feat: Add additional LLM provider options to be used #1
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@@ -32,3 +32,4 @@ report.[0-9]_.[0-9]_.[0-9]_.[0-9]_.json | |
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| # Finder (MacOS) folder config | ||
| .DS_Store | ||
| qdrant_storage/ | ||
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@@ -2,7 +2,7 @@ import { stepCountIs, ToolLoopAgent, type ToolSet } from "ai" | |
| import { z } from "zod" | ||
| import type { Blackboard } from "../blackboard" | ||
| import type { SessionSummary } from "../blackboard/types" | ||
| import type { RuntimeConfig } from "../config" | ||
| import { createBlackboardTools } from "../tools/blackboard" | ||
| import type { CodebaseTools } from "../tools/codebase" | ||
| import type { DocTools } from "../tools/docs" | ||
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@@ -121,6 +121,7 @@ export function createOrchestratorAgent( | |
| codebaseTools: Partial<CodebaseTools> | ||
| interactionTools: InteractionTools | ||
| }, | ||
| runtimeConfig: RuntimeConfig, | ||
| ) { | ||
| const systemPrompt = buildSystemPrompt(context) | ||
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@@ -147,10 +148,27 @@ export function createOrchestratorAgent( | |
| ...blackboardTools, | ||
| } | ||
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| // Create sub-agents with injected config | ||
| const researchAgent = createResearchAgent(blackboard, researchTools, { | ||
| maxRetries: runtimeConfig.agents.runtime.research.maxRetries, | ||
| model: runtimeConfig.models.fast, | ||
| providerOptions: runtimeConfig.agents.runtime.research.providerOptions, | ||
| }) | ||
| const plannerAgent = createPlannerAgent(blackboard, plannerTools, { | ||
| maxRetries: runtimeConfig.agents.runtime.planner.maxRetries, | ||
| model: runtimeConfig.models.fast, | ||
| providerOptions: runtimeConfig.agents.runtime.planner.providerOptions, | ||
| }) | ||
| const writerAgent = createWriterAgent(blackboard, writerTools, { | ||
| maxRetries: runtimeConfig.agents.runtime.writer.maxRetries, | ||
| model: runtimeConfig.models.prose, | ||
| providerOptions: runtimeConfig.agents.runtime.writer.providerOptions, | ||
| }) | ||
| const userAgent = createUserAgent(blackboard, userTools, { | ||
| maxRetries: runtimeConfig.agents.runtime.userInteraction.maxRetries, | ||
| model: runtimeConfig.models.fast, | ||
| providerOptions: runtimeConfig.agents.runtime.userInteraction.providerOptions, | ||
| }) | ||
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Contributor
There was a problem hiding this comment. @Aqua-123 i'm assuming we should now specify provider options via docbot.config.json? same for fallback models? (which used to be both hardcoded in config.ts)
Author
There was a problem hiding this comment. So the flow of user config being loaded is that
{
"providers": [
{
"type": "openai-compatible",
"name": "lmstudio", // ← this becomes the provider prefix
"baseURL": "http://localhost:1234/v1"
}
],
"models": {
"planning": "lmstudio/loaded-model", // ← "lmstudio" + "loaded-model"
"prose": "lmstudio/loaded-model",
...
}
}
registerProviders(configs) {
if (configs.length > 0) {
this.useGateway = false // ← switches OFF gateway mode
}
for (const config of configs) {
if (config.type === "openai-compatible") {
this.registerOpenAICompatible(config) // ← registers "lmstudio" → factory
}
}
}
getModel(modelId: string) {
const providerName = "lmstudio" // parsed from "lmstudio/loaded-model"
const modelName = "loaded-model"
// 1. Check custom providers first ← MATCHES HERE
if (this.customProviders.has("lmstudio")) {
return this.customProviders.get("lmstudio")!("loaded-model")
}
// 2. Native overrides (openai, anthropic, etc. with custom keys)
// 3. Gateway mode (default, but disabled when providers are configured)
// 4. Default native providers (uses env vars)
// 5. Error if unknown
}
createOpenAICompatible({
name: "lmstudio",
baseURL: "http://localhost:1234/v1",
apiKey: config.apiKey, // optional
})So what is not taken as proper config input is
Now we can determine which of these we want to add these configurable or not |
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| const orchestratorTools = { | ||
| ...createWorkflowTools(), | ||
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@@ -408,12 +426,12 @@ export function createOrchestratorAgent( | |
| }, | ||
| } | ||
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| const runtime = runtimeConfig.agents.runtime.orchestrator | ||
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| const agent = new ToolLoopAgent({ | ||
| instructions: systemPrompt, | ||
| maxRetries: runtime.maxRetries, | ||
| model: runtimeConfig.models.planning, | ||
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| prepareStep: ({ messages }) => { | ||
| // inject current session state at every step so the orchestrator | ||
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P2: Inconsistent example: the
nanomodel referencesgoogle/gemini-3-flashbut theprovidersarray only includesopenaiandanthropic. Users following this example will get errors. Either add{ "type": "google" }to providers, or change nano to use an openai/anthropic model.Prompt for AI agents