Daily Archives: July 9, 2025

10 Practical AI Use Cases Using Only Open-Source Tools + Gemini API (with Build Steps)

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🔟 Practical AI Use Cases Using Only Open-Source Tools + Gemini API (with Build Steps)

The AI revolution in 2025 is being led by open tools. With Gemini 1.5 Pro via Google AI Studio (free tier), developers can build smart, efficient systems using frameworks like CrewAI, LangChain, LlamaIndex, and ChromaDB.

Here are 10 real-world use cases you can build—no GPT or paid APIs required.

1. Resume Reviewer & Optimizer

🧑 User Story:
As a job seeker, I want AI to tailor my resume to a job description to highlight skill gaps and improve structure.

🛠 Tools: CrewAI, Gemini 1.5 (via AI Studio), Replit (free IDE)

🧱 Build Steps:

  1. Set up CrewAI with agents like SkillMatcherAgent, RewriterAgent.
  2. Upload user resume & JD as input in Replit interface.
  3. Call Gemini API with prompt: “Review this resume vs this JD and suggest edits.”
  4. Output edits, highlights, and reworded content via Streamlit UI.

2. Support Ticket Classifier Bot

🧑 User Story:
As a support manager, I want to auto-classify tickets and suggest replies based on FAQs.

🛠 Tools: LangChain, Gemini, Supabase (for storing FAQs), FastAPI

🧱 Build Steps:

  1. Use Supabase to store structured FAQ dataset (problem + solution).
  2. Ingest the dataset into LangChain retriever.
  3. Create a FastAPI backend with a POST /ticket endpoint.
  4. On ticket submission, use Gemini prompt: “Classify and answer this support query using this FAQ set.”
  5. Return classification and answer.

3. Reddit + News Market Trend Analyzer

🧑 User Story:
As a seller, I want weekly summaries of product trends from Reddit and news articles.

🛠 Tools: BeautifulSoup, LangChain, Gemini, Streamlit

🧱 Build Steps:

  1. Scrape subreddits like r/Entrepreneur or r/Shopify + Google News headlines.
  2. Parse and clean data.
  3. Feed data to LangChain with a summarize-reason-recommend chain using Gemini.
  4. Output weekly report in a Streamlit dashboard.

4. AI Coding Assistant for Students

🧑 User Story:
As a student, I want help understanding and debugging code line-by-line.

🛠 Tools: CrewAI, Gemini, Replit, Tabby (open-source Copilot alternative)

🧱 Build Steps:

  1. Use Tabby to provide real-time inline suggestions.
  2. Create CrewAI agents: CodeExplainerAgent, BugFixerAgent.
  3. User pastes code in Replit.
  4. Agent sends code snippet to Gemini: “Explain what this code does and fix any bugs.”
  5. Display line-by-line explanation.

5. YouTube Script & Thumbnail Generator

🧑 User Story:
As a creator, I want AI to generate video scripts and thumbnail ideas.

🛠 Tools: Gemini, LangChain, Canva CLI

🧱 Build Steps:

  1. Prompt Gemini: “Generate 5 YouTube titles on topic X. Write a script for one. Suggest a thumbnail idea.”
  2. Use LangChain output parsers to structure script + thumbnail text.
  3. Auto-generate a thumbnail prompt (e.g., “Cartoon man typing on laptop with glowing AI text”) and pass to Canva CLI.
  4. Output content in Markdown/HTML.

6. Adaptive Quiz Generator

🧑 User Story:
As a learner, I want adaptive quizzes that target my weak areas.

🛠 Tools: LlamaIndex, Gemini, Gradio

🧱 Build Steps:

  1. Upload academic content (PDFs, textbooks) to LlamaIndex.
  2. Create a Gradio UI to track quiz attempts.
  3. Use Gemini to generate 5 questions, then score them.
  4. Based on incorrect answers, ask Gemini: “Generate follow-up questions on these concepts.”

7. Multilingual Product Description Generator

🧑 User Story:
As a seller, I want SEO-friendly product descriptions in multiple languages.

🛠 Tools: LangChain, LibreTranslate, Gemini, Flask

🧱 Build Steps:

  1. User inputs product specs via simple web form.
  2. Gemini generates an SEO-rich English description.
  3. Send to LibreTranslate API for conversion to Hindi, Spanish, etc.
  4. Display output via Flask UI.

8. AI Book Summarizer

🧑 User Story:
As a reader, I want summaries of entire books or chapters.

🛠 Tools: PyPDF, LlamaIndex, Gemini, Streamlit

🧱 Build Steps:

  1. Upload a book PDF to Streamlit app.
  2. Extract chapters using PyPDF.
  3. Chunk content and feed into LlamaIndex.
  4. Ask Gemini: “Summarize Chapter 1 in under 300 words with key takeaways.”
  5. Present summary in clean UI.

9. Internal Document Q&A Bot

🧑 User Story:
As an employee, I want an AI to answer questions from company documents.

🛠 Tools: LlamaIndex, Haystack, Gemini, ChromaDB

🧱 Build Steps:

  1. Upload company documents (PDFs, CSVs) into LlamaIndex and embed with ChromaDB.
  2. User asks a question via Streamlit or Telegram Bot.
  3. Retrieve relevant context chunks and ask Gemini: “Based on this document, answer the user query.”
  4. Return factual answer with source citations.

10. AI Health Symptom Triage Assistant

🧑 User Story:
As a clinic receptionist, I want AI to ask patients about symptoms and suggest urgency level.

🛠 Tools: CrewAI, Gemini, FastAPI, MedPrompt Dataset

🧱 Build Steps:

  1. Create agents: SymptomChecker, TriageAdvisor, EmergencyEscalator.
  2. User submits symptoms via web/mobile form.
  3. Gemini prompt: “Based on these symptoms and the dataset, advise urgency (low/moderate/high).”
  4. Return structured output with possible next steps: self-care, telehealth, or ER visit.

✅ Final Thoughts

You now have 10 agent-based AI solutions, all built using:

  • Free Gemini tokens (Google AI Studio)
  • Open-source tools: CrewAI, LangChain, LlamaIndex, Gradio, ChromaDB, etc.

No GPT. No cost.

For 10 more uses case with solution, visit my linkedin article:

No GPT? No Problem. 10 Free AI Projects to Automate Real Workflows with Gemini + Open Tools | LinkedIn