Here are 9 projects to take your app to the next level in 2023.

[Lunary](https://github.com/lunary-ai/lunary) (sponsored)

[Guidance](https://github.com/guidance-ai/guidance)

[LiteLLM](https://github.com/BerriAI/litellm)

[LangChain](https://github.com/langchain-ai/langchain)

[DeepEval](https://github.com/confident-ai/deepeval)

[pgVector](https://github.com/pgvector/pgvector)

[promptfoo](https://github.com/promptfoo/promptfoo)

[Model Fusion](https://github.com/lgrammel/modelfusion)

9 Open Source tools to take your AI app to the next level

In the era of AI-driven applications, the ability to efficiently handle and search through vector data is crucial.

🌌 [Lunary.ai](https://github.com/lunary-ai/lunary)

🧲 [PGVector](https://github.com/pgvector/pgvector)

🌐 [Weaviate](https://github.com/weaviate/weaviate)

🎨 [ChromaDB](https://github.com/chroma-core/chroma)

🔍 [Milvus](https://github.com/milvus-io/milvus)

🧭 [Qdrant](https://github.com/qdrant/qdrant)

🔎 [ElasticSearch](https://github.com/elastic/elasticsearch)

6 Open-Source Vector Databases to Power Your AI App

Here are 7 open-source tools that you can add to your development workflow to be faster and more productive. These tools go from simple code completion, to full fledged app builders.

🤖 [continue](https://github.com/continuedev/continue)

🏎️ [gpt-pilot](https://github.com/Pythagora-io/gpt-pilot)

📝 [auto-commit](https://github.com/m1guelpf/auto-commit)

🏗️ [ChatDev](https://github.com/OpenBMB/ChatDev)

🧑‍🚀 [TabbyML](https://github.com/TabbyML/tabby)

🛜 [localpilot](https://github.com/danielgross/localpilot)

📈 [lunary](https://github.com/lunary-ai/lunary)

🍥 [swirl](https://github.com/swirlai/swirl-search)

7 Open Source AI projects to code faster in 2023

Explore Langfuse and compare it with top open-source alternatives.

Top 4 Open Source Alternatives to Langfuse

Discover 5 alternatives to LangSmith to observe, evaluate and improve your LangChain and LLM apps.

LangSmith alternatives: 5 tools to capture LLM data

This guide helps you understand why Azure OpenAI timeout errors happen and how you can fix them

Important Considerations for Azure OpenAI Timeout Challenges

1. Proxy Settings and Network Restrictions

3. Timeout Behavior in Streaming vs. Non-Streaming Requests

4. Synchronizing Cloud Function Timeouts with Azure

5. Balancing Retry Mechanisms and Rate Limits

Troubleshoot Timeout Errors in Azure OpenAI

Use the Azure OpenAI Batch API in Python to save cost and process large LLM workloads.

Using the Batch API with Azure OpenAI

Learn to build multi-user chatbots, focusing on the key differences in OpenAI and Anthropic's support for such use-cases.

Why OpenAI is better for Multi-User Scenarios

Building Your Multi-User ChatBot with OpenAI

How to build a multi-user chatbot?

ChatGPT Canvas is a handy tool for writers and developers. Understand what it does and how it compares to Claude Artifacts.

How can ChatGPT Canvas handle coding tasks?

Comparing ChatGPT Canvas with Claude Artifacts

ChatGPT Canvas: Tool for Writers and Developers

Datadog is a popular monitoring tool for infrastructure and applications. Let's see why and explore alternatives.

Datadog LLM Observability: Examples, Demo and Pricing

Prompt Templates, Chat Tracking in Python and faster dashboard.

December 2023 Update

Claude v3, evaluations and stability improvements.

February 2024 Update

Radars, evaluations out of private alpha & major app overhaul.

January 2024 Update

Explore how to load and process data from Airtable tables using LangChain's AirtableLoader, with examples of both synchronous and asynchronous loading methods.

