llm-chatbot-python
https://graphacademy.neo4j.com/courses/llm-chatbot-python/
Stars: 79
This repository provides resources for building a chatbot backed by Neo4j using Python. It includes instructions on running the application, setting up tests, and installing necessary libraries. The chatbot is designed to interact with users and provide recommendations based on data stored in a Neo4j database. The repository is part of the Neo4j GraphAcademy course on building chatbots with Python.
README:
= Build an Neo4j-backed Chatbot using Python
This repository accompanies the link:https://graphacademy.neo4j.com/courses/llm-chatbot-python/?ref=github[Build an Neo4j-backed Chatbot using Python^] course on link:https://graphacademy.neo4j.com/?ref=github[Neo4j GraphAcademy^].
For a complete walkthrough of this repository, link:https://graphacademy.neo4j.com/courses/llm-chatbot-python/?ref=github[enrol now^].
== Running the application
To run the application, you must install the libraries listed in requirements.txt
.
[source,sh] pip install -r requirements.txt
Then run the streamlit run
command to start the app on link:http://localhost:8501/[http://localhost:8501/^].
[source,sh] streamlit run bot.py
== Tests
To run the solution tests:
. Create Neo4j instance with the recommendations
dataset
. Run the link:https://raw.githubusercontent.com/neo4j-graphacademy/courses/refs/heads/main/asciidoc/courses/llm-chatbot-python/modules/3-tools/lessons/1-vector-tool/reset.cypher[Cypher to add embeddings and create the vector index^].
. Create a virtual environment and install the requirements.
+
[source,sh]
pip install -r requirements.txt
. Install pytest
+
[source,sh]
pip install pytest
. Create a secrets.toml
file in the .streamlit
directory. Use secrets.toml.example
as a template.
. Run the tests
+
[source,sh]
pytest
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for llm-chatbot-python
Similar Open Source Tools
llm-chatbot-python
This repository provides resources for building a chatbot backed by Neo4j using Python. It includes instructions on running the application, setting up tests, and installing necessary libraries. The chatbot is designed to interact with users and provide recommendations based on data stored in a Neo4j database. The repository is part of the Neo4j GraphAcademy course on building chatbots with Python.
axoned
Axone is a public dPoS layer 1 designed for connecting, sharing, and monetizing resources in the AI stack. It is an open network for collaborative AI workflow management compatible with any data, model, or infrastructure, allowing sharing of data, algorithms, storage, compute, APIs, both on-chain and off-chain. The 'axoned' node of the AXONE network is built on Cosmos SDK & Tendermint consensus, enabling companies & individuals to define on-chain rules, share off-chain resources, and create new applications. Validators secure the network by maintaining uptime and staking $AXONE for rewards. The blockchain supports various platforms and follows Semantic Versioning 2.0.0. A docker image is available for quick start, with documentation on querying networks, creating wallets, starting nodes, and joining networks. Development involves Go and Cosmos SDK, with smart contracts deployed on the AXONE blockchain. The project provides a Makefile for building, installing, linting, and testing. Community involvement is encouraged through Discord, open issues, and pull requests.
agentok
Agentok Studio is a tool built upon AG2, a powerful agent framework from Microsoft, offering intuitive visual tools to streamline the creation and management of complex agent-based workflows. It simplifies the process for creators and developers by generating native Python code with minimal dependencies, enabling users to create self-contained code that can be executed anywhere. The tool is currently under development and not recommended for production use, but contributions are welcome from the community to enhance its capabilities and functionalities.
labelbox-python
Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.
agents
Polymarket Agents is a developer framework and set of utilities for building AI agents to trade autonomously on Polymarket. It integrates with Polymarket API, provides AI agent utilities for prediction markets, supports local and remote RAG, sources data from various services, and offers comprehensive LLM tools for prompt engineering. The architecture features modular components like APIs and scripts for managing local environments, server set-up, and CLI for end-user commands.
