chore(docs): update documentation and assets for RA.Aid project using Docusaurus
- Add new versioned documentation for RA.Aid project. - Include installation instructions, quick starts, and markdown features. - Add configuration files for Docusaurus setup. - Introduce new images and logos for branding. - Create a sidebar for better navigation in documentation. - Implement a .gitignore file for the docs directory to exclude unnecessary files. feat(docs): add SVG illustrations for Docusaurus documentation to enhance visual appeal feat(docs): create tsconfig.json for improved TypeScript support in Docusaurus fix(pyproject.toml): update dependencies to latest versions for better compatibility and features fix(__main__.py): improve expert provider selection logic based on available API keys feat(llm.py): implement function to fetch available OpenAI models and select expert model fix(file_listing.py): enhance file listing functionality to include hidden files option and improve error handling fix(deepseek_chat.py): add timeout and max_retries parameters to ChatDeepseekReasoner initialization fix(version.py): bump version to 0.14.1 for release readiness feat(models_params.py): add default_temperature to model parameters for consistency and configurability refactor(interactive.py): enhance run_interactive_command to support expected runtime and improve output capture fix(prompts.py): update instructions to clarify file modification methods refactor(provider_strategy.py): streamline expert model selection logic for clarity and maintainability chore(tool_configs.py): update tool imports to reflect changes in write_file functionality refactor(agent.py): enhance LLM initialization to include temperature and improve error handling feat(memory.py): normalize file paths in emit_related_files to prevent duplicates feat(programmer.py): add get_aider_executable function to retrieve the aider executable path test: add comprehensive tests for new features and refactor existing tests for clarity and coverage
This commit is contained in:
Ariel Frischer
commit
6970a885e4
41
CHANGELOG.md
41
CHANGELOG.md
|
|
@ -5,6 +5,47 @@ All notable changes to this project will be documented in this file.
|
|||
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
|
||||
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
|
||||
|
||||
## [0.14.1] - 2025-02-13
|
||||
|
||||
### Added
|
||||
- Added expected_runtime_seconds parameter for shell commands with graceful process shutdown
|
||||
- Added config printing at startup (#88)
|
||||
|
||||
### Changed
|
||||
- Enforce byte limit in interactive commands
|
||||
- Normalize/dedupe related file paths
|
||||
- Relax aider version requirement for SWE-bench compatibility
|
||||
- Upgrade langchain/langgraph dependencies
|
||||
|
||||
### Fixed
|
||||
- Fixed aider flags (#89)
|
||||
- Fixed write_file_tool references
|
||||
|
||||
## [0.14.0] - 2025-02-12
|
||||
|
||||
### Added
|
||||
- Status panel showing tool/LLM status and outputs
|
||||
- Automatic detection of OpenAI expert models
|
||||
- Timeouts on LLM clients
|
||||
|
||||
### Changed
|
||||
- Improved interactive TTY process capture and history handling
|
||||
- Upgraded langgraph dependencies
|
||||
- Improved prompts and work logging
|
||||
- Refined token/bytes ratio handling
|
||||
- Support default temperature on per-model basis
|
||||
- Reduced tool count for more reliable tool calling
|
||||
- Updated logo and branding assets
|
||||
- Set environment variables to disable common interactive modes
|
||||
|
||||
### Fixed
|
||||
- Various test fixes
|
||||
- Bug fixes for completion message handling and file content operations
|
||||
- Interactive command input improvements
|
||||
- Use reasoning_effort=high for OpenAI expert models
|
||||
- Do not default to o1 model (#82)
|
||||
- Make current working directory and date available to more agents
|
||||
|
||||
## [0.13.2] - 2025-02-02
|
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|
||||
- Fix temperature parameter error for expert tool.
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
<img src="assets/logo.png" alt="RA.Aid - Develop software autonomously." style="margin-bottom: 20px;">
|
||||
<img src="assets/RA-black-bg.png" alt="RA.Aid - Develop software autonomously." style="margin-bottom: 20px;">
|
||||
|
||||
[](https://www.python.org)
|
||||
[](LICENSE)
|
||||
|
|
|
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@ -0,0 +1,20 @@
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# Dependencies
|
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/node_modules
|
||||
|
||||
# Production
|
||||
/build
|
||||
|
||||
# Generated files
|
||||
.docusaurus
|
||||
.cache-loader
|
||||
|
||||
# Misc
|
||||
.DS_Store
|
||||
.env.local
|
||||
.env.development.local
|
||||
.env.test.local
|
||||
.env.production.local
|
||||
|
||||
npm-debug.log*
|
||||
yarn-debug.log*
|
||||
yarn-error.log*
|
||||
|
|
@ -0,0 +1,41 @@
|
|||
# Website
|
||||
|
||||
This website is built using [Docusaurus](https://docusaurus.io/), a modern static website generator.
|
||||
|
||||
### Installation
|
||||
|
||||
```
|
||||
$ yarn
|
||||
```
|
||||
|
||||
### Local Development
|
||||
|
||||
```
|
||||
$ yarn start
|
||||
```
|
||||
|
||||
This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.
|
||||
|
||||
### Build
|
||||
|
||||
```
|
||||
$ yarn build
|
||||
```
|
||||
|
||||
This command generates static content into the `build` directory and can be served using any static contents hosting service.
|
||||
|
||||
### Deployment
|
||||
|
||||
Using SSH:
|
||||
|
||||
```
|
||||
$ USE_SSH=true yarn deploy
|
||||
```
|
||||
|
||||
Not using SSH:
|
||||
|
||||
```
|
||||
$ GIT_USER=<Your GitHub username> yarn deploy
|
||||
```
|
||||
|
||||
If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the `gh-pages` branch.
|
||||
|
|
@ -0,0 +1 @@
|
|||
---\nsidebar_position: 1\n---\n\n# Getting Started\n\nWelcome to the documentation. This page will help you get started.
|
||||
|
|
@ -0,0 +1,48 @@
|
|||
---
|
||||
sidebar_position: 1
|
||||
slug: /
|
||||
---
|
||||
|
||||
# Intro
|
||||
|
||||
Let's discover **Docusaurus in less than 5 minutes**.
|
||||
|
||||
## Getting Started
|
||||
|
||||
Get started by **creating a new site**.
|
||||
|
||||
Or **try Docusaurus immediately** with **[docusaurus.new](https://docusaurus.new)**.
|
||||
|
||||
### What you'll need
|
||||
|
||||
- [Node.js](https://nodejs.org/en/download/) version 18.0 or above:
|
||||
- When installing Node.js, you are recommended to check all checkboxes related to dependencies.
|
||||
|
||||
## Generate a new site
|
||||
|
||||
Generate a new Docusaurus site using the **classic template**.
|
||||
|
||||
The classic template will automatically be added to your project after you run the command:
|
||||
|
||||
```bash
|
||||
npm init docusaurus@latest my-website classic
|
||||
```
|
||||
|
||||
You can type this command into Command Prompt, Powershell, Terminal, or any other integrated terminal of your code editor.
|
||||
|
||||
The command also installs all necessary dependencies you need to run Docusaurus.
|
||||
|
||||
## Start your site
|
||||
|
||||
Run the development server:
|
||||
|
||||
```bash
|
||||
cd my-website
|
||||
npm run start
|
||||
```
|
||||
|
||||
The `cd` command changes the directory you're working with. In order to work with your newly created Docusaurus site, you'll need to navigate the terminal there.
|
||||
|
||||
The `npm run start` command builds your website locally and serves it through a development server, ready for you to view at http://localhost:3000/.
|
||||
|
||||
Open `docs/intro.md` (this page) and edit some lines: the site **reloads automatically** and displays your changes.
|
||||
|
|
@ -0,0 +1,8 @@
|
|||
{
|
||||
"label": "Quick Starts",
|
||||
"position": 2,
|
||||
"link": {
|
||||
"type": "generated-index",
|
||||
"description": "5 minutes to learn the most important Docusaurus concepts."
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,23 @@
|
|||
---
|
||||
sidebar_position: 6
|
||||
---
|
||||
|
||||
# Congratulations!
|
||||
|
||||
You have just learned the **basics of Docusaurus** and made some changes to the **initial template**.
|
||||
|
||||
Docusaurus has **much more to offer**!
|
||||
|
||||
Have **5 more minutes**? Take a look at **[versioning](../tutorial-extras/manage-docs-versions.md)** and **[i18n](../tutorial-extras/translate-your-site.md)**.
|
||||
|
||||
Anything **unclear** or **buggy** in this tutorial? [Please report it!](https://github.com/facebook/docusaurus/discussions/4610)
|
||||
|
||||
## What's next?
|
||||
|
||||
- Read the [official documentation](https://docusaurus.io/)
|
||||
- Modify your site configuration with [`docusaurus.config.js`](https://docusaurus.io/docs/api/docusaurus-config)
|
||||
- Add navbar and footer items with [`themeConfig`](https://docusaurus.io/docs/api/themes/configuration)
|
||||
- Add a custom [Design and Layout](https://docusaurus.io/docs/styling-layout)
|
||||
- Add a [search bar](https://docusaurus.io/docs/search)
|
||||
- Find inspirations in the [Docusaurus showcase](https://docusaurus.io/showcase)
|
||||
- Get involved in the [Docusaurus Community](https://docusaurus.io/community/support)
|
||||
|
|
@ -0,0 +1,34 @@
|
|||
---
|
||||
sidebar_position: 3
|
||||
---
|
||||
|
||||
# Create a Blog Post
|
||||
|
||||
Docusaurus creates a **page for each blog post**, but also a **blog index page**, a **tag system**, an **RSS** feed...
|
||||
|
||||
## Create your first Post
|
||||
|
||||
Create a file at `blog/2021-02-28-greetings.md`:
|
||||
|
||||
```md title="blog/2021-02-28-greetings.md"
|
||||
---
|
||||
slug: greetings
|
||||
title: Greetings!
|
||||
authors:
|
||||
- name: Joel Marcey
|
||||
title: Co-creator of Docusaurus 1
|
||||
url: https://github.com/JoelMarcey
|
||||
image_url: https://github.com/JoelMarcey.png
|
||||
- name: Sébastien Lorber
|
||||
title: Docusaurus maintainer
|
||||
url: https://sebastienlorber.com
|
||||
image_url: https://github.com/slorber.png
|
||||
tags: [greetings]
|
||||
---
|
||||
|
||||
Congratulations, you have made your first post!
|
||||
|
||||
Feel free to play around and edit this post as much as you like.
|
||||
```
|
||||
|
||||
A new blog post is now available at [http://localhost:3000/blog/greetings](http://localhost:3000/blog/greetings).
|
||||
|
|
@ -0,0 +1,57 @@
|
|||
---
|
||||
sidebar_position: 2
|
||||
---
|
||||
|
||||
# Create a Document
|
||||
|
||||
Documents are **groups of pages** connected through:
|
||||
|
||||
- a **sidebar**
|
||||
- **previous/next navigation**
|
||||
- **versioning**
|
||||
|
||||
## Create your first Doc
|
||||
|
||||
Create a Markdown file at `docs/hello.md`:
|
||||
|
||||
```md title="docs/hello.md"
|
||||
# Hello
|
||||
|
||||
This is my **first Docusaurus document**!
|
||||
```
|
||||
|
||||
A new document is now available at [http://localhost:3000/docs/hello](http://localhost:3000/docs/hello).
|
||||
|
||||
## Configure the Sidebar
|
||||
|
||||
Docusaurus automatically **creates a sidebar** from the `docs` folder.
|
||||
|
||||
Add metadata to customize the sidebar label and position:
|
||||
|
||||
```md title="docs/hello.md" {1-4}
|
||||
---
|
||||
sidebar_label: 'Hi!'
|
||||
sidebar_position: 3
|
||||
---
|
||||
|
||||
# Hello
|
||||
|
||||
This is my **first Docusaurus document**!
|
||||
```
|
||||
|
||||
It is also possible to create your sidebar explicitly in `sidebars.js`:
|
||||
|
||||
```js title="sidebars.js"
|
||||
export default {
|
||||
tutorialSidebar: [
|
||||
'intro',
|
||||
// highlight-next-line
|
||||
'hello',
|
||||
{
|
||||
type: 'category',
|
||||
label: 'Tutorial',
|
||||
items: ['quickstarts/create-a-document'],
|
||||
},
|
||||
],
|
||||
};
|
||||
```
|
||||
|
|
@ -0,0 +1,31 @@
|
|||
---
|
||||
sidebar_position: 5
|
||||
---
|
||||
|
||||
# Deploy your site
|
||||
|
||||
Docusaurus is a **static-site-generator** (also called **[Jamstack](https://jamstack.org/)**).
|
||||
|
||||
It builds your site as simple **static HTML, JavaScript and CSS files**.
|
||||
|
||||
## Build your site
|
||||
|
||||
Build your site **for production**:
|
||||
|
||||
```bash
|
||||
npm run build
|
||||
```
|
||||
|
||||
The static files are generated in the `build` folder.
|
||||
|
||||
## Deploy your site
|
||||
|
||||
Test your production build locally:
|
||||
|
||||
```bash
|
||||
npm run serve
|
||||
```
|
||||
|
||||
The `build` folder is now served at [http://localhost:3000/](http://localhost:3000/).
|
||||
|
||||
You can now deploy the `build` folder **almost anywhere** easily, **for free** or very small cost (read the **[Deployment Guide](https://docusaurus.io/docs/deployment)**).
|
||||
|
|
@ -0,0 +1,14 @@
|
|||
# Installation
|
||||
|
||||
Create a new Python 3.12 virtual environment and install RA.Aid:
|
||||
|
||||
```bash
|
||||
uv venv -p 3.12
|
||||
source .venv/bin/activate # On Unix/macOS
|
||||
# or
|
||||
.venv\Scripts\activate # On Windows
|
||||
|
||||
uv pip install ra-aid
|
||||
```
|
||||
|
||||
Once installed, see the [Recommended Configuration](recommended) to set up RA.Aid with the recommended settings.
|
||||
|
|
@ -0,0 +1,152 @@
|
|||
---
|
||||
sidebar_position: 4
|
||||
---
|
||||
|
||||
# Markdown Features
|
||||
|
||||
Docusaurus supports **[Markdown](https://daringfireball.net/projects/markdown/syntax)** and a few **additional features**.
|
||||
|
||||
## Front Matter
|
||||
|
||||
Markdown documents have metadata at the top called [Front Matter](https://jekyllrb.com/docs/front-matter/):
|
||||
|
||||
```text title="my-doc.md"
|
||||
// highlight-start
|
||||
---
|
||||
id: my-doc-id
|
||||
title: My document title
|
||||
description: My document description
|
||||
slug: /my-custom-url
|
||||
---
|
||||
// highlight-end
|
||||
|
||||
## Markdown heading
|
||||
|
||||
Markdown text with [links](./hello.md)
|
||||
```
|
||||
|
||||
## Links
|
||||
|
||||
Regular Markdown links are supported, using url paths or relative file paths.
|
||||
|
||||
```md
|
||||
Let's see how to [Create a page](/recommended).
|
||||
```
|
||||
|
||||
```md
|
||||
Let's see how to [Create a page](./recommended.md).
|
||||
```
|
||||
|
||||
**Result:** Let's see how to [Create a page](./recommended.md).
|
||||
|
||||
## Images
|
||||
|
||||
Regular Markdown images are supported.
|
||||
|
||||
You can use absolute paths to reference images in the static directory (`static/img/docusaurus.png`):
|
||||
|
||||
```md
|
||||
|
||||
```
|
||||
|
||||
|
||||
|
||||
You can reference images relative to the current file as well. This is particularly useful to colocate images close to the Markdown files using them:
|
||||
|
||||
```md
|
||||
|
||||
```
|
||||
|
||||
## Code Blocks
|
||||
|
||||
Markdown code blocks are supported with Syntax highlighting.
|
||||
|
||||
````md
|
||||
```jsx title="src/components/HelloDocusaurus.js"
|
||||
function HelloDocusaurus() {
|
||||
return <h1>Hello, Docusaurus!</h1>;
|
||||
}
|
||||
```
|
||||
````
|
||||
|
||||
```jsx title="src/components/HelloDocusaurus.js"
|
||||
function HelloDocusaurus() {
|
||||
return <h1>Hello, Docusaurus!</h1>;
|
||||
}
|
||||
```
|
||||
|
||||
## Admonitions
|
||||
|
||||
Docusaurus has a special syntax to create admonitions and callouts:
|
||||
|
||||
```md
|
||||
:::tip My tip
|
||||
|
||||
Use this awesome feature option
|
||||
|
||||
:::
|
||||
|
||||
:::danger Take care
|
||||
|
||||
This action is dangerous
|
||||
|
||||
:::
|
||||
```
|
||||
|
||||
:::tip My tip
|
||||
|
||||
Use this awesome feature option
|
||||
|
||||
:::
|
||||
|
||||
:::danger Take care
|
||||
|
||||
This action is dangerous
|
||||
|
||||
:::
|
||||
|
||||
## MDX and React Components
|
||||
|
||||
[MDX](https://mdxjs.com/) can make your documentation more **interactive** and allows using any **React components inside Markdown**:
|
||||
|
||||
```jsx
|
||||
export const Highlight = ({children, color}) => (
|
||||
<span
|
||||
style={{
|
||||
backgroundColor: color,
|
||||
borderRadius: '20px',
|
||||
color: '#fff',
|
||||
padding: '10px',
|
||||
cursor: 'pointer',
|
||||
}}
|
||||
onClick={() => {
|
||||
alert(`You clicked the color ${color} with label ${children}`)
|
||||
}}>
|
||||
{children}
|
||||
</span>
|
||||
);
|
||||
|
||||
This is <Highlight color="#25c2a0">Docusaurus green</Highlight> !
|
||||
|
||||
This is <Highlight color="#1877F2">Facebook blue</Highlight> !
|
||||
```
|
||||
|
||||
export const Highlight = ({children, color}) => (
|
||||
<span
|
||||
style={{
|
||||
backgroundColor: color,
|
||||
borderRadius: '20px',
|
||||
color: '#fff',
|
||||
padding: '10px',
|
||||
cursor: 'pointer',
|
||||
}}
|
||||
onClick={() => {
|
||||
alert(`You clicked the color ${color} with label ${children}`);
|
||||
}}>
|
||||
{children}
|
||||
</span>
|
||||
);
|
||||
|
||||
This is <Highlight color="#25c2a0">Docusaurus green</Highlight> !
|
||||
|
||||
This is <Highlight color="#1877F2">Facebook blue</Highlight> !
|
||||
|
|
@ -0,0 +1,52 @@
|
|||
# Recommended Config
|
||||
|
||||
This configuration combines the strengths of multiple AI models to provide the best experience:
|
||||
|
||||
- Anthropic Sonnet excels at driving the agent's core reasoning and planning
|
||||
- OpenAI's models provide robust debugging and logical analysis capabilities
|
||||
- Tavily web search integration allows the agent to find relevant information online
|
||||
|
||||
:::info
|
||||
RA.Aid must be installed before using these configurations. If you haven't installed it yet, please see the [Installation Guide](installation).
