pacha
Connect your private data to LLMs
Stars: 75
Pacha is an AI tool designed for retrieving context for natural language queries using a SQL interface and Python programming environment. It is optimized for working with Hasura DDN for multi-source querying. Pacha is used in conjunction with language models to produce informed responses in AI applications, agents, and chatbots.
README:
Connect realtime data to your AI
Pacha is an AI tool that does retrieval of context for a natural language query using a SQL interface and a Python programming environment. Pacha is specially built to work with Hasura DDN for authorized multi-source querying.
You would use Pacha with your favourite LLMs to generate grounded responses in your AI apps/agents/chatbots.
- Python version 3.12 or later
- Docker Compose version 2.22.0 or later
- Access to OpenAI or Anthropic.
- A datasource available in Hasura Connector Hub
git clone https://github.com/hasura/pacha.git
cd pacha- Docker installed on your system
- Hasura CLI (optional, for local development)
-
Clone the Pacha repository:
git clone https://github.com/hasura/pacha.git cd pacha -
Create an empty SQLite database file:
touch pacha.db
This creates an empty
pacha.dbfile in the current directory, which will be used as the SQLite database for Pacha. -
Copy the example environment file and configure it:
cp .pacha.env.example .pacha.env
Edit the
.pacha.envfile and fill in the required details:PORT=5001 ANTHROPIC_API_KEY=your_anthropic_api_key SECRET_KEY=your_secret_key CORS_ORIGINS="https://console.hasura.io" -
Build and start the Pacha server:
docker compose up --build
-
Open http://localhost:5001 to open Pacha UI.
-
Use the settings icon (gear) next to the "Pacha Chat" title to configure:
- Pacha server URL (e.g.,
http://localhost:5001if running locally) - Secret token (if you've set one in your
.pacha.envfile)
- Pacha server URL (e.g.,
- For local development or custom builds, you can modify the
Dockerfilein theenginedirectory. - Ensure all required environment variables are set in your
.pacha.envfile or passed to the Docker container.
- If you encounter CORS issues, verify the
CORS_ORIGINSsetting in your.pacha.envfile. - For API key related errors, double-check your
ANTHROPIC_API_KEYin the.pacha.envfile.
- Install Poetry
- Run
poetry installto install Python dependencies.
- Create a Hasura account at hasura.io/ddn
- Scaffold a local Hasura project on a hub connector datasource like this:
poetry run ddn_setup -hc <hub-connector-name> -c <connection string> --dir ddn_projectExample (with Postgres):
poetry run ddn_setup -hc 'hasura/postgres' -c 'postgresql://postgres:postgres@localhost:5432/postgres' --dir ddn_projectExample (with SQL Server):
poetry run ddn_setup -hc 'hasura/sqlserver' -c 'Server=localhost,21433;Uid=SA;Database=sakila;Pwd=Password!;TrustServerCertificate=true' --dir ddn_project- The above generated metadata is where you would configure row / column access control rules for your data.
- Start a local Hasura engine with:
docker compose -f ddn_project/docker-compose.hasura.yaml up -dexamples/chat_with_tool.py is a CLI chat interface that uses Pacha as a tool provided to a supported LLM.
ANTHROPIC_API_KEY=<api-key> poetry run chat_with_tool -d ddn -u <DDN SQL URL> -H <header to pass to DDN> --llm anthropicExample:
ANTHROPIC_API_KEY=<api-key> poetry run chat_with_tool -d ddn -u http://localhost:3000/v1/sql -H 'x-hasura-role: admin' --llm anthropicYou can also run Pacha with OpenAI:
OPENAI_API_KEY=<api-key> poetry run chat_with_tool -d ddn -u <DDN SQL URL> -H <header to pass to DDN> --llm openaiIf you want to run against a custom SQL backend that's not Hasura DDN, you can implement the DataEngine class in pacha/data_engine, and pass that to the Pacha SDK. See usage here.
You can see example Postgres implementation of DataEngine in pacha/data_engine/postgres.py.
