Find and compare the best Artificial Intelligence software for LangChain in 2024
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Use the comparison tool below to compare the top Artificial Intelligence software for LangChain on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Langfuse is a free and open-source LLM engineering platform that helps teams to debug, analyze, and iterate their LLM Applications. Observability: Incorporate Langfuse into your app to start ingesting traces. Langfuse UI : inspect and debug complex logs, user sessions and user sessions Langfuse Prompts: Manage versions, deploy prompts and manage prompts within Langfuse Analytics: Track metrics such as cost, latency and quality (LLM) to gain insights through dashboards & data exports Evals: Calculate and collect scores for your LLM completions Experiments: Track app behavior and test it before deploying new versions Why Langfuse? - Open source - Models and frameworks are agnostic - Built for production - Incrementally adaptable - Start with a single LLM or integration call, then expand to the full tracing for complex chains/agents - Use GET to create downstream use cases and export the data
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ZenML
ZenML
FreeSimplify your MLOps pipelines. ZenML allows you to manage, deploy and scale any infrastructure. ZenML is open-source and free. Two simple commands will show you the magic. ZenML can be set up in minutes and you can use all your existing tools. ZenML interfaces ensure your tools work seamlessly together. Scale up your MLOps stack gradually by changing components when your training or deployment needs change. Keep up to date with the latest developments in the MLOps industry and integrate them easily. Define simple, clear ML workflows and save time by avoiding boilerplate code or infrastructure tooling. Write portable ML codes and switch from experiments to production in seconds. ZenML's plug and play integrations allow you to manage all your favorite MLOps software in one place. Prevent vendor lock-in by writing extensible, tooling-agnostic, and infrastructure-agnostic code. -
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LangGraph
LangChain
FreeLangGraph gives you the precision and control to build agents that can reliably handle complex tasks. LangGraph Platform allows you to build and scale agentic apps. LangGraph's flexible Framework supports diverse control flows, including single agent, multi-agent and hierarchical. It also handles realistic and complex scenarios. Moderation and quality loops are easy to add, ensuring that agents do not veer off course. LangGraph Platform can be used to template your cognitive architecture, so that tools, prompts and models can be easily configured with LangGraph Platform Assistants. LangGraph agents are able to work seamlessly with humans, as they can write drafts and wait for approval before taking action. You can easily inspect the agent's action and "time-travel", to take a different course of action. -
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Metal
Metal
$25 per monthMetal is a fully-managed, production-ready ML retrieval platform. Metal embeddings can help you find meaning in unstructured data. Metal is a managed services that allows you build AI products without having to worry about managing infrastructure. Integrations with OpenAI and CLIP. Easy processing & chunking of your documents. Profit from our system in production. MetalRetriever is easily pluggable. Simple /search endpoint to run ANN queries. Get started for free. Metal API Keys are required to use our API and SDKs. Authenticate by populating headers with your API Key. Learn how to integrate Metal into your application using our Typescript SDK. You can use this library in JavaScript as well, even though we love TypeScript. Fine-tune spp programmatically. Indexed vector data of your embeddings. Resources that are specific to your ML use case. -
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Langdock
Langdock
FreeNative support for ChatGPT, LangChain and more. Bing, HuggingFace, and more to come. Add your API documentation by hand or import an OpenAPI specification. Access the request prompt and parameters, headers, bodies, and more. View detailed live metrics on how your plugin performs, including latencies and errors. Create your own dashboards to track funnels and aggregate metrics. -
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Deep Lake
activeloop
$995 per monthWe've been working on Generative AI for 5 years. Deep Lake combines the power and flexibility of vector databases and data lakes to create enterprise-grade LLM-based solutions and refine them over time. Vector search does NOT resolve retrieval. You need a serverless search for multi-modal data including embeddings and metadata to solve this problem. You can filter, search, and more using the cloud, or your laptop. Visualize your data and embeddings to better understand them. Track and compare versions to improve your data and your model. OpenAI APIs are not the foundation of competitive businesses. Your data can be used to fine-tune LLMs. As models are being trained, data can be efficiently streamed from remote storage to GPUs. Deep Lake datasets can be visualized in your browser or Jupyter Notebook. Instantly retrieve different versions and materialize new datasets on the fly via queries. Stream them to PyTorch, TensorFlow, or Jupyter Notebook. -
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Flowise