|
||||
:::
|
||||
|
||||
## Getting API Keys
|
||||
|
||||
To use RA.Aid with the recommended configuration, you'll need to obtain API keys from the following services:
|
||||
|
||||
1. **OpenAI API Key**: Create an account at [OpenAI's platform](https://platform.openai.com) and generate an API key from your dashboard.
|
||||
|
||||
2. **Anthropic API Key**: Sign up at [Anthropic's Console](https://console.anthropic.com), then generate an API key from the API Keys section.
|
||||
|
||||
3. **Tavily API Key** (optional): Create an account at [Tavily](https://app.tavily.com/sign-in) and get your API key from the dashboard.
|
||||
|
||||
Please keep your API keys secure and never share them publicly. Each service has its own pricing and usage terms.
|
||||
|
||||
## Configuration
|
||||
|
||||
Configure your API keys:
|
||||
|
||||
```bash
|
||||
# For OpenAI (required)
|
||||
export OPENAI_API_KEY=your_api_key_here
|
||||
|
||||
# For Anthropic (required)
|
||||
export ANTHROPIC_API_KEY=your_api_key_here
|
||||
|
||||
# For web search capability (optional)
|
||||
export TAVILY_API_KEY=your_api_key_here
|
||||
```
|
||||
|
||||
## Basic Usage
|
||||
|
||||
Start RA.Aid in interactive chat mode:
|
||||
|
||||
```bash
|
||||
ra-aid --chat
|
||||
```
|
||||
|
||||
Or run with a single command:
|
||||
|
||||
```bash
|
||||
ra-aid -m "Help me understand this code"
|
||||
```
|
||||
|
|
@ -0,0 +1,7 @@
|
|||
{
|
||||
"label": "Tutorial - Extras",
|
||||
"position": 3,
|
||||
"link": {
|
||||
"type": "generated-index"
|
||||
}
|
||||
}
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 25 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 27 KiB |
|
|
@ -0,0 +1,55 @@
|
|||
---
|
||||
sidebar_position: 1
|
||||
---
|
||||
|
||||
# Manage Docs Versions
|
||||
|
||||
Docusaurus can manage multiple versions of your docs.
|
||||
|
||||
## Create a docs version
|
||||
|
||||
Release a version 1.0 of your project:
|
||||
|
||||
```bash
|
||||
npm run docusaurus docs:version 1.0
|
||||
```
|
||||
|
||||
The `docs` folder is copied into `versioned_docs/version-1.0` and `versions.json` is created.
|
||||
|
||||
Your docs now have 2 versions:
|
||||
|
||||
- `1.0` at `http://localhost:3000/docs/` for the version 1.0 docs
|
||||
- `current` at `http://localhost:3000/docs/next/` for the **upcoming, unreleased docs**
|
||||
|
||||
## Add a Version Dropdown
|
||||
|
||||
To navigate seamlessly across versions, add a version dropdown.
|
||||
|
||||
Modify the `docusaurus.config.js` file:
|
||||
|
||||
```js title="docusaurus.config.js"
|
||||
export default {
|
||||
themeConfig: {
|
||||
navbar: {
|
||||
items: [
|
||||
// highlight-start
|
||||
{
|
||||
type: 'docsVersionDropdown',
|
||||
},
|
||||
// highlight-end
|
||||
],
|
||||
},
|
||||
},
|
||||
};
|
||||
```
|
||||
|
||||
The docs version dropdown appears in your navbar:
|
||||
|
||||
|
||||
|
||||
## Update an existing version
|
||||
|
||||
It is possible to edit versioned docs in their respective folder:
|
||||
|
||||
- `versioned_docs/version-1.0/hello.md` updates `http://localhost:3000/docs/hello`
|
||||
- `docs/hello.md` updates `http://localhost:3000/docs/next/hello`
|
||||
|
|
@ -0,0 +1,88 @@
|
|||
---
|
||||
sidebar_position: 2
|
||||
---
|
||||
|
||||
# Translate your site
|
||||
|
||||
Let's translate `docs/intro.md` to French.
|
||||
|
||||
## Configure i18n
|
||||
|
||||
Modify `docusaurus.config.js` to add support for the `fr` locale:
|
||||
|
||||
```js title="docusaurus.config.js"
|
||||
export default {
|
||||
i18n: {
|
||||
defaultLocale: 'en',
|
||||
locales: ['en', 'fr'],
|
||||
},
|
||||
};
|
||||
```
|
||||
|
||||
## Translate a doc
|
||||
|
||||
Copy the `docs/intro.md` file to the `i18n/fr` folder:
|
||||
|
||||
```bash
|
||||
mkdir -p i18n/fr/docusaurus-plugin-content-docs/current/
|
||||
|
||||
cp docs/intro.md i18n/fr/docusaurus-plugin-content-docs/current/intro.md
|
||||
```
|
||||
|
||||
Translate `i18n/fr/docusaurus-plugin-content-docs/current/intro.md` in French.
|
||||
|
||||
## Start your localized site
|
||||
|
||||
Start your site on the French locale:
|
||||
|
||||
```bash
|
||||
npm run start -- --locale fr
|
||||
```
|
||||
|
||||
Your localized site is accessible at [http://localhost:3000/fr/](http://localhost:3000/fr/) and the `Getting Started` page is translated.
|
||||
|
||||
:::caution
|
||||
|
||||
In development, you can only use one locale at a time.
|
||||
|
||||
:::
|
||||
|
||||
## Add a Locale Dropdown
|
||||
|
||||
To navigate seamlessly across languages, add a locale dropdown.
|
||||
|
||||
Modify the `docusaurus.config.js` file:
|
||||
|
||||
```js title="docusaurus.config.js"
|
||||
export default {
|
||||
themeConfig: {
|
||||
navbar: {
|
||||
items: [
|
||||
// highlight-start
|
||||
{
|
||||
type: 'localeDropdown',
|
||||
},
|
||||
// highlight-end
|
||||
],
|
||||
},
|
||||
},
|
||||
};
|
||||
```
|
||||
|
||||
The locale dropdown now appears in your navbar:
|
||||
|
||||
|
||||
|
||||
## Build your localized site
|
||||
|
||||
Build your site for a specific locale:
|
||||
|
||||
```bash
|
||||
npm run build -- --locale fr
|
||||
```
|
||||
|
||||
Or build your site to include all the locales at once:
|
||||
|
||||
```bash
|
||||
npm run build
|
||||
```
|
||||
|
|
@ -0,0 +1,72 @@
|
|||
import {themes as prismThemes} from 'prism-react-renderer';
|
||||
import type {Config} from '@docusaurus/types';
|
||||
import type * as Preset from '@docusaurus/preset-classic';
|
||||
|
||||
const config: Config = {
|
||||
title: 'RA-Aid Documentation',
|
||||
favicon: 'img/favicon.ico',
|
||||
url: 'https://ra-aid.0.dev',
|
||||
baseUrl: '/',
|
||||
|
||||
onDuplicateRoutes: 'ignore',
|
||||
onBrokenLinks: 'throw',
|
||||
onBrokenMarkdownLinks: 'warn',
|
||||
|
||||
i18n: {
|
||||
defaultLocale: 'en',
|
||||
locales: ['en'],
|
||||
},
|
||||
|
||||
presets: [
|
||||
[
|
||||
'classic',
|
||||
{
|
||||
docs: {
|
||||
sidebarPath: './sidebars.ts',
|
||||
routeBasePath: '/',
|
||||
},
|
||||
theme: {
|
||||
customCss: './src/css/custom.css',
|
||||
},
|
||||
} satisfies Preset.Options,
|
||||
],
|
||||
],
|
||||
|
||||
themeConfig: {
|
||||
navbar: {
|
||||
logo: {
|
||||
alt: 'Site Logo',
|
||||
src: 'img/logo-black-transparent.png',
|
||||
srcDark: 'img/logo-white-transparent.gif',
|
||||
href: 'https://ra-aid.ai'
|
||||
},
|
||||
items: [
|
||||
{
|
||||
type: 'doc',
|
||||
position: 'left',
|
||||
docId: 'intro',
|
||||
label: 'Docs',
|
||||
},
|
||||
{
|
||||
href: 'https://github.com/smallcloudai/refact-aide',
|
||||
label: 'GitHub',
|
||||
position: 'right',
|
||||
},
|
||||
],
|
||||
},
|
||||
footer: {
|
||||
style: 'dark',
|
||||
copyright: `Copyright © ${new Date().getFullYear()} My Project, Inc. Built with Docusaurus.`,
|
||||
},
|
||||
prism: {
|
||||
theme: prismThemes.github,
|
||||
darkTheme: prismThemes.dracula,
|
||||
},
|
||||
colorMode: {
|
||||
defaultMode: 'dark',
|
||||
respectPrefersColorScheme: false,
|
||||
},
|
||||
} satisfies Preset.ThemeConfig,
|
||||
};
|
||||
|
||||
export default config;
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,47 @@
|
|||
{
|
||||
"name": "docs",
|
||||
"version": "0.0.0",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"docusaurus": "docusaurus",
|
||||
"start": "docusaurus start",
|
||||
"build": "docusaurus build",
|
||||
"swizzle": "docusaurus swizzle",
|
||||
"deploy": "docusaurus deploy",
|
||||
"clear": "docusaurus clear",
|
||||
"serve": "docusaurus serve",
|
||||
"write-translations": "docusaurus write-translations",
|
||||
"write-heading-ids": "docusaurus write-heading-ids",
|
||||
"typecheck": "tsc"
|
||||
},
|
||||
"dependencies": {
|
||||
"@docusaurus/core": "3.7.0",
|
||||
"@docusaurus/preset-classic": "3.7.0",
|
||||
"@mdx-js/react": "^3.0.0",
|
||||
"clsx": "^2.0.0",
|
||||
"prism-react-renderer": "^2.3.0",
|
||||
"react": "^19.0.0",
|
||||
"react-dom": "^19.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@docusaurus/module-type-aliases": "3.7.0",
|
||||
"@docusaurus/tsconfig": "3.7.0",
|
||||
"@docusaurus/types": "3.7.0",
|
||||
"typescript": "~5.6.2"
|
||||
},
|
||||
"browserslist": {
|
||||
"production": [
|
||||
">0.5%",
|
||||
"not dead",
|
||||
"not op_mini all"
|
||||
],
|
||||
"development": [
|
||||
"last 3 chrome version",
|
||||
"last 3 firefox version",
|
||||
"last 5 safari version"
|
||||
]
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=18.0"
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,33 @@
|
|||
import type {SidebarsConfig} from '@docusaurus/plugin-content-docs';
|
||||
|
||||
// This runs in Node.js - Don't use client-side code here (browser APIs, JSX...)
|
||||
|
||||
/**
|
||||
* Creating a sidebar enables you to:
|
||||
- create an ordered group of docs
|
||||
- render a sidebar for each doc of that group
|
||||
- provide next/previous navigation
|
||||
|
||||
The sidebars can be generated from the filesystem, or explicitly defined here.
|
||||
|
||||
Create as many sidebars as you want.
|
||||
*/
|
||||
const sidebars: SidebarsConfig = {
|
||||
// By default, Docusaurus generates a sidebar from the docs folder structure
|
||||
tutorialSidebar: [{type: 'autogenerated', dirName: '.'}],
|
||||
|
||||
// But you can create a sidebar manually
|
||||
/*
|
||||
tutorialSidebar: [
|
||||
'intro',
|
||||
'hello',
|
||||
{
|
||||
type: 'category',
|
||||
label: 'Tutorial',
|
||||
items: ['quickstarts/create-a-document'],
|
||||
},
|
||||
],
|
||||
*/
|
||||
};
|
||||
|
||||
export default sidebars;
|
||||
|
|
@ -0,0 +1,71 @@
|
|||
import type {ReactNode} from 'react';
|
||||
import clsx from 'clsx';
|
||||
import Heading from '@theme/Heading';
|
||||
import styles from './styles.module.css';
|
||||
|
||||
type FeatureItem = {
|
||||
title: string;
|
||||
Svg: React.ComponentType<React.ComponentProps<'svg'>>;
|
||||
description: ReactNode;
|
||||
};
|
||||
|
||||
const FeatureList: FeatureItem[] = [
|
||||
{
|
||||
title: 'Easy to Use',
|
||||
Svg: require('@site/static/img/undraw_docusaurus_mountain.svg').default,
|
||||
description: (
|
||||
<>
|
||||
Docusaurus was designed from the ground up to be easily installed and
|
||||
used to get your website up and running quickly.
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
title: 'Focus on What Matters',
|
||||
Svg: require('@site/static/img/undraw_docusaurus_tree.svg').default,
|
||||
description: (
|
||||
<>
|
||||
Docusaurus lets you focus on your docs, and we'll do the chores. Go
|
||||
ahead and move your docs into the <code>docs</code> directory.
|
||||
</>
|
||||
),
|
||||
},
|
||||
{
|
||||
title: 'Powered by React',
|
||||
Svg: require('@site/static/img/undraw_docusaurus_react.svg').default,
|
||||
description: (
|
||||
<>
|
||||
Extend or customize your website layout by reusing React. Docusaurus can
|
||||
be extended while reusing the same header and footer.
|
||||
</>
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
function Feature({title, Svg, description}: FeatureItem) {
|
||||
return (
|
||||
<div className={clsx('col col--4')}>
|
||||
<div className="text--center">
|
||||
<Svg className={styles.featureSvg} role="img" />
|
||||
</div>
|
||||
<div className="text--center padding-horiz--md">
|
||||
<Heading as="h3">{title}</Heading>
|
||||
<p>{description}</p>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
export default function HomepageFeatures(): ReactNode {
|
||||
return (
|
||||
<section className={styles.features}>
|
||||
<div className="container">
|
||||
<div className="row">
|
||||
{FeatureList.map((props, idx) => (
|
||||
<Feature key={idx} {...props} />
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
);
|
||||
}
|
||||
|
|
@ -0,0 +1,11 @@
|
|||
.features {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
padding: 2rem 0;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.featureSvg {
|
||||
height: 200px;
|
||||
width: 200px;
|
||||
}
|
||||
|
|
@ -0,0 +1,30 @@
|
|||
/**
|
||||
* Any CSS included here will be global. The classic template
|
||||
* bundles Infima by default. Infima is a CSS framework designed to
|
||||
* work well for content-centric websites.
|
||||
*/
|
||||
|
||||
/* You can override the default Infima variables here. */
|
||||
:root {
|
||||
--ifm-color-primary: #2e8555;
|
||||
--ifm-color-primary-dark: #29784c;
|
||||
--ifm-color-primary-darker: #277148;
|
||||
--ifm-color-primary-darkest: #205d3b;
|
||||
--ifm-color-primary-light: #33925d;
|
||||
--ifm-color-primary-lighter: #359962;
|
||||
--ifm-color-primary-lightest: #3cad6e;
|
||||
--ifm-code-font-size: 95%;
|
||||
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.1);
|
||||
}
|
||||
|
||||
/* For readability concerns, you should choose a lighter palette in dark mode. */
|
||||
[data-theme='dark'] {
|
||||
--ifm-color-primary: #25c2a0;
|
||||
--ifm-color-primary-dark: #21af90;
|
||||
--ifm-color-primary-darker: #1fa588;
|
||||
--ifm-color-primary-darkest: #1a8870;
|
||||
--ifm-color-primary-light: #29d5b0;
|
||||
--ifm-color-primary-lighter: #32d8b4;
|
||||
--ifm-color-primary-lightest: #4fddbf;
|
||||
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.3);
|
||||
}
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 54 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.0 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 3.5 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 23 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 25 KiB |
File diff suppressed because one or more lines are too long
|
After Width: | Height: | Size: 6.3 KiB |
|
|
@ -0,0 +1,171 @@
|
|||
<svg xmlns="http://www.w3.org/2000/svg" width="1088" height="687.962" viewBox="0 0 1088 687.962">
|
||||
<title>Easy to Use</title>
|
||||
<g id="Group_12" data-name="Group 12" transform="translate(-57 -56)">
|
||||
<g id="Group_11" data-name="Group 11" transform="translate(57 56)">
|
||||
<path id="Path_83" data-name="Path 83" d="M1017.81,560.461c-5.27,45.15-16.22,81.4-31.25,110.31-20,38.52-54.21,54.04-84.77,70.28a193.275,193.275,0,0,1-27.46,11.94c-55.61,19.3-117.85,14.18-166.74,3.99a657.282,657.282,0,0,0-104.09-13.16q-14.97-.675-29.97-.67c-15.42.02-293.07,5.29-360.67-131.57-16.69-33.76-28.13-75-32.24-125.27-11.63-142.12,52.29-235.46,134.74-296.47,155.97-115.41,369.76-110.57,523.43,7.88C941.15,276.621,1036.99,396.031,1017.81,560.461Z" transform="translate(-56 -106.019)" fill="#3f3d56"/>
|
||||
<path id="Path_84" data-name="Path 84" d="M986.56,670.771c-20,38.52-47.21,64.04-77.77,80.28a193.272,193.272,0,0,1-27.46,11.94c-55.61,19.3-117.85,14.18-166.74,3.99a657.3,657.3,0,0,0-104.09-13.16q-14.97-.675-29.97-.67-23.13.03-46.25,1.72c-100.17,7.36-253.82-6.43-321.42-143.29L382,283.981,444.95,445.6l20.09,51.59,55.37-75.98L549,381.981l130.2,149.27,36.8-81.27L970.78,657.9l14.21,11.59Z" transform="translate(-56 -106.019)" fill="#f2f2f2"/>
|
||||
<path id="Path_85" data-name="Path 85" d="M302,282.962l26-57,36,83-31-60Z" opacity="0.1"/>
|
||||
<path id="Path_86" data-name="Path 86" d="M610.5,753.821q-14.97-.675-29.97-.67L465.04,497.191Z" transform="translate(-56 -106.019)" opacity="0.1"/>
|
||||
<path id="Path_87" data-name="Path 87" d="M464.411,315.191,493,292.962l130,150-132-128Z" opacity="0.1"/>
|
||||
<path id="Path_88" data-name="Path 88" d="M908.79,751.051a193.265,193.265,0,0,1-27.46,11.94L679.2,531.251Z" transform="translate(-56 -106.019)" opacity="0.1"/>
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||||
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||||
<path d="M424.01111,602.10586a6.60242,6.60242,0,0,0-.848.08493c-.05042-.19906-.09821-.39945-.15394-.59852A6.62667,6.62667,0,1,0,416.45211,590.21q-.2203-.22491-.44458-.44589a6.62391,6.62391,0,1,0-11.39689-6.56369c-.1964-.05575-.39413-.10218-.59054-.15262a6.63957,6.63957,0,1,0-13.10084,0c-.19641.05042-.39414.09687-.59055.15262a6.62767,6.62767,0,1,0-11.39689,6.56369,26.52755,26.52755,0,1,0,44.2313,25.52756,6.6211,6.6211,0,1,0,.848-13.18579" transform="translate(-35.5 -118.5)" fill="#44d860" fill-rule="evenodd" />
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||||
<path d="M410.74039,545.70532a3.31768,3.31768,0,1,0,0-6.63536,3.41133,3.41133,0,0,0-.42333.04247c-.02655-.09953-.04911-.19907-.077-.29859a3.319,3.319,0,0,0-1.278-6.37923,3.28174,3.28174,0,0,0-2.00122.68742q-.10947-.11346-.22294-.22295a3.282,3.282,0,0,0,.67149-1.98265,3.31768,3.31768,0,0,0-6.37-1.2992,13.27078,13.27078,0,1,0,0,25.54082,3.31768,3.31768,0,0,0,6.37-1.2992,3.282,3.282,0,0,0-.67149-1.98265q.11347-.10947.22294-.22294a3.28174,3.28174,0,0,0,2.00122.68742,3.31768,3.31768,0,0,0,1.278-6.37923c.02786-.0982.05042-.19907.077-.29859a3.41325,3.41325,0,0,0,.42333.04246" transform="translate(-35.5 -118.5)" fill="#44d860" fill-rule="evenodd" />
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|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 12 KiB |
|
|
@ -0,0 +1,8 @@
|
|||
{
|
||||
// This file is not used in compilation. It is here just for a nice editor experience.
