AI Social Post Generator
Budget / Salary₹600–1,500
TypeFreelance project
LocationRemote
Posted3 hours ago
I need an AI solution that automatically produces engaging, on-brand social media posts for Facebook, Twitter, and Instagram. The tool should let me feed in a short brief, keywords, or a reference link and then return ready-to-publish copy that matches each platform’s ideal length, tone, and hashtag style.
I’m open to GPT-based approaches, custom fine-tuned models, or a lightweight rules engine—whichever delivers natural-sounding text and can be expanded later. A simple web interface or a clean command-line script in Python is fine as the front end, but the core generation logic must be clear, well-documented, and modular so I can update prompts or retrain without starting from scratch.
Deliverables
• Source code with clear instructions to run locally
• A short setup guide covering required libraries, environment variables, and rate-limit considerations
• Example prompts and the corresponding AI-generated posts for the three platforms
• Brief notes on how to adjust tone or length parameters for future campaigns
I will test by running five prompts and verifying that the output sounds native to each network, respects character limits, and avoids repetitive phrasing.
I’m open to GPT-based approaches, custom fine-tuned models, or a lightweight rules engine—whichever delivers natural-sounding text and can be expanded later. A simple web interface or a clean command-line script in Python is fine as the front end, but the core generation logic must be clear, well-documented, and modular so I can update prompts or retrain without starting from scratch.
Deliverables
• Source code with clear instructions to run locally
• A short setup guide covering required libraries, environment variables, and rate-limit considerations
• Example prompts and the corresponding AI-generated posts for the three platforms
• Brief notes on how to adjust tone or length parameters for future campaigns
I will test by running five prompts and verifying that the output sounds native to each network, respects character limits, and avoids repetitive phrasing.
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