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Feb 18Wed
Feb 10Tue
  1. Dify Blog

    Dify guides: Preparing LLM application prompts for workflows

    Dify guides on how to design workflow-ready LLM application prompts by defining clear optimization goals, constructing prompts that include task descriptions, examples, and context, and separating system rules from user input. System prompts contain permanent constraints (such as roles, formats, and safety boundaries), while user prompts contain requests for specific content (such as documents and questions). It requires the model to output structured results (such as JSON) and provide evidence to support scoring to reduce hallucinations and improve the usability of the output in downstream steps.

  2. Prime Intellect Blog

    Prime Intellect Lab: An end-to-end platform for training custom models

    Prime Intellect Lab releases an end-to-end model training platform that integrates Environments Hub, hosting training and hosting evaluation, supporting large-scale agent reinforcement learning, reasoning, and evaluation without managing GPU clusters or algorithm details. The platform is built based on environments, including task datasets and executors, and has completed over 3000 reinforcement learning runs through private testing.

Jan 29Thu
  1. LangChain Blog

    How does the LangChain Deep Agents SDK implement efficient context management?

    The LangChain Deep Agents SDK manages limited memory of AI agents through three compression techniques: offloading large tool results (>20,000 tokens) and inputs (>85% context window) to the file system, and using LLM to generate session summaries. The SDK triggers compression on Claude Sonnet 4.5 in terminal benchmark tests, retaining complete records through filesystem search and summaries, supporting frequent compression to optimize performance.

Jan 20Tue
  1. Factory News

    Factory introduces Agent Readiness tool to assess the level of AI agent support in codebases

    Factory introduces Agent Readiness tool, which evaluates the support of codebases in eight technical pillars and five maturity levels by running the /readiness-report command, and provides specific improvement suggestions. The tool aims to address performance differences caused by codebase environment issues in AI coding agent deployment, supporting three interaction methods: CLI, Dashboard, and API, and can quickly improve basic configuration file and document missing issues through automation repair features.

Jan 15Thu
  1. Anthropic Research50

    How scientists use Claude to accelerate research and discovery

    Scientists have achieved significant progress in biological illustration, computational biology, and protein understanding benchmarks using Claude 4.5, a model now available to top researchers worldwide via API for free, and has built custom systems that go beyond literature reviews or coding assistance. In the lab, Claude serves as a collaborative partner throughout the research process, compressing projects that usually take months into hours using various tools, and discovering large-scale data patterns that humans might overlook, eliminating bottlenecks in knowledge-intensive tasks, and even enabling entirely new research approaches that traditional methods cannot adopt.

Jan 14Wed
Jan 9Fri
Jan 8Thu
  1. Dify Blog

    Dify deploys a private AI agent on NVIDIA DGX Spark.

    Dify combined with NVIDIA DGX Spark provides an end-to-end private AI deployment solution, supporting local running of models such as Llama 3, Qwen 2.5, and DeepSeek V3, with a maximum single-device support of 200B parameters and interconnected device support of 405B parameters. It enables zero-code AI application development through the Dify platform.

Dec 22Mon
Dec 18Thu
Nov 26Wed
Nov 21Fri
  1. Dify Blog70

    Kakaku uses Dify to accelerate AI applications: fast, secure, and scalable

    Kakaku has addressed speed, security, and scalability issues in AI application development through the Dify platform, making 30% of employees AI builders and launching a product data extractor within 3 hours, cumulatively building nearly 950 internal applications. Dify Enterprise provides a multi-workspace architecture, single sign-on, sandbox environment, and production-grade infrastructure, achieving a combination of central control and local freedom.

Nov 13Thu
Oct 30Thu
  1. Dify Blog

    Dify Integrates TiDB Vector: Enhancing Knowledge Pipelines with Distributed Vector Storage

    Dify Knowledge Pipeline has officially integrated TiDB Vector, allowing developers to seamlessly reuse processes like parsing tables, extracting entities, and embedding text for knowledge construction in downstream AI applications. TiDB Vector supports hybrid SQL + vector search, filtering structured metadata via SQL syntax before performing semantic retrieval to ensure precise, context-aware responses, and leverages TiDB's distributed architecture for enterprise-grade scalability and stability.

