RRepoGEO

REPOGEO REPORT · LITE

labteral/chatgpt-python

Default branch master · commit 3b982543 · scanned 6/8/2026, 6:07:53 PM

GitHub: 523 stars · 74 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

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 labteral/chatgpt-python, 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.

OVERALL DIRECTION
  • highreadme#1
    Reposition README opening to highlight unofficial ChatGPT focus

    Why:

    CURRENT
    Library that allows developers to easily integrate the ChatGPT into their Python projects.
    COPY-PASTE FIX
    An unofficial Python SDK designed to simplify integration with OpenAI's ChatGPT, providing a high-level interface for conversational AI in your Python applications.
  • mediumtopics#2
    Add more specific topics to clarify SDK role

    Why:

    CURRENT
    chatgpt, davinci, gpt-3, gpt3-library, openai
    COPY-PASTE FIX
    chatgpt, davinci, gpt-3, gpt3-library, openai, python-sdk, conversational-ai, ai-assistant, wrapper, gpt, gpt-3-5, unofficial-api
  • lowabout#3
    Enhance description to highlight ease of integration

    Why:

    CURRENT
    Unofficial Python SDK for OpenAI's ChatGPT
    COPY-PASTE FIX
    An unofficial Python SDK for OpenAI's ChatGPT, designed for easy integration of conversational AI into Python projects.

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.

Recall
0 / 2
0% of queries surface labteral/chatgpt-python
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Python Library
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Python Library · recommended 1×
  2. Google Cloud Generative AI SDK for Python · recommended 1×
  3. Anthropic Python SDK · recommended 1×
  4. Hugging Face Transformers Library · recommended 1×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    Need a simple Python SDK to connect my application with a powerful conversational AI.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Python Library
    2. Google Cloud Generative AI SDK for Python
    3. Anthropic Python SDK
    4. Hugging Face Transformers Library
    5. LangChain

    AI recommended 5 alternatives but never named labteral/chatgpt-python. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking Python tools for developing interactive text-based AI assistants easily.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Haystack (deepset-ai/haystack)
    3. Rasa (RasaHQ/rasa)
    4. OpenAI Python Library (openai/openai-python)
    5. LlamaIndex (run-llama/llama_index)
    6. NLTK (nltk/nltk)
    7. spaCy (explosion/spaCy)

    AI recommended 7 alternatives but never named labteral/chatgpt-python. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

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 labteral/chatgpt-python?
    pass
    AI named labteral/chatgpt-python explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts labteral/chatgpt-python in production, what risks or prerequisites should they evaluate first?
    pass
    AI named labteral/chatgpt-python 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 labteral/chatgpt-python solve, and who is the primary audience?
    pass
    AI named labteral/chatgpt-python explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite