REPOGEO REPORT · LITE
malywut/gpt_examples
Default branch main · commit 26084dd7 · scanned 6/5/2026, 5:02:15 AM
GitHub: 677 stars · 290 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface malywut/gpt_examples, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highlicense#1Add a LICENSE file to the repository
Why:
COPY-PASTE FIXCreate a LICENSE file in the repository root with a standard open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that reflects the intended usage of the code examples.
- highabout#2Add a concise description and relevant topics to the repository
Why:
CURRENTDescription: (none), Topics: (none)
COPY-PASTE FIXDescription: Practical Python code examples and use cases for building applications with GPT-4 and ChatGPT, directly from the book "Developing Apps with GPT-4 and ChatGPT". Topics: ['gpt', 'gpt-4', 'chatgpt', 'openai', 'python', 'llm', 'generative-ai', 'code-examples', 'application-development', 'book-companion']
- mediumreadme#3Clarify the README's opening sentence to emphasize standalone examples
Why:
CURRENTThis repository contains different examples and use cases showcased in the book <a href="https://appswithgpt.com">Developing Apps with GPT-4 and ChatGPT</a>.
COPY-PASTE FIXThis repository provides practical, standalone Python code examples and use cases for building applications with GPT-4 and ChatGPT, directly from the book "Developing Apps with GPT-4 and ChatGPT".
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- LangChain · recommended 2×
- LlamaIndex · recommended 2×
- Haystack · recommended 2×
- OpenAI Python Library · recommended 1×
- Hugging Face `transformers` library · recommended 1×
- CATEGORY QUERYHow to build applications using large language models with Python examples?you: not recommendedAI recommended (in order):
- LangChain
- LlamaIndex
- OpenAI Python Library
- Hugging Face `transformers` library
- Haystack
- LiteLLM
AI recommended 6 alternatives but never named malywut/gpt_examples. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking Python code examples for creating a question-answering system from documents?you: not recommendedAI recommended (in order):
- Haystack
- LangChain
- LlamaIndex
- Hugging Face Transformers
- Faiss
- Pinecone
- Weaviate
- ChromaDB
- DeepPavlov
- Rasa
AI recommended 10 alternatives but never named malywut/gpt_examples. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenessfail
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of malywut/gpt_examples?passAI named malywut/gpt_examples explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts malywut/gpt_examples in production, what risks or prerequisites should they evaluate first?passAI named malywut/gpt_examples explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo malywut/gpt_examples solve, and who is the primary audience?passAI did not name malywut/gpt_examples — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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malywut/gpt_examples — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite