mirror of
https://github.com/TriliumNext/Notes.git
synced 2025-07-27 18:12:29 +08:00
well, we ripped out our custom ollama implementation in favor of the SDK
This commit is contained in:
perf3ct
parent
7f92dfc3f1
commit
53223b5750
16
package-lock.json
generated
16
package-lock.json
generated
@ -67,6 +67,7 @@
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"multer": "1.4.5-lts.2",
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"normalize-strings": "1.1.1",
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"normalize.css": "8.0.1",
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"ollama": "0.5.14",
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"rand-token": "1.0.1",
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"safe-compare": "1.1.4",
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"sanitize-filename": "1.6.3",
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@ -15894,6 +15895,15 @@
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"node": "^10.13.0 || >=12.0.0"
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}
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},
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"node_modules/ollama": {
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"version": "0.5.14",
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"resolved": "https://registry.npmjs.org/ollama/-/ollama-0.5.14.tgz",
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"integrity": "sha512-pvOuEYa2WkkAumxzJP0RdEYHkbZ64AYyyUszXVX7ruLvk5L+EiO2G71da2GqEQ4IAk4j6eLoUbGk5arzFT1wJA==",
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"license": "MIT",
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"dependencies": {
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"whatwg-fetch": "^3.6.20"
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}
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},
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"node_modules/omggif": {
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"version": "1.0.10",
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"resolved": "https://registry.npmjs.org/omggif/-/omggif-1.0.10.tgz",
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@ -21335,6 +21345,12 @@
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"node": ">=18"
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}
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},
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"node_modules/whatwg-fetch": {
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"version": "3.6.20",
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"resolved": "https://registry.npmjs.org/whatwg-fetch/-/whatwg-fetch-3.6.20.tgz",
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"integrity": "sha512-EqhiFU6daOA8kpjOWTL0olhVOF3i7OrFzSYiGsEMB8GcXS+RrzauAERX65xMeNWVqxA6HXH2m69Z9LaKKdisfg==",
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"license": "MIT"
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},
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"node_modules/whatwg-mimetype": {
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"version": "4.0.0",
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"resolved": "https://registry.npmjs.org/whatwg-mimetype/-/whatwg-mimetype-4.0.0.tgz",
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@ -129,6 +129,7 @@
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"multer": "1.4.5-lts.2",
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"normalize-strings": "1.1.1",
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"normalize.css": "8.0.1",
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"ollama": "0.5.14",
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"rand-token": "1.0.1",
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"safe-compare": "1.1.4",
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"sanitize-filename": "1.6.3",
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@ -1,7 +1,7 @@
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import axios from 'axios';
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import options from "../../services/options.js";
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import log from "../../services/log.js";
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import type { Request, Response } from "express";
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import { Ollama } from "ollama";
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/**
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* @swagger
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@ -40,19 +40,16 @@ async function listModels(req: Request, res: Response) {
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try {
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const baseUrl = req.query.baseUrl as string || await options.getOption('ollamaBaseUrl') || 'http://localhost:11434';
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// Call Ollama API to get models
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const response = await axios.get(`${baseUrl}/api/tags?format=json`, {
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headers: { 'Content-Type': 'application/json' },
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timeout: 10000
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});
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// Create Ollama client
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const ollama = new Ollama({ host: baseUrl });
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// Call Ollama API to get models using the official client
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const response = await ollama.list();
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// Return the models list
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const models = response.data.models || [];
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// Important: don't use "return res.send()" - just return the data
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return {
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success: true,
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models: models
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models: response.models || []
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};
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} catch (error: any) {
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log.error(`Error listing Ollama models: ${error.message || 'Unknown error'}`);
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@ -4,17 +4,29 @@ import type { EmbeddingConfig } from "../embeddings_interface.js";
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import { NormalizationStatus } from "../embeddings_interface.js";
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import { LLM_CONSTANTS } from "../../constants/provider_constants.js";
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import type { EmbeddingModelInfo } from "../../interfaces/embedding_interfaces.js";
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import { Ollama } from "ollama";
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/**
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* Ollama embedding provider implementation
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* Ollama embedding provider implementation using the official Ollama client
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*/
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export class OllamaEmbeddingProvider extends BaseEmbeddingProvider {
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name = "ollama";
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private client: Ollama | null = null;
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constructor(config: EmbeddingConfig) {
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super(config);
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}
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/**
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* Get the Ollama client instance
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*/
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private getClient(): Ollama {
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if (!this.client) {
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this.client = new Ollama({ host: this.baseUrl });
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}
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return this.client;
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}
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/**
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* Initialize the provider by detecting model capabilities
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*/
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@ -39,24 +51,13 @@ export class OllamaEmbeddingProvider extends BaseEmbeddingProvider {
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*/
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private async fetchModelCapabilities(modelName: string): Promise<EmbeddingModelInfo | null> {
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try {
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// First try the /api/show endpoint which has detailed model information
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const url = new URL(`${this.baseUrl}/api/show`);
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url.searchParams.append('name', modelName);
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const client = this.getClient();
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// Get model info using the client's show method
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const modelData = await client.show({ model: modelName });
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const showResponse = await fetch(url, {
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method: 'GET',
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headers: { "Content-Type": "application/json" },
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signal: AbortSignal.timeout(10000)
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});
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if (!showResponse.ok) {
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throw new Error(`HTTP error! status: ${showResponse.status}`);
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}
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const data = await showResponse.json();
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if (data && data.parameters) {
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const params = data.parameters;
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if (modelData && modelData.parameters) {
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const params = modelData.parameters as any;
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// Extract context length from parameters (different models might use different parameter names)
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const contextWindow = params.context_length ||
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params.num_ctx ||
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@ -66,7 +67,7 @@ export class OllamaEmbeddingProvider extends BaseEmbeddingProvider {
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// Some models might provide embedding dimensions
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const embeddingDimension = params.embedding_length || params.dim || null;
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log.info(`Fetched Ollama model info from API for ${modelName}: context window ${contextWindow}`);
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log.info(`Fetched Ollama model info for ${modelName}: context window ${contextWindow}`);
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return {
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name: modelName,
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@ -76,7 +77,7 @@ export class OllamaEmbeddingProvider extends BaseEmbeddingProvider {
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};
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}
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} catch (error: any) {
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log.info(`Could not fetch model info from Ollama show API: ${error.message}. Will try embedding test.`);
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log.info(`Could not fetch model info from Ollama API: ${error.message}. Will try embedding test.`);
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// We'll fall back to embedding test if this fails
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}
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@ -162,26 +163,20 @@ export class OllamaEmbeddingProvider extends BaseEmbeddingProvider {
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* Detect embedding dimension by making a test API call
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*/
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private async detectEmbeddingDimension(modelName: string): Promise<number> {
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const testResponse = await fetch(`${this.baseUrl}/api/embeddings`, {
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method: 'POST',
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({
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try {
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const client = this.getClient();
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const embedResponse = await client.embeddings({
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model: modelName,