autoarena
AutoArena is a tool designed to create leaderboards ranking Language Model outputs against one another using automated judge evaluation. It allows users to rank outputs from different LLMs, RAG setups, and prompts to find the best configuration of their system. Users can perform automated head-to-head evaluation using judges from various platforms like OpenAI, Anthropic, and Cohere. Additionally, users can define and run custom judges, connect to internal services, or implement bespoke logic. AutoArena enables users to run the application locally, providing full control over their environment and data.
flake
Nixified.ai aims to simplify and provide access to a vast repository of AI executable code that would otherwise be challenging to run independently due to package management and complexity issues. The tool primarily runs on NixOS and Linux, with compatibility on Windows through NixOS-WSL. It can automatically utilize the GPU of the Windows host by setting LD_LIBRARY_PATH in the wrapper script. Users can explore the tool's offerings through the nix repl, with the main outputs including ComfyUI, a modular node-based Stable Diffusion WebUI, and deprecated packages like InvokeAI and textgen. To enable binary cache and save time building packages, users need to trust nixified-ai's binary cache by adding specific lines to their system configuration files.
lerobot
LeRobot is a state-of-the-art AI library for real-world robotics in PyTorch. It aims to provide models, datasets, and tools to lower the barrier to entry to robotics, focusing on imitation learning and reinforcement learning. LeRobot offers pretrained models, datasets with human-collected demonstrations, and simulation environments. It plans to support real-world robotics on affordable and capable robots. The library hosts pretrained models and datasets on the Hugging Face community page.
obs-cleanstream
CleanStream is an OBS plugin that utilizes real-time local AI to clean live audio streams by removing unwanted words and utterances, such as 'uh' and 'um', and configurable words like profanity. It employs a neural network (OpenAI Whisper) to predict speech in real-time and eliminate undesired words. The plugin runs efficiently using the Whisper.cpp project from ggerganov. CleanStream offers users the ability to adjust settings and add the plugin to any audio-generating source in OBS, providing a seamless experience for content creators looking to enhance the quality of their live audio streams.
habitat-lab
Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks.
obs-cleanstream
CleanStream is an OBS plugin that utilizes AI to clean live audio streams by removing unwanted words and utterances, such as 'uh's and 'um's, and configurable words like profanity. It uses a neural network (OpenAI Whisper) in real-time to predict speech and eliminate unwanted words. The plugin is still experimental and not recommended for live production use, but it is functional for testing purposes. Users can adjust settings and configure the plugin to enhance audio quality during live streams.
poke-env
A Python interface for creating battling Pokemon agents, 'poke-env' allows users to develop rule-based or Reinforcement Learning bots to battle on Pokemon Showdown. The tool provides an easy-to-use interface for agent creation and offers documentation, examples, and starting code for beginners. Users can install 'poke-env' via pip and set up a development server for testing. The project is inspired by an artificial intelligence class project and relies on data from Smogon forums' RMT section. It is licensed under MIT and can be cited using a provided BibTeX entry.
OpenDevin
OpenDevin is an open-source project aiming to replicate Devin, an autonomous AI software engineer capable of executing complex engineering tasks and collaborating actively with users on software development projects. The project aspires to enhance and innovate upon Devin through the power of the open-source community. Users can contribute to the project by developing core functionalities, frontend interface, or sandboxing solutions, participating in research and evaluation of LLMs in software engineering, and providing feedback and testing on the OpenDevin toolset.
contracts
AXONE Smart Contracts repository hosts Smart Contracts for the AXONE network, compatible with any Cosmos blockchains using the CosmWasm framework. It includes storage, sovereignty, and resource management oriented Smart Contracts. Each contract has different functionalities and maturity stages, with detailed tech documentation and emojis indicating maturity levels. The repository provides tools for building, testing, deploying, and interacting with Smart Contracts, along with guidelines for contributing and community engagement.