Flowise
FreeFlowise is open source and will always be free to use for commercial and private purposes. Build LLMs apps easily with Flowise, an open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Open source MIT License, see your LLM applications running live, and manage component integrations. GitHub Q&A using conversational retrieval QA chains. Language translation using LLM chains with a chat model and chat prompt template. Conversational agent for chat model that uses chat-specific prompts. -
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Typeblock
Typeblock
$20 per monthCreate AI apps that can be shared using a simple editor similar to Notion. No need to hire expensive developers or write code. We take care of the hosting, database and deployment. Typeblock empowers you to create AI tools in less than 2 minutes, whether you're a marketing team, an agency, or an entrepreneur. Create SEO-optimized blogs and publish them instantly to your CMS. Create a tool that will generate highly personalized cold email for your sales team. Create a tool that will help you write Facebook ads, LinkedIn posts or Twitter threads. Create an app to write landing page copy for the marketing team. Build tools that create highly engaging newsletters using AI. -
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Zep
Zep
FreeZep will ensure that your assistant remembers previous conversations and brings them up when they are relevant. In milliseconds, you can identify your user's intention, create semantic routers and trigger events. Emails, phone number, dates, names and more are extracted quickly and accurately. Your assistant will never lose track of a user. Classify intent, emotions, and more, and convert dialog into structured data. Your users will never have to wait. We do not send your data to a third-party LLM service. SDKs for all your favorite frameworks and languages. Automatically populate prompts, no matter how far back they are, with a summary relevant past conversations. Zep summarizes and embeds your Assistant's chat logs. It then executes retrieval pipelines. Instantly and accurately categorize chat dialog. Understanding user intent and emotion. Route chains based upon semantic context and trigger events. Extract business data quickly from chat conversations. -
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PlugBear
Runbear
$31 per monthPlugBear provides a low-code/no-code solution to connect communication channels with LLM applications (Large Language Model). It allows, for example, the creation of a Slack Bot from an LLM application in just a few simple clicks. PlugBear is notified when a trigger event occurs on the integrated channels. It then transforms messages into LLM applications, and initiates generation. PlugBear then transforms the generated results so that they are compatible with each channel. This allows users to interact with LLM applications seamlessly across different channels. -
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CodeQwen
QwenLM
FreeCodeQwen, developed by the Qwen Team, Alibaba Cloud, is the code version. It is a transformer based decoder only language model that has been pre-trained with a large number of codes. A series of benchmarks shows that the code generation is strong and that it performs well. Supporting long context generation and understanding with a context length of 64K tokens. CodeQwen is a 92-language coding language that provides excellent performance for text-to SQL, bug fixes, and more. CodeQwen chat is as simple as writing a few lines of code using transformers. We build the tokenizer and model using pre-trained methods and use the generate method for chatting. The chat template is provided by the tokenizer. Following our previous practice, we apply the ChatML Template for chat models. The model will complete the code snippets in accordance with the prompts without any additional formatting. -
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Comet LLM
Comet LLM
FreeCometLLM allows you to visualize and log your LLM chains and prompts. CometLLM can be used to identify effective prompting strategies, streamline troubleshooting and ensure reproducible workflows. Log your prompts, responses, variables, timestamps, duration, and metadata. Visualize your responses and prompts in the UI. Log your chain execution to the level you require. Visualize your chain in the UI. OpenAI chat models automatically track your prompts. Track and analyze feedback from users. Compare your prompts in the UI. Comet LLM Projects are designed to help you perform smart analysis of logged prompt engineering workflows. Each column header corresponds with a metadata attribute that was logged in the LLM Project, so the exact list can vary between projects. -
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Agenta
Agenta
FreeWith confidence, collaborate on prompts, monitor and evaluate LLM apps. Agenta is an integrated platform that allows teams to build robust LLM applications quickly. Create a playground where your team can experiment together. Comparing different prompts, embeddings, and models in a systematic way before going into production is key. Share a link with the rest of your team to get human feedback. Agenta is compatible with all frameworks, including Langchain, Lama Index and others. Model providers (OpenAI, Cohere, Huggingface, self-hosted, etc.). You can see the costs, latency and chain of calls for your LLM app. You can create simple LLM applications directly from the UI. If you want to create customized applications, then you will need to use Python to write the code. Agenta is model-agnostic, and works with any model provider or framework. Our SDK is currently only available in Python. -