You can run Pacha against any LLM that supports function/tool calling by using the Pacha tool directly from pacha/sdk/tools.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for pacha
Similar Open Source Tools
pacha
Pacha is an AI tool designed for retrieving context for natural language queries using a SQL interface and Python programming environment. It is optimized for working with Hasura DDN for multi-source querying. Pacha is used in conjunction with language models to produce informed responses in AI applications, agents, and chatbots.
backend.ai-webui
Backend.AI Web UI is a user-friendly web and app interface designed to make AI accessible for end-users, DevOps, and SysAdmins. It provides features for session management, inference service management, pipeline management, storage management, node management, statistics, configurations, license checking, plugins, help & manuals, kernel management, user management, keypair management, manager settings, proxy mode support, service information, and integration with the Backend.AI Web Server. The tool supports various devices, offers a built-in websocket proxy feature, and allows for versatile usage across different platforms. Users can easily manage resources, run environment-supported apps, access a web-based terminal, use Visual Studio Code editor, manage experiments, set up autoscaling, manage pipelines, handle storage, monitor nodes, view statistics, configure settings, and more.
sandbox
Sandbox is an open-source cloud-based code editing environment with custom AI code autocompletion and real-time collaboration. It consists of a frontend built with Next.js, TailwindCSS, Shadcn UI, Clerk, Monaco, and Liveblocks, and a backend with Express, Socket.io, Cloudflare Workers, D1 database, R2 storage, Workers AI, and Drizzle ORM. The backend includes microservices for database, storage, and AI functionalities. Users can run the project locally by setting up environment variables and deploying the containers. Contributions are welcome following the commit convention and structure provided in the repository.
please-cli
Please CLI is an AI helper script designed to create CLI commands by leveraging the GPT model. Users can input a command description, and the script will generate a Linux command based on that input. The tool offers various functionalities such as invoking commands, copying commands to the clipboard, asking questions about commands, and more. It supports parameters for explanation, using different AI models, displaying additional output, storing API keys, querying ChatGPT with specific models, showing the current version, and providing help messages. Users can install Please CLI via Homebrew, apt, Nix, dpkg, AUR, or manually from source. The tool requires an OpenAI API key for operation and offers configuration options for setting API keys and OpenAI settings. Please CLI is licensed under the Apache License 2.0 by TNG Technology Consulting GmbH.
loz
Loz is a command-line tool that integrates AI capabilities with Unix tools, enabling users to execute system commands and utilize Unix pipes. It supports multiple LLM services like OpenAI API, Microsoft Copilot, and Ollama. Users can run Linux commands based on natural language prompts, enhance Git commit formatting, and interact with the tool in safe mode. Loz can process input from other command-line tools through Unix pipes and automatically generate Git commit messages. It provides features like chat history access, configurable LLM settings, and contribution opportunities.
MindSearch
MindSearch is an open-source AI Search Engine Framework that mimics human minds to provide deep AI search capabilities. It allows users to deploy their own search engine using either close-source or open-source language models. MindSearch offers features such as answering any question using web knowledge, in-depth knowledge discovery, detailed solution paths, optimized UI experience, and dynamic graph construction process.
alcless
Alcoholless is a lightweight security sandbox for macOS programs, originally designed for securing Homebrew but can be used for any CLI programs. It allows AI agents to run shell commands with reduced risk of breaking the host OS. The tool creates a separate environment for executing commands, syncing changes back to the host directory upon command exit. It uses utilities like sudo, su, pam_launchd, and rsync, with potential future integration of FSKit for file syncing. The tool also generates a sudo configuration for user-specific sandbox access, enabling users to run commands as the sandbox user without a password.
openai_trtllm
OpenAI-compatible API for TensorRT-LLM and NVIDIA Triton Inference Server, which allows you to integrate with langchain
BuildCLI
BuildCLI is a command-line interface (CLI) tool designed for managing and automating common tasks in Java project development. It simplifies the development process by allowing users to create, compile, manage dependencies, run projects, generate documentation, manage configuration profiles, dockerize projects, integrate CI/CD tools, and generate structured changelogs. The tool aims to enhance productivity and streamline Java project management by providing a range of functionalities accessible directly from the terminal.
