codebook.md

Codebook: AI app cloud-deploy threads (GitHub issues)

One row = one public GitHub issue thread (issue + its comments) about deploying an AI app to a remote host. Published rows contain no text and no author information: only the link, metadata and our coded columns. Coded columns come from keyword rules (scripts/code.py). Some rows were read thread by thread by the AI assistant (Claude) that built the dataset: the review samples, and every row the keywords could not settle under the relevance rules (v4). Its judgements replace the keyword values (relevance_method = agent_reviewed, coding_method = keyword+agent_reviewed). No person has checked these rows yet.

Identification and metadata (from the GitHub API)

column	type	definition
url	string	link to the issue on github.com (the only way to read the text, which belongs to its authors)
source	string	always github_issues in this version
repo	string	owner/name of the repository
repo_group	enum	why the repo was searched: host (deploy platform CLI), framework (AI app framework or AI app), framework_generic (general framework: Streamlit, Gradio; the thread itself must show an AI app), sample (cloud vendor AI sample app), builder (AI app builder or coding agent)
created_at	ISO 8601 UTC	issue creation
closed_at	ISO 8601 UTC or empty	last close time
state	enum	open / closed at collection time
state_reason	enum or empty	GitHub's own value: completed, not_planned, duplicate, reopened, empty
n_comments	int	comment count at collection time
n_reactions	int	total reactions on the issue body
time_to_first_response_h	float or empty	hours from creation to the first comment by someone other than the author, bots excluded; empty = no such comment
time_to_close_h	float or empty	hours from creation to closed_at
maintainer_replied	yes/no	at least one comment by a user whose author_association is OWNER, MEMBER or COLLABORATOR (other than the author)
collected_on	date	snapshot date

Coded columns

column	values	rule (summary)
thread_type	problem, feature, docs, question, pr_ci, other	what the thread is. problem: something breaks or blocks; feature: asks for a new capability; docs: asks for or fixes documentation; question: how-to, nothing broken yet; pr_ci: a code change, release or CI/test pipeline (issues only in this version, so "PR" means an issue about one); other: none of these (measurements, discussions). Rule, first match wins: a title tag ([CI], test:, [Docs], docs:, [Feature], feat:, [RFC], [Question], [Usage], [Bug]…); CI/test words in the title or a CI label; docs words in the title (docs, documentation, README, guide, tutorial) with no error word, or a documentation label without a bug label; a feature label (enhancement, feature, rfc, integration request) or a feature title pattern (Add support…, Support for…, Allow…, option to…) with no error word; an error word (error, fails, broken, cannot, 4xx/5xx, timeout…) or a bug label; a question pattern (How to…, Is it possible…, …?) or a question/support label; an error word in the body; else other. Agreement with the reviewer on a fresh sample: 49/60 (82%); most misses are keyword other that the reviewer reads as feature or question
target_host	vercel, netlify, cloudflare, fly, railway, render, heroku, supabase, hf_spaces, hf_inference_endpoints, streamlit_cloud, posit_connect, langgraph_platform, azure, gcp, aws, digitalocean, runpod, modal, replicate, kubernetes (generic, any cloud), vps_docker (self-managed server, Docker, Coolify-like panels), unspecified	first host named in the title, else in the body, else the repo's own platform (e.g. vercel/vercel → vercel, Azure samples → azure)
app_type	chatbot, rag, ai_generated_web_app, model_serving, agent, other	agent cues > RAG cues > builder repo > serving cues > chat cues; repo defaults for single-purpose repos
framework	one of streamlit, gradio, chainlit, nextjs, remix, sveltekit, nuxt, vite_react, astro, fastapi, flask, django, express_node, hono, langgraph, langchain, llamaindex, vercel_ai_sdk, flowise, langflow, open_webui, nextchat, chatbot_ui, cog, tgi, ollama, vllm, dify, ragflow, anythingllm, hf_chat_ui, litellm, mastra, google_adk, crewai, agno, skypilot, prompty, unspecified	the repo's framework if it is one, else first framework named. In builder repos the framework of the generated app is usually not stated, so unspecified; self-hosted bolt.diy is remix
stack	;-list of the values above	every framework named (repo framework first)
model_provider	;-list (max 3) of azure_openai, openai, anthropic, google, aws_bedrock, local_ollama, huggingface, mistral, deepseek, groq, openrouter, replicate, cohere, or unspecified	providers named in title or body; repo default for single-provider samples
topic	build, runtime_dependencies, provisioning_iac (cloud template / infrastructure provisioning, e.g. azd up, Bicep, Terraform), memory_model_size, secrets_api_keys, gpu, costs_quota, cold_start, timeouts, database, auth_permissions, networking, streaming, routing_config, agent_behavior (a coding or deploy agent itself causes the problem: deploys unasked, claims a deploy worked, deploys to the wrong target, or is blocked by its own safety check; error_type says which), observability (monitoring, tracing and telemetry tooling: Langfuse, OpenTelemetry/OTLP, Sentry, Prometheus, Grafana, Datadog, metrics, ServiceMonitor; plain logs do not count), performance_scaling (slowness, latency, throughput, concurrency, autoscaling, replicas, high availability), other	what the thread is about, whatever its thread_type (a failure, a feature request, a question or a docs request). Called problem_category before 2026-10-30. From the error_type found in the title; else a topical cue in the title (GPU, cold start, database, auth, cost); else the error_type found in the body; coding_confidence says which. Only when all of these give other: the three topics added on 2026-10-30, title first, then body (agent_behavior needs an agent context: the Claude Code repo, or the text names an agent such as Claude, Codex, Copilot, Cursor; observability and performance_scaling use stricter terms in the body, on its text without code blocks). So they never take a row from the 14 older topics, and coding_confidence does not change for them (it stays none when no error or older cue was found). Else other
error_type	secret_exposed (credentials deployed or published by mistake: a credential word such as secret, API key, password, .env must sit next to a leak/expose/publish word; memory leaks are oom, exposed ports port_binding), iac_template_error, oom, size_limit (incl. disk/volume full), timeout, missing_env_var, quota_billing, permission_rbac, port_binding, module_dependency, build_failure, cors_network, streaming, not_found_routing, server_error_5xx, agent_deployed_unasked (the agent deploys or pushes to production without permission or confirmation, or against instructions), agent_false_success (the agent says a deploy worked, was verified or happened when it did not), agent_wrong_target (the agent deploys to the wrong project, environment, account, repo or branch), agent_blocked_refused (an auto-mode classifier, safety filter or the model blocks or refuses a legitimate, user-authorised deploy: a false positive), other_unknown	first matching pattern in the title, else in the first 3,000 characters of the body. For provisioning failures the inner cause (quota, permission) wins when stated. The four agent_* types (added 2026-10-30) come with topic = agent_behavior only; they replace other_unknown, or a server_error_5xx found only in the body
resolution_type	unanswered, self_resolved, config_fix, version_upgrade, version_downgrade, workaround, platform_limit_no_fix, user_error_config, duplicate, stale_closed, open_unresolved, closed_unclear	from replies (non-author, non-bot), labels and state_reason
resolved	yes/no	closed as completed (not by a stale bot), or the author says it works / is solved
ai_generated_app	yes/no/unknown	yes if the thread is in an AI app builder or coding-agent repo, or the text says the app was built/generated with an AI tool. no only when the thread is about self-hosting the builder itself (e.g. deploying bolt.diy). Otherwise unknown: people rarely say they wrote the app by hand
ai_tool	lovable, bolt, v0, cursor, claude_code, replit, copilot, windsurf, dyad, codex, or empty	tool named, or repo default
coding_method	keyword / keyword+agent_reviewed	keyword+agent_reviewed: the AI reviewer read the thread and corrected the codes (host, app type, framework…)
coding_confidence	title / body / none	where the error keywords or the older topic cues were found; title rows agree best with the review. The three topics added 2026-10-30 do not set it
relevance_method	keyword / agent_reviewed	who decided the row is relevant (and its thread_type): the keyword rules, or the AI reviewer (Claude), not a person

