use 127.0.0.1

docs/public/schemas/llms.json

@@ -47,6 +47,15 @@
                         "type": "boolean",
                         "description": "Indicates if tools are supported"
                     },
+                    "listModels": {
+                        "type": "boolean",
+                        "default": true,
+                        "description": "Indicates if listing models is supported"
+                    },
+                    "pullModel": {
+                        "type": "boolean",
+                        "description": "Indicates if pulling models is supported"
+                    },
                     "openaiCompatibility": {
                         "type": "string",
                         "description": "Uses OpenAI API compatibility layer documentation URL"

packages/cli/src/info.ts

@@ -18,6 +18,7 @@ import {
     ModelConnectionInfo,
     resolveModelConnectionInfo,
 } from "../../core/src/models"
+import { deleteEmptyValues } from "../../core/src/util"
 import { CORE_VERSION } from "../../core/src/version"
 import { YAMLStringify } from "../../core/src/yaml"
 import { buildProject } from "./build"
@@ -64,11 +65,19 @@ export async function envInfo(
                 if (models) {
                     const lm = await resolveLanguageModel(modelProvider.id)
                     if (lm.listModels) {
-                        const ms = await lm.listModels(conn)
+                        const ms = await lm.listModels(conn, {})
                         if (ms?.length) conn.models = ms
                     }
                 }
-                res.providers.push(conn)
+                res.providers.push(
+                    deleteEmptyValues({
+                        provider: conn.provider,
+                        source: conn.source,
+                        base: conn.base,
+                        type: conn.type,
+                        models: conn.models,
+                    })
+                )
             }
         } catch (e) {
             if (error)

packages/core/src/aici.ts

@@ -15,6 +15,8 @@ import {
     ChatCompletionContentPartText,
     ChatCompletionResponse,
 } from "./chattypes"
+import { TraceOptions } from "./trace"
+import { CancellationOptions } from "./cancellation"
 
 /**
  * Renders an AICI node into a string representation.
@@ -404,7 +406,10 @@ const AICIChatCompletion: ChatCompletionHandler = async (
  * @param cfg - The configuration for the language model.
  * @returns A list of language model information.
  */
-async function listModels(cfg: LanguageModelConfiguration) {
+async function listModels(
+    cfg: LanguageModelConfiguration,
+    options?: TraceOptions & CancellationOptions
+) {
     const { token, base, version } = cfg
     const url = `${base}/proxy/info`
     const fetch = await createFetch()

packages/core/src/chat.ts

@@ -127,7 +127,8 @@ export interface LanguageModelInfo {
 }
 
 export type ListModelsFunction = (
-    cfg: LanguageModelConfiguration
+    cfg: LanguageModelConfiguration,
+    options: TraceOptions & CancellationOptions
 ) => Promise<LanguageModelInfo[]>
 
 export type PullModelFunction = (

packages/core/src/constants.ts

@@ -108,19 +108,20 @@ export const MARKDOWN_PROMPT_FENCE = "`````"
 
 export const OPENAI_API_BASE = "https://api.openai.com/v1"
 export const OLLAMA_DEFAUT_PORT = 11434
-export const OLLAMA_API_BASE = "http://localhost:11434/v1"
-export const LLAMAFILE_API_BASE = "http://localhost:8080/v1"
-export const LOCALAI_API_BASE = "http://localhost:8080/v1"
-export const LITELLM_API_BASE = "http://localhost:4000"
+export const OLLAMA_API_BASE = "http://127.0.0.1:11434/v1"
+export const LLAMAFILE_API_BASE = "http://127.0.0.1:8080/v1"
+export const LOCALAI_API_BASE = "http://127.0.0.1:8080/v1"
+export const LITELLM_API_BASE = "http://127.0.0.1:4000"
+export const LMSTUDIO_API_BASE = "http://127.0.0.1:1234/v1"
+export const JAN_API_BASE = "http://127.0.0.1:1337/v1"
+
 export const ANTHROPIC_API_BASE = "https://api.anthropic.com"
 export const HUGGINGFACE_API_BASE = "https://api-inference.huggingface.co/v1"
 export const GOOGLE_API_BASE =
     "https://generativelanguage.googleapis.com/v1beta/openai/"
 export const ALIBABA_BASE =
     "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
 export const MISTRAL_API_BASE = "https://api.mistral.ai/v1"
-export const LMSTUDIO_API_BASE = "http://localhost:1234/v1"
-export const JAN_API_BASE = "http://localhost:1337/v1"
 
 export const PROMPTFOO_CACHE_PATH = ".genaiscript/cache/tests"
 export const PROMPTFOO_CONFIG_DIR = ".genaiscript/config/tests"
@@ -190,6 +191,8 @@ export const MODEL_PROVIDERS = Object.freeze<
         topP?: boolean
         prediction?: boolean
         bearerToken?: boolean
+        listModels?: boolean
+        pullModel?: boolean
         aliases?: Record<string, string>
     }[]
 >(CONFIGURATION_DATA.providers)

