Ali Daud’s Post

LangChain speeds up application development using LLMs significantly. Now we just need the right ideas for applications besides chatbots. How are you going to accelerate you enterprise with GenAI? #langchain #genai #llms #acceleration https://lnkd.in/echD6G7m

LLM based development tools: PromptFlow vs LangChain vs Semantic Kernel #MSFTAdvocate

Revolutionizing Software Development with LangChain for LLM Application Development At Data Logic Solution, we are constantly seeking innovative tools to streamline our workflow and enhance the capabilities of our applications. LangChain is an open-source development framework transforming the landscape of LLM (Large Language Model) application development. Here's how LangChain can benefit you: Open-Source Advantages  For Users: Accessibility: Free access to a robust toolkit for LLM development.  Customization: Flexibility to tailor applications to specific project needs. For Contributors: Collaboration: Engage with a community of developers for rapid innovation.  Improvement: Continuously enhance and share tools with the community.    Why LangChain is Ideal for Software Developers Cost-Effective: Leverage open-source tools to reduce development costs.  Scalable Solutions: Modular design allows easy scaling and adaptation to project needs.  Enhanced Efficiency: Reusable components streamline development processes, saving time and effort.  Improved Decision Making: Powerful data analysis tools and automation enhance outcomes' quality.  Empower Your Development with LangChain  By adopting LangChain, we can harness the power of AI to create more efficient, scalable, and intelligent applications. This framework not only simplifies complex processes but also provides the tools needed to stay ahead in the ever-evolving tech landscape. Join the community of innovators and elevate your development capabilities with LangChain! Please visit our website for more details; https://lnkd.in/dBrQqXPD #AI #MachineLearning #SoftwareDevelopment #Langchain #LLMs #TechDevelopment #Programming #Developers  

Software Development Trends for 2024 and Beyond As we step into 2024, the software development landscape is evolving rapidly, driven by new technologies, methodologies, and an insatiable demand for innovation. Whether you’re a seasoned developer or a curious enthusiast, staying ahead of the curve is crucial. Let’s dive into the 17 most influential software development trends that are shaping the future of software creation and deployment: ▪ Python: The ever-popular Python continues to dominate. Its versatility, ease of use, and robust libraries make it a top choice for developers. ▪ DevSecOps: Security is no longer an afterthought. DevSecOps integrates security practices into the development process, ensuring safer and more reliable software. ▪ Progressive Web Apps (PWAs): PWAs combine the best of web and mobile apps, delivering seamless experiences across devices and platforms. ▪ Automated Code Reviews: Tools that analyze code quality and enforce best practices are gaining traction. Quality matters more than ever. ▪ AI and ML: Artificial Intelligence and Machine Learning are revolutionizing software development. From predictive analytics to natural language processing, these technologies are reshaping the industry. ▪ Kubernetes: Container orchestration is essential for scalability and efficient deployment. Kubernetes remains a dominant force in managing containerized applications. ▪ Web 3.0: The next evolution of the web, characterized by decentralized applications (DApps), blockchain, and enhanced user control. Embrace these trends, experiment, and keep pushing the boundaries of what’s possible! 🌟 #softwaredevelopment #techtrends #innovation

Finished with the idea of the project. We are the DocuFlow team: 🔹I am teamlead+Python backend 🔹frontend developer 🔹backend on Golang. DocuFlow is an innovative system that will allow customers to easily and conveniently create and process documents. Now banking contracts will be simple and understandable for the client. With the help of AI, the software will divide the document into paragraphs and explain it clearly. Also, our program will store contracts for different areas of business, which the client can download to use in their activities. And he will be able to edit each point after consulting AI with the help of our application. The platform can be an intermediary between a lawyer and a client - to involve lawyers for help in difficult situations. So the program facilitates working with documents - from creation to its explanation #program #idea #hackathon #document #platform #DocuFlow #ai #teamlead

🚀 From punch cards to AI-powered algorithms, the evolution of software development has been a thrilling ride. 💻 Embracing new languages, methodologies, and paradigms has reshaped our tech landscape. 🌟 Starting with Fortran & COBOL, we now thrive on dynamic languages, functional programming, and open-source collaborations. 🔄 Agile disrupted the game, focusing on adaptability & continuous improvement. Enter DevOps - bridging development & operations for seamless tech magic. ⚙️ Today, AI, machine learning, and quantum computing redefine limits. Scalability, security, and user-centric design steer our course. 🔮 Reflecting on this journey reminds us of the rapid tech strides and our constant need to adapt. What's next? Exciting advancements await, and as developers, we're geared up for the challenge! 🎉 Let's celebrate this software odyssey and brace ourselves for the futuristic tech marvels ahead! 🌈 #techevolution #innovationjourney #devops #ai #futuretech