palimpzest
Palimpzest (PZ) is a tool for managing and optimizing workloads, particularly for data processing tasks. It provides a CLI tool and Python demos for users to register datasets, run workloads, and access results. Users can easily initialize their system, register datasets, and manage configurations using the CLI commands provided. Palimpzest also supports caching intermediate results and configuring for parallel execution with remote services like OpenAI and together.ai. The tool aims to streamline the workflow of working with datasets and optimizing performance for data extraction tasks.
lhotse
Lhotse is a Python library designed to make speech and audio data preparation flexible and accessible. It aims to attract a wider community to speech processing tasks by providing a Python-centric design and an expressive command-line interface. Lhotse offers standard data preparation recipes, PyTorch Dataset classes for speech tasks, and efficient data preparation for model training with audio cuts. It supports data augmentation, feature extraction, and feature-space cut mixing. The tool extends Kaldi's data preparation recipes with seamless PyTorch integration, human-readable text manifests, and convenient Python classes.
For similar tasks
Flowise
Flowise is a tool that allows users to build customized LLM flows with a drag-and-drop UI. It is open-source and self-hostable, and it supports various deployments, including AWS, Azure, Digital Ocean, GCP, Railway, Render, HuggingFace Spaces, Elestio, Sealos, and RepoCloud. Flowise has three different modules in a single mono repository: server, ui, and components. The server module is a Node backend that serves API logics, the ui module is a React frontend, and the components module contains third-party node integrations. Flowise supports different environment variables to configure your instance, and you can specify these variables in the .env file inside the packages/server folder.
nlux
nlux is an open-source Javascript and React JS library that makes it super simple to integrate powerful large language models (LLMs) like ChatGPT into your web app or website. With just a few lines of code, you can add conversational AI capabilities and interact with your favourite LLM.
generative-ai-go
The Google AI Go SDK enables developers to use Google's state-of-the-art generative AI models (like Gemini) to build AI-powered features and applications. It supports use cases like generating text from text-only input, generating text from text-and-images input (multimodal), building multi-turn conversations (chat), and embedding.
awesome-langchain-zh
The awesome-langchain-zh repository is a collection of resources related to LangChain, a framework for building AI applications using large language models (LLMs). The repository includes sections on the LangChain framework itself, other language ports of LangChain, tools for low-code development, services, agents, templates, platforms, open-source projects related to knowledge management and chatbots, as well as learning resources such as notebooks, videos, and articles. It also covers other LLM frameworks and provides additional resources for exploring and working with LLMs. The repository serves as a comprehensive guide for developers and AI enthusiasts interested in leveraging LangChain and LLMs for various applications.
Large-Language-Model-Notebooks-Course
This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.
ai-chatbot
Next.js AI Chatbot is an open-source app template for building AI chatbots using Next.js, Vercel AI SDK, OpenAI, and Vercel KV. It includes features like Next.js App Router, React Server Components, Vercel AI SDK for streaming chat UI, support for various AI models, Tailwind CSS styling, Radix UI for headless components, chat history management, rate limiting, session storage with Vercel KV, and authentication with NextAuth.js. The template allows easy deployment to Vercel and customization of AI model providers.
awesome-local-llms
The 'awesome-local-llms' repository is a curated list of open-source tools for local Large Language Model (LLM) inference, covering both proprietary and open weights LLMs. The repository categorizes these tools into LLM inference backend engines, LLM front end UIs, and all-in-one desktop applications. It collects GitHub repository metrics as proxies for popularity and active maintenance. Contributions are encouraged, and users can suggest additional open-source repositories through the Issues section or by running a provided script to update the README and make a pull request. The repository aims to provide a comprehensive resource for exploring and utilizing local LLM tools.
Awesome-AI-Data-Guided-Projects
A curated list of data science & AI guided projects to start building your portfolio. The repository contains guided projects covering various topics such as large language models, time series analysis, computer vision, natural language processing (NLP), and data science. Each project provides detailed instructions on how to implement specific tasks using different tools and technologies.
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.