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prompt: "Test"
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}),
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signal: AbortSignal.timeout(10000)
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});
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if (!testResponse.ok) {
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throw new Error(`HTTP error! status: ${testResponse.status}`);
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}
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const data = await testResponse.json();
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if (data && Array.isArray(data.embedding)) {
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return data.embedding.length;
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} else {
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throw new Error("Could not detect embedding dimensions");
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});
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if (embedResponse && Array.isArray(embedResponse.embedding)) {
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return embedResponse.embedding.length;
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} else {
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throw new Error("Could not detect embedding dimensions");
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}
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} catch (error) {
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throw new Error(`Failed to detect embedding dimensions: ${error}`);
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}
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}
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@ -218,26 +213,15 @@ export class OllamaEmbeddingProvider extends BaseEmbeddingProvider {
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const charLimit = (modelInfo.contextWidth || 8192) * 4; // Rough estimate: avg 4 chars per token
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const trimmedText = text.length > charLimit ? text.substring(0, charLimit) : text;
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const response = await fetch(`${this.baseUrl}/api/embeddings`, {
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method: 'POST',
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({
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model: modelName,
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prompt: trimmedText,
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format: "json"
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}),
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signal: AbortSignal.timeout(60000) // Increased timeout for larger texts (60 seconds)
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const client = this.getClient();
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const response = await client.embeddings({
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model: modelName,
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prompt: trimmedText
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});
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if (!response.ok) {
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throw new Error(`HTTP error! status: ${response.status}`);
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}
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const data = await response.json();
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if (data && Array.isArray(data.embedding)) {
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if (response && Array.isArray(response.embedding)) {
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// Success! Return the embedding
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return new Float32Array(data.embedding);
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return new Float32Array(response.embedding);
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} else {
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throw new Error("Unexpected response structure from Ollama API");
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}
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@ -1,45 +1,13 @@
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import options from '../../options.js';
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import { BaseAIService } from '../base_ai_service.js';
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import type { Message, ChatCompletionOptions, ChatResponse } from '../ai_interface.js';
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import sanitizeHtml from 'sanitize-html';
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import { OllamaMessageFormatter } from '../formatters/ollama_formatter.js';
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import log from '../../log.js';
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import type { ToolCall } from '../tools/tool_interfaces.js';
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import toolRegistry from '../tools/tool_registry.js';
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import type { OllamaOptions } from './provider_options.js';
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import { getOllamaOptions } from './providers.js';
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interface OllamaFunctionArguments {
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[key: string]: any;
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}
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interface OllamaFunctionCall {
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function: {
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name: string;
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arguments: OllamaFunctionArguments | string;
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};
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id?: string;
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}
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interface OllamaMessage {
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role: string;
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content: string;
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tool_calls?: OllamaFunctionCall[];
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}
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interface OllamaResponse {
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model: string;
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created_at: string;
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message: OllamaMessage;
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done: boolean;
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done_reason?: string;
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total_duration: number;
