Best Prompt Management Tools for LangChain

Compare the Top Prompt Management Tools that integrate with LangChain as of September 2025

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This a list of Prompt Management tools that integrate with LangChain. Use the filters on the left to add additional filters for products that have integrations with LangChain. View the products that work with LangChain in the table below.

What are Prompt Management Tools for LangChain?

Prompt management tools are software programs designed to assist users in organizing and managing a variety of prompts. These tools utilize artificial intelligence technology to help streamline the process of creating, editing, and categorizing prompts for tasks such as email responses or social media posts. They offer customizable options, allowing users to tailor their prompts to fit their specific needs and preferences. These tools can improve efficiency and productivity by providing real-time suggestions and auto-completion features. Additionally, they can analyze data and metrics to optimize prompt performance over time. Compare and read user reviews of the best Prompt Management tools for LangChain currently available using the table below. This list is updated regularly.

1

Langfuse

Langfuse

Langfuse is an open source LLM engineering platform to help teams collaboratively debug, analyze and iterate on their LLM Applications. Observability: Instrument your app and start ingesting traces to Langfuse Langfuse UI: Inspect and debug complex logs and user sessions Prompts: Manage, version and deploy prompts from within Langfuse Analytics: Track metrics (LLM cost, latency, quality) and gain insights from dashboards & data exports Evals: Collect and calculate scores for your LLM completions Experiments: Track and test app behavior before deploying a new version Why Langfuse? - Open source - Model and framework agnostic - Built for production - Incrementally adoptable - start with a single LLM call or integration, then expand to full tracing of complex chains/agents - Use GET API to build downstream use cases and export data

1 Rating

Starting Price: $29/month

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2

Agenta

Agenta

Collaborate on prompts, evaluate, and monitor LLM apps with confidence. Agenta is a comprehensive platform that enables teams to quickly build robust LLM apps. Create a playground connected to your code where the whole team can experiment and collaborate. Systematically compare different prompts, models, and embeddings before going to production. Share a link to gather human feedback from the rest of the team. Agenta works out of the box with all frameworks (Langchain, Lama Index, etc.) and model providers (OpenAI, Cohere, Huggingface, self-hosted models, etc.). Gain visibility into your LLM app's costs, latency, and chain of calls. You have the option to create simple LLM apps directly from the UI. However, if you would like to write customized applications, you need to write code with Python. Agenta is model agnostic and works with all model providers and frameworks. The only limitation at present is that our SDK is available only in Python.

Starting Price: Free

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3

Comet LLM

Comet LLM

CometLLM is a tool to log and visualize your LLM prompts and chains. Use CometLLM to identify effective prompt strategies, streamline your troubleshooting, and ensure reproducible workflows. Log your prompts and responses, including prompt template, variables, timestamps and duration, and any metadata that you need. Visualize your prompts and responses in the UI. Log your chain execution down to the level of granularity that you need. Visualize your chain execution in the UI. Automatically tracks your prompts when using the OpenAI chat models. Track and analyze user feedback. Diff your prompts and chain execution in the UI. Comet LLM Projects have been designed to support you in performing smart analysis of your logged prompt engineering workflows. Each column header corresponds to a metadata attribute logged in the LLM project, so the exact list of the displayed default headers can vary across projects.

Starting Price: Free

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4

HoneyHive

HoneyHive

AI engineering doesn't have to be a black box. Get full visibility with tools for tracing, evaluation, prompt management, and more. HoneyHive is an AI observability and evaluation platform designed to assist teams in building reliable generative AI applications. It offers tools for evaluating, testing, and monitoring AI models, enabling engineers, product managers, and domain experts to collaborate effectively. Measure quality over large test suites to identify improvements and regressions with each iteration. Track usage, feedback, and quality at scale, facilitating the identification of issues and driving continuous improvements. HoneyHive supports integration with various model providers and frameworks, offering flexibility and scalability to meet diverse organizational needs. It is suitable for teams aiming to ensure the quality and performance of their AI agents, providing a unified platform for evaluation, monitoring, and prompt management.

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5

Orq.ai

Orq.ai

Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security.

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6

Literal AI

Literal AI

Literal AI is a collaborative platform designed to assist engineering and product teams in developing production-grade Large Language Model (LLM) applications. It offers a suite of tools for observability, evaluation, and analytics, enabling efficient tracking, optimization, and integration of prompt versions. Key features include multimodal logging, encompassing vision, audio, and video, prompt management with versioning and AB testing capabilities, and a prompt playground for testing multiple LLM providers and configurations. Literal AI integrates seamlessly with various LLM providers and AI frameworks, such as OpenAI, LangChain, and LlamaIndex, and provides SDKs in Python and TypeScript for easy instrumentation of code. The platform also supports the creation of experiments against datasets, facilitating continuous improvement and preventing regressions in LLM applications.

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