|
||||
"extends": "@docusaurus/tsconfig",
|
||||
"compilerOptions": {
|
||||
"baseUrl": "."
|
||||
},
|
||||
"exclude": [".docusaurus", "build"]
|
||||
}
|
||||
|
|
@ -22,20 +22,21 @@ classifiers = [
|
|||
"Topic :: Software Development :: Libraries :: Python Modules"
|
||||
]
|
||||
dependencies = [
|
||||
"langchain-anthropic>=0.3.1",
|
||||
"langchain-openai",
|
||||
"langchain-google-genai",
|
||||
"langgraph>=0.2.70",
|
||||
"langgraph-checkpoint>=2.0.9",
|
||||
"langgraph-sdk>=0.1.48",
|
||||
"langchain-core>=0.3.34",
|
||||
"langchain-anthropic>=0.3.7",
|
||||
"langchain-openai>=0.3.5",
|
||||
"langchain-google-genai>=2.0.9",
|
||||
"langgraph>=0.2.71",
|
||||
"langgraph-checkpoint>=2.0.12",
|
||||
"langgraph-sdk>=0.1.51",
|
||||
"langchain-core>=0.3.35",
|
||||
"langchain>=0.3.18",
|
||||
"rich>=13.0.0",
|
||||
"GitPython>=3.1",
|
||||
"fuzzywuzzy==0.18.0",
|
||||
"rapidfuzz>=3.11.0",
|
||||
"pathspec>=0.11.0",
|
||||
"aider-chat>=0.73.0",
|
||||
"pyte>=0.8.2",
|
||||
"aider-chat>=0.72.0",
|
||||
"tavily-python>=0.5.0",
|
||||
"litellm",
|
||||
"fastapi>=0.104.0",
|
||||
|
|
|
|||
|
|
@ -7,6 +7,7 @@ from datetime import datetime
|
|||
from langgraph.checkpoint.memory import MemorySaver
|
||||
from rich.console import Console
|
||||
from rich.panel import Panel
|
||||
from rich.text import Text
|
||||
|
||||
from ra_aid import print_error, print_stage_header
|
||||
from ra_aid.__version__ import __version__
|
||||
|
|
@ -113,9 +114,9 @@ Examples:
|
|||
parser.add_argument(
|
||||
"--expert-provider",
|
||||
type=str,
|
||||
default="openai",
|
||||
default=None,
|
||||
choices=VALID_PROVIDERS,
|
||||
help="The LLM provider to use for expert knowledge queries (default: openai)",
|
||||
help="The LLM provider to use for expert knowledge queries",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--expert-model",
|
||||
|
|
@ -234,10 +235,18 @@ Examples:
|
|||
|
||||
# Handle expert provider/model defaults
|
||||
if not parsed_args.expert_provider:
|
||||
# If no expert provider specified, use main provider instead of defaulting to
|
||||
# to any particular model since we do not know if we have access to any other model.
|
||||
parsed_args.expert_provider = parsed_args.provider
|
||||
parsed_args.expert_model = parsed_args.model
|
||||
# Check for OpenAI API key first
|
||||
if os.environ.get("OPENAI_API_KEY"):
|
||||
parsed_args.expert_provider = "openai"
|
||||
parsed_args.expert_model = None # Will be auto-selected
|
||||
# If no OpenAI key but DeepSeek key exists, use DeepSeek
|
||||
elif os.environ.get("DEEPSEEK_API_KEY"):
|
||||
parsed_args.expert_provider = "deepseek"
|
||||
parsed_args.expert_model = "deepseek-reasoner"
|
||||
else:
|
||||
# Fall back to main provider if neither is available
|
||||
parsed_args.expert_provider = parsed_args.provider
|
||||
parsed_args.expert_model = parsed_args.model
|
||||
|
||||
# Validate temperature range if provided
|
||||
if parsed_args.temperature is not None and not (
|
||||
|
|
@ -299,27 +308,55 @@ def main():
|
|||
) # Will exit if main env vars missing
|
||||
logger.debug("Environment validation successful")
|
||||
|
||||
if expert_missing:
|
||||
console.print(
|
||||
Panel(
|
||||
"[yellow]Expert tools disabled due to missing configuration:[/yellow]\n"
|
||||
+ "\n".join(f"- {m}" for m in expert_missing)
|
||||
+ "\nSet the required environment variables or args to enable expert mode.",
|
||||
title="Expert Tools Disabled",
|
||||
style="yellow",
|
||||
# Validate model configuration early
|
||||
from ra_aid.models_params import models_params
|
||||
|
||||
model_config = models_params.get(args.provider, {}).get(args.model or "", {})
|
||||
supports_temperature = model_config.get(
|
||||
"supports_temperature",
|
||||
args.provider
|
||||
in ["anthropic", "openai", "openrouter", "openai-compatible", "deepseek"],
|
||||
)
|
||||
|
||||
if supports_temperature and args.temperature is None:
|
||||
args.temperature = model_config.get("default_temperature")
|
||||
if args.temperature is None:
|
||||
print_error(
|
||||
f"Temperature must be provided for model {args.model} which supports temperature"
|
||||
)
|
||||
sys.exit(1)
|
||||
logger.debug(
|
||||
f"Using default temperature {args.temperature} for model {args.model}"
|
||||
)
|
||||
|
||||
if web_research_missing:
|
||||
console.print(
|
||||
Panel(
|
||||
"[yellow]Web research disabled due to missing configuration:[/yellow]\n"
|
||||
+ "\n".join(f"- {m}" for m in web_research_missing)
|
||||
+ "\nSet the required environment variables to enable web research.",
|
||||
title="Web Research Disabled",
|
||||
style="yellow",
|
||||
)
|
||||
)
|
||||
# Display status lines
|
||||
status = Text()
|
||||
# Model info
|
||||
status.append("🤖 ")
|
||||
status.append(f"{args.provider}/{args.model}")
|
||||
if args.temperature is not None:
|
||||
status.append(f" @ T{args.temperature}")
|
||||
status.append("\n")
|
||||
|
||||
# Expert info
|
||||
status.append("🤔 ")
|
||||
if expert_enabled:
|
||||
status.append(f"{args.expert_provider}/{args.expert_model}")
|
||||
else:
|
||||
status.append("Expert: ")
|
||||
status.append("Disabled", style="italic")
|
||||
status.append("\n")
|
||||
|
||||
# Search info
|
||||
status.append("🔍 Search: ")
|
||||
status.append(
|
||||
"Enabled" if web_research_enabled else "Disabled",
|
||||
style=None if web_research_enabled else "italic",
|
||||
)
|
||||
|
||||
console.print(
|
||||
Panel(status, title="Config", border_style="bright_blue", padding=(0, 1))
|
||||
)
|
||||
|
||||
# Handle chat mode
|
||||
if args.chat:
|
||||
|
|
@ -368,6 +405,7 @@ def main():
|
|||
_global_memory["config"]["model"] = args.model
|
||||
_global_memory["config"]["expert_provider"] = args.expert_provider
|
||||
_global_memory["config"]["expert_model"] = args.expert_model
|
||||
_global_memory["config"]["temperature"] = args.temperature
|
||||
|
||||
# Create chat agent with appropriate tools
|
||||
chat_agent = create_agent(
|
||||
|
|
@ -442,6 +480,8 @@ def main():
|
|||
|
||||
# Store fallback tool configuration
|
||||
_global_memory["config"]["no_fallback_tool"] = args.no_fallback_tool
|
||||
# Store temperature in global config
|
||||
_global_memory["config"]["temperature"] = args.temperature
|
||||
|
||||
# Run research stage
|
||||
print_stage_header("Research Stage")
|
||||
|
|
|
|||
|
|
@ -1,3 +1,3 @@
|
|||
"""Version information."""
|
||||
|
||||
__version__ = "0.13.2"
|
||||
__version__ = "0.14.1"
|
||||
|
|
|
|||
|
|
@ -10,8 +10,8 @@ from langchain_openai import ChatOpenAI
|
|||
class ChatDeepseekReasoner(ChatOpenAI):
|
||||
"""ChatDeepseekReasoner with custom overrides for R1/reasoner models."""
|
||||
|
||||
def __init__(self, *args, **kwargs):
|
||||
super().__init__(*args, **kwargs)
|
||||
def __init__(self, *args, timeout: int = 180, max_retries: int = 5, **kwargs):
|
||||
super().__init__(*args, timeout=timeout, max_retries=max_retries, **kwargs)
|
||||
|
||||
def invocation_params(
|
||||
self, options: Optional[Dict[str, Any]] = None, **kwargs: Any
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
"""Module for efficient file listing using git."""
|
||||
|
||||
import os
|
||||
import subprocess
|
||||
from pathlib import Path
|
||||
from typing import List, Optional, Tuple
|
||||
|
|
@ -70,7 +71,7 @@ def is_git_repo(directory: str) -> bool:
|
|||
|
||||
|
||||
def get_file_listing(
|
||||
directory: str, limit: Optional[int] = None
|
||||
directory: str, limit: Optional[int] = None, include_hidden: bool = False
|
||||
) -> Tuple[List[str], int]:
|
||||
"""
|
||||
Get a list of tracked files in a git repository.
|
||||
|
|
@ -82,6 +83,7 @@ def get_file_listing(
|
|||
Args:
|
||||
directory: Path to the git repository
|
||||
limit: Optional maximum number of files to return
|
||||
include_hidden: Whether to include hidden files (starting with .) in the results
|
||||
|
||||
Returns:
|
||||
Tuple[List[str], int]: Tuple containing:
|
||||
|
|
@ -95,42 +97,72 @@ def get_file_listing(
|
|||
FileListerError: For other unexpected errors
|
||||
"""
|
||||
try:
|
||||
# Check if directory is a git repo first
|
||||
# Check if directory exists and is accessible
|
||||
if not os.path.exists(directory):
|
||||
raise DirectoryNotFoundError(f"Directory not found: {directory}")
|
||||
if not os.path.isdir(directory):
|
||||
raise DirectoryNotFoundError(f"Not a directory: {directory}")
|
||||
|
||||
# Check if it's a git repository
|
||||
if not is_git_repo(directory):
|
||||
return [], 0
|
||||
|
||||
# Run git ls-files
|
||||
result = subprocess.run(
|
||||
["git", "ls-files"],
|
||||
cwd=directory,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=True,
|
||||
)
|
||||
# Get list of files from git ls-files
|
||||
try:
|
||||
# Get both tracked and untracked files
|
||||
tracked_files_process = subprocess.run(
|
||||
["git", "ls-files"],
|
||||
cwd=directory,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=True,
|
||||
)
|
||||
untracked_files_process = subprocess.run(
|
||||
["git", "ls-files", "--others", "--exclude-standard"],
|
||||
cwd=directory,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=True,
|
||||
)
|
||||
except subprocess.CalledProcessError as e:
|
||||
raise GitCommandError(f"Git command failed: {e}")
|
||||
except PermissionError as e:
|
||||
raise DirectoryAccessError(f"Permission denied: {e}")
|
||||
|
||||
# Process the output
|
||||
files = [line.strip() for line in result.stdout.splitlines() if line.strip()]
|
||||
# Combine and process the files
|
||||
all_files = []
|
||||
for file in (
|
||||
tracked_files_process.stdout.splitlines()
|
||||
+ untracked_files_process.stdout.splitlines()
|
||||
):
|
||||
file = file.strip()
|
||||
if not file:
|
||||
continue
|
||||
# Skip hidden files unless explicitly included
|
||||
if not include_hidden and (
|
||||
file.startswith(".")
|
||||
or any(part.startswith(".") for part in file.split("/"))
|
||||
):
|
||||
continue
|
||||
# Skip .aider files
|
||||
if ".aider" in file:
|
||||
continue
|
||||
all_files.append(file)
|
||||
|
||||
# Deduplicate and sort for consistency
|
||||
files = list(dict.fromkeys(files)) # Remove duplicates while preserving order
|
||||
# Remove duplicates and sort
|
||||
all_files = sorted(set(all_files))
|
||||
total_count = len(all_files)
|
||||
|
||||
# Sort for consistency
|
||||
files.sort()
|
||||
|
||||
# Get total count before truncation
|
||||
total_count = len(files)
|
||||
|
||||
# Truncate if limit specified
|
||||
# Apply limit if specified
|
||||
if limit is not None:
|
||||
files = files[:limit]
|
||||
all_files = all_files[:limit]
|
||||
|
||||
return files, total_count
|
||||
return all_files, total_count
|
||||
|
||||
except subprocess.CalledProcessError as e:
|
||||
raise GitCommandError(f"Git command failed: {e}")
|
||||
except (DirectoryNotFoundError, DirectoryAccessError, GitCommandError):
|
||||
# Re-raise known exceptions
|
||||
raise
|
||||
except PermissionError as e:
|
||||
raise DirectoryAccessError(f"Cannot access directory {directory}: {e}")
|
||||
raise DirectoryAccessError(f"Permission denied: {e}")
|
||||
except Exception as e:
|
||||
if isinstance(e, FileListerError):
|
||||
raise
|
||||
raise FileListerError(f"Error listing files: {e}")
|
||||
raise FileListerError(f"Unexpected error: {e}")
|
||||
|
|
|
|||
|
|
@ -6,12 +6,57 @@ from langchain_core.language_models import BaseChatModel
|
|||
from langchain_core.messages import BaseMessage
|
||||
from langchain_google_genai import ChatGoogleGenerativeAI
|
||||
from langchain_openai import ChatOpenAI
|
||||
from openai import OpenAI
|
||||
|
||||
from ra_aid.chat_models.deepseek_chat import ChatDeepseekReasoner
|
||||
from ra_aid.logging_config import get_logger
|
||||
|
||||
from .models_params import models_params
|
||||
|
||||
|
||||
def get_available_openai_models() -> List[str]:
|
||||
"""Fetch available OpenAI models using OpenAI client.
|
||||
|
||||
Returns:
|
||||
List of available model names
|
||||
"""
|
||||
try:
|
||||
# Use OpenAI client to fetch models
|
||||
client = OpenAI()
|
||||
models = client.models.list()
|
||||
return [str(model.id) for model in models.data]
|
||||
except Exception:
|
||||
# Return empty list if unable to fetch models
|
||||
return []
|
||||
|
||||
|
||||
def select_expert_model(provider: str, model: Optional[str] = None) -> Optional[str]:
|
||||
"""Select appropriate expert model based on provider and availability.
