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description=GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more. - Canner/WrenAI;

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github canner wrenai genbi generative bi for ai agents an open source governed text to sql through an open context layer that turns natural language questions into trusted dashboards charts and sql across 20 data sources such as bigquery snowflake postgresql clickhouse amazon redshift databricks and more github skip to content navigation menu toggle navigation sign in appearance settings platform ai code creation github copilot write better code with ai github copilot app direct agents from issue to merge mcp registry new integrate external tools developer workflows actions automate any workflow codespaces instant dev environments issues plan and track work code review manage code changes code quality enforce quality at merge application security github advanced security find and fix vulnerabilities code security secure your code as you build secret protection stop leaks before they start explore why github documentation blog changelog marketplace view all features solutions by company 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search code repositories users issues pull requests search clear search syntax tips provide feedback we read every piece of feedback and take your input very seriously include my email address so i can be contacted cancel submit feedback saved searches use saved searches to filter your results more quickly name query to see all available qualifiers see our documentation cancel create saved search sign in sign up appearance settings resetting focus you signed in with another tab or window reload to refresh your session you signed out in another tab or window reload to refresh your session you switched accounts on another tab or window reload to refresh your session dismiss alert message uh oh there was an error while loading please reload this page canner wrenai public notifications you must be signed in to change notification settings fork 1 9k star 16 5k code issues 275 pull requests 89 discussions actions projects security and quality 0 insights additional navigation options code issues pull requests discussions actions projects security and quality insights canner wrenai main branches tags go to file code open more actions menu folders and files name name last commit message last commit date latest commit history 2 595 commits 2 595 commits claude claude github github core core docs core docs core evals spodbtify_ab evals spodbtify_ab examples v5 jaffle examples v5 jaffle misc misc scripts scripts sdk sdk skills skills editorconfig editorconfig gitignore gitignore gitmodules gitmodules release please manifest json release please manifest json changelog md changelog md code_of_conduct md code_of_conduct md contributing md contributing md license license license agpl 3 0 license agpl 3 0 license apache 2 0 license apache 2 0 license cc by 4 0 license cc by 4 0 readme md readme md security md security md release please config json release please config json view all files repository files navigation readme code of conduct contributing license agpl 3 0 license apache 2 0 license cc by 4 0 license security more items open source genbi generative bi for ai agents your agents generate deploy and govern dashboards from any database grounded in a context layer they can actually trust docs discord vision blog 2026 05 07 wren engine has merged into this repo under core the previous canner wren engine repo is archived the previous wrenai genbi app the docker based chat first bi product is preserved on the legacy v1 branch tag v1 final and is now wren genbi classic see a note on the genbi name below read the announcement what wrenai is wrenai is the open source genbi engine it lets ai agents generate deploy and govern business intelligence from a sql answer to a shareable dashboard across 22 data sources what makes the output trustworthy is the layer underneath an open context layer that gives agents what schemas don t that means business semantics approved definitions examples memory and governance plus the unstructured company knowledge that lives in your docs wikis and chat threads generative bi is only as good as the context it stands on and wren is that context made reviewable and reusable by every agent you already run genbi in three beats generate deploy know generate your agent turns a business question into governed sql and charts schema aware retrieval mdl planning dry plan validation and structured errors keep it correct instead of confidently wrong deploy turn any answer into a shareable browser side dashboard powered by wren core wasm and ship it to your own vercel or cloudflare pages account with one command know the knowledge that makes all of this correct lives in versionable evidence linked files semantic models mdl company definitions instructions md and a memory of what worked reviewable git friendly never locked inside someone else s ui why agent builders pick wrenai generative bi end to end not just text to sql generate the answer deploy the dashboard share the url all driven by the agents you already use knowledge management built in business meaning approved definitions and proven examples are captured as reviewable version controlled context not buried in prompts open by default open sourced core sdk and skills under the apache 2 0 license correctness as primitives rich schema retrieval dry plan validation structured errors with hints value profiling eval runner the agent orchestrates the trace lives in its reasoning sits on top of your existing stack warehouse transformation pipelines your existing semantic layer not another tool to maintain how wren compares a raw llm agent a traditional bi tool a bare semantic layer wrenai writes sql for you often wrong governed knows your business definitions partial in tool schema only non schema knowledge generates deploys dashboards manual in tool agent driven works through your agents claude code cursor mcp open reviewable git friendly context partial governed execution across 22 sources per connector definitions only wren is for you if you want ai agents to produce trustworthy bi answers and dashboards not just plausible sql your business logic definitions enums units approved joins lives outside the database and your agents keep getting it wrong you want context that s open reviewable and version controlled usable by every agent and person not gated behind one vendor s ui skip wren if you only need a one off chart from a single csv or you