RRepoGEO

REPOGEO REPORT · LITE

ninehills/chatglm-openai-api

Default branch main · commit f9e068c2 · scanned 6/10/2026, 12:12:42 AM

GitHub: 507 stars · 53 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
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 ninehills/chatglm-openai-api, 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 the README's opening sentence to emphasize 'local' and 'serve'

    Why:

    CURRENT
    Provide OpenAI style API for ChatGLM-6B/ChatGLM2-6B and Chinese Embeddings Model
    COPY-PASTE FIX
    Serve local ChatGLM-6B/ChatGLM2-6B and Chinese Embeddings Models via an OpenAI-compatible API.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    chatglm, openai-api, llm, chinese-llm, local-llm, embeddings, api-wrapper, python
  • mediumreadme#3
    Add a sentence to the README highlighting the core differentiator

    Why:

    COPY-PASTE FIX
    Unlike general local LLM servers, `chatglm-openai-api` is specifically designed and optimized for ChatGLM models and includes dedicated support for Chinese embeddings, making it ideal for applications requiring robust Chinese language processing.

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 ninehills/chatglm-openai-api
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ollama
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Ollama · recommended 1×
  2. LM Studio · recommended 1×
  3. text-generation-webui · recommended 1×
  4. LocalAI · recommended 1×
  5. vLLM · recommended 1×
  • CATEGORY QUERY
    How to expose a local large language model with an OpenAI-compatible API?
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LM Studio
    3. text-generation-webui
    4. LocalAI
    5. vLLM
    6. LiteLLM

    AI recommended 6 alternatives but never named ninehills/chatglm-openai-api. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an API wrapper for Chinese language models compatible with OpenAI client libraries.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Python client library (openai/openai-python)
    2. Baidu Qianfan
    3. Aliyun PAI-EAS
    4. Zhipu AI
    5. LangChain (langchain-ai/langchain)
    6. LlamaIndex (run-llama/llama_index)
    7. FastChat (lm-sys/FastChat)
    8. Hugging Face `transformers` library (huggingface/transformers)
    9. vLLM (vllm-project/vllm)
    10. text-generation-inference (huggingface/text-generation-inference)

    AI recommended 10 alternatives but never named ninehills/chatglm-openai-api. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 ninehills/chatglm-openai-api?
    pass
    AI did not name ninehills/chatglm-openai-api — 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 ninehills/chatglm-openai-api in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ninehills/chatglm-openai-api 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 ninehills/chatglm-openai-api solve, and who is the primary audience?
    pass
    AI named ninehills/chatglm-openai-api explicitly

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

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ninehills/chatglm-openai-api — 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