{"id":"danswer-danswer-model-server","name":"danswer-model-server","homepage":"https://hub.docker.com/r/danswer/danswer-model-server","repo_url":"https://hub.docker.com/r/danswer/danswer-model-server","category":"ai-ml","subcategories":[],"tags":["ai-ml","infrastructure","llm","model-serving","self-hosted","rag"],"what_it_does":"Provides a model-serving layer for “danswer” that exposes LLM/model inference capabilities via a server process (used by Danswer for answering/search/assistant features).","use_cases":["Serving LLM/model inference for Danswer deployments","Powering question-answering and retrieval-augmented generation workflows","Building internal assistant functionality that requires consistent model access"],"not_for":["Direct end-user consumption (should be used behind an application layer)","Workloads needing a fully managed SaaS experience (this appears to be a self-hosted component)"],"best_when":"You want to self-host the Danswer model-serving component and integrate it with Danswer’s backend workflow.","avoid_when":"You need a turn-key hosted API with guaranteed uptime, SLAs, and managed security controls; or you can’t manage GPU/model dependencies.","alternatives":["OpenAI/Anthropic hosted APIs","Self-hosted inference servers such as vLLM, TGI (Text Generation Inference), or Triton (depending on model and infrastructure)","Danswer/other RAG stacks that use different model server components"],"af_score":22.0,"security_score":43.5,"reliability_score":35.0,"package_type":"mcp_server","discovery_source":["docker_mcp"],"priority":"low","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-04-04T19:54:49.388826+00:00","interface":{"has_rest_api":false,"has_graphql":false,"has_grpc":false,"has_mcp_server":false,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":["Not determined from provided information"],"oauth":false,"scopes":false,"notes":"No concrete auth mechanism details were provided in the prompt content, so exact method/scope behavior cannot be verified."},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"Pricing not determinable from provided information; likely self-hosted infrastructure costs (GPU/compute) rather than per-request SaaS pricing."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":22.0,"security_score":43.5,"reliability_score":35.0,"mcp_server_quality":0.0,"documentation_accuracy":0.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":40.0,"rate_limit_clarity":0.0,"tls_enforcement":60.0,"auth_strength":40.0,"scope_granularity":20.0,"dependency_hygiene":50.0,"secret_handling":50.0,"security_notes":"Without explicit documentation/observables, security scores are necessarily approximate. Model servers typically run as internal services; ensure HTTPS (or network isolation), protect admin endpoints, and store secrets in environment variables/secret managers. Agents should not assume structured error codes, rate limiting headers, or fine-grained auth scopes exist unless verified in the actual server docs/config.","uptime_documented":0.0,"version_stability":50.0,"breaking_changes_history":50.0,"error_recovery":40.0,"idempotency_support":"false","idempotency_notes":null,"pagination_style":"none","retry_guidance_documented":false,"known_agent_gotchas":["Authentication/interface details were not provided, so an agent may need to inspect the repo/source to learn request/response formats and failure modes.","Model-serving components often depend on GPU availability and model download/cache behavior; agents may need retry/backoff for transient startup and warm-up delays."]}}