RRepoGEO

REPOGEO REPORT · LITE

kturung/langgraph_streamlit_codeassistant

Default branch main · commit 84388ea4 · scanned 5/31/2026, 9:07:08 AM

GitHub: 500 stars · 102 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 kturung/langgraph_streamlit_codeassistant, 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
  • highabout#1
    Add a concise About description

    Why:

    COPY-PASTE FIX
    An AI-powered assistant application integrating Python execution and React rendering for data analysis, visualization, and interactive web development, now with multimodal (vision) capabilities.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ["ai-assistant", "langgraph", "streamlit", "python", "code-generation", "data-analysis", "data-visualization", "multimodal-ai", "react", "jupyter"]
  • mediumreadme#3
    Refine README's opening paragraph for clearer positioning

    Why:

    CURRENT
    # Python and React AI Assistant Application

This application is an AI-powered assistant that integrates Python execution capabilities with React component rendering on the fly, offering a comprehensive environment for data analysis, visualization, and interactive web development.
    COPY-PASTE FIX
    # LangGraph & Streamlit AI Code Assistant

This application is a sophisticated AI-powered assistant built with LangGraph for orchestrating complex, stateful agent workflows, delivered via a Streamlit user interface. It integrates Python execution and dynamic React component rendering on the fly, providing a comprehensive environment for data analysis, visualization, and interactive web development, now with multimodal (vision) capabilities.

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 kturung/langgraph_streamlit_codeassistant
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI API
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 1×
  2. Jupyter Kernel Gateway · recommended 1×
  3. Jupyter Client · recommended 1×
  4. FastAPI · recommended 1×
  5. React · recommended 1×
  • CATEGORY QUERY
    How to build an AI assistant that can execute Python code and render interactive web components?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Jupyter Kernel Gateway
    3. Jupyter Client
    4. FastAPI
    5. React
    6. Vue.js
    7. Plotly.js
    8. ECharts
    9. Altair
    10. Docker
    11. Kubernetes

    AI recommended 11 alternatives but never named kturung/langgraph_streamlit_codeassistant. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an AI tool for data analysis and visualization with multimodal input capabilities.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Vertex AI Workbench
    2. Databricks Lakehouse Platform
    3. MLflow (mlflow/mlflow)
    4. Hugging Face Transformers (huggingface/transformers)
    5. Gradio (gradio-app/gradio)
    6. Streamlit (streamlit/streamlit)
    7. KNIME Analytics Platform
    8. Microsoft Azure Machine Learning

    AI recommended 8 alternatives but never named kturung/langgraph_streamlit_codeassistant. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    Suggestion:

  • 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 kturung/langgraph_streamlit_codeassistant?
    pass
    AI did not name kturung/langgraph_streamlit_codeassistant — 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?

  • If a team adopts kturung/langgraph_streamlit_codeassistant in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kturung/langgraph_streamlit_codeassistant 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 kturung/langgraph_streamlit_codeassistant solve, and who is the primary audience?
    pass
    AI did not name kturung/langgraph_streamlit_codeassistant — 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

Drop this badge into the README of kturung/langgraph_streamlit_codeassistant. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
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