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load_duration: number;
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prompt_eval_count: number;
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prompt_eval_duration: number;
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eval_count: number;
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eval_duration: number;
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}
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import { Ollama, type ChatRequest, type ChatResponse as OllamaChatResponse } from 'ollama';
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// Add an interface for tool execution feedback status
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interface ToolExecutionStatus {
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@ -52,6 +20,7 @@ interface ToolExecutionStatus {
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export class OllamaService extends BaseAIService {
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private formatter: OllamaMessageFormatter;
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private client: Ollama | null = null;
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constructor() {
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super('Ollama');
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@ -62,6 +31,17 @@ export class OllamaService extends BaseAIService {
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return super.isAvailable() && !!options.getOption('ollamaBaseUrl');
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}
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private getClient(): Ollama {
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if (!this.client) {
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const baseUrl = options.getOption('ollamaBaseUrl');
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if (!baseUrl) {
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throw new Error('Ollama base URL is not configured');
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}
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this.client = new Ollama({ host: baseUrl });
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}
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return this.client;
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}
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async generateChatCompletion(messages: Message[], opts: ChatCompletionOptions = {}): Promise<ChatResponse> {
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if (!this.isAvailable()) {
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throw new Error('Ollama service is not available. Check API URL in settings.');
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@ -108,79 +88,39 @@ export class OllamaService extends BaseAIService {
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log.info(`Sending to Ollama with formatted messages: ${messagesToSend.length}`);
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}
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// Build request body base
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const requestBody: any = {
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model: providerOptions.model,
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messages: messagesToSend
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};
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// Debug logging for stream option
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log.info(`Stream option in providerOptions: ${providerOptions.stream}`);
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log.info(`Stream option type: ${typeof providerOptions.stream}`);
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// Handle streaming in a way that respects the provided option but ensures consistency:
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// - If explicitly true, set to true
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// - If explicitly false, set to false
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// - If undefined, default to false unless we have a streamCallback
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if (providerOptions.stream !== undefined) {
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// Explicit value provided - respect it
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requestBody.stream = providerOptions.stream === true;
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log.info(`Stream explicitly provided in options, set to: ${requestBody.stream}`);
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} else if (opts.streamCallback) {
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// No explicit value but we have a stream callback - enable streaming
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requestBody.stream = true;
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log.info(`Stream not explicitly set but streamCallback provided, enabling streaming`);
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} else {
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// Default to false
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requestBody.stream = false;
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log.info(`Stream not explicitly set and no streamCallback, defaulting to false`);
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}
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// Log request details
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log.info(`========== OLLAMA API REQUEST ==========`);
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log.info(`Model: ${providerOptions.model}, Messages: ${messagesToSend.length}`);
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log.info(`Stream: ${opts.streamCallback ? true : false}`);
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// Log additional information about the streaming context
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log.info(`Streaming context: Will stream to client: ${typeof opts.streamCallback === 'function'}`);
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// If we have a streaming callback but the stream flag isn't set for some reason, warn about it
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if (typeof opts.streamCallback === 'function' && !requestBody.stream) {
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log.info(`WARNING: Stream callback provided but stream=false in request. This may cause streaming issues.`);
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}
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// Add options object if provided
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if (providerOptions.options) {
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requestBody.options = { ...providerOptions.options };
