Comprehensive solutions de test logiciel Tools for Every Need

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solutions de test logiciel

  • LangSmith enhances AI application development with smart tools for testing and data management.
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    What is LangSmith?
    LangSmith is designed for AI developers, offering a suite of tools to streamline application development. With features such as application testing, performance analytics, and team collaboration, it simplifies the testing and optimization processes. By providing users with insights into application behavior, LangSmith enables developers to enhance their AI solutions effectively. This ensures a better user experience and higher adoption rates for AI applications.
    LangSmith Core Features
    • Application testing tools
    • Performance analytics
    • Team collaboration features
    • Code integration
    LangSmith Pro & Cons

    The Cons

    Not open-source, limiting customization and community contributions.
    No direct mobile or app store presence mentioned.
    Limited information on potential pricing tiers and costs.

    The Pros

    Unified platform for observability and evaluation of AI agents.
    Detailed tracing and debugging of LLM app behavior.
    Supports human feedback and automated LLM-as-Judge evaluation.
    Collaborative tools for prompt experimentation and improvement.
    Flexible deployment with hybrid and self-hosted options.
    API-first and OTEL-compliant to integrate with existing DevOps tools.
    Does not add latency to AI applications.
    LangSmith Pricing
    Has free planYES
    Free trial details
    Pricing modelFreemium
    Is credit card requiredNo
    Has lifetime planNo
    Billing frequencyMonthly

    Details of Pricing Plan

    Developer

    0 USD
    • For hobbyist projects by solo devs
    • First 5k traces included
    • Tracing to debug agent execution
    • Continuous evals, online and offline
    • Prompt Hub, Playground, and Canvas
    • Annotation queues for human feedback
    • Monitoring and alerting

    Plus

    39 USD
    • Batteries-included tooling for building reliable agents fast
    • First 10k traces included
    • Up to 10 seats
    • Higher rate limits for LangSmith traces
    • 1 dev-sized LangGraph Platform deployment included
    • Email support
    • Everything in Developer plan

    Enterprise

    0 USD
    • For teams with advanced deployment, security, and support needs
    • Custom pricing
    • Alternative deployment options including hybrid and self-hosted
    • Custom SSO and RBAC
    • Access to deployed engineering team
    • Support SLA
    • Team trainings and architectural guidance
    • Everything in Plus plan
    For the latest prices, please visit: https://www.langchain.com/pricing-langsmith
  • Automate solving technical tickets by generating and validating code solutions efficiently.
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    What is Producta?
    Producta is an AI-powered tool designed to streamline the software development process by automating the handling of technical tickets. It uses large language models (LLMs) to validate tasks, plan work, generate solutions, and test them. By integrating with your issue tracker, Producta ensures that your tickets are clearly defined and accurately addressed. This minimizes the time spent on corrections and maximizes productivity. Whether you're creating new tasks from ideas or solving existing ones, Producta offers a hands-free approach to managing your development workflow.
  • An AI-driven data driver extension for Robot Framework leveraging LLMs to auto-generate test data and scenarios.
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    What is Robot Framework AI Agent Datadriver?
    Robot Framework AI Agent Datadriver is an open-source extension for Robot Framework that leverages large language models to automate and enhance data-driven testing. By integrating with OpenAI’s API, the plugin can generate diverse input sets, create edge case scenarios, and validate outputs on the fly. Test engineers define test templates using standard Robot Framework syntax and the DataDriver library; the AI Agent analyzes prompts and data schemas to produce rich test parameters. This approach reduces manual data preparation, accelerates test development, and improves overall coverage and accuracy for functional and regression testing suites.
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