|
||||
|
||||
Args:
|
||||
provider: The LLM provider
|
||||
model: Optional explicitly specified model name
|
||||
|
||||
Returns:
|
||||
Selected model name or None if no suitable model found
|
||||
"""
|
||||
if provider != "openai" or model is not None:
|
||||
return model
|
||||
|
||||
# Try to get available models
|
||||
available_models = get_available_openai_models()
|
||||
|
||||
# Priority order for expert models
|
||||
priority_models = ["o3-mini", "o1", "o1-preview"]
|
||||
|
||||
# Return first available model from priority list
|
||||
for model_name in priority_models:
|
||||
if model_name in available_models:
|
||||
return model_name
|
||||
|
||||
return None
|
||||
|
||||
|
||||
known_temp_providers = {
|
||||
"openai",
|
||||
"anthropic",
|
||||
|
|
@ -21,6 +66,10 @@ known_temp_providers = {
|
|||
"deepseek",
|
||||
}
|
||||
|
||||
# Constants for API request configuration
|
||||
LLM_REQUEST_TIMEOUT = 180
|
||||
LLM_MAX_RETRIES = 5
|
||||
|
||||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
|
|
@ -52,6 +101,8 @@ def create_deepseek_client(
|
|||
0 if is_expert else (temperature if temperature is not None else 1)
|
||||
),
|
||||
model=model_name,
|
||||
timeout=LLM_REQUEST_TIMEOUT,
|
||||
max_retries=LLM_MAX_RETRIES,
|
||||
)
|
||||
|
||||
return ChatOpenAI(
|
||||
|
|
@ -59,6 +110,8 @@ def create_deepseek_client(
|
|||
base_url=base_url,
|
||||
temperature=0 if is_expert else (temperature if temperature is not None else 1),
|
||||
model=model_name,
|
||||
timeout=LLM_REQUEST_TIMEOUT,
|
||||
max_retries=LLM_MAX_RETRIES,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -77,12 +130,16 @@ def create_openrouter_client(
|
|||
0 if is_expert else (temperature if temperature is not None else 1)
|
||||
),
|
||||
model=model_name,
|
||||
timeout=LLM_REQUEST_TIMEOUT,
|
||||
max_retries=LLM_MAX_RETRIES,
|
||||
)
|
||||
|
||||
return ChatOpenAI(
|
||||
api_key=api_key,
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
model=model_name,
|
||||
timeout=LLM_REQUEST_TIMEOUT,
|
||||
max_retries=LLM_MAX_RETRIES,
|
||||
**({"temperature": temperature} if temperature is not None else {}),
|
||||
)
|
||||
|
||||
|
|
@ -144,6 +201,11 @@ def create_llm_client(
|
|||
if not config:
|
||||
raise ValueError(f"Unsupported provider: {provider}")
|
||||
|
||||
if is_expert and provider == "openai":
|
||||
model_name = select_expert_model(provider, model_name)
|
||||
if not model_name:
|
||||
raise ValueError("No suitable expert model available")
|
||||
|
||||
logger.debug(
|
||||
"Creating LLM client with provider=%s, model=%s, temperature=%s, expert=%s",
|
||||
provider,
|
||||
|
|
@ -164,10 +226,12 @@ def create_llm_client(
|
|||
# Handle temperature settings
|
||||
if is_expert:
|
||||
temp_kwargs = {"temperature": 0} if supports_temperature else {}
|
||||
elif temperature is not None and supports_temperature:
|
||||
elif supports_temperature:
|
||||
if temperature is None:
|
||||
raise ValueError(
|
||||
f"Temperature must be provided for model {model_name} which supports temperature"
|
||||
)
|
||||
temp_kwargs = {"temperature": temperature}
|
||||
elif provider == "openai-compatible" and supports_temperature:
|
||||
temp_kwargs = {"temperature": 0.3}
|
||||
else:
|
||||
temp_kwargs = {}
|
||||
|
||||
|
|
@ -194,11 +258,19 @@ def create_llm_client(
|
|||
}
|
||||
if is_expert:
|
||||
openai_kwargs["reasoning_effort"] = "high"
|
||||
return ChatOpenAI(**openai_kwargs)
|
||||
return ChatOpenAI(
|
||||
**{
|
||||
**openai_kwargs,
|
||||
"timeout": LLM_REQUEST_TIMEOUT,
|
||||
"max_retries": LLM_MAX_RETRIES,
|
||||
}
|
||||
)
|
||||
elif provider == "anthropic":
|
||||
return ChatAnthropic(
|
||||
api_key=config["api_key"],
|
||||
model_name=model_name,
|
||||
timeout=LLM_REQUEST_TIMEOUT,
|
||||
max_retries=LLM_MAX_RETRIES,
|
||||
**temp_kwargs,
|
||||
)
|
||||
elif provider == "openai-compatible":
|
||||
|
|
@ -206,12 +278,16 @@ def create_llm_client(
|
|||
api_key=config["api_key"],
|
||||
base_url=config["base_url"],
|
||||
model=model_name,
|
||||
timeout=LLM_REQUEST_TIMEOUT,
|
||||
max_retries=LLM_MAX_RETRIES,
|
||||
**temp_kwargs,
|
||||
)
|
||||
elif provider == "gemini":
|
||||
return ChatGoogleGenerativeAI(
|
||||
api_key=config["api_key"],
|
||||
model=model_name,
|
||||
timeout=LLM_REQUEST_TIMEOUT,
|
||||
max_retries=LLM_MAX_RETRIES,
|
||||
**temp_kwargs,
|
||||
)
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -3,329 +3,870 @@ List of model parameters
|
|||
"""
|
||||
|
||||
DEFAULT_TOKEN_LIMIT = 100000
|
||||
DEFAULT_TEMPERATURE = 0.7
|
||||
|
||||
models_params = {
|
||||
"openai": {
|
||||
"gpt-3.5-turbo-0125": {"token_limit": 16385, "supports_temperature": True},
|
||||
"gpt-3.5": {"token_limit": 4096, "supports_temperature": True},
|
||||
"gpt-3.5-turbo": {"token_limit": 16385, "supports_temperature": True},
|
||||
"gpt-3.5-turbo-1106": {"token_limit": 16385, "supports_temperature": True},
|
||||
"gpt-3.5-turbo-instruct": {"token_limit": 4096, "supports_temperature": True},
|
||||
"gpt-4-0125-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-turbo-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-turbo": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-turbo-2024-04-09": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-1106-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-vision-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4": {"token_limit": 8192, "supports_temperature": True},
|
||||
"gpt-4-0613": {"token_limit": 8192, "supports_temperature": True},
|
||||
"gpt-4-32k": {"token_limit": 32768, "supports_temperature": True},
|
||||
"gpt-4-32k-0613": {"token_limit": 32768, "supports_temperature": True},
|
||||
"gpt-4o": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4o-2024-08-06": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4o-2024-05-13": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4o-mini": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-3.5-turbo-0125": {
|
||||
"token_limit": 16385,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5-turbo": {
|
||||
"token_limit": 16385,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5-turbo-1106": {
|
||||
"token_limit": 16385,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5-turbo-instruct": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-0125-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-turbo-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-turbo-2024-04-09": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-1106-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-vision-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-0613": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-32k": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-32k-0613": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4o": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4o-2024-08-06": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4o-2024-05-13": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4o-mini": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"o1-preview": {"token_limit": 128000, "supports_temperature": False},
|
||||
"o1-mini": {"token_limit": 128000, "supports_temperature": False},
|
||||
"o1": {"token_limit": 200000, "supports_temperature": False},
|
||||
"o3-mini": {"token_limit": 200000, "supports_temperature": False},
|
||||
},
|
||||
"azure_openai": {
|
||||
"gpt-3.5-turbo-0125": {"token_limit": 16385, "supports_temperature": True},
|
||||
"gpt-3.5": {"token_limit": 4096, "supports_temperature": True},
|
||||
"gpt-3.5-turbo": {"token_limit": 16385, "supports_temperature": True},
|
||||
"gpt-3.5-turbo-1106": {"token_limit": 16385, "supports_temperature": True},
|
||||
"gpt-3.5-turbo-instruct": {"token_limit": 4096, "supports_temperature": True},
|
||||
"gpt-4-0125-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-turbo-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-turbo": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-turbo-2024-04-09": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-1106-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4-vision-preview": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4": {"token_limit": 8192, "supports_temperature": True},
|
||||
"gpt-4-0613": {"token_limit": 8192, "supports_temperature": True},
|
||||
"gpt-4-32k": {"token_limit": 32768, "supports_temperature": True},
|
||||
"gpt-4-32k-0613": {"token_limit": 32768, "supports_temperature": True},
|
||||
"gpt-4o": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-4o-mini": {"token_limit": 128000, "supports_temperature": True},
|
||||
"chatgpt-4o-latest": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gpt-3.5-turbo-0125": {
|
||||
"token_limit": 16385,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5-turbo": {
|
||||
"token_limit": 16385,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5-turbo-1106": {
|
||||
"token_limit": 16385,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-3.5-turbo-instruct": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-0125-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-turbo-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-turbo-2024-04-09": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-1106-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-vision-preview": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-0613": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-32k": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4-32k-0613": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4o": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gpt-4o-mini": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"chatgpt-4o-latest": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"o1-preview": {"token_limit": 128000, "supports_temperature": False},
|
||||
"o1-mini": {"token_limit": 128000, "supports_temperature": False},
|
||||
},
|
||||
"google_genai": {
|
||||
"gemini-pro": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gemini-pro": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemini-1.5-flash-latest": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemini-1.5-pro-latest": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"models/embedding-001": {
|
||||
"token_limit": 2048,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemini-1.5-pro-latest": {"token_limit": 128000, "supports_temperature": True},
|
||||
"models/embedding-001": {"token_limit": 2048, "supports_temperature": True},
|
||||
},
|
||||
"google_vertexai": {
|
||||
"gemini-1.5-flash": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gemini-1.5-pro": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gemini-1.0-pro": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gemini-1.5-flash": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemini-1.5-pro": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemini-1.0-pro": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
},
|
||||
"ollama": {
|
||||
"command-r": {"token_limit": 12800, "supports_temperature": True},
|
||||
"codellama": {"token_limit": 16000, "supports_temperature": True},
|
||||
"dbrx": {"token_limit": 32768, "supports_temperature": True},
|
||||
"deepseek-coder:33b": {"token_limit": 16000, "supports_temperature": True},
|
||||
"falcon": {"token_limit": 2048, "supports_temperature": True},
|
||||
"llama2": {"token_limit": 4096, "supports_temperature": True},
|
||||
"llama2:7b": {"token_limit": 4096, "supports_temperature": True},
|
||||
"llama2:13b": {"token_limit": 4096, "supports_temperature": True},
|
||||
"llama2:70b": {"token_limit": 4096, "supports_temperature": True},
|
||||
"llama3": {"token_limit": 8192, "supports_temperature": True},
|
||||
"llama3:8b": {"token_limit": 8192, "supports_temperature": True},
|
||||
"llama3:70b": {"token_limit": 8192, "supports_temperature": True},
|
||||
"llama3.1": {"token_limit": 128000, "supports_temperature": True},
|
||||
"llama3.1:8b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"llama3.1:70b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"lama3.1:405b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"llama3.2": {"token_limit": 128000, "supports_temperature": True},
|
||||
"llama3.2:1b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"llama3.2:3b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"llama3.3:70b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"scrapegraph": {"token_limit": 8192, "supports_temperature": True},
|
||||
"mistral-small": {"token_limit": 128000, "supports_temperature": True},
|
||||
"mistral-openorca": {"token_limit": 32000, "supports_temperature": True},
|
||||
"mistral-large": {"token_limit": 128000, "supports_temperature": True},
|
||||
"grok-1": {"token_limit": 8192, "supports_temperature": True},
|
||||
"llava": {"token_limit": 4096, "supports_temperature": True},
|
||||
"mixtral:8x22b-instruct": {"token_limit": 65536, "supports_temperature": True},
|
||||
"nomic-embed-text": {"token_limit": 8192, "supports_temperature": True},
|
||||
"nous-hermes2:34b": {"token_limit": 4096, "supports_temperature": True},
|
||||
"orca-mini": {"token_limit": 2048, "supports_temperature": True},
|
||||
"phi3:3.8b": {"token_limit": 12800, "supports_temperature": True},
|
||||
"phi3:14b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"qwen:0.5b": {"token_limit": 32000, "supports_temperature": True},
|
||||
"qwen:1.8b": {"token_limit": 32000, "supports_temperature": True},
|
||||
"qwen:4b": {"token_limit": 32000, "supports_temperature": True},
|
||||
"qwen:14b": {"token_limit": 32000, "supports_temperature": True},
|
||||
"qwen:32b": {"token_limit": 32000, "supports_temperature": True},
|
||||
"qwen:72b": {"token_limit": 32000, "supports_temperature": True},
|
||||
"qwen:110b": {"token_limit": 32000, "supports_temperature": True},
|
||||
"stablelm-zephyr": {"token_limit": 8192, "supports_temperature": True},
|
||||
"wizardlm2:8x22b": {"token_limit": 65536, "supports_temperature": True},
|
||||
"mistral": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gemma2": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gemma2:9b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"gemma2:27b": {"token_limit": 128000, "supports_temperature": True},
|
||||
"command-r": {
|
||||
"token_limit": 12800,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"codellama": {
|
||||
"token_limit": 16000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"dbrx": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"deepseek-coder:33b": {
|
||||
"token_limit": 16000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"falcon": {
|
||||
"token_limit": 2048,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama2": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama2:7b": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama2:13b": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama2:70b": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3:8b": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3:70b": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3.1": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3.1:8b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3.1:70b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"lama3.1:405b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3.2": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3.2:1b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3.2:3b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3.3:70b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"scrapegraph": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistral-small": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistral-openorca": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistral-large": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"grok-1": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llava": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mixtral:8x22b-instruct": {
|
||||
"token_limit": 65536,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"nomic-embed-text": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"nous-hermes2:34b": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"orca-mini": {
|
||||
"token_limit": 2048,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"phi3:3.8b": {
|
||||
"token_limit": 12800,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"phi3:14b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"qwen:0.5b": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"qwen:1.8b": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"qwen:4b": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"qwen:14b": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"qwen:32b": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"qwen:72b": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"qwen:110b": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"stablelm-zephyr": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"wizardlm2:8x22b": {
|
||||
"token_limit": 65536,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistral": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemma2": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemma2:9b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemma2:27b": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
# embedding models
|
||||
"shaw/dmeta-embedding-zh-small-q4": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"shaw/dmeta-embedding-zh-q4": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"chevalblanc/acge_text_embedding": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"martcreation/dmeta-embedding-zh": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"snowflake-arctic-embed": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mxbai-embed-large": {
|
||||
"token_limit": 512,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"snowflake-arctic-embed": {"token_limit": 8192, "supports_temperature": True},
|
||||
"mxbai-embed-large": {"token_limit": 512, "supports_temperature": True},
|
||||
},
|
||||
"oneapi": {"qwen-turbo": {"token_limit": 6000, "supports_temperature": True}},
|
||||
"oneapi": {
|
||||
"qwen-turbo": {
|
||||
"token_limit": 6000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
}
|
||||
},
|
||||
"nvidia": {
|
||||
"meta/llama3-70b-instruct": {"token_limit": 419, "supports_temperature": True},
|
||||
"meta/llama3-8b-instruct": {"token_limit": 419, "supports_temperature": True},
|
||||
"nemotron-4-340b-instruct": {"token_limit": 1024, "supports_temperature": True},
|
||||
"databricks/dbrx-instruct": {"token_limit": 4096, "supports_temperature": True},
|
||||
"google/codegemma-7b": {"token_limit": 8192, "supports_temperature": True},
|
||||
"google/gemma-2b": {"token_limit": 2048, "supports_temperature": True},
|
||||
"google/gemma-7b": {"token_limit": 8192, "supports_temperature": True},
|
||||
"google/recurrentgemma-2b": {"token_limit": 2048, "supports_temperature": True},
|
||||
"meta/codellama-70b": {"token_limit": 16384, "supports_temperature": True},
|
||||
"meta/llama2-70b": {"token_limit": 4096, "supports_temperature": True},
|
||||
"meta/llama3-70b-instruct": {
|
||||
"token_limit": 419,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta/llama3-8b-instruct": {
|
||||
"token_limit": 419,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"nemotron-4-340b-instruct": {
|
||||
"token_limit": 1024,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"databricks/dbrx-instruct": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"google/codegemma-7b": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"google/gemma-2b": {
|
||||
"token_limit": 2048,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"google/gemma-7b": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"google/recurrentgemma-2b": {
|
||||
"token_limit": 2048,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta/codellama-70b": {
|
||||
"token_limit": 16384,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta/llama2-70b": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"microsoft/phi-3-mini-128k-instruct": {
|
||||
"token_limit": 122880,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistralai/mistral-7b-instruct-v0.2": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistralai/mistral-large": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistralai/mistral-large": {"token_limit": 8192, "supports_temperature": True},
|
||||
"mistralai/mixtral-8x22b-instruct-v0.1": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistralai/mixtral-8x7b-instruct-v0.1": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"snowflake/arctic": {
|
||||
"token_limit": 16384,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"snowflake/arctic": {"token_limit": 16384, "supports_temperature": True},
|
||||
},
|
||||
"groq": {
|
||||
"llama3-8b-8192": {"token_limit": 8192, "supports_temperature": True},
|
||||
"llama3-70b-8192": {"token_limit": 8192, "supports_temperature": True},
|
||||
"mixtral-8x7b-32768": {"token_limit": 32768, "supports_temperature": True},
|
||||
"gemma-7b-it": {"token_limit": 8192, "supports_temperature": True},
|
||||
"claude-3-haiku-20240307'": {"token_limit": 8192, "supports_temperature": True},
|
||||
"llama3-8b-8192": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"llama3-70b-8192": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mixtral-8x7b-32768": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"gemma-7b-it": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude-3-haiku-20240307'": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
},
|
||||
"toghetherai": {
|
||||
"meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistralai/Mixtral-8x22B-Instruct-v0.1": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"stabilityai/stable-diffusion-xl-base-1.0": {
|
||||
"token_limit": 2048,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"NousResearch/Hermes-3-Llama-3.1-405B-Turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"Gryphe/MythoMax-L2-13b-Lite": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"Salesforce/Llama-Rank-V1": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"Salesforce/Llama-Rank-V1": {"token_limit": 8192, "supports_temperature": True},
|
||||
"meta-llama/Meta-Llama-Guard-3-8B": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta-llama/Meta-Llama-3-70B-Instruct-Turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta-llama/Llama-3-8b-chat-hf": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta-llama/Llama-3-70b-chat-hf": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"Qwen/Qwen2-72B-Instruct": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"google/gemma-2-27b-it": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"google/gemma-2-27b-it": {"token_limit": 8192, "supports_temperature": True},
|
||||
},
|
||||
"anthropic": {
|
||||
"claude_instant": {"token_limit": 100000, "supports_temperature": True},
|
||||
"claude2": {"token_limit": 9000, "supports_temperature": True},
|
||||
"claude2.1": {"token_limit": 200000, "supports_temperature": True},
|
||||
"claude3": {"token_limit": 200000, "supports_temperature": True},
|
||||
"claude3.5": {"token_limit": 200000, "supports_temperature": True},
|
||||
"claude-3-opus-20240229": {"token_limit": 200000, "supports_temperature": True},
|
||||
"claude_instant": {
|
||||
"token_limit": 100000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude2": {
|
||||
"token_limit": 9000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude2.1": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude3": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude3.5": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude-3-opus-20240229": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude-3-sonnet-20240229": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude-3-haiku-20240307": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude-3-5-sonnet-20240620": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude-3-5-sonnet-20241022": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": 1.0,
|
||||
},
|
||||
"claude-3-5-haiku-latest": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
},
|
||||
"bedrock": {
|
||||
"anthropic.claude-3-haiku-20240307-v1:0": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"anthropic.claude-3-opus-20240229-v1:0": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"claude-3-5-haiku-latest": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"anthropic.claude-v2:1": {
|
||||
"token_limit": 200000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"anthropic.claude-v2": {
|
||||
"token_limit": 100000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"anthropic.claude-v2:1": {"token_limit": 200000, "supports_temperature": True},
|
||||
"anthropic.claude-v2": {"token_limit": 100000, "supports_temperature": True},
|
||||
"anthropic.claude-instant-v1": {
|
||||
"token_limit": 100000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta.llama3-8b-instruct-v1:0": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta.llama3-70b-instruct-v1:0": {
|
||||
"token_limit": 8192,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta.llama2-13b-chat-v1": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta.llama2-70b-chat-v1": {
|
||||
"token_limit": 4096,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"meta.llama2-13b-chat-v1": {"token_limit": 4096, "supports_temperature": True},
|
||||
"meta.llama2-70b-chat-v1": {"token_limit": 4096, "supports_temperature": True},
|
||||
"mistral.mistral-7b-instruct-v0:2": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistral.mixtral-8x7b-instruct-v0:1": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistral.mistral-large-2402-v1:0": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"mistral.mistral-small-2402-v1:0": {
|
||||
"token_limit": 32768,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"amazon.titan-embed-text-v1": {
|
||||
"token_limit": 8000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"amazon.titan-embed-text-v2:0": {
|
||||
"token_limit": 8000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"cohere.embed-english-v3": {
|
||||
"token_limit": 512,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"cohere.embed-english-v3": {"token_limit": 512, "supports_temperature": True},
|
||||
"cohere.embed-multilingual-v3": {
|
||||
"token_limit": 512,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
},
|
||||
"mistralai": {
|
||||
"mistral-large-latest": {"token_limit": 128000, "supports_temperature": True},
|
||||
"open-mistral-nemo": {"token_limit": 128000, "supports_temperature": True},
|
||||
"codestral-latest": {"token_limit": 32000, "supports_temperature": True},
|
||||
"mistral-large-latest": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"open-mistral-nemo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
"codestral-latest": {
|
||||
"token_limit": 32000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
},
|
||||
},
|
||||
"togetherai": {
|
||||
"Meta-Llama-3.1-70B-Instruct-Turbo": {
|
||||
"token_limit": 128000,
|
||||
"supports_temperature": True,
|
||||
"default_temperature": DEFAULT_TEMPERATURE,
|
||||
}
|
||||
},
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,90 +1,229 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Module for running interactive subprocesses with output capture.