gitingest
GitIngest is a tool that allows users to turn any Git repository into a prompt-friendly text ingest for LLMs. It provides easy code context by generating a text digest from a git repository URL or directory. The tool offers smart formatting for optimized output format for LLM prompts and provides statistics about file and directory structure, size of the extract, and token count. GitIngest can be used as a CLI tool on Linux and as a Python package for code integration. The tool is built using Tailwind CSS for frontend, FastAPI for backend framework, tiktoken for token estimation, and apianalytics.dev for simple analytics. Users can self-host GitIngest by building the Docker image and running the container. Contributions to the project are welcome, and the tool aims to be beginner-friendly for first-time contributors with a simple Python and HTML codebase.
AirCasting
AirCasting is a platform for gathering, visualizing, and sharing environmental data. It aims to provide a central hub for environmental data, making it easier for people to access and use this information to make informed decisions about their environment.
trubrics-python
Trubrics is a Python client for event tracking and analyzing LLM interactions. It offers fast and non-blocking queuing system with automatic flushing to Trubrics API. Users can track events and LLM interactions, adjust logging verbosity, and configure flush intervals and batch sizes. The tool simplifies tracking user interactions and analyzing data for LLM applications.
tiledesk-dashboard
Tiledesk is an open-source live chat platform with integrated chatbots written in Node.js and Express. It is designed to be a multi-channel platform for web, Android, and iOS, and it can be used to increase sales or provide post-sales customer service. Tiledesk's chatbot technology allows for automation of conversations, and it also provides APIs and webhooks for connecting external applications. Additionally, it offers a marketplace for apps and features such as CRM, ticketing, and data export.
raycast_api_proxy
The Raycast AI Proxy is a tool that acts as a proxy for the Raycast AI application, allowing users to utilize the application without subscribing. It intercepts and forwards Raycast requests to various AI APIs, then reformats the responses for Raycast. The tool supports multiple AI providers and allows for custom model configurations. Users can generate self-signed certificates, add them to the system keychain, and modify DNS settings to redirect requests to the proxy. The tool is designed to work with providers like OpenAI, Azure OpenAI, Google, and more, enabling tasks such as AI chat completions, translations, and image generation.
director
Director is a context infrastructure tool for AI agents that simplifies managing MCP servers, prompts, and configurations by packaging them into portable workspaces accessible through a single endpoint. It allows users to define context workspaces once and share them across different AI clients, enabling seamless collaboration, instant context switching, and secure isolation of untrusted servers without cloud dependencies or API keys. Director offers features like workspaces, universal portability, local-first architecture, sandboxing, smart filtering, unified OAuth, observability, multiple interfaces, and compatibility with all MCP clients and servers.
cursor-tools
cursor-tools is a CLI tool designed to enhance AI agents with advanced skills, such as web search, repository context, documentation generation, GitHub integration, Xcode tools, and browser automation. It provides features like Perplexity for web search, Gemini 2.0 for codebase context, and Stagehand for browser operations. The tool requires API keys for Perplexity AI and Google Gemini, and supports global installation for system-wide access. It offers various commands for different tasks and integrates with Cursor Composer for AI agent usage.