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AgentOps
AgentOps
$40 per monthPlatform for AI agents testing and debugging by the industry's leading developers. We developed the tools, so you don't need to. Visually track events, such as LLM, tools, and agent interactions. Rewind and playback agent runs with pinpoint precision. Keep a complete data trail from prototype to production of logs, errors and prompt injection attacks. Native integrations with top agent frameworks. Track, save and monitor each token that your agent sees. Monitor and manage agent spending using the most recent price monitoring. Save up to 25x on specialized LLMs by fine-tuning them based on completed completions. Build your next agent using evals and replays. You can visualize the behavior of your agents in your AgentOps dashboard with just two lines of coding. After you set up AgentOps each execution of your program will be recorded as a "session" and the data will automatically be recorded for you. -
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Remind
Remind
FreeRecall your tasks to optimize your workflow. Boost your productivity today by using your artificial memory. Remind is a powerful application that captures, transcribes, and indexes digital activity on your device. This makes it easy to remember important information. Download the Remind repo from our site or Github. Install it on your device and follow the instructions on GitHub to get started. Advanced AI technology allows you to capture and store your digital activity. Remind lets you customize different components to meet your needs. You can change settings such as the frequency and format of screenshots. -
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VESSL AI
VESSL AI
$100 + compute/month Fully managed infrastructure, tools and workflows allow you to build, train and deploy models faster. Scale inference and deploy custom AI & LLMs in seconds on any infrastructure. Schedule batch jobs to handle your most demanding tasks, and only pay per second. Optimize costs by utilizing GPUs, spot instances, and automatic failover. YAML simplifies complex infrastructure setups by allowing you to train with a single command. Automate the scaling up of workers during periods of high traffic, and scaling down to zero when inactive. Deploy cutting edge models with persistent endpoints within a serverless environment to optimize resource usage. Monitor system and inference metrics, including worker counts, GPU utilization, throughput, and latency in real-time. Split traffic between multiple models to evaluate. -
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SWE-Kit
Composio
$49 per monthSweKit lets you build PR agents that review code, suggest improvement, enforce coding standard, identify potential issues and automate merge approvals. This streamlines the review process while improving code quality. Automate the creation of new features, debugging complex issues, creating and running tests, optimizing code for performance, maintainingability, and ensuring best practices across codebases, accelerating development. Use advanced code indexing and intelligent file navigation to explore and interact with huge codebases. Ask questions, track dependencies, uncover logic flow, and gain instant insight, enabling seamless communications with complex code structures. Keep your documentation up-to-date with your code. Update Mintlify documentation automatically whenever code changes are made. This ensures that your documentation is accurate, current, and ready for you and your team. -
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Opik
Comet
$39 per monthWith a suite observability tools, you can confidently evaluate, test and ship LLM apps across your development and production lifecycle. Log traces and spans. Define and compute evaluation metrics. Score LLM outputs. Compare performance between app versions. Record, sort, find, and understand every step that your LLM app makes to generate a result. You can manually annotate and compare LLM results in a table. Log traces in development and production. Run experiments using different prompts, and evaluate them against a test collection. You can choose and run preconfigured evaluation metrics, or create your own using our SDK library. Consult the built-in LLM judges to help you with complex issues such as hallucination detection, factuality and moderation. Opik LLM unit tests built on PyTest provide reliable performance baselines. Build comprehensive test suites for every deployment to evaluate your entire LLM pipe-line. -
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Arize Phoenix
Arize AI
FreePhoenix is a free, open-source library for observability. It was designed to be used for experimentation, evaluation and troubleshooting. It allows AI engineers to visualize their data quickly, evaluate performance, track issues, and export the data to improve. Phoenix was built by Arize AI and a group of core contributors. Arize AI is the company behind AI Observability Platform, an industry-leading AI platform. Phoenix uses OpenTelemetry, OpenInference, and other instrumentation. The main Phoenix package arize-phoenix. We offer a variety of helper packages to suit specific use cases. Our semantic layer adds LLM telemetry into OpenTelemetry. Automatically instrumenting popular package. Phoenix's open source library supports tracing AI applications via manual instrumentation, or through integrations LlamaIndex Langchain OpenAI and others. LLM tracing records requests' paths as they propagate across multiple steps or components in an LLM application. -