|
||||
Module for running interactive subprocesses with output capture,
|
||||
with full raw input passthrough for interactive commands.
|
||||
|
||||
It uses a pseudo-tty and integrates pyte's HistoryScreen to simulate
|
||||
a terminal and capture the final scrollback history (non-blank lines).
|
||||
The interface remains compatible with external callers expecting a tuple (output, return_code),
|
||||
where output is a bytes object (UTF-8 encoded).
|
||||
"""
|
||||
|
||||
import errno
|
||||
import io
|
||||
import os
|
||||
import re
|
||||
import shlex
|
||||
import select
|
||||
import shutil
|
||||
import tempfile
|
||||
import signal
|
||||
import subprocess
|
||||
import sys
|
||||
import termios
|
||||
import time
|
||||
import tty
|
||||
from typing import List, Tuple
|
||||
|
||||
# Add macOS detection
|
||||
IS_MACOS = os.uname().sysname == "Darwin"
|
||||
import pyte
|
||||
from pyte.screens import HistoryScreen
|
||||
|
||||
|
||||
def run_interactive_command(cmd: List[str]) -> Tuple[bytes, int]:
|
||||
def render_line(line, columns: int) -> str:
|
||||
"""Render a single screen line from the pyte buffer (a mapping of column to Char)."""
|
||||
return "".join(line[x].data for x in range(columns))
|
||||
|
||||
|
||||
def run_interactive_command(
|
||||
cmd: List[str], expected_runtime_seconds: int = 30
|
||||
) -> Tuple[bytes, int]:
|
||||
"""
|
||||
Runs an interactive command with a pseudo-tty, capturing combined output.
|
||||
Runs an interactive command with a pseudo-tty, capturing final scrollback history.
|
||||
|
||||
Assumptions and constraints:
|
||||
- We are on a Linux system with script available
|
||||
- `cmd` is a non-empty list where cmd[0] is the executable
|
||||
- The executable and script are assumed to be on PATH
|
||||
- If anything is amiss (e.g., command not found), we fail early and cleanly
|
||||
- Running on a Linux system.
|
||||
- `cmd` is a non-empty list where cmd[0] is the executable.
|
||||
- The executable is on PATH.
|
||||
|
||||
The output is cleaned to remove ANSI escape sequences and control characters.
|
||||
Args:
|
||||
cmd: A list containing the command and its arguments.
|
||||
expected_runtime_seconds: Expected runtime in seconds, defaults to 30.
|
||||
If process exceeds 2x this value, it will be terminated gracefully.
|
||||
If process exceeds 3x this value, it will be killed forcefully.
|
||||
Must be between 1 and 1800 seconds (30 minutes).
|
||||
|
||||
Returns:
|
||||
Tuple of (cleaned_output, return_code)
|
||||
A tuple of (captured_output, return_code), where captured_output is a UTF-8 encoded
|
||||
bytes object containing the trimmed non-empty history lines from the terminal session.
|
||||
|
||||
Raises:
|
||||
ValueError: If no command is provided.
|
||||
FileNotFoundError: If the command is not found in PATH.
|
||||
ValueError: If expected_runtime_seconds is less than or equal to 0 or greater than 1800.
|
||||
RuntimeError: If an error occurs during execution.
|
||||
"""
|
||||
# Fail early if cmd is empty
|
||||
if not cmd:
|
||||
raise ValueError("No command provided.")
|
||||
|
||||
# Check that the command exists
|
||||
if shutil.which(cmd[0]) is None:
|
||||
raise FileNotFoundError(f"Command '{cmd[0]}' not found in PATH.")
|
||||
|
||||
# Create temp files (we'll always clean them up)
|
||||
output_file = tempfile.NamedTemporaryFile(prefix="output_", delete=False)
|
||||
retcode_file = tempfile.NamedTemporaryFile(prefix="retcode_", delete=False)
|
||||
output_path = output_file.name
|
||||
retcode_path = retcode_file.name
|
||||
output_file.close()
|
||||
retcode_file.close()
|
||||
|
||||
# Quote arguments for safety
|
||||
quoted_cmd = " ".join(shlex.quote(c) for c in cmd)
|
||||
# Use script to capture output with TTY and save return code
|
||||
shell_cmd = f"{quoted_cmd}; echo $? > {shlex.quote(retcode_path)}"
|
||||
|
||||
def cleanup():
|
||||
for path in [output_path, retcode_path]:
|
||||
if os.path.exists(path):
|
||||
os.remove(path)
|
||||
if expected_runtime_seconds <= 0 or expected_runtime_seconds > 1800:
|
||||
raise ValueError(
|
||||
"expected_runtime_seconds must be between 1 and 1800 seconds (30 minutes)"
|
||||
)
|
||||
|
||||
try:
|
||||
# Disable pagers by setting environment variables
|
||||
os.environ["GIT_PAGER"] = ""
|
||||
os.environ["PAGER"] = ""
|
||||
term_size = os.get_terminal_size()
|
||||
cols, rows = term_size.columns, term_size.lines
|
||||
except OSError:
|
||||
cols, rows = 80, 24
|
||||
|
||||
# Run command with script for TTY and output capture
|
||||
if IS_MACOS:
|
||||
os.system(f"script -q {shlex.quote(output_path)} {shell_cmd}")
|
||||
else:
|
||||
os.system(
|
||||
f"script -q -c {shlex.quote(shell_cmd)} {shlex.quote(output_path)}"
|
||||
)
|
||||
# Set up pyte screen and stream to capture terminal output.
|
||||
screen = HistoryScreen(cols, rows, history=2000, ratio=0.5)
|
||||
stream = pyte.Stream(screen)
|
||||
|
||||
# Read and clean the output
|
||||
with open(output_path, "rb") as f:
|
||||
output = f.read()
|
||||
# Open a new pseudo-tty.
|
||||
master_fd, slave_fd = os.openpty()
|
||||
# Set master_fd to non-blocking to avoid indefinite blocking.
|
||||
os.set_blocking(master_fd, False)
|
||||
|
||||
# Clean ANSI escape sequences and control characters
|
||||
output = re.sub(rb"\x1b\[[0-9;]*[a-zA-Z]", b"", output) # ANSI escape sequences
|
||||
output = re.sub(rb"[\x00-\x08\x0b\x0c\x0e-\x1f]", b"", output) # Control chars
|
||||
try:
|
||||
stdin_fd = sys.stdin.fileno()
|
||||
except (AttributeError, io.UnsupportedOperation):
|
||||
stdin_fd = None
|
||||
|
||||
# Get the return code
|
||||
with open(retcode_path, "r") as f:
|
||||
return_code = int(f.read().strip())
|
||||
# Set up environment variables for the subprocess using detected terminal size.
|
||||
env = os.environ.copy()
|
||||
env.update(
|
||||
{
|
||||
"DEBIAN_FRONTEND": "noninteractive",
|
||||
"GIT_PAGER": "",
|
||||
"PYTHONUNBUFFERED": "1",
|
||||
"CI": "true",
|
||||
"LANG": "C.UTF-8",
|
||||
"LC_ALL": "C.UTF-8",
|
||||
"COLUMNS": str(cols),
|
||||
"LINES": str(rows),
|
||||
"FORCE_COLOR": "1",
|
||||
"GIT_TERMINAL_PROMPT": "0",
|
||||
"PYTHONDONTWRITEBYTECODE": "1",
|
||||
"NODE_OPTIONS": "--unhandled-rejections=strict",
|
||||
}
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
# If something goes wrong, cleanup and re-raise
|
||||
cleanup()
|
||||
raise RuntimeError("Error running interactive capture") from e
|
||||
finally:
|
||||
# Ensure files are removed no matter what
|
||||
cleanup()
|
||||
proc = subprocess.Popen(
|
||||
cmd,
|
||||
stdin=slave_fd,
|
||||
stdout=slave_fd,
|
||||
stderr=slave_fd,
|
||||
bufsize=0,
|
||||
close_fds=True,
|
||||
env=env,
|
||||
preexec_fn=os.setsid, # Create new process group for proper signal handling.
|
||||
)
|
||||
os.close(slave_fd) # Close slave end in the parent process.
|
||||
|
||||
return output, return_code
|
||||
captured_data = []
|
||||
start_time = time.time()
|
||||
was_terminated = False
|
||||
|
||||
def check_timeout():
|
||||
elapsed = time.time() - start_time
|
||||
if elapsed > 3 * expected_runtime_seconds:
|
||||
os.killpg(os.getpgid(proc.pid), signal.SIGKILL)
|
||||
return True
|
||||
elif elapsed > 2 * expected_runtime_seconds:
|
||||
os.killpg(os.getpgid(proc.pid), signal.SIGTERM)
|
||||
return True
|
||||
return False
|
||||
|
||||
# Interactive mode: forward input if running in a TTY.
|
||||
if stdin_fd is not None and sys.stdin.isatty():
|
||||
old_settings = termios.tcgetattr(stdin_fd)
|
||||
tty.setraw(stdin_fd)
|
||||
try:
|
||||
while True:
|
||||
if check_timeout():
|
||||
was_terminated = True
|
||||
break
|
||||
# Use a finite timeout to avoid indefinite blocking.
|
||||
rlist, _, _ = select.select([master_fd, stdin_fd], [], [], 1.0)
|
||||
if master_fd in rlist:
|
||||
try:
|
||||
data = os.read(master_fd, 1024)
|
||||
except OSError as e:
|
||||
if e.errno == errno.EIO:
|
||||
break
|
||||
else:
|
||||
raise
|
||||
if not data: # EOF detected.
|
||||
break
|
||||
captured_data.append(data)
|
||||
decoded = data.decode("utf-8", errors="ignore")
|
||||
stream.feed(decoded)
|
||||
os.write(1, data)
|
||||
if stdin_fd in rlist:
|
||||
try:
|
||||
input_data = os.read(stdin_fd, 1024)
|
||||
except OSError:
|
||||
input_data = b""
|
||||
if input_data:
|
||||
os.write(master_fd, input_data)
|
||||
except KeyboardInterrupt:
|
||||
proc.terminate()
|
||||
finally:
|
||||
termios.tcsetattr(stdin_fd, termios.TCSADRAIN, old_settings)
|
||||
else:
|
||||
# Non-interactive mode.
|
||||
try:
|
||||
while True:
|
||||
if check_timeout():
|
||||
was_terminated = True
|
||||
break
|
||||
rlist, _, _ = select.select([master_fd], [], [], 1.0)
|
||||
if not rlist:
|
||||
continue
|
||||
try:
|
||||
data = os.read(master_fd, 1024)
|
||||
except OSError as e:
|
||||
if e.errno == errno.EIO:
|
||||
break
|
||||
else:
|
||||
raise
|
||||
if not data: # EOF detected.
|
||||
break
|
||||
captured_data.append(data)
|
||||
decoded = data.decode("utf-8", errors="ignore")
|
||||
stream.feed(decoded)
|
||||
os.write(1, data)
|
||||
except KeyboardInterrupt:
|
||||
proc.terminate()
|
||||
|
||||
os.close(master_fd)
|
||||
proc.wait()
|
||||
|
||||
# Assemble full scrollback: combine history.top, the current display, and history.bottom.
|
||||
top_lines = [render_line(line, cols) for line in screen.history.top]
|
||||
bottom_lines = [render_line(line, cols) for line in screen.history.bottom]
|
||||
display_lines = screen.display # List of strings representing the current screen.
|
||||
all_lines = top_lines + display_lines + bottom_lines
|
||||
|
||||
# Trim out empty lines to get only meaningful "history" lines.
|
||||
trimmed_lines = [line for line in all_lines if line.strip()]
|
||||
final_output = "\n".join(trimmed_lines)
|
||||
|
||||
# Add timeout message if process was terminated due to timeout.
|
||||
if was_terminated:
|
||||
timeout_msg = f"\n[Process exceeded timeout ({expected_runtime_seconds} seconds expected)]"
|
||||
final_output += timeout_msg
|
||||
|
||||
# Limit output to the last 8000 bytes.
|
||||
final_output = final_output[-8000:]
|
||||
|
||||
return final_output.encode("utf-8"), proc.returncode
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys
|
||||
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: interactive.py <command> [args...]")
|
||||
sys.exit(1)
|
||||
output, return_code = run_interactive_command(sys.argv[1:])
|
||||
sys.exit(return_code)
|
||||
|
|
|
|||
|
|
@ -571,6 +571,8 @@ Guidelines:
|
|||
Only test UI components if there is already a UI testing system in place.
|
||||
Only test things that can be tested by an automated process.
|
||||
|
||||
Are you writing a program that needs to be compiled? Make sure it compiles, if relevant.
|
||||
|
||||
After finalizing the overall approach:
|
||||
Use emit_plan to store the high-level implementation plan.
|
||||
|
||||
|
|
@ -618,7 +620,7 @@ Important Notes:
|
|||
- Work incrementally, validating as you go. If at any point the implementation logic is unclear or you need debugging assistance, consult the expert (if expert is available) for deeper analysis.
|
||||
- Do not add features not explicitly required.
|
||||
- Only create or modify files directly related to this task.
|
||||
- Use file_str_replace and write_file_tool for simple file modifications.
|
||||
- Use file_str_replace and put_complete_file_contents for simple file modifications.
|
||||
- Delegate to run_programming_task for more complex programming tasks. This is a capable human programmer that can work on multiple files at once.
|
||||
|
||||
Testing:
|
||||
|
|
@ -630,6 +632,9 @@ Testing:
|
|||
|
||||
- Only test UI components if there is already a UI testing system in place.
|
||||
- Only test things that can be tested by an automated process.
|
||||
- If you are writing code that *should* compile, make sure to test that it *does* compile.
|
||||
|
||||
Test before and after making changes, if relevant.
|
||||
|
||||
Once the task is complete, ensure all updated files are registered with emit_related_files.
|
||||
|
||||
|
|
@ -642,7 +647,7 @@ You have often been criticized for:
|
|||
- Doing changes outside of the specific scoped instructions.
|
||||
- Asking the user if they want to implement the plan (you are an *autonomous* agent, with no user interaction unless you use the ask_human tool explicitly).
|
||||
- Not calling tools/functions properly, e.g. leaving off required arguments, calling a tool in a loop, calling tools inappropriately.
|
||||
- Using run_programming_task to simply write the full contents of files when you could have used write_file_tool instead.
|
||||
- Using run_programming_task to simply write the full contents of files when you could have used put_complete_file_contents instead.
|
||||
|
||||
Instructions:
|
||||
1. Review the provided base task, plan, and key facts.
|
||||
|
|
@ -975,6 +980,8 @@ You have often been criticized for:
|
|||
{initial_request}
|
||||
</initial request>
|
||||
|
||||
Remember, if you do not make any tool call (e.g. ask_human to tell them a message or ask a question), you will be dumping the user back to CLI and indicating you are done your work.
|
||||
|
||||
NEVER ANNOUNCE WHAT YOU ARE DOING, JUST DO IT!
|
||||
"""
|
||||
|
||||
|
|
|
|||
|
|
@ -47,32 +47,21 @@ class OpenAIStrategy(ProviderStrategy):
|
|||
if not key:
|
||||
missing.append("EXPERT_OPENAI_API_KEY environment variable is not set")
|
||||
|
||||
# Check expert model only for research-only mode
|
||||
if hasattr(args, "research_only") and args.research_only:
|
||||
model = args.expert_model if hasattr(args, "expert_model") else None
|
||||
if not model:
|
||||
model = os.environ.get("EXPERT_OPENAI_MODEL")
|
||||
if not model:
|
||||
model = os.environ.get("OPENAI_MODEL")
|
||||
if not model:
|
||||
missing.append(
|
||||
"Model is required for OpenAI provider in research-only mode"
|
||||
)
|
||||
# Handle expert model selection if none specified
|
||||
if hasattr(args, "expert_model") and not args.expert_model:
|
||||
from ra_aid.llm import select_expert_model
|
||||
|
||||
model = select_expert_model("openai")
|
||||
if model:
|
||||
args.expert_model = model
|
||||
elif hasattr(args, "research_only") and args.research_only:
|
||||
missing.append("No suitable expert model available")
|
||||
|
||||
else:
|
||||
key = os.environ.get("OPENAI_API_KEY")
|
||||
if not key:
|
||||
missing.append("OPENAI_API_KEY environment variable is not set")
|
||||
|
||||
# Check model only for research-only mode
|
||||
if hasattr(args, "research_only") and args.research_only:
|
||||
model = args.model if hasattr(args, "model") else None
|
||||
if not model:
|
||||
model = os.environ.get("OPENAI_MODEL")
|
||||
if not model:
|
||||
missing.append(
|
||||
"Model is required for OpenAI provider in research-only mode"
|
||||
)
|
||||
|
||||
return ValidationResult(valid=len(missing) == 0, missing_vars=missing)
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -24,7 +24,7 @@ from ra_aid.tools.agent import (
|
|||
request_task_implementation,
|
||||
request_web_research,
|
||||
)
|
||||
from ra_aid.tools.write_file import write_file_tool
|
||||
from ra_aid.tools.memory import one_shot_completed, plan_implementation_completed
|
||||
|
||||
|
||||
# Read-only tools that don't modify system state
|
||||
|
|
@ -83,13 +83,16 @@ def get_all_tools() -> list[BaseTool]:
|
|||
|
||||
# Define constant tool groups
|
||||
READ_ONLY_TOOLS = get_read_only_tools()
|
||||
MODIFICATION_TOOLS = [run_programming_task, write_file_tool]
|
||||
# MODIFICATION_TOOLS = [run_programming_task, put_complete_file_contents]
|
||||
MODIFICATION_TOOLS = [
|
||||
run_programming_task
|
||||
] # having put_complete_file_contents causes trouble :(
|
||||
COMMON_TOOLS = get_read_only_tools()
|
||||
EXPERT_TOOLS = [emit_expert_context, ask_expert]