re happy letting an agent guess at sql with no governance quickstart wrenai is agent driven by design install the cli install a one file discovery stub for your ai client then let your ai agent drive the rest workflow guides live inside the cli itself and are served on demand so content always matches the installed version 1 install the cli pip install wrenai core duckdb included pip install wrenai postgres memory add per datasource and memory extras as needed tip for users in mainland china if pip install is slow or fails use the tsinghua mirror pip install wrenai i https pypi tuna tsinghua edu cn simple if huggingface model downloads time out add export hf_endpoint https hf mirror com before running the cli 2 install the discovery stub for your ai client npx skills add canner wrenai auto detects claude code cursor cline codex the stub is 50 lines it teaches your agent to fetch workflow guides via wren skills get name and shaped prompts via wren ask question guided direct and everything else lives in the cli 3 ask your agent to set things up open your agent in a project directory and say something like use wren to set up my postgres database the agent runs wren skills get onboarding follows the guide step by step checks your environment creates a connection profile scaffolds the project and runs a first query 4 optional enrich the project the know beat once onboarding finishes ask enrich my wren project with the business context in raw the agent runs wren skills get enrich context and follows the guide in grill mode one question at a time or auto pilot mode agent reads project raw and proposes both modes write to mdl instructions queries and memory all reviewable all git friendly 5 ask questions the generate beat who are our top 10 customers by sales this quarter your agent fetches mdl context recalls similar past queries writes governed sql and executes via wren query 6 build deploy a dashboard the deploy beat turn that into an interactive dashboard i can filter and share and deploy it to vercel the agent runs wren skills get genbi builds a browser side genbi app from your project s context previews it locally and ships it to your own vercel or cloudflare pages account returning a live shareable url see the build deploy a genbi app guide want to try it without your own database ask your agent to use the bundled jaffle_shop sample dataset same flow querying a real warehouse end to end in a couple of minutes two beats first then the third day 1 agent driven wren skills get onboarding workflow guide set up project first query generate wren skills get enrich context workflow guide add business context know wren skills get genbi workflow guide build deploy a dashboard deploy day to day wren query sql query through the mdl semantic layer wren ask question guided wrap a question for a weaker agent wren ask question direct wrap a question for a stronger agent fast at first deep when you need it always reviewable and git friendly what s included modeling definition language mdl models columns relationships views cubes metrics row level column level access control rlac clac engine apache datafusion based 22 data sources genbi dashboards agent built browser side apps powered by wren core wasm deployable to vercel cloudflare pages knowledge memory business meaning in version controlled instructions md and queries yml plus a local lancedb memory index hybrid retrieval for recall agent sdk wren langchain langchain langgraph wren pydantic reference python integration for other stacks governed execution primitives functions dry plan row limits access control what s next end to end correctness primitives value profiling rich retrieval structured errors golden eval runner agent native distribution first class sdks across major agent frameworks see github discussions for what s prioritized next full governed execution audit logs rate limits approval workflow data flow inspector full roadmap and design notes see the introduction a note on the genbi name genbi now refers to this open source generative bi capability agents that generate governed answers and deploy dashboards on top of wren s context layer the earlier wren ai genbi app the docker based chat first bi product is now wren genbi classic preserved on the legacy v1 branch no new features or security fixes for a maintained hosted version of that classic experience see wren ai commercial documentation quickstart from skill install to first answer build deploy a genbi app generate a dashboard and ship it concepts what context is what mdl is how memory works connect a database postgres bigquery snowflake duckdb and more agent sdks what s shipping today what s next community discord chat with the team and other builders github discussions design conversations rfcs longer threads twitter x release notes and short updates blog vision post mortems deep dives contributing we build in the open issues prs connector contributions sdk integrations docs fixes are all welcome contributor guide connector ecosystem program three tier ownership official community blessed community owned architecture map find the right place to land your change looking for somewhere to start try the good first issue label project structure click to expand core wren core rust semantic engine apache datafusion wren core base shared manifest types mdl builder wren core py python bindings pypi wren core wren core wasm webassembly build npm wren core wasm wren python sdk and cli pypi wrenai wren mdl mdl json schema sdk wren langchain reference agent sdk integration skills agent skills for context authoring docs module documentation examples example projects contributors license apache 2 0 see license come build open genbi with us if wrenai helps you drop a it genuinely helps us grow ️ back to top about genbi generative bi for ai agents an open source governed text to sql through an open context layer that turns natural language questions into trusted dashboards charts and sql across 20 data sources such as bigquery snowflake postgresql clickhouse amazon redshift databricks and more docs getwren ai oss introduction topics agent bigquery charts sql postgresql openai vertex genbi text to sql rag text2sql duckdb llm anthropic sqlai text to chart context engineering resources readme license unknown and 3 other licenses found licenses found unknown license agpl 3 0 license agpl 3 0 apache 2 0 license apache 2 0 cc by 4 0 license cc by 4 0 code of conduct code of conduct contributing contributing security policy security policy uh oh there was an error while loading please 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