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}
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// Add tools if enabled
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// Get tools if enabled
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let tools = [];
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if (providerOptions.enableTools !== false) {
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// Use provided tools or get from registry
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try {
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requestBody.tools = providerOptions.tools && providerOptions.tools.length > 0
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tools = providerOptions.tools && providerOptions.tools.length > 0
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? providerOptions.tools
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: toolRegistry.getAllToolDefinitions();
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// Handle empty tools array
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if (requestBody.tools.length === 0) {
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if (tools.length === 0) {
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log.info('No tools found, attempting to initialize tools...');
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const toolInitializer = await import('../tools/tool_initializer.js');
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await toolInitializer.default.initializeTools();
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requestBody.tools = toolRegistry.getAllToolDefinitions();
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log.info(`After initialization: ${requestBody.tools.length} tools available`);
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tools = toolRegistry.getAllToolDefinitions();
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log.info(`After initialization: ${tools.length} tools available`);
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}
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if (tools.length > 0) {
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log.info(`Sending ${tools.length} tool definitions to Ollama`);
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}
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} catch (error: any) {
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log.error(`Error preparing tools: ${error.message || String(error)}`);
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requestBody.tools = []; // Empty fallback
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tools = []; // Empty fallback
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}
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}
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// Log request details
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log.info(`========== OLLAMA API REQUEST ==========`);
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log.info(`Model: ${requestBody.model}, Messages: ${requestBody.messages.length}, Tools: ${requestBody.tools ? requestBody.tools.length : 0}`);
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log.info(`Stream: ${requestBody.stream || false}, JSON response expected: ${providerOptions.expectsJsonResponse}`);
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if (requestBody.options) {
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log.info(`Options: ${JSON.stringify(requestBody.options)}`);
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}
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// Check message structure and log detailed information about each message
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requestBody.messages.forEach((msg: any, index: number) => {
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messagesToSend.forEach((msg: any, index: number) => {
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const keys = Object.keys(msg);
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log.info(`Message ${index}, Role: ${msg.role}, Keys: ${keys.join(', ')}`);
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@ -194,16 +134,7 @@ export class OllamaService extends BaseAIService {
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// Log tool-related details
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if (keys.includes('tool_calls')) {
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log.info(`Message ${index} has ${msg.tool_calls.length} tool calls:`);
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msg.tool_calls.forEach((call: any, callIdx: number) => {
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log.info(` Tool call ${callIdx}: ${call.function?.name || 'unknown'}, ID: ${call.id || 'unspecified'}`);
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if (call.function?.arguments) {
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const argsPreview = typeof call.function.arguments === 'string'
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? call.function.arguments.substring(0, 100)
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: JSON.stringify(call.function.arguments).substring(0, 100);
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log.info(` Arguments: ${argsPreview}...`);
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}
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});
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log.info(`Message ${index} has ${msg.tool_calls.length} tool calls`);
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}
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if (keys.includes('tool_call_id')) {
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@ -215,231 +146,163 @@ export class OllamaService extends BaseAIService {
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}
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});
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// Log tool definitions
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if (requestBody.tools && requestBody.tools.length > 0) {
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log.info(`Sending ${requestBody.tools.length} tool definitions:`);
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requestBody.tools.forEach((tool: any, toolIdx: number) => {
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log.info(` Tool ${toolIdx}: ${tool.function?.name || 'unnamed'}`);
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if (tool.function?.description) {
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log.info(` Description: ${tool.function.description.substring(0, 100)}...`);
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}
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if (tool.function?.parameters) {
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const paramNames = tool.function.parameters.properties
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||||