LangChain exemplifies the importance of building robust abstractions as a proven strategy for developing scalable software. ⚡️ LangChain serves as an abstraction layer built on top of LLM APIs, aimed at facilitating the creation of efficient, reliable, and high-performance applications utilizing Large Language Models (LLMs). When working with LLMs, developers often face the challenge of writing extensive boilerplate code to achieve basic functionalities like text summarization. This time-consuming process can be streamlined by leveraging the prebuilt functions provided by LangChain. Similar to other software libraries, LangChain is designed to simplify development tasks and enhance iteration speed. By utilizing established abstractions, developers can avoid reinventing solutions for recurring sub-problems. This principle underlines the essence of abstraction, which is to provide a conceptual layer atop an existing system, enhancing its functionality and usability. While LangChain facilitates the development of practical LLM applications, it also underscores one of the fundamental concepts in software engineering: abstraction. Effective abstraction enables developers to design systems in various ways, tailored to specific use cases. These abstractions, whether in the form of interfaces or data models, create a mental framework for understanding the system, thereby facilitating further development. Whether you're an aspiring programmer or a seasoned expert, mastering the art of building effective abstractions is key to advancing your skills and enhancing your software development capabilities! 🚀 #artificialintelligence #genai #langchain #engineering

📝 Key takeaways from the following LangChain course: "LangChain for LLM Application Development" on DeepLearning.AI by Harrison Chase. 1️⃣ Parsing - LangChain can parse the output if you use the following Keywords: Thought, Action, Observation (and its tools do use them). This is how a model can interact with other tools and chains. 2️⃣ Memory - ConversationSummaryMemory (among others) is super handy, as it lets you work with chat memory while balancing LLM cost and user experience by remembering what is important. Vector data memory and Entity memories and various combinations are also super intriguing. 3️⃣ Routing and MultiPrompting - this is where we see the LLMs make decisions about what to do, which leads us to the next point. 4️⃣ Agents - using LLMs as a reasoning engine. Use tools, get to know the agent_scratchpad, keep temperature at zero or close to zero, debug what's happening as the chain executes. 5️⃣ Tools - Just add the @tool decorator and a docstring to create a tool out of any function. The course also talks about Chains, Retrievals, Q&A, Evaluation and Debugging and it's a great intro to LangChain. 🔗 Course link https://lnkd.in/dTpHTqnf What other technologies besides vector stores do you use to build GenAI apps? Share them in the comments.

Just a shower thought. We all have seen code suggestions for developers, similarly, there should be an LLM trained on performance optimizations (configurations/best practices) of various infrastructure including application, database, messaging etc. This way a devOps/dev person can get an optimized configuration for an application without having to dig through the product documentation. The LLMs can change the suggested settings based on the inputs provided. Like for e.g. there could be different JVM configurations for a Java application that is throughput optimized compared to one needing real time response. Coming from experience, developers might not be aware of things like Kubernetes CPU/MEM limits and Heap settings. I have seen examples where application heap was set less than MEM and consequently the application used to crash with OOM Killed. This LLM could give them a better starting point. Another usecase can be AI scaling application clusters not only based on CPU/MEM and API response time, but based on things like User statistics and patterns, like predicting a peak hour in advance and starting to scale the environment before the actual peak hits (to improve user experience). Similarly scaling down once the load is reduced. #showerthought #performance #AI #configurations #devops

**Excited to Share My Latest Learning Milestone! 🎉📚**  I’m thrilled to announce that I’ve recently completed a **Comprehensive Course on LangFlow and LangChain** offered by **Tutorials Point**!  This course has been an incredible journey into the world of **AI-powered workflows** and the **LangChain framework**, which is transforming how we build intelligent, context-aware applications.  ### Key Highlights from the Course:   1. **Understanding LangFlow:** Simplifying the creation of advanced AI workflows through visual programming.   2. **Mastering LangChain:** Leveraging its robust framework to integrate language models into real-world applications seamlessly.   3. **Hands-On Projects:** Applying concepts to build solutions that bridge automation and intelligence.  I’m excited to see how these tools can redefine productivity and problem-solving in various domains.  A big thank you to **Tutorials Point** for providing such a well-structured and insightful course. Looking forward to applying these skills in upcoming projects!  If you’ve worked with LangFlow or LangChain, I’d love to hear about your experience and ideas. Let’s connect and exchange knowledge! 🚀  #LangFlow #LangChain #AIWorkflows #LearningJourney #SkillBuilding #DataAnalytics #TutorialsPoint