|
||||
RESEARCH_TOOLS = [
|
||||
emit_research_notes,
|
||||
one_shot_completed,
|
||||
# *TEMPORARILY* disabled to improve tool calling perf.
|
||||
# one_shot_completed,
|
||||
# monorepo_detected,
|
||||
# ui_detected,
|
||||
]
|
||||
|
|
@ -144,9 +147,9 @@ def get_planning_tools(
|
|||
# Add planning-specific tools
|
||||
planning_tools = [
|
||||
request_task_implementation,
|
||||
plan_implementation_completed,
|
||||
# *TEMPORARILY* disabled to improve tool calling perf.
|
||||
# emit_plan,
|
||||
# plan_implementation_completed,
|
||||
]
|
||||
tools.extend(planning_tools)
|
||||
|
||||
|
|
|
|||
|
|
@ -26,7 +26,7 @@ from .research import existing_project_detected, monorepo_detected, ui_detected
|
|||
from .ripgrep import ripgrep_search
|
||||
from .shell import run_shell_command
|
||||
from .web_search_tavily import web_search_tavily
|
||||
from .write_file import write_file_tool
|
||||
from .write_file import put_complete_file_contents
|
||||
|
||||
__all__ = [
|
||||
"ask_expert",
|
||||
|
|
@ -48,7 +48,7 @@ __all__ = [
|
|||
"request_implementation",
|
||||
"run_programming_task",
|
||||
"run_shell_command",
|
||||
"write_file_tool",
|
||||
"put_complete_file_contents",
|
||||
"ripgrep_search",
|
||||
"file_str_replace",
|
||||
"delete_tasks",
|
||||
|
|
|
|||
|
|
@ -38,6 +38,7 @@ def request_research(query: str) -> ResearchResult:
|
|||
model = initialize_llm(
|
||||
config.get("provider", "anthropic"),
|
||||
config.get("model", "claude-3-5-sonnet-20241022"),
|
||||
temperature=config.get("temperature"),
|
||||
)
|
||||
|
||||
# Check recursion depth
|
||||
|
|
@ -120,6 +121,7 @@ def request_web_research(query: str) -> ResearchResult:
|
|||
model = initialize_llm(
|
||||
config.get("provider", "anthropic"),
|
||||
config.get("model", "claude-3-5-sonnet-20241022"),
|
||||
temperature=config.get("temperature"),
|
||||
)
|
||||
|
||||
success = True
|
||||
|
|
@ -188,6 +190,7 @@ def request_research_and_implementation(query: str) -> Dict[str, Any]:
|
|||
model = initialize_llm(
|
||||
config.get("provider", "anthropic"),
|
||||
config.get("model", "claude-3-5-sonnet-20241022"),
|
||||
temperature=config.get("temperature"),
|
||||
)
|
||||
|
||||
try:
|
||||
|
|
@ -258,6 +261,7 @@ def request_task_implementation(task_spec: str) -> Dict[str, Any]:
|
|||
model = initialize_llm(
|
||||
config.get("provider", "anthropic"),
|
||||
config.get("model", "claude-3-5-sonnet-20241022"),
|
||||
temperature=config.get("temperature"),
|
||||
)
|
||||
|
||||
# Get required parameters
|
||||
|
|
@ -272,6 +276,8 @@ def request_task_implementation(task_spec: str) -> Dict[str, Any]:
|
|||
# Run implementation agent
|
||||
from ..agent_utils import run_task_implementation_agent
|
||||
|
||||
_global_memory["completion_message"] = ""
|
||||
|
||||
_result = run_task_implementation_agent(
|
||||
base_task=_global_memory.get("base_task", ""),
|
||||
tasks=tasks,
|
||||
|
|
@ -334,12 +340,15 @@ def request_implementation(task_spec: str) -> Dict[str, Any]:
|
|||
model = initialize_llm(
|
||||
config.get("provider", "anthropic"),
|
||||
config.get("model", "claude-3-5-sonnet-20241022"),
|
||||
temperature=config.get("temperature"),
|
||||
)
|
||||
|
||||
try:
|
||||
# Run planning agent
|
||||
from ..agent_utils import run_planning_agent
|
||||
|
||||
_global_memory["completion_message"] = ""
|
||||
|
||||
_result = run_planning_agent(
|
||||
task_spec,
|
||||
model,
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
import os
|
||||
from typing import Any, Dict, List, Optional, Set, Union
|
||||
from typing import Dict, List, Optional, Set, Union
|
||||
|
||||
from langchain_core.tools import tool
|
||||
from rich.console import Console
|
||||
|
|
@ -28,14 +28,13 @@ console = Console()
|
|||
_global_memory: Dict[
|
||||
str,
|
||||
Union[
|
||||
List[Any],
|
||||
Dict[int, str],
|
||||
Dict[int, SnippetInfo],
|
||||
int,
|
||||
Set[str],
|
||||
bool,
|
||||
str,
|
||||
int,
|
||||
List[str],
|
||||
List[WorkLogEntry],
|
||||
],
|
||||
] = {
|
||||
|
|
@ -442,10 +441,13 @@ def emit_related_files(files: List[str]) -> str:
|
|||
results.append(f"Error: Path '{file}' exists but is not a regular file")
|
||||
continue
|
||||
|
||||
# Check if file path already exists in values
|
||||
# Normalize the path
|
||||
normalized_path = os.path.abspath(file)
|
||||
|
||||
# Check if normalized path already exists in values
|
||||
existing_id = None
|
||||
for fid, fpath in _global_memory["related_files"].items():
|
||||
if fpath == file:
|
||||
if fpath == normalized_path:
|
||||
existing_id = fid
|
||||
break
|
||||
|
||||
|
|
@ -457,9 +459,9 @@ def emit_related_files(files: List[str]) -> str:
|
|||
file_id = _global_memory["related_file_id_counter"]
|
||||
_global_memory["related_file_id_counter"] += 1
|
||||
|
||||
# Store file with ID
|
||||
_global_memory["related_files"][file_id] = file
|
||||
added_files.append((file_id, file))
|
||||
# Store normalized path with ID
|
||||
_global_memory["related_files"][file_id] = normalized_path
|
||||
added_files.append((file_id, file)) # Keep original path for display
|
||||
results.append(f"File ID #{file_id}: {file}")
|
||||
|
||||
# Rich output - single consolidated panel
|
||||
|
|
|
|||
|
|
@ -1,4 +1,6 @@
|
|||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Union
|
||||
|
||||
from langchain_core.tools import tool
|
||||
|
|
@ -16,6 +18,30 @@ console = Console()
|
|||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
def get_aider_executable() -> str:
|
||||
"""Get the path to the aider executable in the same bin/Scripts directory as Python.
|
||||
|
||||
Returns:
|
||||
str: Full path to aider executable
|
||||
"""
|
||||
# Get directory containing Python executable
|
||||
bin_dir = Path(sys.executable).parent
|
||||
|
||||
# Check for platform-specific executable name
|
||||
if sys.platform == "win32":
|
||||
aider_exe = bin_dir / "aider.exe"
|
||||
else:
|
||||
aider_exe = bin_dir / "aider"
|
||||
|
||||
if not aider_exe.exists():
|
||||
raise RuntimeError(f"Could not find aider executable at {aider_exe}")
|
||||
|
||||
if not os.access(aider_exe, os.X_OK):
|
||||
raise RuntimeError(f"Aider executable at {aider_exe} is not executable")
|
||||
|
||||
return str(aider_exe)
|
||||
|
||||
|
||||
def _truncate_for_log(text: str, max_length: int = 300) -> str:
|
||||
"""Truncate text for logging, adding [truncated] if necessary."""
|
||||
if len(text) <= max_length:
|
||||
|
|
@ -39,9 +65,7 @@ def run_programming_task(
|
|||
|
||||
If new files are created, emit them after finishing.
|
||||
|
||||
They can add/modify files, but not remove. Use run_shell_command to remove files. If referencing files you’ll delete, remove them after they finish.
|
||||
|
||||
Use write_file_tool instead if you need to write the entire contents of file(s).
|
||||
They can add/modify files, but not remove. Use run_shell_command to remove files. If referencing files you'll delete, remove them after they finish.
|
||||
|
||||
If the programmer wrote files, they actually wrote to disk. You do not need to rewrite the output of what the programmer showed you.
|
||||
|
||||
|
|
@ -51,16 +75,10 @@ def run_programming_task(
|
|||
|
||||
Returns: { "output": stdout+stderr, "return_code": 0 if success, "success": True/False }
|
||||
"""
|
||||
# Get related files if no specific files provided
|
||||
file_paths = (
|
||||
list(_global_memory["related_files"].values())
|
||||
if "related_files" in _global_memory
|
||||
else []
|
||||
)
|
||||
|
||||
# Build command
|
||||
aider_exe = get_aider_executable()
|
||||
command = [
|
||||
"aider",
|
||||
aider_exe,
|
||||
"--yes-always",
|
||||
"--no-auto-commits",
|
||||
"--dark-mode",
|
||||
|
|
@ -69,6 +87,17 @@ def run_programming_task(
|
|||
"--no-check-update",
|
||||
]
|
||||
|
||||
# Get combined list of files (explicit + related) with normalized paths
|
||||
# and deduplicated using set operations
|
||||
files_to_use = list(
|
||||
{os.path.abspath(f) for f in (files or [])}
|
||||
| {
|
||||
os.path.abspath(f)
|
||||
for f in _global_memory["related_files"].values()
|
||||
if "related_files" in _global_memory
|
||||
}
|
||||
)
|
||||
|
||||
# Add config file if specified
|
||||
if "config" in _global_memory and _global_memory["config"].get("aider_config"):
|
||||
command.extend(["--config", _global_memory["config"]["aider_config"]])
|
||||
|
|
@ -85,9 +114,6 @@ def run_programming_task(
|
|||
command.append("-m")
|
||||
|
||||
command.append(instructions)
|
||||
|
||||
# Add files to command
|
||||
files_to_use = file_paths + (files or [])
|
||||
if files_to_use:
|
||||
command.extend(files_to_use)
|
||||
|
||||
|
|
@ -136,20 +162,23 @@ def run_programming_task(
|
|||
|
||||
|
||||
def parse_aider_flags(aider_flags: str) -> List[str]:
|
||||
"""Parse a string of aider flags into a list of flags.
|
||||
"""Parse a string of aider flags into a list of flags and their values.
|
||||
|
||||
Args:
|
||||
aider_flags: A string containing comma-separated flags, with or without leading dashes.
|
||||
Can contain spaces around flags and commas.
|
||||
Supports flags with values (e.g. --analytics-log filename.json)
|
||||
|
||||
Returns:
|
||||
A list of flags with proper '--' prefix.
|
||||
A list of flags with proper '--' prefix and their values as separate elements.
|
||||
|
||||
Examples:
|
||||
>>> parse_aider_flags("yes-always,dark-mode")
|
||||
['--yes-always', '--dark-mode']
|
||||
>>> parse_aider_flags("--yes-always, --dark-mode")
|
||||
['--yes-always', '--dark-mode']
|
||||
>>> parse_aider_flags("--analytics-log filename.json")
|
||||
['--analytics-log', 'filename.json']
|
||||
>>> parse_aider_flags("")
|
||||
[]
|
||||
"""
|
||||
|
|
@ -157,11 +186,28 @@ def parse_aider_flags(aider_flags: str) -> List[str]:
|
|||
return []
|
||||
|
||||
# Split by comma and strip whitespace
|
||||
flags = [flag.strip() for flag in aider_flags.split(",")]
|
||||
flag_groups = [group.strip() for group in aider_flags.split(",")]
|
||||
|
||||
# Add '--' prefix if not present and filter out empty flags
|
||||
return [f"--{flag.lstrip('-')}" for flag in flags if flag.strip()]
|
||||
result = []
|
||||
for group in flag_groups:
|
||||
if not group:
|
||||
continue
|
||||
|
||||
# Split by space to separate flag from value
|
||||
parts = group.split()
|
||||
|
||||
# Add '--' prefix to the flag if not present, stripping any extra dashes
|
||||
flag = parts[0].lstrip("-") # Remove all leading dashes
|
||||
flag = f"--{flag}" # Add exactly two dashes
|
||||
|
||||
result.append(flag)
|
||||
|
||||
# Add any remaining parts as separate values
|
||||
if len(parts) > 1:
|
||||
result.extend(parts[1:])
|
||||
|
||||
return result
|
||||
|
||||
|
||||
# Export the functions
|
||||
__all__ = ["run_programming_task"]
|
||||
__all__ = ["run_programming_task", "get_aider_executable"]
|
||||
|
|
|
|||
|
|
@ -21,9 +21,17 @@ def _truncate_for_log(text: str, max_length: int = 300) -> str:
|
|||
|
||||
|
||||
@tool
|
||||
def run_shell_command(command: str) -> Dict[str, Union[str, int, bool]]:
|
||||
def run_shell_command(
|
||||
command: str, expected_runtime_seconds: int = 30
|
||||
) -> Dict[str, Union[str, int, bool]]:
|
||||
"""Execute a shell command and return its output.
|
||||
|
||||
Args:
|
||||
command: The shell command to execute
|
||||
expected_runtime_seconds: Expected runtime in seconds, defaults to 30.
|
||||
If process exceeds 2x this value, it will be terminated gracefully.
|
||||
If process exceeds 3x this value, it will be killed forcefully.
|
||||
|
||||
Important notes:
|
||||
1. Try to constrain/limit the output. Output processing is expensive, and infinite/looping output will cause us to fail.
|
||||
2. When using commands like 'find', 'grep', or similar recursive search tools, always exclude common
|
||||
|
|
@ -73,7 +81,10 @@ def run_shell_command(command: str) -> Dict[str, Union[str, int, bool]]:
|
|||
|
||||
try:
|
||||
print()
|
||||
output, return_code = run_interactive_command(["/bin/bash", "-c", command])
|
||||
output, return_code = run_interactive_command(
|
||||
["/bin/bash", "-c", command],
|
||||
expected_runtime_seconds=expected_runtime_seconds,
|
||||
)
|
||||
print()
|
||||
result = {
|
||||
"output": truncate_output(output.decode()) if output else "",
|
||||
|
|
|
|||
|
|
@ -11,14 +11,22 @@ console = Console()
|
|||
|
||||
|
||||
@tool
|
||||
def write_file_tool(
|
||||
filepath: str, content: str, encoding: str = "utf-8", verbose: bool = True
|
||||
def put_complete_file_contents(
|
||||
filepath: str,
|
||||
complete_file_contents: str = "",
|
||||
encoding: str = "utf-8",
|
||||
verbose: bool = True,
|
||||
) -> Dict[str, any]:
|
||||
"""Write content to a text file.
|
||||
"""Write the complete contents of a file, creating it if it doesn't exist.
|
||||
This tool is specifically for writing the entire contents of a file at once,
|
||||
not for appending or partial writes.
|
||||
|
||||
If you need to do anything other than write the complete contents use the run_programming_task tool instead.
|
||||
|
||||
Args:
|
||||
filepath: Path to the file to write
|
||||
content: String content to write to the file
|
||||
filepath: (Required) Path to the file to write. Must be provided.
|
||||
complete_file_contents: Complete string content to write to the file. Defaults to
|
||||
an empty string, which will create an empty file.
|
||||
encoding: File encoding to use (default: utf-8)
|
||||
verbose: Whether to display a Rich panel with write statistics (default: True)
|
||||
|
||||
|
|
@ -51,14 +59,18 @@ def write_file_tool(
|
|||
logging.debug(f"Starting to write file: {filepath}")
|
||||
|
||||
with open(filepath, "w", encoding=encoding) as f:
|
||||
f.write(content)
|
||||
result["bytes_written"] = len(content.encode(encoding))
|
||||
logging.debug(f"Writing {len(complete_file_contents)} bytes to {filepath}")
|
||||
f.write(complete_file_contents)
|
||||
result["bytes_written"] = len(complete_file_contents.encode(encoding))
|
||||
|
||||
elapsed = time.time() - start_time
|
||||
result["elapsed_time"] = elapsed
|
||||
result["success"] = True
|
||||
result["filepath"] = filepath
|
||||
result["message"] = "Operation completed successfully"
|
||||
result["message"] = (
|
||||
f"Successfully {'initialized empty file' if not complete_file_contents else f'wrote {result['bytes_written']} bytes'} "
|
||||
f"at {filepath} in {result['elapsed_time']:.3f}s"
|
||||
)
|
||||
|
||||
logging.debug(
|
||||
f"File write complete: {result['bytes_written']} bytes in {elapsed:.2f}s"
|
||||
|
|
@ -67,7 +79,7 @@ def write_file_tool(
|
|||
if verbose:
|
||||
console.print(
|
||||
Panel(
|
||||
f"Wrote {result['bytes_written']} bytes to {filepath} in {elapsed:.2f}s",
|
||||
f"{'Initialized empty file' if not complete_file_contents else f'Wrote {result['bytes_written']} bytes'} at {filepath} in {elapsed:.2f}s",
|
||||
title="💾 File Write",
|
||||
border_style="bright_green",
|
||||
)
|
||||
|
|
|
|||
|
|
@ -26,12 +26,12 @@ def test_shell_pipeline():
|
|||
|
||||
def test_stderr_capture():
|
||||
"""Test that stderr is properly captured in combined output."""
|
||||
# Use a command that definitely writes to stderr
|
||||
# Use a command that definitely writes to stderr.
|
||||
output, retcode = run_interactive_command(
|
||||
["/bin/bash", "-c", "ls /nonexistent/path"]
|
||||
)
|
||||
assert b"No such file or directory" in output
|
||||
assert retcode != 0 # ls returns 0 upon success
|
||||
assert retcode != 0 # ls returns non-zero on failure.
|
||||
|
||||
|
||||
def test_command_not_found():
|
||||
|
|
@ -50,7 +50,8 @@ def test_interactive_command():
|
|||
"""Test running an interactive command.
|
||||
|
||||
This test verifies that output appears in real-time using process substitution.
|
||||
We use a command that prints to both stdout and stderr to verify capture."""
|
||||
We use a command that prints to both stdout and stderr.
|
||||
"""
|
||||
output, retcode = run_interactive_command(
|
||||
["/bin/bash", "-c", "echo stdout; echo stderr >&2"]
|
||||
)
|
||||
|
|
@ -62,29 +63,41 @@ def test_interactive_command():
|
|||
def test_large_output():
|
||||
"""Test handling of commands that produce large output."""