? Object.keys(tool.function.parameters.properties)
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: [];
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log.info(` Parameters: ${paramNames.join(', ')}`);
|
||||
}
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||||
});
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||||
}
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||||
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// Log full request body (with improved logging for debug purposes)
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const requestStr = JSON.stringify(requestBody);
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||||
log.info(`========== FULL OLLAMA REQUEST ==========`);
|
||||
|
||||
// Log request in manageable chunks
|
||||
log.info(`Full request: ${requestStr}`);
|
||||
log.info(`========== END FULL OLLAMA REQUEST ==========`);
|
||||
|
||||
// Send the request
|
||||
const response = await fetch(`${providerOptions.baseUrl}/api/chat`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify(requestBody)
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const errorBody = await response.text();
|
||||
log.error(`Ollama API error: ${response.status} ${response.statusText} - ${errorBody}`);
|
||||
throw new Error(`Ollama API error: ${response.status} ${response.statusText}`);
|
||||
}
|
||||
|
||||
const data: OllamaResponse = await response.json();
|
||||
|
||||
// Log response details
|
||||
log.info(`========== OLLAMA API RESPONSE ==========`);
|
||||
log.info(`Model: ${data.model}, Content length: ${data.message.content.length} chars`);
|
||||
log.info(`Tokens: ${data.prompt_eval_count} prompt, ${data.eval_count} completion, ${data.prompt_eval_count + data.eval_count} total`);
|
||||
log.info(`Duration: ${data.total_duration}ns total, ${data.prompt_eval_duration}ns prompt, ${data.eval_duration}ns completion`);
|
||||
log.info(`Done: ${data.done}, Reason: ${data.done_reason || 'not specified'}`);
|
||||
|
||||
// Log content preview
|
||||
const contentPreview = data.message.content && data.message.content.length > 300
|
||||
? `${data.message.content.substring(0, 300)}...`
|
||||
: data.message.content;
|
||||
log.info(`Response content: ${contentPreview}`);
|
||||
|
||||
// Log the full raw response for debugging
|
||||
log.info(`========== FULL OLLAMA RESPONSE ==========`);
|
||||
log.info(`Raw response object: ${JSON.stringify(data)}`);
|
||||
|
||||
// Handle the response and extract tool calls if present
|
||||
const chatResponse: ChatResponse = {
|
||||
text: data.message.content,
|
||||
model: data.model,
|
||||
provider: this.getName(),
|
||||
usage: {
|
||||
promptTokens: data.prompt_eval_count,
|
||||
completionTokens: data.eval_count,
|
||||
totalTokens: data.prompt_eval_count + data.eval_count
|
||||
// Get client instance
|
||||
const client = this.getClient();
|
||||
|
||||
// Convert our message format to Ollama's format
|
||||
const convertedMessages = messagesToSend.map(msg => {
|
||||
const converted: any = {
|
||||
role: msg.role,
|
||||
content: msg.content
|
||||
};
|
||||
|
||||
if (msg.tool_calls) {
|
||||
converted.tool_calls = msg.tool_calls.map(tc => {
|
||||
// For Ollama, arguments must be an object, not a string
|
||||
let processedArgs = tc.function.arguments;
|
||||
|
||||
// If arguments is a string, try to parse it as JSON
|
||||
if (typeof processedArgs === 'string') {
|
||||
try {
|
||||
processedArgs = JSON.parse(processedArgs);
|
||||
} catch (e) {
|
||||
// If parsing fails, create an object with a single property
|
||||
log.info(`Could not parse tool arguments as JSON: ${e}`);
|
||||
processedArgs = { raw: processedArgs };
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
id: tc.id,
|
||||
function: {
|
||||
name: tc.function.name,
|
||||
arguments: processedArgs
|
||||
}
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
if (msg.tool_call_id) {
|
||||
converted.tool_call_id = msg.tool_call_id;
|
||||
}
|
||||
|
||||
if (msg.name) {
|
||||
converted.name = msg.name;
|
||||
}
|
||||
|
||||
return converted;
|
||||
});
|
||||
|
||||
// Prepare base request options
|
||||
const baseRequestOptions = {
|
||||
model: providerOptions.model,
|
||||
messages: convertedMessages,
|
||||
options: providerOptions.options,
|
||||
// Add tools if available
|
||||
tools: tools.length > 0 ? tools : undefined
|
||||
};
|
||||
|
||||
// Add tool calls if present
|
||||
if (data.message.tool_calls && data.message.tool_calls.length > 0) {
|
||||
log.info(`========== OLLAMA TOOL CALLS DETECTED ==========`);
|
||||
log.info(`Ollama response includes ${data.message.tool_calls.length} tool calls`);
|
||||
|
||||
// Log detailed information about each tool call
|
||||
const transformedToolCalls: ToolCall[] = [];
|
||||
|
||||
// Log detailed information about the tool calls in the response
|
||||
log.info(`========== OLLAMA TOOL CALLS IN RESPONSE ==========`);
|
||||
data.message.tool_calls.forEach((toolCall, index) => {
|
||||
log.info(`Tool call ${index + 1}:`);
|
||||
log.info(` Name: ${toolCall.function?.name || 'unknown'}`);
|
||||
log.info(` ID: ${toolCall.id || `auto-${index + 1}`}`);
|
||||
|
||||
// Generate a unique ID if none is provided
|
||||
const id = toolCall.id || `tool-call-${Date.now()}-${index}`;
|
||||
|
||||
// Handle arguments based on their type
|
||||
let processedArguments: Record<string, any> | string;
|
||||
|
||||
if (typeof toolCall.function.arguments === 'string') {
|
||||
// Log raw string arguments in full for debugging
|
||||
log.info(` Raw string arguments: ${toolCall.function.arguments}`);
|
||||
|
||||
// Try to parse JSON string arguments
|
||||
try {
|
||||
processedArguments = JSON.parse(toolCall.function.arguments);
|
||||
log.info(` Successfully parsed arguments to object with keys: ${Object.keys(processedArguments).join(', ')}`);
|
||||
log.info(` Parsed argument values:`);
|
||||
Object.entries(processedArguments).forEach(([key, value]) => {
|
||||
const valuePreview = typeof value === 'string'
|
||||
? (value.length > 100 ? `${value.substring(0, 100)}...` : value)
|
||||
: JSON.stringify(value);
|
||||
log.info(` ${key}: ${valuePreview}`);
|
||||
});
|
||||
} catch (e: unknown) {
|
||||
// If parsing fails, keep as string and log the error
|
||||
processedArguments = toolCall.function.arguments;
|
||||
const errorMessage = e instanceof Error ? e.message : String(e);
|
||||
log.info(` Could not parse arguments as JSON: ${errorMessage}`);
|
||||
log.info(` Keeping as string: ${processedArguments.substring(0, 200)}${processedArguments.length > 200 ? '...' : ''}`);
|
||||
|
||||
// Try to clean and parse again with more aggressive methods
|
||||
try {
|
||||
const cleaned = toolCall.function.arguments
|
||||
.replace(/^['"]|['"]$/g, '') // Remove surrounding quotes
|
||||
.replace(/\\"/g, '"') // Replace escaped quotes
|
||||
.replace(/([{,])\s*'([^']+)'\s*:/g, '$1"$2":') // Replace single quotes around property names