Relevance (rules v4, decided by the dataset owner on 2026-10-28)

A thread is relevant if it is about deploying or running an AI app on a host (cloud AND AI). Relevance is yes or no; the earlier adjacent level is gone, and feature and docs requests stay in, told apart by thread_type.

1. Repo context counts. A Kubernetes or Docker thread in an AI app's repo (Dify, Langflow…) is relevant even if the thread never mentions AI.
2. A host is a remote machine: public cloud, VPS, company server, Kubernetes. Docker on a laptop, WSL or a local GPU is not.
3. Model serving on a host (vLLM, TGI, Ollama on a remote GPU, a model deployed on Azure) is relevant; app_type = model_serving.
4. An agent that deploys and hits its own limits (Claude Code blocked by a classifier, permission denied, a false "it's deployed") is relevant; ai_generated_app = yes.
5. Feature and docs requests stay in, with thread_type saying what they are.
6. An app bug seen on a server but not caused by the deploy, the config or the host runtime is not relevant (a model looping on a k8s GPU, a UI bug after an update). There must be a link to the host.
7. Calling a cloud's managed AI API without deploying your own app is not relevant (Vertex batch, Bedrock, Azure OpenAI calls, "deployment name" settings, LiteLLM router "deployments").
8. General frameworks (Streamlit, Gradio, Next.js, host CLIs): the thread must show an AI app (model, LLM, RAG…); the repo alone is not enough. Rule 1 applies to AI-specific repos only.
9. Tests or CI of a framework's cloud integration are relevant; thread_type = pr_ci.

How the rules are applied. Keywords first (relevance() in scripts/code.py): the title must name a hosting platform or a deploy verb, plus the exclusions above (local cues, managed-API names without a hosting term, router senses of "deployment", CI without a cloud named, Claude Code threads about the desktop app, browser pane, OAuth or connectors). Where the keywords cannot settle a row they set kw_unsure (private file only): Claude Code threads whose deploy context is unclear, model-serving threads that name no host, app-behaviour titles with no host cue (rule 6), threads whose only host cue is "in production", managed-API titles that also say "deploy". Every such row was judged by the AI reviewer (manual/judgement_v4.csv).

Only rows coded relevant are published.