Using LangChain's Airtable Document Loader

Learn how to use the Annoy vector store for approximate nearest neighbor search in LangChain to efficiently store and query document embeddings.

Using Annoy Vector Store in LangChain

Learn how to leverage Anyscale's embeddings API for text embedding capabilities in your LangChain applications.

Using Anyscale Embeddings in LangChain

Configure Apache Doris vector store integration in LangChain with ApacheDorisSettings for efficient vector storage and retrieval

LangChain Apache Doris Settings for Vector Storage

Learn how to use ApertureDB vector store with LangChain to store, index and search document embeddings for similarity search and RAG applications.

LangChain ApertureDB Vector Store - Store and Search Embeddings

Learn how to store and search vectors using Azure Cosmos DB NoSQL Vector Search with LangChain.

How to Use AzureCosmosDBNoSqlVectorSearch

Using LangChain Azure Cosmos DB NoSQL Vector Search Store

Learn how to use BearlyInterpreterTool to execute Python code in a secure sandbox environment and handle file operations in LangChain.

Using the Bearly Code Interpreter Tool in LangChain

Learn how to load documents from Apache Cassandra databases using the CassandraLoader in LangChain to retrieve and process data for your AI applications.

Loading Documents from Cassandra with LangChain

Learn how to implement semantic-based caching for LLM responses using CassandraSemanticCache in LangChain to improve performance and reduce costs.

Using LangChain's CassandraSemanticCache for Semantic-Based LLM Response Caching

Learn how to use the Cassandra vector store in LangChain to store and search documents using vector embeddings and metadata filtering.

Using LangChain Cassandra Vector Store for Document Storage and Retrieval

Learn how to create chains that automatically add relevant citations from context to LLM responses using LangChain's citation fuzzy matching

LangChain Citation Fuzzy Matching - Adding Citations to LLM Responses

Learn how to parse and load linguistic annotation files in CoNLL-U format using LangChain's CoNLLULoader.

Parsing CoNLL-U Files with LangChain CoNLLULoader

Learn how to configure connection parameters for Baidu and Tencent Cloud vector databases in LangChain.

LangChain Connection Parameters for Vector Databases

Learn how to use ConneryService to interact with Connery Runner API, list available actions, and run plugin actions in your LangChain applications.

Using Connery Service in LangChain to Run Plugin Actions

Learn how to transform LangChain message objects into API-compatible dictionaries using the convert_message_to_dict utility function.

Converting LangChain Messages to API Format with convert_message_to_dict

Learn how to convert chat messages into a format suitable for fine-tuning OpenAI models using LangChain's convert_messages_for_finetuning

How to use convert_messages_for_finetuning

Using with Message Loader and Pre-processing

Preparing Messages for LangChain Fine-tuning with OpenAI

Learn how to calculate cosine similarity between vectors in LangChain using the cosine_similarity utility function, with practical examples for text embeddings and semantic routing.

LangChain Cosine Similarity Guide - Calculate Vector Similarities

Learn how to use LangChain's CubeSemanticLoader to retrieve and process Cube's data model metadata for enhancing LLM context and queries.

Using LangChain CubeSemanticLoader for Data Model Metadata

Learn how to use the DataheraldAPIWrapper in LangChain to convert natural language queries into SQL statements using Dataherald's powerful text-to-SQL capabilities.

Working with DataheraldAPI in LangChain for Text-to-SQL

Learn how to use China Mobile's ECloud ElasticSearch vector search service in LangChain for efficient document retrieval and similarity search.

ECloud Vector Search in LangChain - Using China Mobile's ElasticSearch Service

Learn how to fetch and load Ethereum blockchain transactions and balances using LangChain's EtherscanLoader.

Loading Ethereum Transactions with LangChain EtherscanLoader

Learn how to load and process Facebook Messenger chat histories using LangChain's chat loader utilities.

What is SingleFileFacebookMessengerChatLoader?