|
||||
.replace(/([{,])\s*(\w+)\s*:/g, '$1"$2":'); // Add quotes around unquoted property names
|
||||
|
||||
log.info(` Attempting to parse cleaned argument: ${cleaned}`);
|
||||
const reparseArg = JSON.parse(cleaned);
|
||||
log.info(` Successfully parsed cleaned argument with keys: ${Object.keys(reparseArg).join(', ')}`);
|
||||
// Use reparsed arguments if successful
|
||||
processedArguments = reparseArg;
|
||||
} catch (cleanErr: unknown) {
|
||||
const cleanErrMessage = cleanErr instanceof Error ? cleanErr.message : String(cleanErr);
|
||||
log.info(` Failed to parse cleaned arguments: ${cleanErrMessage}`);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// If it's already an object, use it directly and log details
|
||||
processedArguments = toolCall.function.arguments;
|
||||
log.info(` Object arguments with keys: ${Object.keys(processedArguments).join(', ')}`);
|
||||
log.info(` Argument values:`);
|
||||
Object.entries(processedArguments).forEach(([key, value]) => {
|
||||
const valuePreview = typeof value === 'string'
|
||||
? (value.length > 100 ? `${value.substring(0, 100)}...` : value)
|
||||
: JSON.stringify(value);
|
||||
log.info(` ${key}: ${valuePreview}`);
|
||||
});
|
||||
// Handle streaming
|
||||
if (opts.streamCallback) {
|
||||
let responseText = '';
|
||||
let responseToolCalls: any[] = [];
|
||||
|
||||
log.info(`Using streaming mode with Ollama client`);
|
||||
|
||||
let streamResponse: OllamaChatResponse | null = null;
|
||||
|
||||
// Create streaming request
|
||||
const streamingRequest = {
|
||||
...baseRequestOptions,
|
||||
stream: true as const // Use const assertion to fix the type
|
||||
};
|
||||
|
||||
// Get the async iterator
|
||||
const streamIterator = await client.chat(streamingRequest);
|
||||
|
||||
// Process each chunk
|
||||
for await (const chunk of streamIterator) {
|
||||
// Save the last chunk for final stats
|
||||
streamResponse = chunk;
|
||||
|
||||
// Accumulate text
|
||||
if (chunk.message?.content) {
|
||||
responseText += chunk.message.content;
|
||||
}
|
||||
|
||||
// If arguments are still empty or invalid, create a default argument
|
||||
if (!processedArguments ||
|
||||
(typeof processedArguments === 'object' && Object.keys(processedArguments).length === 0)) {
|
||||
log.info(` Empty or invalid arguments for tool ${toolCall.function.name}, creating default`);
|
||||
|
||||
// Get tool definition to determine required parameters
|
||||
const allToolDefs = toolRegistry.getAllToolDefinitions();
|
||||
const toolDef = allToolDefs.find(t => t.function?.name === toolCall.function.name);
|
||||
|
||||
if (toolDef && toolDef.function && toolDef.function.parameters) {
|
||||
const params = toolDef.function.parameters;
|
||||
processedArguments = {};
|
||||
|
||||
// Create default values for required parameters
|
||||
if (params.required && Array.isArray(params.required)) {
|
||||
params.required.forEach((param: string) => {
|
||||
// Extract text from the response to use as default value
|
||||
const defaultValue = data.message.content?.includes(param)
|
||||
? extractValueFromText(data.message.content, param)
|
||||
: "default";
|
||||
|
||||
(processedArguments as Record<string, any>)[param] = defaultValue;
|
||||
log.info(` Added default value for required param ${param}: ${defaultValue}`);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Check for tool calls
|
||||
if (chunk.message?.tool_calls && chunk.message.tool_calls.length > 0) {
|
||||
responseToolCalls = [...chunk.message.tool_calls];
|
||||
}
|
||||
|
||||
// Convert to our standard ToolCall format
|
||||
transformedToolCalls.push({
|
||||
id,
|
||||
type: 'function',
|
||||
function: {
|
||||
name: toolCall.function.name,
|
||||
arguments: processedArguments
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
// Add transformed tool calls to response
|
||||
chatResponse.tool_calls = transformedToolCalls;
|
||||
log.info(`Transformed ${transformedToolCalls.length} tool calls for execution`);
|
||||
log.info(`Tool calls after transformation: ${JSON.stringify(chatResponse.tool_calls)}`);
|
||||
|
||||
// Ensure tool_calls is properly exposed and formatted
|
||||
// This is to make sure the pipeline can detect and execute the tools
|
||||
if (transformedToolCalls.length > 0) {
|
||||
// Make sure the tool_calls are exposed in the exact format expected by pipeline
|
||||
chatResponse.tool_calls = transformedToolCalls.map(tc => ({
|
||||
id: tc.id,
|
||||
type: 'function',
|
||||
function: {
|
||||
name: tc.function.name,
|
||||
arguments: tc.function.arguments
|
||||
}
|
||||
}));
|
||||
|
||||
// If the content is empty, use a placeholder to avoid issues
|
||||
if (!chatResponse.text) {
|
||||
chatResponse.text = "Processing your request...";
|
||||
|
||||
// Call the callback with the current chunk content
|
||||
if (opts.streamCallback) {
|
||||
// Original callback expects text content, isDone flag, and optional original chunk
|
||||
opts.streamCallback(
|
||||
chunk.message?.content || '',
|
||||
!!chunk.done,
|
||||
chunk
|
||||
);
|
||||
}
|
||||
|
||||
log.info(`Final tool_calls format for pipeline: ${JSON.stringify(chatResponse.tool_calls)}`);
|
||||
}
|
||||
log.info(`========== END OLLAMA TOOL CALLS ==========`);
|
||||
|
||||
// Create the final response after streaming is complete
|
||||
return {
|
||||
text: responseText,
|
||||
model: providerOptions.model,
|
||||
provider: this.getName(),
|
||||
tool_calls: this.transformToolCalls(responseToolCalls),
|
||||
usage: {
|
||||
promptTokens: streamResponse?.prompt_eval_count || 0,
|
||||
completionTokens: streamResponse?.eval_count || 0,
|
||||
totalTokens: (streamResponse?.prompt_eval_count || 0) + (streamResponse?.eval_count || 0)
|
||||
}
|
||||
};
|
||||
} else {
|
||||
log.info(`========== NO OLLAMA TOOL CALLS DETECTED ==========`);
|
||||
log.info(`Checking raw message response format: ${JSON.stringify(data.message)}`);
|
||||
|
||||
// Attempt to analyze the response to see if it contains tool call intent
|
||||
const responseText = data.message.content || '';
|
||||
if (responseText.includes('search_notes') ||
|
||||
responseText.includes('create_note') ||
|
||||
responseText.includes('function') ||
|
||||
responseText.includes('tool')) {
|
||||
log.info(`Response may contain tool call intent but isn't formatted properly`);
|
||||
log.info(`Content that might indicate tool call intent: ${responseText.substring(0, 500)}`);
|
||||
// Non-streaming request
|
||||
log.info(`Using non-streaming mode with Ollama client`);
|
||||
|
||||
// Create non-streaming request
|
||||
const nonStreamingRequest = {
|
||||
...baseRequestOptions,
|
||||
stream: false as const // Use const assertion for type safety
|
||||
};
|
||||
|
||||
const response = await client.chat(nonStreamingRequest);
|
||||
|
||||
// Log response details
|
||||
log.info(`========== OLLAMA API RESPONSE ==========`);
|
||||
log.info(`Model: ${response.model}, Content length: ${response.message?.content?.length || 0} chars`);
