - title_embedding=list(model.encode(f"search_document: {core_features_chat_title}")), - content_embedding=list( - model.encode( - f"search_document: {core_features_chat_title}\n{core_features_chat}" - ) - ), -) +base_path = Path("./backend/onyx/seeding") +input_path = base_path / "initial_docs_cohere.json" +output_path = base_path / "initial_docs.json" -core_features_code_interpreter_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/code_interpreter", - title=core_features_code_interpreter_title, - content=core_features_code_interpreter, - title_embedding=list( - model.encode(f"search_document: {core_features_code_interpreter_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_code_interpreter_title}\n{core_features_code_interpreter}" - ) - ), -) +raw_docs: list[dict] = json.loads(input_path.read_text()) -core_features_connectors_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/connectors", - title=core_features_connectors_title, - content=core_features_connectors, - title_embedding=list( - model.encode(f"search_document: {core_features_connectors_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_connectors_title}\n{core_features_connectors}" - ) - ), -) +documents: list[SeedPresaveDocument] = [] +for d in raw_docs: + title = (d.get("title") or "").strip() + content = d.get("content") or "" + url = d.get("url") or "" + chunk_ind = int(d.get("chunk_ind", 0) or 0) -core_features_image_generation_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/image_generation", - title=core_features_image_generation_title, - content=core_features_image_generation, - title_embedding=list( - model.encode(f"search_document: {core_features_image_generation_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_image_generation_title}\n{core_features_image_generation}" - ) - ), -) + title_emb = list(model.encode(f"search_document: {title}")) + content_emb = list(model.encode(f"search_document: {title}\n{content}")) -core_features_internal_search_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/internal_search", - title=core_features_internal_search_title, - content=core_features_internal_search, - title_embedding=list( - model.encode(f"search_document: {core_features_internal_search_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_internal_search_title}\n{core_features_internal_search}" + documents.append( + SeedPresaveDocument( + url=url, + title=title, + content=content, + title_embedding=title_emb, + content_embedding=content_emb, + chunk_ind=chunk_ind, ) - ), -) - -core_features_web_search_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/web_search", - title=core_features_web_search_title, - content=core_features_web_search, - title_embedding=list( - model.encode(f"search_document: {core_features_web_search_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_web_search_title}\n{core_features_web_search}" - ) - ), -) - -core_features_workflows_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/core_features/workflows", - title=core_features_workflows_title, - content=core_features_workflows, - title_embedding=list( - model.encode(f"search_document: {core_features_workflows_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {core_features_workflows_title}\n{core_features_workflows}" - ) - ), -) - -# Getting Started -getting_started_faq_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/getting_started/faq", - title=getting_started_faq_title, - content=getting_started_faq, - title_embedding=list(model.encode(f"search_document: {getting_started_faq_title}")), - content_embedding=list( - model.encode( - f"search_document: {getting_started_faq_title}\n{getting_started_faq}" - ) - ), -) - -getting_started_use_cases_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/getting_started/use_cases", - title=getting_started_use_cases_title, - content=getting_started_use_cases, - title_embedding=list( - model.encode(f"search_document: {getting_started_use_cases_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {getting_started_use_cases_title}\n{getting_started_use_cases}" - ) - ), -) - -# Miscellaneous -miscellaneous_contact_us_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/miscellaneous/contact_us", - title=miscellaneous_contact_us_title, - content=miscellaneous_contact_us, - title_embedding=list( - model.encode(f"search_document: {miscellaneous_contact_us_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {miscellaneous_contact_us_title}\n{miscellaneous_contact_us}" - ) - ), -) - -miscellaneous_open_source_statement_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/miscellaneous/open_source_statement", - title=miscellaneous_open_source_statement_title, - content=miscellaneous_open_source_statement, - title_embedding=list( - model.encode(f"search_document: {miscellaneous_open_source_statement_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {miscellaneous_open_source_statement_title}\n{miscellaneous_open_source_statement}" - ) - ), -) - -# Onyx Anywhere -onyx_anywhere_chrome_extension_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/chrome_extension", - title=onyx_anywhere_chrome_extension_title, - content=onyx_anywhere_chrome_extension, - title_embedding=list( - model.encode(f"search_document: {onyx_anywhere_chrome_extension_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {onyx_anywhere_chrome_extension_title}\n{onyx_anywhere_chrome_extension}" - ) - ), -) - -onyx_anywhere_mobile_app_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/mobile_app", - title=onyx_anywhere_mobile_app_title, - content=onyx_anywhere_mobile_app, - title_embedding=list( - model.encode(f"search_document: {onyx_anywhere_mobile_app_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {onyx_anywhere_mobile_app_title}\n{onyx_anywhere_mobile_app}" - ) - ), -) - -onyx_anywhere_slack_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/slack", - title=onyx_anywhere_slack_title, - content=onyx_anywhere_slack, - title_embedding=list(model.encode(f"search_document: {onyx_anywhere_slack_title}")), - content_embedding=list( - model.encode( - f"search_document: {onyx_anywhere_slack_title}\n{onyx_anywhere_slack}" - ) - ), -) - -onyx_anywhere_web_interface_doc = SeedPresaveDocument( - url=DOCUMENTATION_BASE_URL + "/overview/onyx_anywhere/web_interface", - title=onyx_anywhere_web_interface_title, - content=onyx_anywhere_web_interface, - title_embedding=list( - model.encode(f"search_document: {onyx_anywhere_web_interface_title}") - ), - content_embedding=list( - model.encode( - f"search_document: {onyx_anywhere_web_interface_title}\n{onyx_anywhere_web_interface}" - ) - ), -) - -documents = [ - # Welcome - welcome_doc, - # Core Features - core_features_actions_doc, - core_features_agents_doc, - core_features_chat_doc, - core_features_code_interpreter_doc, - core_features_connectors_doc, - core_features_image_generation_doc, - core_features_internal_search_doc, - core_features_web_search_doc, - core_features_workflows_doc, - # Getting Started - getting_started_faq_doc, - getting_started_use_cases_doc, - # Miscellaneous - miscellaneous_contact_us_doc, - miscellaneous_open_source_statement_doc, - # Onyx Anywhere - onyx_anywhere_chrome_extension_doc, - onyx_anywhere_mobile_app_doc, - onyx_anywhere_slack_doc, - onyx_anywhere_web_interface_doc, -] - -documents_dict = [doc.model_dump() for doc in documents] + ) -with open("./backend/onyx/seeding/initial_docs.json", "w") as json_file: - json.dump(documents_dict, json_file, indent=4) +output_path.write_text(json.dumps([d.model_dump() for d in documents], indent=4)) diff --git a/backend/tests/regression/search_quality/test_queries.json.template b/backend/tests/regression/search_quality/test_queries.json.template index e5646d3f03b..eaa2306616b 100644 --- a/backend/tests/regression/search_quality/test_queries.json.template +++ b/backend/tests/regression/search_quality/test_queries.json.template @@ -4,11 +4,7 @@ "ground_truth": [ { "doc_source": "web", - "doc_link": "https://docs.onyx.app/more/use_cases/overview" - }, - { - "doc_source": "web", - "doc_link": "https://docs.onyx.app/more/use_cases/ai_platform" + "doc_link": "https://docs.onyx.app/welcome" } ], "categories": [ From b538f112c2eeefb94d822e802001840f1fea58d8 Mon Sep 17 00:00:00 2001 From: Wenxi Date: Mon, 8 Sep 2025 14:40:17 -0700 Subject: [PATCH 4/4] greptile nit Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> --- backend/scripts/document_seeding_prep.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/backend/scripts/document_seeding_prep.py b/backend/scripts/document_seeding_prep.py index 4933c00b455..c836034fd78 100644 --- a/backend/scripts/document_seeding_prep.py +++ b/backend/scripts/document_seeding_prep.py @@ -38,7 +38,7 @@ class SeedPresaveDocument(BaseModel): title = (d.get("title") or "").strip() content = d.get("content") or "" url = d.get("url") or "" - chunk_ind = int(d.get("chunk_ind", 0) or 0) + chunk_ind = int(d.get("chunk_ind", 0)) title_emb = list(model.encode(f"search_document: {title}")) content_emb = list(model.encode(f"search_document: {title}\n{content}"))