How to Use SingleFileFacebookMessengerChatLoader

Loading Facebook Messenger Chats with LangChain's SingleFileFacebookMessengerChatLoader

Learn how to leverage Golden's extensive knowledge graph using LangChain's GoldenQueryAPIWrapper to get structured data about companies, products, and more.

Querying Golden's Knowledge Graph with LangChain's GoldenQueryAPIWrapper

Learn how to search and retrieve job postings from Google Jobs using LangChain's GoogleJobsAPIWrapper - perfect for building job search applications and career tools.

Find Jobs with LangChain's GoogleJobsAPIWrapper

Learn how to use GuardrailsOutputParser in LangChain to enforce structured output and validate LLM responses.

4. Creating a Parser from a Pydantic Model

Using the GuardrailsOutputParser in LangChain for Structured Output

Learn how to use HuggingFace cross encoder models in LangChain for text similarity scoring and reranking search results.

Using with ContextualCompressionRetriever

Using Cross Encoders in LangChain with HuggingFace Models

Learn how to create and use image prompts for multimodal models with LangChain's ImagePromptTemplate class.

Using ImagePromptTemplate in LangChain for Multimodal Models

Learn how to load and process iMessage conversations from macOS into chat messages using LangChain's IMessageChatLoader.

Working with iMessage Data in LangChain using IMessageChatLoader

Learn how to generate text embeddings using the InfinityEmbeddingsLocal class with LangChain, an optimized local embeddings solution.

Using LangChain Infinity Local Embeddings for Text Embeddings

Learn how to integrate Infobip messaging services into your LangChain applications to send SMS and emails using the InfobipAPIWrapper

LangChain Infobip Integration - Sending SMS and Emails Programmatically

Learn how to leverage Jina AI's powerful embedding models in LangChain for both text and image content using the JinaEmbeddings class.

Using Jina Embeddings in LangChain for Text and Image Embeddings

Learn how to create JSON-based chat agents in LangChain that can interact with tools and handle complex conversations.

Building JSON Chat Agents in LangChain

Learn how to configure Kinetica settings in LangChain to connect to Kinetica database and customize vector search parameters.

LangChain Kinetica Settings Configuration

Learn how to load and process chat data from LangSmith datasets using LangChain's LangSmithDatasetChatLoader.

Loading LangSmith Chat Datasets in LangChain

Learn how to parse and process source code intelligently using LangChain's LanguageParser to split code into meaningful segments based on language syntax.

LangChain LanguageParser - Intelligent Code Parsing for Multiple Languages

Learn how to use LangChain's load_dataset module to import and work with custom datasets from the Hugging Face hub for model evaluation and testing.

Load Custom Datasets in LangChain for Model Evaluation

Learn how to configure and use ManticoreSearchSettings to customize your vector store connection and behavior in LangChain.

Working with ManticoreSearch Settings in LangChain

Learn how to extract and process social media content from Mastodon using LangChain's document loader for toots.

Load Mastodon Posts with LangChain's MastodonTootsLoader

Learn how to use LangChain's MathpixPDFLoader to accurately extract text and formulas from PDF documents using the Mathpix OCR service.

LangChain MathPix PDF Loader - Extract Text from PDFs with High Precision

Learn how to merge consecutive chat messages from the same sender in LangChain using merge_chat_runs to optimize chat conversation processing.

Using merge_chat_runs in LangChain - Chat Message Processing

Learn how to merge documents from multiple data sources using LangChain's MergedDataLoader to create a unified collection of documents for your LLM applications.

Combine Document Loaders in LangChain with MergedDataLoader

Learn how to generate embeddings using MLflow AI Gateway models with LangChain's MlflowAIGatewayEmbeddings class.

Generating Embeddings for Multiple Documents

Integration with Other LangChain Components

LangChain MLflow AI Gateway Embeddings: Connect to MLflow Embedding Models

Learn how to track and monitor your LangChain experiments using the MLflow callback handler for metrics, artifacts and experiment tracking.

MLflow Callback Handler in LangChain - Track Your LLM Experiments

Learn how to generate embeddings using MLflow's AI Gateway integration in LangChain with MlflowEmbeddings.