|
||||
log.info(`Tokens: ${response.prompt_eval_count || 0} prompt, ${response.eval_count || 0} completion, ${(response.prompt_eval_count || 0) + (response.eval_count || 0)} total`);
|
||||
|
||||
// Log content preview
|
||||
const contentPreview = response.message?.content && response.message.content.length > 300
|
||||
? `${response.message.content.substring(0, 300)}...`
|
||||
: response.message?.content || '';
|
||||
log.info(`Response content: ${contentPreview}`);
|
||||
|
||||
// Handle the response and extract tool calls if present
|
||||
const chatResponse: ChatResponse = {
|
||||
text: response.message?.content || '',
|
||||
model: response.model || providerOptions.model,
|
||||
provider: this.getName(),
|
||||
usage: {
|
||||
promptTokens: response.prompt_eval_count || 0,
|
||||
completionTokens: response.eval_count || 0,
|
||||
totalTokens: (response.prompt_eval_count || 0) + (response.eval_count || 0)
|
||||
}
|
||||
};
|
||||
|
||||
// Add tool calls if present
|
||||
if (response.message?.tool_calls && response.message.tool_calls.length > 0) {
|
||||
log.info(`Ollama response includes ${response.message.tool_calls.length} tool calls`);
|
||||
chatResponse.tool_calls = this.transformToolCalls(response.message.tool_calls);
|
||||
log.info(`Transformed tool calls: ${JSON.stringify(chatResponse.tool_calls)}`);
|
||||
}
|
||||
|
||||
log.info(`========== END OLLAMA RESPONSE ==========`);
|
||||
return chatResponse;
|
||||
}
|
||||
|
||||
log.info(`========== END OLLAMA RESPONSE ==========`);
|
||||
return chatResponse;
|
||||
} catch (error: any) {
|
||||
// Enhanced error handling with detailed diagnostics
|
||||
log.error(`Ollama service error: ${error.message || String(error)}`);
|
||||
@ -447,40 +310,45 @@ export class OllamaService extends BaseAIService {
|
||||
log.error(`Error stack trace: ${error.stack}`);
|
||||
}
|
||||
|
||||
if (error.message && error.message.includes('Cannot read properties of null')) {
|
||||
log.error('Tool registry connection issue detected. Tool may not be properly registered or available.');
|
||||
log.error('Check tool registry initialization and tool availability before execution.');
|
||||
}
|
||||
|
||||
// Propagate the original error
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets the context window size in tokens for a given model
|
||||
* @param modelName The name of the model
|
||||
* @returns The context window size in tokens
|
||||
* Transform Ollama tool calls to the standard format expected by the pipeline
|
||||
*/
|
||||
private async getModelContextWindowTokens(modelName: string): Promise<number> {
|
||||
try {
|
||||
// Import model capabilities service
|
||||
const modelCapabilitiesService = (await import('../model_capabilities_service.js')).default;
|
||||
|
||||
// Get model capabilities
|
||||
const modelCapabilities = await modelCapabilitiesService.getModelCapabilities(modelName);
|
||||
|
||||
// Get context window tokens with a default fallback
|
||||
const contextWindowTokens = modelCapabilities.contextWindowTokens || 8192;
|
||||
|
||||
log.info(`Using context window size for ${modelName}: ${contextWindowTokens} tokens`);
|
||||
|
||||
return contextWindowTokens;
|
||||
} catch (error: any) {
|
||||
// Log error but provide a reasonable default
|
||||
log.error(`Error getting model context window: ${error.message}`);
|
||||
return 8192; // Default to 8192 tokens if there's an error
|
||||
private transformToolCalls(toolCalls: any[] | undefined): ToolCall[] {
|
||||
if (!toolCalls || !Array.isArray(toolCalls) || toolCalls.length === 0) {
|
||||
return [];
|
||||
}
|
||||
|
||||
return toolCalls.map((toolCall, index) => {
|
||||
// Generate a unique ID if none is provided
|
||||
const id = toolCall.id || `tool-call-${Date.now()}-${index}`;
|
||||
|
||||
// Handle arguments based on their type
|
||||
let processedArguments: Record<string, any> | string = toolCall.function?.arguments || {};
|
||||
|
||||
if (typeof processedArguments === 'string') {
|
||||
try {
|
||||
processedArguments = JSON.parse(processedArguments);
|
||||
} catch (error) {
|
||||
// If we can't parse as JSON, create a simple object
|
||||
log.info(`Could not parse tool arguments as JSON in transformToolCalls: ${error}`);
|
||||
processedArguments = { raw: processedArguments };
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
id,
|
||||
type: 'function',
|
||||
function: {
|
||||
name: toolCall.function?.name || '',
|
||||
arguments: processedArguments
|
||||
}
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
@ -526,27 +394,3 @@ export class OllamaService extends BaseAIService {
|
||||
return updatedMessages;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Simple utility to extract a value from text based on a parameter name
|
||||
* @param text The text to search in
|
||||
* @param param The parameter name to look for
|
||||
* @returns Extracted value or default
|
||||
*/
|
||||
function extractValueFromText(text: string, param: string): string {
|
||||
// Simple regex to find "param: value" or "param = value" or "param value" patterns
|
||||
const patterns = [
|
||||
new RegExp(`${param}[\\s]*:[\\s]*["']?([^"',\\s]+)["']?`, 'i'),
|
||||
new RegExp(`${param}[\\s]*=[\\s]*["']?([^"',\\s]+)["']?`, 'i'),
|
||||
new RegExp(`${param}[\\s]+["']?([^"',\\s]+)["']?`, 'i')
|
||||
];
|
||||
|
||||
for (const pattern of patterns) {
|
||||
const match = text.match(pattern);
|
||||
if (match && match[1]) {
|
||||
return match[1];
|
||||
}
|
||||
}
|
||||
|
||||
return "default_value";
|
||||
}
|
||||
|
||||
@ -566,24 +566,28 @@ export async function getOllamaOptions(
|
||||
}
|
||||
|
||||
/**
|
||||
* Get context window size for Ollama model
|
||||
* Get context window size for Ollama model using the official client
|
||||
*/
|
||||
async function getOllamaModelContextWindow(modelName: string): Promise<number> {
|
||||
try {
|
||||
const baseUrl = options.getOption('ollamaBaseUrl');
|
||||
|
||||
if (!baseUrl) {
|
||||
throw new Error('Ollama base URL is not configured');
|
||||
}
|
||||
|
||||
// Use the official Ollama client
|
||||
const { Ollama } = await import('ollama');
|
||||
const client = new Ollama({ host: baseUrl });
|
||||
|
||||
// Try to get model information from Ollama API
|
||||
const response = await fetch(`${baseUrl}/api/show`, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ name: modelName })
|
||||
});
|
||||
const modelData = await client.show({ model: modelName });
|
||||
|
||||
if (response.ok) {
|
||||
const data = await response.json();
|
||||
// Get context window from model parameters
|
||||
if (data && data.parameters && data.parameters.num_ctx) {
|
||||
return data.parameters.num_ctx;
|
||||
// Get context window from model parameters
|
||||
if (modelData && modelData.parameters) {
|
||||
const params = modelData.parameters as any;
|
||||
if (params.num_ctx) {
|
||||
return params.num_ctx;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user