You will get Podcast/YouTube Automation: Transcribe → SEO → Publish
Project details
I build a production‑ready pipeline that turns your podcast or YouTube video into a complete, publishable content package. You get clean transcripts, structured show notes (TL;DR, key points, quotes, resources), YouTube‑optimized titles/descriptions/tags with chapters, and a full blog post. Optionally, I auto‑publish to YouTube and WordPress and create a Notion page. The pipeline runs locally or in Docker, with clear logs, retries, and a simple Gradio Web UI to run jobs and review outputs. I focus on reliability, speed, and results — fewer manual steps, faster turnaround, and consistent quality.
What’s included
Transcription with timestamps (SRT/VTT/JSON)
Show notes: TL;DR, key points, quotes, resources
YouTube package: 5–10 titles, long description with chapters, 15–25 tags, 10 hashtags
Blog post (800–1,200 words, Markdown/HTML)
Optional publishing: YouTube metadata update, WordPress draft, Notion page
Organized output folder + final execution report (JSON)
Gradio Web UI to run/view outputs (optional handover)
Delivery
A neatly organized output folder per episode containing: transcripts, summary.json, chapters.json, youtube.json (SEO), notes.md, blog.md, and report.json
What’s included
Transcription with timestamps (SRT/VTT/JSON)
Show notes: TL;DR, key points, quotes, resources
YouTube package: 5–10 titles, long description with chapters, 15–25 tags, 10 hashtags
Blog post (800–1,200 words, Markdown/HTML)
Optional publishing: YouTube metadata update, WordPress draft, Notion page
Organized output folder + final execution report (JSON)
Gradio Web UI to run/view outputs (optional handover)
Delivery
A neatly organized output folder per episode containing: transcripts, summary.json, chapters.json, youtube.json (SEO), notes.md, blog.md, and report.json
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Content Creation, Automatic Speech Recognition, Conversational AI, Machine Translation, Natural Language Generation, Natural Language Understanding, Sequence ModelingAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, PyTorchAI Models
ChatGPT, GPT-4, LLaMA, WhisperWhat's included
| Service Tiers |
Starter
$249
|
Standard
$599
|
Advanced
$999
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | ||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$50Frequently asked questions
About Rodrigo
AI Automation Developer | Python, RAG, APIs, Chatbots, FastAPI
Sao Paulo, Brazil - 4:51 am local time
✔ Custom AI chatbots (RAG, OpenAI, vector DB)
✔ Data automation & web/API pipelines
✔ FastAPI backends and integrations
✔ Content automation (YouTube / Podcast / transcription)
✔ CRM / Slack / Notion / Google / HubSpot integrations
Tech stack:
Python, FastAPI, OpenAI, LangChain, LlamaIndex, Docker, Postgres,
FAISS, Pinecone, Qdrant, Whisper, FFmpeg, Zapier, n8n
✔ Clean code
✔ Production-ready
✔ Dockerized
✔ Documented
✔ Easy to deploy
Experience:
30+ years working in mission-critical audiovisual and live production
(VW, Coca-Cola, Itaú, Apple, FIFA 2014, CBLOL)
Process:
1. Quick discovery
2. Architecture
3. Build & test
4. Delivery + docs
5. Optional monitoring
PT / EN | Americas / Europe time zones
Fast response (24h)
Steps for completing your project
After purchasing the project, send requirements so Rodrigo can start the project.
Delivery time starts when Rodrigo receives requirements from you.
Rodrigo works on your project following the steps below.
Revisions may occur after the delivery date.
Intake & Access Check (Day 0)
We confirm goals, success criteria, language/tone, target keywords, and destinations (YouTube/WordPress/Notion). You share links/files and access (OAuth/App Password/Token) via Upwork Messages. Outcome: brief plan + schedule.
Dry Run: Ingest + Transcribe (Day 1)
Ingest from YouTube/local file, extract/normalize audio, transcribe with Whisper (API or local). Quick QC on timestamps/language. If anything looks off, we adjust settings before full processing. Outcome: transcript (SRT/VTT/JSON) preview.