|
||||
# Generate a large output with predictable content
|
||||
cmd = 'for i in {1..10000}; do echo "Line $i of test output"; done'
|
||||
# Each line will be approximately 30 bytes
|
||||
cmd = 'for i in {1..1000}; do echo "Line $i of test output"; done'
|
||||
output, retcode = run_interactive_command(["/bin/bash", "-c", cmd])
|
||||
# Clean up any leading artifacts
|
||||
output_cleaned = output.lstrip(b"^D")
|
||||
# Verify the output size is limited to 8000 bytes
|
||||
assert (
|
||||
len(output_cleaned) <= 8000
|
||||
), f"Output exceeded 8000 bytes: {len(output_cleaned)} bytes"
|
||||
# Verify we have the last lines (should contain the highest numbers)
|
||||
assert b"Line 1000" in output_cleaned, "Missing last line of output"
|
||||
assert retcode == 0
|
||||
|
||||
# Clean up specific artifacts (e.g., ^D)
|
||||
output_cleaned = output.lstrip(b"^D") # Remove the leading ^D if present
|
||||
|
||||
# Split and filter lines
|
||||
lines = [
|
||||
line.strip()
|
||||
for line in output_cleaned.splitlines()
|
||||
if b"Script" not in line and line.strip()
|
||||
]
|
||||
def test_byte_limit():
|
||||
"""Test that output is properly limited to 8000 bytes."""
|
||||
# Create a string that's definitely over 8000 bytes
|
||||
# Each line will be about 80 bytes
|
||||
cmd = 'for i in {1..200}; do printf "%04d: %s\\n" "$i" "This is a line with padding to ensure we go over the byte limit quickly"; done'
|
||||
output, retcode = run_interactive_command(["/bin/bash", "-c", cmd])
|
||||
output_cleaned = output.lstrip(b"^D")
|
||||
|
||||
# Verify we got all 10000 lines
|
||||
assert len(lines) == 10000, f"Expected 10000 lines, but got {len(lines)}"
|
||||
# Verify exact 8000 byte limit
|
||||
assert (
|
||||
len(output_cleaned) <= 8000
|
||||
), f"Output exceeded 8000 bytes: {len(output_cleaned)} bytes"
|
||||
|
||||
# Verify content of some lines
|
||||
assert lines[0] == b"Line 1 of test output", f"Unexpected line: {lines[0]}"
|
||||
assert lines[999] == b"Line 1000 of test output", f"Unexpected line: {lines[999]}"
|
||||
assert lines[-1] == b"Line 10000 of test output", f"Unexpected line: {lines[-1]}"
|
||||
# Get the last line number from the output
|
||||
last_line = output_cleaned.splitlines()[-1]
|
||||
last_num = int(last_line.split(b":")[0])
|
||||
|
||||
# Verify return code
|
||||
assert retcode == 0, f"Unexpected return code: {retcode}"
|
||||
# Verify we have a high number in the last line (should be near 200)
|
||||
assert last_num > 150, f"Expected last line number to be near 200, got {last_num}"
|
||||
|
||||
assert retcode == 0
|
||||
|
||||
|
||||
def test_unicode_handling():
|
||||
|
|
@ -109,7 +122,6 @@ def test_multiple_commands():
|
|||
|
||||
def test_cat_medium_file():
|
||||
"""Test that cat command properly captures output for medium-length files."""
|
||||
# Create a temporary file with known content
|
||||
with tempfile.NamedTemporaryFile(mode="w", delete=False) as f:
|
||||
for i in range(500):
|
||||
f.write(f"This is test line {i}\n")
|
||||
|
|
@ -119,33 +131,39 @@ def test_cat_medium_file():
|
|||
output, retcode = run_interactive_command(
|
||||
["/bin/bash", "-c", f"cat {temp_path}"]
|
||||
)
|
||||
# Split by newlines and filter out script header/footer lines
|
||||
output_cleaned = output.lstrip(b"^D")
|
||||
lines = [
|
||||
line
|
||||
for line in output.splitlines()
|
||||
for line in output_cleaned.splitlines()
|
||||
if b"Script" not in line and line.strip()
|
||||
]
|
||||
assert len(lines) == 500
|
||||
assert retcode == 0
|
||||
|
||||
# Verify content integrity by checking first and last lines
|
||||
assert b"This is test line 0" in lines[0]
|
||||
assert b"This is test line 499" in lines[-1]
|
||||
# With 8000 byte limit, we expect to see the last portion of lines
|
||||
# The exact number may vary due to terminal settings, but we should
|
||||
# at least have the last lines of the file
|
||||
assert (
|
||||
len(lines) >= 90
|
||||
), f"Expected at least 90 lines due to 8000 byte limit, got {len(lines)}"
|
||||
|
||||
# Most importantly, verify we have the last lines
|
||||
last_line = lines[-1].decode("utf-8")
|
||||
assert (
|
||||
"This is test line 499" in last_line
|
||||
), f"Expected last line to be 499, got: {last_line}"
|
||||
|
||||
assert retcode == 0
|
||||
finally:
|
||||
os.unlink(temp_path)
|
||||
|
||||
|
||||
def test_realtime_output():
|
||||
"""Test that output appears in real-time and is captured correctly."""
|
||||
# Create a command that sleeps briefly between outputs
|
||||
# Create a command that sleeps briefly between outputs.
|
||||
cmd = "echo 'first'; sleep 0.1; echo 'second'; sleep 0.1; echo 'third'"
|
||||
output, retcode = run_interactive_command(["/bin/bash", "-c", cmd])
|
||||
|
||||
# Filter out script header/footer lines
|
||||
lines = [
|
||||
line for line in output.splitlines() if b"Script" not in line and line.strip()
|
||||
]
|
||||
|
||||
assert b"first" in lines[0]
|
||||
assert b"second" in lines[1]
|
||||
assert b"third" in lines[2]
|
||||
|
|
@ -154,16 +172,10 @@ def test_realtime_output():
|
|||
|
||||
def test_tty_available():
|
||||
"""Test that commands have access to a TTY."""
|
||||
# Run the tty command
|
||||
output, retcode = run_interactive_command(["/bin/bash", "-c", "tty"])
|
||||
|
||||
# Clean up specific artifacts (e.g., ^D)
|
||||
output_cleaned = output.lstrip(b"^D") # Remove leading ^D if present
|
||||
|
||||
# Debug: Print cleaned output
|
||||
output_cleaned = output.lstrip(b"^D")
|
||||
print(f"Cleaned TTY Output: {output_cleaned}")
|
||||
|
||||
# Check if the output contains a valid TTY path
|
||||
# Check if the output contains a valid TTY path.
|
||||
assert (
|
||||
b"/dev/pts/" in output_cleaned or b"/dev/ttys" in output_cleaned
|
||||
), f"Unexpected TTY output: {output_cleaned}"
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import os
|
||||
from dataclasses import dataclass
|
||||
from unittest import mock
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
import pytest
|
||||
|
|
@ -12,10 +13,12 @@ from ra_aid.agents.ciayn_agent import CiaynAgent
|
|||
from ra_aid.env import validate_environment
|
||||
from ra_aid.llm import (
|
||||
create_llm_client,
|
||||
get_available_openai_models,
|
||||
get_env_var,
|
||||
get_provider_config,
|
||||
initialize_expert_llm,
|
||||
initialize_llm,
|
||||
select_expert_model,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -55,7 +58,11 @@ def test_initialize_expert_defaults(clean_env, mock_openai, monkeypatch):
|
|||
_llm = initialize_expert_llm("openai", "o1")
|
||||
|
||||
mock_openai.assert_called_once_with(
|
||||
api_key="test-key", model="o1", reasoning_effort="high"
|
||||
api_key="test-key",
|
||||
model="o1",
|
||||
reasoning_effort="high",
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -69,6 +76,8 @@ def test_initialize_expert_openai_custom(clean_env, mock_openai, monkeypatch):
|
|||
model="gpt-4-preview",
|
||||
temperature=0,
|
||||
reasoning_effort="high",
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -78,7 +87,11 @@ def test_initialize_expert_gemini(clean_env, mock_gemini, monkeypatch):
|
|||
_llm = initialize_expert_llm("gemini", "gemini-2.0-flash-thinking-exp-1219")
|
||||
|
||||
mock_gemini.assert_called_once_with(
|
||||
api_key="test-key", model="gemini-2.0-flash-thinking-exp-1219", temperature=0
|
||||
api_key="test-key",
|
||||
model="gemini-2.0-flash-thinking-exp-1219",
|
||||
temperature=0,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -88,7 +101,11 @@ def test_initialize_expert_anthropic(clean_env, mock_anthropic, monkeypatch):
|
|||
_llm = initialize_expert_llm("anthropic", "claude-3")
|
||||
|
||||
mock_anthropic.assert_called_once_with(
|
||||
api_key="test-key", model_name="claude-3", temperature=0
|
||||
api_key="test-key",
|
||||
model_name="claude-3",
|
||||
temperature=0,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -102,6 +119,8 @@ def test_initialize_expert_openrouter(clean_env, mock_openai, monkeypatch):
|
|||
base_url="https://openrouter.ai/api/v1",
|
||||
model="models/mistral-large",
|
||||
temperature=0,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -116,6 +135,8 @@ def test_initialize_expert_openai_compatible(clean_env, mock_openai, monkeypatch
|
|||
base_url="http://test-url",
|
||||
model="local-model",
|
||||
temperature=0,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -146,38 +167,55 @@ def test_estimate_tokens():
|
|||
def test_initialize_openai(clean_env, mock_openai):
|
||||
"""Test OpenAI provider initialization"""
|
||||
os.environ["OPENAI_API_KEY"] = "test-key"
|
||||
_model = initialize_llm("openai", "gpt-4")
|
||||
_model = initialize_llm("openai", "gpt-4", temperature=0.7)
|
||||
|
||||
mock_openai.assert_called_once_with(api_key="test-key", model="gpt-4")
|
||||
mock_openai.assert_called_once_with(
|
||||
api_key="test-key", model="gpt-4", temperature=0.7, timeout=180, max_retries=5
|
||||
)
|
||||
|
||||
|
||||
def test_initialize_gemini(clean_env, mock_gemini):
|
||||
"""Test Gemini provider initialization"""
|
||||
os.environ["GEMINI_API_KEY"] = "test-key"
|
||||
_model = initialize_llm("gemini", "gemini-2.0-flash-thinking-exp-1219")
|
||||
_model = initialize_llm(
|
||||
"gemini", "gemini-2.0-flash-thinking-exp-1219", temperature=0.7
|
||||
)
|
||||
|
||||
mock_gemini.assert_called_once_with(
|
||||
api_key="test-key", model="gemini-2.0-flash-thinking-exp-1219"
|
||||
mock_gemini.assert_called_with(
|
||||
api_key="test-key",
|
||||
model="gemini-2.0-flash-thinking-exp-1219",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
def test_initialize_anthropic(clean_env, mock_anthropic):
|
||||
"""Test Anthropic provider initialization"""
|
||||
os.environ["ANTHROPIC_API_KEY"] = "test-key"
|
||||
_model = initialize_llm("anthropic", "claude-3")
|
||||
_model = initialize_llm("anthropic", "claude-3", temperature=0.7)
|
||||
|
||||
mock_anthropic.assert_called_once_with(api_key="test-key", model_name="claude-3")
|
||||
mock_anthropic.assert_called_with(
|
||||
api_key="test-key",
|
||||
model_name="claude-3",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
def test_initialize_openrouter(clean_env, mock_openai):
|
||||
"""Test OpenRouter provider initialization"""
|
||||
os.environ["OPENROUTER_API_KEY"] = "test-key"
|
||||
_model = initialize_llm("openrouter", "mistral-large")
|
||||
_model = initialize_llm("openrouter", "mistral-large", temperature=0.7)
|
||||
|
||||
mock_openai.assert_called_once_with(
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
model="mistral-large",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -185,24 +223,22 @@ def test_initialize_openai_compatible(clean_env, mock_openai):
|
|||
"""Test OpenAI-compatible provider initialization"""
|
||||
os.environ["OPENAI_API_KEY"] = "test-key"
|
||||
os.environ["OPENAI_API_BASE"] = "https://custom-endpoint/v1"
|
||||
_model = initialize_llm("openai-compatible", "local-model")
|
||||
_model = initialize_llm("openai-compatible", "local-model", temperature=0.3)
|
||||
|
||||
mock_openai.assert_called_once_with(
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://custom-endpoint/v1",
|
||||
model="local-model",
|
||||
temperature=0.3,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
def test_initialize_unsupported_provider(clean_env):
|
||||
"""Test initialization with unsupported provider raises ValueError"""
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
initialize_llm("unsupported", "model")
|
||||
assert (
|
||||
str(exc_info.value)
|
||||
== "Missing required environment variable for provider: unsupported"
|
||||
)
|
||||
with pytest.raises(ValueError, match=r"Unsupported provider: unknown"):
|
||||
initialize_llm("unknown", "model")
|
||||
|
||||
|
||||
def test_temperature_defaults(clean_env, mock_openai, mock_anthropic, mock_gemini):
|
||||
|
|
@ -211,24 +247,46 @@ def test_temperature_defaults(clean_env, mock_openai, mock_anthropic, mock_gemin
|
|||
os.environ["ANTHROPIC_API_KEY"] = "test-key"
|
||||
os.environ["OPENAI_API_BASE"] = "http://test-url"
|
||||
os.environ["GEMINI_API_KEY"] = "test-key"
|
||||
|
||||
# Test openai-compatible default temperature
|
||||
initialize_llm("openai-compatible", "test-model")
|
||||
initialize_llm("openai-compatible", "test-model", temperature=0.3)
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="http://test-url",
|
||||
model="test-model",
|
||||
temperature=0.3,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
# Test other providers don't set temperature by default
|
||||
initialize_llm("openai", "test-model")
|
||||
mock_openai.assert_called_with(api_key="test-key", model="test-model")
|
||||
# Test error when no temperature provided for models that support it
|
||||
with pytest.raises(ValueError, match="Temperature must be provided for model"):
|
||||
initialize_llm("openai", "test-model")
|
||||
|
||||
initialize_llm("anthropic", "test-model")
|
||||
mock_anthropic.assert_called_with(api_key="test-key", model_name="test-model")
|
||||
with pytest.raises(ValueError, match="Temperature must be provided for model"):
|
||||
initialize_llm("anthropic", "test-model")
|
||||
|
||||
initialize_llm("gemini", "test-model")
|
||||
mock_gemini.assert_called_with(api_key="test-key", model="test-model")
|
||||
with pytest.raises(ValueError, match="Temperature must be provided for model"):
|
||||
initialize_llm("gemini", "test-model")
|
||||
|
||||
# Test expert models don't require temperature
|
||||
initialize_expert_llm("openai", "o1")
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
model="o1",
|
||||
reasoning_effort="high",
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
initialize_expert_llm("openai", "o1-mini")
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
model="o1-mini",
|
||||
reasoning_effort="high",
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
def test_explicit_temperature(clean_env, mock_openai, mock_anthropic, mock_gemini):
|
||||
|
|
@ -243,19 +301,31 @@ def test_explicit_temperature(clean_env, mock_openai, mock_anthropic, mock_gemin
|
|||
# Test OpenAI
|
||||
initialize_llm("openai", "test-model", temperature=test_temp)
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key", model="test-model", temperature=test_temp
|
||||
api_key="test-key",
|
||||
model="test-model",
|
||||
temperature=test_temp,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
# Test Gemini
|
||||
initialize_llm("gemini", "test-model", temperature=test_temp)
|
||||
mock_gemini.assert_called_with(
|
||||
api_key="test-key", model="test-model", temperature=test_temp
|
||||
api_key="test-key",
|
||||
model="test-model",
|
||||
temperature=test_temp,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
# Test Anthropic
|
||||
initialize_llm("anthropic", "test-model", temperature=test_temp)
|
||||
mock_anthropic.assert_called_with(
|
||||
api_key="test-key", model_name="test-model", temperature=test_temp
|
||||
api_key="test-key",
|
||||
model_name="test-model",
|
||||
temperature=test_temp,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
# Test OpenRouter
|
||||
|
|
@ -265,9 +335,68 @@ def test_explicit_temperature(clean_env, mock_openai, mock_anthropic, mock_gemin
|
|||
base_url="https://openrouter.ai/api/v1",
|
||||
model="test-model",
|
||||
temperature=test_temp,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
def test_get_available_openai_models_success():
|
||||
"""Test successful retrieval of OpenAI models."""
|
||||
mock_model = Mock()
|
||||
mock_model.id = "gpt-4"
|
||||
mock_models = Mock()
|
||||
mock_models.data = [mock_model]
|
||||
|
||||
with mock.patch("ra_aid.llm.OpenAI") as mock_client:
|
||||
mock_client.return_value.models.list.return_value = mock_models
|
||||
models = get_available_openai_models()
|
||||
assert models == ["gpt-4"]
|
||||
mock_client.return_value.models.list.assert_called_once()
|
||||
|
||||
|
||||
def test_get_available_openai_models_failure():
|
||||
"""Test graceful handling of model retrieval failure."""
|
||||
with mock.patch("ra_aid.llm.OpenAI") as mock_client:
|
||||
mock_client.return_value.models.list.side_effect = Exception("API Error")
|
||||
models = get_available_openai_models()
|
||||
assert models == []
|
||||
mock_client.return_value.models.list.assert_called_once()
|
||||
|
||||
|
||||
def test_select_expert_model_explicit():
|
||||
"""Test model selection with explicitly specified model."""
|
||||
model = select_expert_model("openai", "gpt-4")
|
||||
assert model == "gpt-4"
|
||||
|
||||
|
||||
def test_select_expert_model_non_openai():
|
||||
"""Test model selection for non-OpenAI provider."""
|
||||
model = select_expert_model("anthropic", None)
|
||||
assert model is None
|
||||
|
||||
|
||||
def test_select_expert_model_priority():
|
||||
"""Test model selection follows priority order."""
|
||||
available_models = ["gpt-4", "o1", "o3-mini"]
|
||||
|
||||
with mock.patch(
|
||||
"ra_aid.llm.get_available_openai_models", return_value=available_models
|
||||
):
|
||||
model = select_expert_model("openai")
|
||||
assert model == "o3-mini"
|
||||
|
||||
|
||||
def test_select_expert_model_no_match():
|
||||
"""Test model selection when no priority models available."""
|
||||
available_models = ["gpt-4", "gpt-3.5"]
|
||||
|
||||
with mock.patch(
|
||||
"ra_aid.llm.get_available_openai_models", return_value=available_models
|
||||
):
|
||||
model = select_expert_model("openai")
|
||||
assert model is None
|
||||
|
||||
|
||||
def test_temperature_validation(clean_env, mock_openai):
|
||||
"""Test temperature validation in command line arguments."""
|
||||
from ra_aid.__main__ import parse_arguments
|
||||
|
|
@ -292,14 +421,12 @@ def test_provider_name_validation():
|
|||
for provider in providers:
|
||||
try:
|
||||
with patch("ra_aid.llm.ChatOpenAI"), patch("ra_aid.llm.ChatAnthropic"):
|
||||
initialize_llm(provider, "test-model")
|
||||
except ValueError:
|
||||
pytest.fail(f"Valid provider {provider} raised ValueError")
|
||||
|
||||
# Test case sensitivity
|
||||
with patch("ra_aid.llm.ChatOpenAI"):
|
||||
with pytest.raises(ValueError):
|
||||
initialize_llm("OpenAI", "test-model")
|
||||
initialize_llm(provider, "test-model", temperature=0.7)
|
||||
except ValueError as e:
|
||||
if "Temperature must be provided" not in str(e):
|
||||
pytest.fail(
|
||||
f"Valid provider {provider} raised unexpected ValueError: {e}"
|
||||
)
|
||||
|
||||
|
||||
def test_initialize_llm_cross_provider(
|
||||
|
|
@ -308,23 +435,31 @@ def test_initialize_llm_cross_provider(
|
|||
"""Test initializing different providers in sequence."""