packages/core/src/llms.json

@@ -17,11 +17,13 @@
         {
             "id": "azure",
             "detail": "Azure OpenAI deployment",
+            "listModels": false,
             "bearerToken": false
         },
         {
             "id": "azure_serverless",
             "detail": "Azure AI OpenAI (serverless deployments)",
+            "listModels": false,
             "bearerToken": false,
             "aliases": {
                 "large": "gpt-4o",
@@ -34,6 +36,7 @@
         {
             "id": "azure_serverless_models",
             "detail": "Azure AI Models (serverless deployments, not OpenAI)",
+            "listModels": false,
             "prediction": false,
             "bearerToken": true
         },
@@ -43,6 +46,7 @@
             "logprobs": false,
             "topLogprobs": false,
             "prediction": false,
+            "listModels": false,
             "aliases": {
                 "large": "claude-3-5-sonnet-latest",
                 "small": "claude-3-5-haiku-latest",
@@ -70,6 +74,7 @@
             "openaiCompatibility": "https://ai.google.dev/gemini-api/docs/openai",
             "prediction": false,
             "bearerToken": true,
+            "listModels": false,
             "aliases": {
                 "large": "gemini-1.5-flash-latest",
                 "small": "gemini-1.5-flash-latest",
@@ -84,6 +89,7 @@
             "id": "huggingface",
             "detail": "Hugging Face models",
             "prediction": false,
+            "listModels": false,
             "aliases": {
                 "large": "Qwen/Qwen2.5-72B-Instruct",
                 "small": "Qwen/Qwen2.5-Coder-32B-Instruct",
@@ -110,6 +116,7 @@
             "openaiCompatibility": "https://www.alibabacloud.com/help/en/model-studio/developer-reference/compatibility-of-openai-with-dashscope",
             "tools": false,
             "prediction": false,
+            "listModels": false,
             "bearerToken": true,
             "aliases": {
                 "large": "qwen-max",
@@ -125,6 +132,7 @@
             "topLogprobs": false,
             "limitations": "Smaller context windows, and rate limiting",
             "prediction": false,
+            "listModels": false,
             "bearerToken": true,
             "aliases": {
                 "large": "gpt-4o",
@@ -145,6 +153,7 @@
             "detail": "Ollama local model",
             "logitBias": false,
             "openaiCompatibility": "https://github.com/ollama/ollama/blob/main/docs/openai.md",
+            "pullModel": true,
             "prediction": false
         },
         {
@@ -155,7 +164,9 @@
         {
             "id": "jan",
             "detail": "Jan local server",
-            "prediction": false
+            "prediction": false,
+            "listModels": true,
+            "top_p": false
         },
         {
             "id": "llamafile",

packages/core/src/lm.ts

@@ -7,12 +7,14 @@ import {
     MODEL_PROVIDER_ANTHROPIC,
     MODEL_PROVIDER_ANTHROPIC_BEDROCK,
     MODEL_PROVIDER_CLIENT,
+    MODEL_PROVIDER_JAN,
     MODEL_PROVIDER_OLLAMA,
     MODEL_PROVIDER_TRANSFORMERS,
+    MODEL_PROVIDERS,
 } from "./constants"
 import { host } from "./host"
 import { OllamaModel } from "./ollama"
-import { OpenAIModel } from "./openai"
+import { LocalOpenAICompatibleModel } from "./openai"
 import { TransformersModel } from "./transformers"
 
 export function resolveLanguageModel(provider: string): LanguageModel {
@@ -27,5 +29,10 @@ export function resolveLanguageModel(provider: string): LanguageModel {
     if (provider === MODEL_PROVIDER_ANTHROPIC_BEDROCK)
         return AnthropicBedrockModel
     if (provider === MODEL_PROVIDER_TRANSFORMERS) return TransformersModel
-    return OpenAIModel
+
+    const features = MODEL_PROVIDERS.find((p) => p.id === provider)
+    return LocalOpenAICompatibleModel(provider, {
+        listModels: features?.listModels !== false,
+        pullModel: features?.pullModel,
+    })
 }

packages/core/src/ollama.ts

@@ -8,6 +8,8 @@ import { OpenAIChatCompletion } from "./openai"
 import { LanguageModelConfiguration } from "./host"
 import { host } from "./host"
 import { logError, logVerbose } from "./util"
+import { TraceOptions } from "./trace"
+import { CancellationOptions } from "./cancellation"
 
 /**
  * Lists available models for the Ollama language model configuration.
@@ -17,10 +19,11 @@ import { logError, logVerbose } from "./util"
  * @returns A promise that resolves to an array of LanguageModelInfo objects.
  */
 async function listModels(
-    cfg: LanguageModelConfiguration
+    cfg: LanguageModelConfiguration,
+    options: TraceOptions & CancellationOptions
 ): Promise<LanguageModelInfo[]> {
     // Create a fetch instance to make HTTP requests
-    const fetch = await createFetch({ retries: 0 })
+    const fetch = await createFetch({ retries: 0, ...options })
     // Fetch the list of models from the remote API
     const res = await fetch(cfg.base.replace("/v1", "/api/tags"), {
         method: "GET",

packages/core/src/openai.ts

@@ -1,5 +1,6 @@
 import {
     deleteUndefinedValues,
+    logError,
     logVerbose,
     normalizeInt,
     trimTrailingSlash,
@@ -18,9 +19,14 @@ import {
     TOOL_URL,
 } from "./constants"
 import { estimateTokens } from "./tokens"
-import { ChatCompletionHandler, LanguageModel, LanguageModelInfo } from "./chat"
+import {
+    ChatCompletionHandler,
+    LanguageModel,
+    LanguageModelInfo,
+    PullModelFunction,
+} from "./chat"
 import { RequestError, errorMessage, serializeError } from "./error"
-import { createFetch, traceFetchPost } from "./fetch"
+import { createFetch, iterateBody, traceFetchPost } from "./fetch"
 import { parseModelIdentifier } from "./models"
 import { JSON5TryParse } from "./json5"
 import {
@@ -39,9 +45,10 @@ import {
     ChatCompletionTokenLogprob,
 } from "./chattypes"
 import { resolveTokenEncoder } from "./encoders"
-import { toSignal } from "./cancellation"
+import { CancellationOptions, toSignal } from "./cancellation"
 import { INITryParse } from "./ini"
 import { serializeChunkChoiceToLogProbs } from "./logprob"
+import { TraceOptions } from "./trace"
 
 export function getConfigHeaders(cfg: LanguageModelConfiguration) {
     let { token, type, base, provider } = cfg
@@ -420,9 +427,10 @@ export const OpenAIChatCompletion: ChatCompletionHandler = async (
 }
 
 async function listModels(
-    cfg: LanguageModelConfiguration
+    cfg: LanguageModelConfiguration,
+    options: TraceOptions & CancellationOptions
 ): Promise<LanguageModelInfo[]> {
-    const fetch = await createFetch({ retries: 0 })
+    const fetch = await createFetch({ retries: 0, ...(options || {}) })
     const res = await fetch(cfg.base + "/models", {
         method: "GET",
         headers: {
@@ -449,8 +457,68 @@ async function listModels(
     )
 }
 
-export const OpenAIModel = Object.freeze<LanguageModel>({
-    completer: OpenAIChatCompletion,
-    id: MODEL_PROVIDER_OPENAI,
-    listModels,
-})
+const pullModel: PullModelFunction = async (modelId, options) => {
+    const { trace, cancellationToken } = options || {}
+    const { provider, model } = parseModelIdentifier(modelId)
+    const fetch = await createFetch({ retries: 0, ...options })
+    const conn = await host.getLanguageModelConfiguration(modelId, {
+        token: true,
+        cancellationToken,
+        trace,
+    })
+    try {
+        // test if model is present
+        const resTags = await fetch(`${conn.base}/models`, {
+            retries: 0,
+            method: "GET",
+            headers: {
+                "User-Agent": TOOL_ID,
+                "Content-Type": "application/json",
+            },
+        })
+        if (resTags.ok) {
+            const { data: models }: { data: { id: string }[] } =
+                await resTags.json()
+            if (models.find((m) => m.id === model)) return { ok: true }
+        }
+
+        // pull
+        logVerbose(`${provider}: pull ${model}`)
+        const resPull = await fetch(`${conn.base}/models/pull`, {
+            method: "POST",
+            headers: {
+                "User-Agent": TOOL_ID,
+                "Content-Type": "application/json",
+            },
+            body: JSON.stringify({ model }),
+        })
+        if (!resPull.ok) {
+            logError(`${provider}: failed to pull model ${model}`)
+            logVerbose(resPull.statusText)
+            return { ok: false, status: resPull.status }
+        }
+        0
+        for await (const chunk of iterateBody(resPull, { cancellationToken }))
+            process.stderr.write(".")
+        process.stderr.write("\n")
+        return { ok: true }
+    } catch (e) {
+        logError(e)
+        trace?.error(e)
+        return { ok: false, error: serializeError(e) }
+    }
+}
+
+export function LocalOpenAICompatibleModel(
+    providerId: string,
+    options: { listModels?: boolean; pullModel?: boolean }
+) {
+    return Object.freeze<LanguageModel>(
+        deleteUndefinedValues({
+            completer: OpenAIChatCompletion,
+            id: providerId,
+            listModels: options?.listModels ? listModels : undefined,
+            pullModel: options?.pullModel ? pullModel : undefined,
+        })
+    )
+}

packages/vscode/src/servermanager.ts

@@ -83,7 +83,7 @@ export class TerminalServerManager implements ServerManager {
     private async startClient(): Promise<WebSocketClient> {
         assert(!this._client)
         this._port = await findRandomOpenPort()
-        const url = `http://localhost:${this._port}?api-key=${encodeURIComponent(this.state.sessionApiKey)}`
+        const url = `http://127.0.0.1:${this._port}?api-key=${encodeURIComponent(this.state.sessionApiKey)}`
         logInfo(`client url: ${url}`)
         const client = (this._client = new WebSocketClient(url))
         client.chatRequest = createChatModelRunner(this.state)