RRepoGEO

REPOGEO REPORT · LITE

ModelEngine-Group/fit-framework

Default branch main · commit e2f285d1 · scanned 6/30/2026, 4:16:44 PM

GitHub: 2,105 stars · 334 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
33 /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
2 / 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 ModelEngine-Group/fit-framework, 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
    Add a concise English summary to the README

    Why:

    COPY-PASTE FIX
    Add the following text right after the `div align="center"` block and before the Chinese H1:

**FIT Framework is an enterprise-grade AI development framework for Java, offering a multi-language function engine (FIT), a streaming orchestration engine (WaterFlow), and FEL, a powerful LangChain alternative for the Java ecosystem. It supports native/Spring dual-mode operation, hot-swappable plugins, and intelligent distributed deployment, seamlessly unifying large language models with existing business systems.**
  • hightopics#2
    Add more specific topics to improve category matching

    Why:

    CURRENT
    agentic-ai, ai, java, plugin, plugin-system, python
    COPY-PASTE FIX
    agentic-ai, ai, java, plugin, plugin-system, python, llm, langchain-alternative, enterprise-ai, ai-framework, orchestration, workflow-engine, spring-ai
  • mediumreadme#3
    Enhance emphasis on FEL as a LangChain alternative for Java

    Why:

    COPY-PASTE FIX
    Within the 'FEL (FIT Expression for LLM)' section, add a sentence like: 'Unlike Python-centric LangChain, FEL is engineered from the ground up for Java, providing a robust, production-ready framework for integrating LLMs into enterprise systems with familiar Java engineering practices.'

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 ModelEngine-Group/fit-framework
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Spring AI
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Spring AI · recommended 1×
  2. Deeplearning4j (DL4J) · recommended 1×
  3. Apache UIMA (Unstructured Information Management Architecture) · recommended 1×
  4. OpenNLP · recommended 1×
  5. Drools · recommended 1×
  • CATEGORY QUERY
    Seeking a robust Java framework for building enterprise AI applications and agents.
    you: not recommended
    AI recommended (in order):
    1. Spring AI
    2. Deeplearning4j (DL4J)
    3. Apache UIMA (Unstructured Information Management Architecture)
    4. OpenNLP
    5. Drools
    6. Weka

    AI recommended 6 alternatives but never named ModelEngine-Group/fit-framework. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to integrate large language models with existing Java business systems effectively?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. openai-java
    3. Spring WebClient
    4. OkHttp
    5. Azure OpenAI Service
    6. Azure SDK for Java
    7. Google Cloud Vertex AI
    8. Google Cloud Client Libraries for Java
    9. Hugging Face Transformers
    10. Hugging Face Inference API
    11. ONNX Runtime
    12. TensorFlow Serving
    13. PyTorch Serve
    14. LangChain4j
    15. Spring Cloud Gateway
    16. NGINX
    17. Project Reactor
    18. Redis
    19. Caffeine
    20. OpenTelemetry
    21. Prometheus
    22. Grafana
    23. FreeMarker
    24. Thymeleaf

    AI recommended 24 alternatives but never named ModelEngine-Group/fit-framework. 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 ModelEngine-Group/fit-framework?
    pass
    AI named ModelEngine-Group/fit-framework explicitly

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

  • If a team adopts ModelEngine-Group/fit-framework in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ModelEngine-Group/fit-framework 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 ModelEngine-Group/fit-framework solve, and who is the primary audience?
    pass
    AI did not name ModelEngine-Group/fit-framework — 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 ModelEngine-Group/fit-framework. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/ModelEngine-Group/fit-framework.svg)](https://repogeo.com/en/r/ModelEngine-Group/fit-framework)
HTML
<a href="https://repogeo.com/en/r/ModelEngine-Group/fit-framework"><img src="https://repogeo.com/badge/ModelEngine-Group/fit-framework.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

ModelEngine-Group/fit-framework — 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