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3 Commits

Author SHA1 Message Date
Ralph Khreish
db6fdebdcd fix: improve ollama object to telemetry structure 2025-05-19 20:49:16 +02:00
HR
60b8e97a1c fix: roomodes typo (#544) 2025-05-19 17:00:06 +02:00
github-actions[bot]
3a6d6dd671 chore: rc version bump 2025-05-18 08:08:54 +00:00
5 changed files with 39 additions and 6 deletions

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@@ -2,18 +2,21 @@
"mode": "exit",
"tag": "rc",
"initialVersions": {
"task-master-ai": "0.13.2"
"task-master-ai": "0.14.0-rc.0"
},
"changesets": [
"beige-doodles-type",
"floppy-plants-marry",
"forty-plums-stay",
"free-bikes-smile",
"many-wasps-sell",
"nice-lies-cover",
"red-oranges-attend",
"red-suns-wash",
"sharp-dingos-melt",
"six-cloths-happen",
"slow-singers-swim",
"small-toys-fly",
"social-masks-fold",
"soft-zoos-flow",
"ten-ways-mate",

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@@ -1,5 +1,23 @@
# task-master-ai
## 0.14.0-rc.1
### Minor Changes
- [#536](https://github.com/eyaltoledano/claude-task-master/pull/536) [`f4a83ec`](https://github.com/eyaltoledano/claude-task-master/commit/f4a83ec047b057196833e3a9b861d4bceaec805d) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Add Ollama as a supported AI provider.
- You can now add it by running `task-master models --setup` and selecting it.
- Ollama is a local model provider, so no API key is required.
- Ollama models are available at `http://localhost:11434/api` by default.
- You can change the default URL by setting the `OLLAMA_BASE_URL` environment variable or by adding a `baseUrl` property to the `ollama` model role in `.taskmasterconfig`.
- If you want to use a custom API key, you can set it in the `OLLAMA_API_KEY` environment variable.
### Patch Changes
- [#442](https://github.com/eyaltoledano/claude-task-master/pull/442) [`2b3ae8b`](https://github.com/eyaltoledano/claude-task-master/commit/2b3ae8bf89dc471c4ce92f3a12ded57f61faa449) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Adds costs information to AI commands using input/output tokens and model costs.
- [#442](https://github.com/eyaltoledano/claude-task-master/pull/442) [`0288311`](https://github.com/eyaltoledano/claude-task-master/commit/0288311965ae2a343ebee4a0c710dde94d2ae7e7) Thanks [@eyaltoledano](https://github.com/eyaltoledano)! - Small fixes - `next` command no longer incorrectly suggests that subtasks be broken down into subtasks in the CLI - fixes the `append` flag so it properly works in the CLI
## 0.14.0-rc.0
### Minor Changes

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@@ -39,7 +39,7 @@
{
"slug": "debug",
"name": "Debug",
"roleDefinition": "You are Roo, an expert software debugger specializing in systematic problem diagnosis and resolution. When activated by another mdode, your task is to meticulously analyze the provided debugging request (potentially referencing Taskmaster tasks, logs, or metrics), use diagnostic tools as instructed to investigate the issue, identify the root cause, and report your findings and recommended next steps back via `attempt_completion`. You focus solely on diagnostics within the scope defined by the delegated task.",
"roleDefinition": "You are Roo, an expert software debugger specializing in systematic problem diagnosis and resolution. When activated by another mode, your task is to meticulously analyze the provided debugging request (potentially referencing Taskmaster tasks, logs, or metrics), use diagnostic tools as instructed to investigate the issue, identify the root cause, and report your findings and recommended next steps back via `attempt_completion`. You focus solely on diagnostics within the scope defined by the delegated task.",
"customInstructions": "Reflect on 5-7 different possible sources of the problem, distill those down to 1-2 most likely sources, and then add logs to validate your assumptions. Explicitly ask the user to confirm the diagnosis before fixing the problem.",
"groups": [
"read",

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@@ -1,6 +1,6 @@
{
"name": "task-master-ai",
"version": "0.14.0-rc.0",
"version": "0.14.0-rc.1",
"description": "A task management system for ambitious AI-driven development that doesn't overwhelm and confuse Cursor.",
"main": "index.js",
"type": "module",

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@@ -3,7 +3,7 @@
* AI provider implementation for Ollama models using the ollama-ai-provider package.
*/
import { createOllama, ollama } from 'ollama-ai-provider';
import { createOllama } from 'ollama-ai-provider';
import { log } from '../../scripts/modules/utils.js'; // Import logging utility
import { generateObject, generateText, streamText } from 'ai';
@@ -48,7 +48,13 @@ async function generateOllamaText({
temperature
});
log('debug', `Ollama generated text: ${result.text}`);
return result.text;
return {
text: result.text,
usage: {
inputTokens: result.usage.promptTokens,
outputTokens: result.usage.completionTokens
}
};
} catch (error) {
log(
'error',
@@ -138,7 +144,13 @@ async function generateOllamaObject({
temperature: temperature,
maxRetries: maxRetries
});
return result.object;
return {
object: result.object,
usage: {
inputTokens: result.usage.promptTokens,
outputTokens: result.usage.completionTokens
}
};
} catch (error) {
log(
'error',