How are model providers configured?

Model providers are configured through JSON config files and a client registry pattern. The primary config is api/config/generator.json, which defines providers and their models. The default provider is google with gemini-2.5-flash as the default model; OpenAI (gpt-5-nano as default), OpenRouter, Ollama, Bedrock, Azure, DashScope, and LiteLLM are all supported (generator.json lines 4-198). A LiteLLM variant of the config lives in generator.litellm.json with litellm as the default provider.

Each provider has a corresponding ChatStreamer subclass in api/chat/_stream.py that registers itself via the provider class attribute: OllamaChatStreamer, OpenRouterChatStreamer, OpenAIChatStreamer, AzureChatStreamer, LiteLLMChatStreamer, BedrockChatStreamer, DashScopeChatStreamer, GoogleGenerativeChatStreamer, and AnthropicChatStreamer. The ChatStreamer.create() factory method (line 40) looks up the provider name in a registry dict and instantiates the right class.

For per-stage model selection, get_model_config() in config.py (line 364) looks up a provider's configuration, resolves the model client class, and extracts model-specific parameters (temperature, top_p, etc.). The same provider+model tuple is passed through all requests (ChatCompletionRequest and WikiTaskRequest via RepoRequestBase schema, api/schemas/base.py line 9). The embedder is configured separately via DEEPWIKI_EMBEDDER_TYPE env var (openai | google | ollama | bedrock) and its own config file (embedder.json).

OpenAI-compatible endpoints are supported via several paths. The LiteLLMClient (api/clients/litellm.py) extends the OpenAI client, connecting to a LiteLLM proxy at LITELLM_BASE_URL (default localhost:4000). The OpenAIClient uses the standard OpenAI API. Any OpenAI-compatible endpoint can be configured by pointing the client to a different base URL. Local models run through OllamaClient (ollama.py) or via the Ollama provider with local models like qwen3:1.7b, llama3:8b, and qwen3:8b (generator.json lines 116-141).

Provider model. Providers are configured through database entities AiProviderConfig and AiModelConfig, or through model configs (ModelConfig). The AiProviderResolver (src/OpenDeepWiki/Services/AI/AiProviderResolver.cs:52) resolves a provider+model pair into a ResolvedAiModel with endpoint, API key, request type, token pricing, and capabilities. It queries the database for active non-deleted configurations.

Supported provider types. AiProviderResolver.ParseRequestType() (line 199–208) maps normalized provider type strings to AiRequestType enum values: OpenAI, AzureOpenAI, OpenAIResponses, Anthropic, DeepSeekOpenAI. The NormalizeProviderType() function (line 137–153) handles aliases: azure, azure-openai → AzureOpenAI; anthropic, claude → Anthropic; deepseek, deepseek-openai-chat → DeepSeekOpenAI; openai-chat, openai → OpenAI. The AgentFactory (src/OpenDeepWiki/Agents/AgentFactory.cs:60) constructs the appropriate HTTP client per type — for Anthropic it uses an Anthropic SDK client, for DeepSeek a DeepSeekOpenAIChatClient, for OpenAI the OpenAI SDK (chat or responses API).

Per-stage model selection. The WikiGeneratorOptions (src/OpenDeepWiki/Services/Wiki/WikiGeneratorOptions.cs:9) has separate fields for each stage: CatalogModel (for catalog and mind map generation), ContentModel (for document content), TranslationModel (optional fallback to ContentModel). Each model field can be paired with a matching *ProviderId (e.g., CatalogProviderId, ContentProviderId) to bind a specific provider. WikiGeneratorOptionsConfigurator (src/OpenDeepWiki/Services/Wiki/WikiGeneratorOptionsConfigurator.cs:5) wires environment variables: WIKI_LANGUAGES, WIKI_MAX_CONCURRENT_GENERATIONS, plus per-stage config via the WikiGenerator config section.

OpenAI-compatible endpoints. Any provider can use an arbitrary BaseUrl (line 210–226). If the base URL is empty, defaults are assigned per type (Anthropic → https://api.anthropic.com, DeepSeek → https://api.deepseek.com/v1, others → https://api.openai.com/v1). This makes any OpenAI-compatible endpoint (vLLM, Ollama, etc.) usable by setting the request type to OpenAI.

Built-in presets. AiProviderPresetCatalog (src/OpenDeepWiki/Services/AI/AiProviderPresetCatalog.cs:12) loads embedded JSON presets from Services.AI.BuiltinProviderPresets.json containing provider definitions like name, type, default base URL, default model list, and pricing. The presets support seeding on first run via AiProviderPresetSeeder.

Overrides. Each provider and model carries RequestOverridesJson and ThinkingConfigJson, allowing per-invocation passthrough of provider-specific parameters. The AiRequestOptions (src/OpenDeepWiki/Agents/AgentFactory.cs:26) exposes SupportsThinking, ThinkingEnabled, and all override fields, which are applied in the handler chain.