For similar tasks
Forza-Mods-AIO
Forza Mods AIO is a free and open-source tool that enhances the gaming experience in Forza Horizon 4 and 5. It offers a range of time-saving and quality-of-life features, making gameplay more enjoyable and efficient. The tool is designed to streamline various aspects of the game, improving user satisfaction and overall enjoyment.
hass-ollama-conversation
The Ollama Conversation integration adds a conversation agent powered by Ollama in Home Assistant. This agent can be used in automations to query information provided by Home Assistant about your house, including areas, devices, and their states. Users can install the integration via HACS and configure settings such as API timeout, model selection, context size, maximum tokens, and other parameters to fine-tune the responses generated by the AI language model. Contributions to the project are welcome, and discussions can be held on the Home Assistant Community platform.
crawl4ai
Crawl4AI is a powerful and free web crawling service that extracts valuable data from websites and provides LLM-friendly output formats. It supports crawling multiple URLs simultaneously, replaces media tags with ALT, and is completely free to use and open-source. Users can integrate Crawl4AI into Python projects as a library or run it as a standalone local server. The tool allows users to crawl and extract data from specified URLs using different providers and models, with options to include raw HTML content, force fresh crawls, and extract meaningful text blocks. Configuration settings can be adjusted in the `crawler/config.py` file to customize providers, API keys, chunk processing, and word thresholds. Contributions to Crawl4AI are welcome from the open-source community to enhance its value for AI enthusiasts and developers.
MaterialSearch
MaterialSearch is a tool for searching local images and videos using natural language. It provides functionalities such as text search for images, image search for images, text search for videos (providing matching video clips), image search for videos (searching for the segment in a video through a screenshot), image-text similarity calculation, and Pexels video search. The tool can be deployed through the source code or Docker image, and it supports GPU acceleration. Users can configure the tool through environment variables or a .env file. The tool is still under development, and configurations may change frequently. Users can report issues or suggest improvements through issues or pull requests.
tenere
Tenere is a TUI interface for Language Model Libraries (LLMs) written in Rust. It provides syntax highlighting, chat history, saving chats to files, Vim keybindings, copying text from/to clipboard, and supports multiple backends. Users can configure Tenere using a TOML configuration file, set key bindings, and use different LLMs such as ChatGPT, llama.cpp, and ollama. Tenere offers default key bindings for global and prompt modes, with features like starting a new chat, saving chats, scrolling, showing chat history, and quitting the app. Users can interact with the prompt in different modes like Normal, Visual, and Insert, with various key bindings for navigation, editing, and text manipulation.
openkore
OpenKore is a custom client and intelligent automated assistant for Ragnarok Online. It is a free, open source, and cross-platform program (Linux, Windows, and MacOS are supported). To run OpenKore, you need to download and extract it or clone the repository using Git. Configure OpenKore according to the documentation and run openkore.pl to start. The tool provides a FAQ section for troubleshooting, guidelines for reporting issues, and information about botting status on official servers. OpenKore is developed by a global team, and contributions are welcome through pull requests. Various community resources are available for support and communication. Users are advised to comply with the GNU General Public License when using and distributing the software.
QA-Pilot
QA-Pilot is an interactive chat project that leverages online/local LLM for rapid understanding and navigation of GitHub code repository. It allows users to chat with GitHub public repositories using a git clone approach, store chat history, configure settings easily, manage multiple chat sessions, and quickly locate sessions with a search function. The tool integrates with `codegraph` to view Python files and supports various LLM models such as ollama, openai, mistralai, and localai. The project is continuously updated with new features and improvements, such as converting from `flask` to `fastapi`, adding `localai` API support, and upgrading dependencies like `langchain` and `Streamlit` to enhance performance.
extension-gen-ai
The Looker GenAI Extension provides code examples and resources for building a Looker Extension that integrates with Vertex AI Large Language Models (LLMs). Users can leverage the power of LLMs to enhance data exploration and analysis within Looker. The extension offers generative explore functionality to ask natural language questions about data and generative insights on dashboards to analyze data by asking questions. It leverages components like BQML Remote Models, BQML Remote UDF with Vertex AI, and Custom Fine Tune Model for different integration options. Deployment involves setting up infrastructure with Terraform and deploying the Looker Extension by creating a Looker project, copying extension files, configuring BigQuery connection, connecting to Git, and testing the extension. Users can save example prompts and configure user settings for the extension. Development of the Looker Extension environment includes installing dependencies, starting the development server, and building for production.
For similar jobs
sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.
teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.
ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.
griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.