Build AI apps like pdf.ai, chatbase.co, jenni.ai with this Git Repo

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ShipGPT provides a boiler plate of possibly all AI use cases with a codebase to develop your own AI application or enable your existing tech with AI. Instead of hiring full stack developers and AI dev wrappers, you can directly access the ready made AI repo built on latest libraries, models and practices. It Empowers you to transform your applications into AI-driven apps or build new ones seamlessly. Our comprehensive backend also enables you to create AI products like ChatBase, ChatPDF, Jenni AI, Audio Pen, ChatDox, ChatWebby or bring your own idea into it. *We want you to ship AI and ship it fast.* Bring AI in your existing app/websites with following use cases*: * Conversational Chatbot for your document files (.pdf, .csv, .docs, .epub, .txt) Conversational Chatbot for Audio files. Conversational Chatbot for Video files. Conversational Chatbot on YouTube Videos. Conversational Chatbot for your Websites data. Image Use cases are coming soon *Save 60+ hours:* Stop procrastination, Ship AI SaaS right now & save 60+ hours: 1. Langchain js trainings and deployment ~~(36hrs)~~ 2. 20+ Prompts ~~(4 hrs)~~ 3. APIs development in Express node js for each usecase (~~6 hrs~~) 4. Pinecone research & deployment (~~6 hrs~~) 5. Use Cases development (Youtube, Audios, Videos, Websites) (~~12 hrs~~) 6. AWS (~~2 hrs+~~) Optional 1. latest builds and updates You will be saving approx *$10K* *Tech Stack: </>* 1. Langchain Js 2. Pinecone Vector Storage (Supabase, type sense → Coming Soon) 3. Node Express Js 4. Open AI (3.5 turbo, gpt-4) 5. Open Source support (Llama2, Falcon, etc) → Coming Soon *Note:* No Third party or licenses libraries or APIs are used in these APIs. We use libraries which are open source and easy to maintain. *Why ShipGPT?* Don’t hire full stackers with $30-$60 / hr to write AI logics for you, we got it covered for you. *Pay once and get updates for life time. (Get it now)* We want you to ship AI & ship it fast. *Amazing Team of AI devs* We are the makers of chatdox, chatwebby and created 100’s of use cases in AI. Building and shipping AI products in every 2 weeks. *Live Support* You will be given live support to help in building your use cases. *Coming up next:* Front End with User Auth. Front End with Stripe checkout sessions. Backend with User Management. 1. Supabase Support for vector storage. 2. Type Sense Support for vector Storage. 3. Llama2 Support for LLM. 4. Falcon 40B LLM *Note:* We will be updating this repo frequently to enable developers to build using AI. Today’s offer: We are offering 40% flat off. Use Code “PH40” Don’t miss out on this opportunity.

Visit product View on Hacker NewsNov 22, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, apps, user · Missing: mac, agents, macos

97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting

95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: ios, apps, video · Missing: mobile apps, personal, entrepreneurs

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas, training · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, audio · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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