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Lunary
Lunary
$20 per monthLunary is a platform for AI developers that helps AI teams to manage, improve and protect chatbots based on Large Language Models (LLM). It includes features like conversation and feedback tracking as well as analytics on costs and performance. There are also debugging tools and a prompt directory to facilitate team collaboration and versioning. Lunary integrates with various LLMs, frameworks, and languages, including OpenAI, LangChain and JavaScript, and offers SDKs in Python and JavaScript. Guardrails to prevent malicious prompts or sensitive data leaks. Deploy Kubernetes/Docker in your VPC. Your team can judge the responses of your LLMs. Learn what languages your users speak. Experiment with LLM models and prompts. Search and filter everything in milliseconds. Receive notifications when agents do not perform as expected. Lunary's core technology is 100% open source. Start in minutes, whether you want to self-host or use the cloud. -
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DataChain
iterative.ai
FreeDataChain connects your unstructured cloud files with AI models, APIs and foundational models to enable instant data insights. Its Pythonic stack accelerates the development by tenfold when switching to Python-based data wrangling, without SQL data islands. DataChain provides dataset versioning to ensure full reproducibility and traceability for each dataset. This helps streamline team collaboration while ensuring data integrity. It allows you analyze your data wherever it is stored, storing raw data (S3, GCP or Azure) and metadata in inefficient datawarehouses. DataChain provides tools and integrations which are cloud-agnostic in terms of both storage and computing. DataChain allows you to query your multi-modal unstructured data. You can also apply intelligent AI filters for training data and snapshot your unstructured dataset, the code used for data selection and any stored or computed meta data. -
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Ragas
Ragas
FreeRagas is a framework that allows you to test and evaluate applications that use the Large Language Model. It provides automatic metrics for assessing performance and robustness. Synthetic test data is generated according to specific requirements. Workflows are also available to ensure quality in development and production monitoring. Ragas integrates seamlessly into existing stacks and provides insights to enhance LLM application. The platform is maintained and developed by a passionate team of individuals who use cutting-edge engineering practices and cutting-edge research to empower visionaries to redefine LLM possibilities. Synthesize high-quality, diverse evaluation data tailored to your needs. Evaluation and quality assurance of your LLM application during production. Use insights to improve the application. Automatic metrics to help you understand performance and robustness of the LLM application. -
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DeepEval
Confident AI
FreeDeepEval is an open-source, easy-to-use framework for evaluating large-language-model systems. It is similar Pytest, but is specialized for unit-testing LLM outputs. DeepEval incorporates research to evaluate LLM results based on metrics like G-Eval (hallucination), answer relevancy, RAGAS etc. This uses LLMs as well as various other NLP models which run locally on your computer for evaluation. DeepEval can handle any implementation, whether it's RAG, fine-tuning or LangChain or LlamaIndex. It allows you to easily determine the best hyperparameters for your RAG pipeline. You can also prevent drifting and even migrate from OpenAI to your own Llama2 without any worries. The framework integrates seamlessly with popular frameworks and supports synthetic dataset generation using advanced evolution techniques. It also allows for efficient benchmarking and optimizing of LLM systems. -
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HumanLayer
HumanLayer
$500 per monthHumanLayer is a SDK and API that allows AI agents to communicate with humans for feedback, input and approvals. It ensures human oversight of high stakes function calls, with approval workflows on Slack, emails, and more. HumanLayer integrates with your Large Language Model (LLM), framework, and other tools to give AI agents safe access to the rest of the world. The platform supports a variety of frameworks and LLMs including LangChain (LangChain), CrewAI (ControlFlow), LlamaIndex (LlamaIndex), Haystack (OpenAI), Claude, Llama3.1(Llama3.1), Mistral, Gemini and Cohere. HumanLayer features include approval workflows, integration of humans as tools, and custom responses that escalate. Pre-fill responses for seamless human-agent interaction. Control which users are able to approve or respond to LLM request. Invert the control flow, from human-initiated requests to agent-initiated ones. Add human contact channels to the toolchain of your agent. -
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Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.