Oct 29Wed
  1. Cognition Blog

    Introducing SWE-1.5: Our fast Agent model

    SWE-1.5 is a boundary-scale model with hundreds of billions of parameters, achieving near SOTA performance in coding, and its service speed has been increased to up to 950 tok/s through collaboration with Cerebras, 6 times faster than Haiku 4.5 and 13 times faster than Sonnet 4.5. SWE-1.5 is now available on Windsurf.

  2. Dify Blog70

    Dify integrates Qdrant high-performance vector database, accelerating the development of next-generation AI applications

    Dify Platform now integrates Qdrant high-performance Rust vector database, providing faster retrieval, hybrid search, and scalable performance for building reliable, production-grade AI applications. This integration enables developers to choose Qdrant without becoming vector search experts through simple configuration, achieving millisecond-level retrieval for millions of documents, complex metadata-based retrieval strategies, and hybrid search capabilities, supporting high-performance scaling from prototype to production.

Oct 27Mon
  1. Prime Intellect Blog75

    Prime Intellect is expanding the scale of its open-source environment project to become a global open evaluation and reinforcement learning environment center.

    Prime Intellect is expanding its open-source environment project into a global open evaluation and reinforcement learning environment center, committing millions of dollars in prizes and seeking partners to accelerate the development of open superintelligence. Over the past two months, more than 400 cutting-edge reinforcement learning environments and evaluations have been collected through bounty programs and reinforcement learning residencies. A new large-scale bounty program will expand to thousands of open-source environments, divided into open access and task-only categories, with prize amounts ranging from 100 to 5000 dollars.

Oct 21Tue
Oct 17Fri
  1. Dify Blog65

    Dify platform integrates Tavily API to achieve real-time web data knowledge pipeline construction

    Dify platform now supports Tavily Real-time Web Search API, allowing users to directly embed web data into knowledge pipelines to enhance accuracy and timeliness; Tavily can be used as a data source plugin in Dify Marketplace, paired with Dify knowledge pipelines, which support modular components from upload and parsing to chunk embedding; users can install the plugin, obtain an API key, and configure LLM nodes to use Tavily search results for generating Q&A pairs and storing them in a knowledge base.

Sep 15Mon
  1. Dify Blog75

    Dify and TrueFoundry AI Gateway Integration Guide

    The Dify platform allows for rapid, code-free construction of chatbots, AI agents, and intelligent search systems, but deploying in production environments often faces challenges. TrueFoundry AI Gateway seamlessly connects development and production, offering cost control, security reinforcement, service degradation, and supplier switching capabilities, supporting real-time cost tracking, role-based access control, multi-region load balancing, and cross-model compatibility.

Sep 4Thu
  1. Dify Blog75

    Dify collaborates with Arize: How to evaluate, monitor, and improve agents

    Dify collaborates with Arize to bring observability tools Phoenix and AX into the Dify ecosystem to evaluate, monitor, and improve agents. Phoenix can automatically track model calls, tool calls, and chain steps, collecting inputs, outputs, latency, and metadata, and supports annotation tracking, building structured test datasets, creating custom evaluations, and running tests.

Aug 27Wed
Jun 27Fri
  1. Anthropic Research

    Anthropic Operates Small Stores with Claude Sonnet 3.7: Project Vend and Its Significance

    Anthropic partnered with Andon Labs to operate an automated store in San Francisco using Claude Sonnet 3.7, testing the ability of large language models to sustain commercial operations. Claudius (an instance of Claude Sonnet 3.7) has real-time web search, email (experimental), note-taking, Slack customer interaction, and automatic checkout system price adjustment features, but failed to successfully operate the store due to multiple pricing errors, hallucinatory order processing, and ignoring profitable opportunities.

Jun 25Wed
May 20Tue
  1. Dify Blog

    Dify Deep Research Workflow: Step-by-Step Guide

    Dify builds deep research workflows using loop variables, structured output, and Agent nodes to achieve iterative exploration and comprehensive report generation. The workflow includes three stages: intent recognition, dynamic research loops (tracking six variables), and research synthesis. Agent nodes utilize exa_search, exa_content, and think tools for information collection and processing. The final output is a cited Markdown report, accelerating the automation of expert-level research methods.

  2. Prime Intellect Blog

    PCCL - Prime Collective Communications Library Released: A fault-tolerant communication library designed for global distributed training.

    PCCL released, designed for global distributed training, with fault tolerance, supports operation on the public internet, bandwidth up to 45 Gbit/s between each pair of data centers, training bandwidth up to 25 Gbit/s between North America and Western Europe, supports dynamic member joining and rejoining, verified its high fault tolerance through long-term stress tests on major sockets (Linux, macOS, Windows WSA).

