Method completePrompt

src/api/providers/lm-studio.ts:190–217

(prompt: string)

	}

	async completePrompt(prompt: string): Promise<string> {
		try {
			// Create params object with optional draft model
			const params: any = {
				model: this.getModel().id,
				messages: [{ role: "user", content: prompt }],
				temperature: this.options.modelTemperature ?? LMSTUDIO_DEFAULT_TEMPERATURE,
				stream: false,
			}

			// Add draft model if speculative decoding is enabled and a draft model is specified
			if (this.options.lmStudioSpeculativeDecodingEnabled && this.options.lmStudioDraftModelId) {
				params.draft_model = this.options.lmStudioDraftModelId
			}

			let response
			try {
				response = await this.client.chat.completions.create(params)
			} catch (error) {
				throw handleOpenAIError(error, this.providerName)
			}
			return response.choices[0]?.message.content || ""
		} catch (error) {
			throw new Error(
				"Please check the LM Studio developer logs to debug what went wrong. You may need to load the model with a larger context length to work with Roo Code's prompts.",
			)
		}
	}
}

export async function getLmStudioModels(baseUrl = "http://localhost:1234") {