RRepoGEO

REPOGEO REPORT · LITE

run-llama/llama_deploy

Default branch main · commit c0ce080c · scanned 5/14/2026, 6:46:46 AM

GitHub: 2,070 stars · 229 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 run-llama/llama_deploy, 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
    Clarify README deprecation message to explicitly name and link successor

    Why:

    CURRENT
    > [!CAUTION]
> **This project is deprecated.** To serve workflows, use llama-agents instead.
    COPY-PASTE FIX
    > [!CAUTION]
> **This project is deprecated.** For active development and to serve agentic workflows, please use [llama-agents](https://github.com/run-llama/llama-agents) instead, which is its direct successor.
  • mediumabout#2
    Update repository description to reflect deprecation and successor

    Why:

    CURRENT
    Deploy your agentic worfklows to production
    COPY-PASTE FIX
    DEPRECATED: This project provided tools to deploy agentic workflows to production. For current development, please use `llama-agents`.
  • lowtopics#3
    Add 'deprecated' and 'successor-llama-agents' to topics

    Why:

    CURRENT
    agents, deployment, framework, llamaindex, llm, multi-agents
    COPY-PASTE FIX
    agents, deployment, framework, llamaindex, llm, multi-agents, deprecated, successor-llama-agents

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 run-llama/llama_deploy
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. Kubernetes (K8s) · recommended 1×
  3. KubeFlow · recommended 1×
  4. KFServing/KServe · recommended 1×
  5. AWS SageMaker · recommended 1×
  • CATEGORY QUERY
    How to deploy LLM-powered multi-agent systems to a production environment?
    you: not recommended
    AI recommended (in order):
    1. Kubernetes (K8s)
    2. KubeFlow
    3. KFServing/KServe
    4. AWS SageMaker
    5. AWS Lambda
    6. ECS
    7. Hugging Face Inference Endpoints
    8. TGI (Text Generation Inference) (huggingface/text-generation-inference)
    9. Azure Machine Learning
    10. Azure Kubernetes Service (AKS)
    11. Azure Container Instances (ACI)
    12. Google Cloud Vertex AI
    13. Google Kubernetes Engine (GKE)
    14. Cloud Run
    15. Ray Serve
    16. Ray RLlib
    17. Ray Core
    18. LangChain
    19. FastAPI
    20. Flask
    21. EC2
    22. GCE
    23. Azure VM
    24. OpenAI
    25. Anthropic

    AI recommended 25 alternatives but never named run-llama/llama_deploy. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework for deploying custom AI agent workflows to production.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. Microsoft Semantic Kernel
    5. OpenAI Assistants API
    6. CrewAI
    7. AutoGen

    AI recommended 7 alternatives but never named run-llama/llama_deploy. 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 run-llama/llama_deploy?
    pass
    AI named run-llama/llama_deploy explicitly

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

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

    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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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
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