May 11Sun
  1. Prime Intellect Blog

    INTELLECT-2 Released: The first 32B parameter model trained through global distributed reinforcement learning

    INTELLECT-2 is the first 32B parameter model trained using global distributed reinforcement learning, employing fully asynchronous RL across dynamic heterogeneous computing contributor groups to train reasoning language models. It has open-sourced the training framework PRIME-RL and components such as TOPLOC and SHARDCAST, while improving the GRPO training recipe and data filtering techniques, enhancing QwQ-32B performance on mathematical and coding tasks.

Apr 17Thu
  1. Dify Blog

    How Dify Integrates with InfraNodus to Achieve Advanced Q&A and Creative Generation

    Dify users can create advanced AI chatbots by integrating InfraNodus. The chatbot not only answers questions but also mines insights and generates new ideas from the knowledge base. InfraNodus can visualize the knowledge base as a knowledge graph, identifying 'structural gaps' in concept connections, and its API generates insight-oriented questions targeting these gaps. Users can seamlessly integrate this capability into Dify applications to initiate conversations, content development, or provide smart prompts for Dify AI agents, thereby embedding enhanced chatbots on websites.

Apr 15Tue
  1. Prime Intellect Blog

    INTELLECT-2: The first globally distributed 32B parameter model for reinforcement learning training.

    INTELLECT-2 Released, First to Achieve Global Distributed 32B Parameter Model Reinforcement Learning Training, Anyone Can Contribute Heterogeneous Computing Power Without Permission, Eliminates Communication Bottlenecks Through Asynchronous Reinforcement Learning Paradigm, Supports Heterogeneous Inference Nodes, Inference Nodes Only Need 4×RTX 3090 GPUs to Participate in Training.

Apr 14Mon
  1. Dify Blog

    Dify applications transform into MCP servers through the mcp-server plugin.

    Dify's mcp-server plugin can transform any Dify application into a server-side endpoint compliant with the MCP protocol, allowing external MCP clients to access it directly. The plugin handles client requests via HTTP and SSE protocols, supporting the use of Dify applications as a single MCP tool for Cursor, Claude Desktop, and others, and allows operation in private network environments to enhance security.

Apr 2Wed
Apr 1Tue
  1. Dify Blog

    Dify MCP Plugin Quick Start Guide: Achieve easy tool calls for AI agents through Zapier

    Dify supports integrating over 7000 Zapier applications into AI agents via MCP plugins. Developers can use the MCP SSE plugin to dynamically call external tools or use the Agent Strategy plugin to enable agents to make autonomous decisions on tool calls. The Zapier MCP server provides over 30000 actions, supporting automated tasks like sending emails via Gmail, requiring server endpoint configuration and setting GPT-4o prompts to control calls.

Mar 26Wed
  1. Dify Blog65

    Cursor how to build SSH plugin for server management in a no-code way

    Dify's newly released SSH plugin achieves server management through AI-driven automation, capable of automated deployment, file processing, script execution, and troubleshooting. This plugin is developed based on the Cursor tool, supporting SSH remote command execution and file transfer with a context length of up to 8k. It is easy to install and can independently complete server configuration, application deployment, and issue resolution through an AI intelligent agent.

  2. Dify Blog

    Enhance Dify RAG with InfraNodus: Expand Your LLM Context

    InfraNodus enhances Dify RAG by generating an overview of the knowledge base, helping it better understand context and improve the quality of answers to open-ended questions. InfraNodus extracts metadata such as topics, relationships, and blind spots, enhancing RAG prompts to enable LLMs to cover a broader range of important issues. InfraNodus can process data like PDFs and text, and supports API-driven automated insight extraction, significantly improving the structure and accuracy of answers after integration with Dify.

  3. Dify Blog

    Dify integrates the Open Audio Fish Audio plugin, making AI applications for TTS and voice cloning simple.

    Dify integrates Fish Audio plugin from Open Audio into its platform, providing real-time text-to-speech (TTS) and voice cloning functions for AI applications. Fish Audio supports formats such as Opus, MP3, WAV, and cloning voice takes only 30-45 seconds. Users can control output parameters through WebSocket API. Developers can install the plugin on Dify marketplace and configure API keys to automatically convert LLM generated text into audio clips of specified voices.