Working with MLflow Embeddings in LangChain

Learn how to generate text embeddings using ModelScope's models through LangChain's ModelScopeEmbeddings class.

ModelScope Hub Embeddings with LangChain

Explore how to use LangChain's NasaAPIWrapper to access NASA's media library, search images, videos and retrieve metadata about space-related content.

Querying NASA Image and Video Library with LangChain NasaAPIWrapper

Learn how to leverage NLPCloud's embedding models in LangChain for processing text in over 50 languages and generating high-quality vector representations.

Using NLPCloud Embeddings with LangChain for Multilingual Text Processing

Learn how to generate text embeddings using Oracle Cloud Infrastructure's GenAI service with LangChain's OCIGenAIEmbeddings.

LangChain with Oracle Cloud Infrastructure (OCI) Embeddings

Learn how to search emails in Office365 using LangChain's SearchEmailsInput class with advanced filtering and query options.

Using Office365 SearchEmailsInput in LangChain

Learn how to interact with Ontotext GraphDB, a powerful graph database and knowledge discovery tool, using LangChain's OntotextGraphDBGraph class.

Loading Schema from Different RDF Formats

Using LangChain with Ontotext GraphDB

Learn how to use Oracle AI Vector Search as a vector store in LangChain for semantic document search and retrieval.

Using Oracle AI Vector Search in LangChain

Learn how to use the PGVecto_rs vector store with LangChain to store and search document embeddings in PostgreSQL.

Using PGVecto_rs Vector Store in LangChain

Learn how to create an asynchronous PlayWright browser instance in LangChain for web automation and scraping tasks.

How to use create_async_playwright_browser

Using the LangChain PlayWright Browser Creator for Web Automation

Learn how to structure Reddit search queries in LangChain using RedditSearchSchema to retrieve posts with custom filtering and sorting options.

LangChain Reddit Search Schema - Making Reddit API Queries

Learn how to use RedisNum filter fields to handle numeric data in Redis vector stores with LangChain.

Using RedisNum Filter Fields in LangChain

Learn how to use LangChain's Requests utility to make HTTP requests with authentication support and async capabilities.

Using the LangChain Requests Utility for HTTP Operations

Learn how to use Google's ScaNN vector store in LangChain for fast and efficient similarity search of document embeddings.

Using ScaNN Vector Store for Efficient Similarity Search in LangChain

Learn how to scrape web content with LangChain's ScrapingAntLoader to convert web pages into LLM-friendly markdown format.

Using LangChain ScrapingAntLoader for Web Scraping

Learn how to use different search types to improve retrieval results in LangChain retrievers.

Search Types in LangChain Retrievers

Learn how to use SearchType enumeration to control search behavior in LangChain retrievers for more effective document retrieval.

Mastering Search Types in LangChain with SearchType Enum

Learn how to use the SelfAskOutputParser class to parse the output of self-ask LLM conversations and extract actions or final answers.

Working with the SelfAskOutputParser in LangChain

Learn how to implement semantic caching for LLM responses using SingleStore DB in LangChain to optimize performance and reduce API costs.

Using SingleStore DB Semantic Cache in LangChain

Learn how to extract and process Slack conversation history using LangChain's SlackChatLoader, with examples of both eager and lazy loading approaches.

Load Slack Chat History with LangChain's SlackChatLoader

Learn how to create text embeddings using iFlytek's SparkLLM embeddings service in LangChain. Supports both synchronous and asynchronous embedding generation.

Using SparkLLM Text Embeddings in LangChain

Learn how to use StarRocks as a vector store for embeddings and semantic search in LangChain applications.

Using StarRocks Vector Store with LangChain

Learn how to parse and structure queries for self-querying retrieval systems using LangChain's StructuredQueryOutputParser.

2. Creating a Parser with Specific Components

April+May 2024 Update

March 2024 Update

February 2024 Update

January 2024 Update

December 2023 Update

LLMonitor is now Lunary.ai