|
||||
# Initialize OpenAI
|
||||
monkeypatch.setenv("OPENAI_API_KEY", "openai-key")
|
||||
_llm1 = initialize_llm("openai", "gpt-4")
|
||||
_llm1 = initialize_llm("openai", "gpt-4", temperature=0.7)
|
||||
mock_openai.assert_called_with(
|
||||
api_key="openai-key", model="gpt-4", temperature=0.7, timeout=180, max_retries=5
|
||||
)
|
||||
|
||||
# Initialize Anthropic
|
||||
monkeypatch.setenv("ANTHROPIC_API_KEY", "anthropic-key")
|
||||
_llm2 = initialize_llm("anthropic", "claude-3")
|
||||
_llm2 = initialize_llm("anthropic", "claude-3", temperature=0.7)
|
||||
mock_anthropic.assert_called_with(
|
||||
api_key="anthropic-key",
|
||||
model_name="claude-3",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
# Initialize Gemini
|
||||
monkeypatch.setenv("GEMINI_API_KEY", "gemini-key")
|
||||
_llm3 = initialize_llm("gemini", "gemini-2.0-flash-thinking-exp-1219")
|
||||
|
||||
# Verify both were initialized correctly
|
||||
mock_openai.assert_called_once_with(api_key="openai-key", model="gpt-4")
|
||||
mock_anthropic.assert_called_once_with(
|
||||
api_key="anthropic-key", model_name="claude-3"
|
||||
)
|
||||
mock_gemini.assert_called_once_with(
|
||||
api_key="gemini-key", model="gemini-2.0-flash-thinking-exp-1219"
|
||||
_llm3 = initialize_llm("gemini", "gemini-pro", temperature=0.7)
|
||||
mock_gemini.assert_called_with(
|
||||
api_key="gemini-key",
|
||||
model="gemini-pro",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -359,7 +494,11 @@ def test_environment_variable_precedence(clean_env, mock_openai, monkeypatch):
|
|||
# Test LLM client creation with expert mode
|
||||
_llm = create_llm_client("openai", "o1", is_expert=True)
|
||||
mock_openai.assert_called_with(
|
||||
api_key="expert-key", model="o1", reasoning_effort="high"
|
||||
api_key="expert-key",
|
||||
model="o1",
|
||||
reasoning_effort="high",
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
# Test environment validation
|
||||
|
|
@ -414,46 +553,25 @@ def test_initialize_deepseek(
|
|||
monkeypatch.setenv("DEEPSEEK_API_KEY", "test-key")
|
||||
|
||||
# Test with reasoner model
|
||||
_model = initialize_llm("deepseek", "deepseek-reasoner")
|
||||
_model = initialize_llm("deepseek", "deepseek-reasoner", temperature=0.7)
|
||||
mock_deepseek_reasoner.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://api.deepseek.com",
|
||||
temperature=1,
|
||||
model="deepseek-reasoner",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
# Test with non-reasoner model
|
||||
_model = initialize_llm("deepseek", "deepseek-chat")
|
||||
# Test with OpenAI-compatible model
|
||||
_model = initialize_llm("deepseek", "deepseek-chat", temperature=0.7)
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://api.deepseek.com",
|
||||
temperature=1,
|
||||
model="deepseek-chat",
|
||||
)
|
||||
|
||||
|
||||
def test_initialize_expert_deepseek(
|
||||
clean_env, mock_openai, mock_deepseek_reasoner, monkeypatch
|
||||
):
|
||||
"""Test expert DeepSeek provider initialization."""
|
||||
monkeypatch.setenv("EXPERT_DEEPSEEK_API_KEY", "test-key")
|
||||
|
||||
# Test with reasoner model
|
||||
_model = initialize_expert_llm("deepseek", "deepseek-reasoner")
|
||||
mock_deepseek_reasoner.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://api.deepseek.com",
|
||||
temperature=0,
|
||||
model="deepseek-reasoner",
|
||||
)
|
||||
|
||||
# Test with non-reasoner model
|
||||
_model = initialize_expert_llm("deepseek", "deepseek-chat")
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://api.deepseek.com",
|
||||
temperature=0,
|
||||
base_url="https://api.deepseek.com", # Updated to match implementation
|
||||
model="deepseek-chat",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -464,69 +582,12 @@ def test_initialize_openrouter_deepseek(
|
|||
monkeypatch.setenv("OPENROUTER_API_KEY", "test-key")
|
||||
|
||||
# Test with DeepSeek R1 model
|
||||
_model = initialize_llm("openrouter", "deepseek/deepseek-r1")
|
||||
_model = initialize_llm("openrouter", "deepseek/deepseek-r1", temperature=0.7)
|
||||
mock_deepseek_reasoner.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
temperature=1,
|
||||
model="deepseek/deepseek-r1",
|
||||
)
|
||||
|
||||
# Test with non-DeepSeek model
|
||||
_model = initialize_llm("openrouter", "mistral/mistral-large")
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
model="mistral/mistral-large",
|
||||
)
|
||||
|
||||
|
||||
def test_initialize_expert_openrouter_deepseek(
|
||||
clean_env, mock_openai, mock_deepseek_reasoner, monkeypatch
|
||||
):
|
||||
"""Test expert OpenRouter DeepSeek model initialization."""
|
||||
monkeypatch.setenv("EXPERT_OPENROUTER_API_KEY", "test-key")
|
||||
|
||||
# Test with DeepSeek R1 model via create_llm_client
|
||||
_model = create_llm_client("openrouter", "deepseek/deepseek-r1", is_expert=True)
|
||||
mock_deepseek_reasoner.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
temperature=0,
|
||||
model="deepseek/deepseek-r1",
|
||||
)
|
||||
|
||||
# Test with non-DeepSeek model
|
||||
_model = create_llm_client("openrouter", "mistral/mistral-large", is_expert=True)
|
||||
mock_openai.assert_called_with(
|
||||
api_key="test-key",
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
model="mistral/mistral-large",
|
||||
temperature=0,
|
||||
)
|
||||
|
||||
|
||||
def test_deepseek_environment_fallback(clean_env, mock_deepseek_reasoner, monkeypatch):
|
||||
"""Test DeepSeek environment variable fallback behavior."""
|
||||
# Test environment variable helper with fallback
|
||||
monkeypatch.setenv("DEEPSEEK_API_KEY", "base-key")
|
||||
assert get_env_var("DEEPSEEK_API_KEY", expert=True) == "base-key"
|
||||
|
||||
# Test provider config with fallback
|
||||
config = get_provider_config("deepseek", is_expert=True)
|
||||
assert config["api_key"] == "base-key"
|
||||
assert config["base_url"] == "https://api.deepseek.com"
|
||||
|
||||
# Test with expert key
|
||||
monkeypatch.setenv("EXPERT_DEEPSEEK_API_KEY", "expert-key")
|
||||
config = get_provider_config("deepseek", is_expert=True)
|
||||
assert config["api_key"] == "expert-key"
|
||||
|
||||
# Test client creation with expert key
|
||||
_model = create_llm_client("deepseek", "deepseek-reasoner", is_expert=True)
|
||||
mock_deepseek_reasoner.assert_called_with(
|
||||
api_key="expert-key",
|
||||
base_url="https://api.deepseek.com",
|
||||
temperature=0,
|
||||
model="deepseek-reasoner",
|
||||
temperature=0.7,
|
||||
timeout=180,
|
||||
max_retries=5,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -1,6 +1,10 @@
|
|||
import pytest
|
||||
|
||||
from ra_aid.tools.programmer import parse_aider_flags, run_programming_task
|
||||
from ra_aid.tools.programmer import (
|
||||
get_aider_executable,
|
||||
parse_aider_flags,
|
||||
run_programming_task,
|
||||
)
|
||||
|
||||
# Test cases for parse_aider_flags function
|
||||
test_cases = [
|
||||
|
|
@ -33,6 +37,37 @@ test_cases = [
|
|||
),
|
||||
("--yes-always", ["--yes-always"], "single flag with dashes"),
|
||||
("yes-always", ["--yes-always"], "single flag without dashes"),
|
||||
# New test cases for flags with values
|
||||
(
|
||||
"--analytics-log filename.json",
|
||||
["--analytics-log", "filename.json"],
|
||||
"flag with value",
|
||||
),
|
||||
(
|
||||
"--analytics-log filename.json, --model gpt4",
|
||||
["--analytics-log", "filename.json", "--model", "gpt4"],
|
||||
"multiple flags with values",
|
||||
),
|
||||
(
|
||||
"--dark-mode, --analytics-log filename.json",
|
||||
["--dark-mode", "--analytics-log", "filename.json"],
|
||||
"mix of simple flags and flags with values",
|
||||
),
|
||||
(
|
||||
" --dark-mode , --model gpt4 ",
|
||||
["--dark-mode", "--model", "gpt4"],
|
||||
"flags with values and extra whitespace",
|
||||
),
|
||||
(
|
||||
"--analytics-log filename.json",
|
||||
["--analytics-log", "filename.json"],
|
||||
"multiple spaces between flag and value",
|
||||
),
|
||||
(
|
||||
"---dark-mode,----model gpt4",
|
||||
["--dark-mode", "--model", "gpt4"],
|
||||
"stripping extra dashes",
|
||||
),
|
||||
]
|
||||
|
||||
|
||||
|
|
@ -56,9 +91,103 @@ def test_aider_config_flag(mocker):
|
|||
"ra_aid.tools.programmer.run_interactive_command", return_value=(b"", 0)
|
||||
)
|
||||
|
||||
run_programming_task("test instruction")
|
||||
run_programming_task.invoke({"instructions": "test instruction"})
|
||||
|
||||
args = mock_run.call_args[0][0] # Get the first positional arg (command list)
|
||||
assert "--config" in args
|
||||
config_index = args.index("--config")
|
||||
assert args[config_index + 1] == "/path/to/config.yml"
|
||||
|
||||
|
||||
def test_path_normalization_and_deduplication(mocker, tmp_path):
|
||||
"""Test path normalization and deduplication in run_programming_task."""
|
||||
# Create a temporary test file
|
||||
test_file = tmp_path / "test.py"
|
||||
test_file.write_text("")
|
||||
new_file = tmp_path / "new.py"
|
||||
|
||||
# Mock dependencies
|
||||
mocker.patch("ra_aid.tools.programmer._global_memory", {"related_files": {}})
|
||||
mocker.patch(
|
||||
"ra_aid.tools.programmer.get_aider_executable", return_value="/path/to/aider"
|
||||
)
|
||||
mock_run = mocker.patch(
|
||||
"ra_aid.tools.programmer.run_interactive_command", return_value=(b"", 0)
|
||||
)
|
||||
|
||||
# Test duplicate paths
|
||||
run_programming_task.invoke(
|
||||
{
|
||||
"instructions": "test instruction",
|
||||
"files": [str(test_file), str(test_file)], # Same path twice
|
||||
}
|
||||
)
|
||||
|
||||
# Get the command list passed to run_interactive_command
|
||||
cmd_args = mock_run.call_args[0][0]
|
||||
# Count occurrences of test_file path in command
|
||||
test_file_count = sum(1 for arg in cmd_args if arg == str(test_file))
|
||||
assert test_file_count == 1, "Expected exactly one instance of test_file path"
|
||||
|
||||
# Test mixed paths
|
||||
run_programming_task.invoke(
|
||||
{
|
||||
"instructions": "test instruction",
|
||||
"files": [str(test_file), str(new_file)], # Two different paths
|
||||
}
|
||||
)
|
||||
|
||||
# Get the command list from the second call
|
||||
cmd_args = mock_run.call_args[0][0]
|
||||
# Verify both paths are present exactly once
|
||||
assert (
|
||||
sum(1 for arg in cmd_args if arg == str(test_file)) == 1
|
||||
), "Expected one instance of test_file"
|
||||
assert (
|
||||
sum(1 for arg in cmd_args if arg == str(new_file)) == 1
|
||||
), "Expected one instance of new_file"
|
||||
|
||||
|
||||
def test_get_aider_executable(mocker):
|
||||
"""Test the get_aider_executable function."""
|
||||
mock_sys = mocker.patch("ra_aid.tools.programmer.sys")
|
||||
mock_path = mocker.patch("ra_aid.tools.programmer.Path")
|
||||
mock_os = mocker.patch("ra_aid.tools.programmer.os")
|
||||
|
||||
# Mock sys.executable and platform
|
||||
mock_sys.executable = "/path/to/venv/bin/python"
|
||||
mock_sys.platform = "linux"
|
||||
|
||||
# Mock Path().parent and exists()
|
||||
mock_path_instance = mocker.MagicMock()
|
||||
mock_path.return_value = mock_path_instance
|
||||
mock_parent = mocker.MagicMock()
|
||||
mock_path_instance.parent = mock_parent
|
||||
mock_aider = mocker.MagicMock()
|
||||
mock_parent.__truediv__.return_value = mock_aider
|
||||
mock_aider.exists.return_value = True
|
||||
|
||||
# Mock os.access to return True
|
||||
mock_os.access.return_value = True
|
||||
mock_os.X_OK = 1 # Mock the execute permission constant
|
||||
|
||||
# Test happy path on Linux
|
||||
aider_path = get_aider_executable()
|
||||
assert aider_path == str(mock_aider)
|
||||
mock_parent.__truediv__.assert_called_with("aider")
|
||||
|
||||
# Test Windows path
|
||||
mock_sys.platform = "win32"
|
||||
aider_path = get_aider_executable()
|
||||
mock_parent.__truediv__.assert_called_with("aider.exe")
|
||||
|
||||
# Test executable not found
|
||||
mock_aider.exists.return_value = False
|
||||
with pytest.raises(RuntimeError, match="Could not find aider executable"):
|
||||
get_aider_executable()
|
||||
|
||||
# Test not executable
|
||||
mock_aider.exists.return_value = True
|
||||
mock_os.access.return_value = False
|
||||
with pytest.raises(RuntimeError, match="is not executable"):
|
||||
get_aider_executable()
|
||||
|
|
|
|||
|
|
@ -464,6 +464,35 @@ def test_related_files_formatting(reset_memory, tmp_path):
|
|||
assert get_memory_value("related_files") == ""
|
||||
|
||||
|
||||
def test_emit_related_files_path_normalization(reset_memory, tmp_path):
|
||||
"""Test that emit_related_files fails to detect duplicates with non-normalized paths"""
|
||||
# Create a test file
|
||||
test_file = tmp_path / "file.txt"
|
||||
test_file.write_text("test content")
|
||||
|
||||
# Change to the temp directory so relative paths work
|
||||
import os
|
||||
|
||||
original_dir = os.getcwd()
|
||||
os.chdir(tmp_path)
|
||||
|
||||
try:
|
||||
# Add file with absolute path
|
||||
result1 = emit_related_files.invoke({"files": ["file.txt"]})
|
||||
assert "File ID #0:" in result1
|
||||
|
||||
# Add same file with relative path - should get same ID due to path normalization
|
||||
result2 = emit_related_files.invoke({"files": ["./file.txt"]})
|
||||
assert "File ID #0:" in result2 # Should reuse ID since it's the same file
|
||||
|
||||
# Verify only one normalized path entry exists
|
||||
assert len(_global_memory["related_files"]) == 1
|
||||
assert os.path.abspath("file.txt") in _global_memory["related_files"].values()
|
||||
finally:
|
||||
# Restore original directory
|
||||
os.chdir(original_dir)
|
||||
|
||||
|
||||
def test_key_snippets_integration(reset_memory, tmp_path):
|
||||
"""Integration test for key snippets functionality"""
|
||||
# Create test files
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@ from unittest.mock import patch
|
|||
|
||||
import pytest
|
||||
|
||||
from ra_aid.tools.write_file import write_file_tool
|
||||
from ra_aid.tools.write_file import put_complete_file_contents
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
|
|
@ -19,7 +19,9 @@ def test_basic_write_functionality(temp_test_dir):
|
|||
test_file = temp_test_dir / "test.txt"
|
||||
content = "Hello, World!\nTest content"
|
||||
|
||||
result = write_file_tool.invoke({"filepath": str(test_file), "content": content})
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(test_file), "complete_file_contents": content}
|
||||
)
|
||||
|
||||
# Verify file contents
|
||||
assert test_file.read_text() == content
|
||||
|
|
@ -29,7 +31,8 @@ def test_basic_write_functionality(temp_test_dir):
|
|||
assert result["success"] is True
|
||||
assert result["filepath"] == str(test_file)
|
||||
assert result["bytes_written"] == len(content.encode("utf-8"))
|
||||
assert "Operation completed" in result["message"]
|
||||
assert "Successfully wrote" in result["message"]
|
||||
assert "bytes" in result["message"]
|
||||
|
||||
|
||||
def test_directory_creation(temp_test_dir):
|
||||
|
|
@ -38,7 +41,9 @@ def test_directory_creation(temp_test_dir):
|
|||
test_file = nested_dir / "test.txt"
|
||||
content = "Test content"
|
||||
|
||||
result = write_file_tool.invoke({"filepath": str(test_file), "content": content})
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(test_file), "complete_file_contents": content}
|
||||
)
|
||||
|
||||
assert test_file.exists()
|
||||
assert test_file.read_text() == content
|
||||
|
|
@ -51,15 +56,23 @@ def test_different_encodings(temp_test_dir):
|
|||
content = "Hello 世界" # Mixed ASCII and Unicode
|
||||
|
||||
# Test UTF-8
|
||||
result_utf8 = write_file_tool.invoke(
|
||||
{"filepath": str(test_file), "content": content, "encoding": "utf-8"}
|
||||
result_utf8 = put_complete_file_contents(
|
||||
{
|
||||
"filepath": str(test_file),
|
||||
"complete_file_contents": content,
|
||||
"encoding": "utf-8",
|
||||
}
|
||||
)
|
||||
assert result_utf8["success"] is True
|
||||
assert test_file.read_text(encoding="utf-8") == content
|
||||
|
||||
# Test UTF-16
|
||||
result_utf16 = write_file_tool.invoke(
|
||||
{"filepath": str(test_file), "content": content, "encoding": "utf-16"}
|
||||
result_utf16 = put_complete_file_contents(
|
||||
{
|
||||
"filepath": str(test_file),
|
||||
"complete_file_contents": content,
|
||||
"encoding": "utf-16",
|
||||
}
|
||||
)
|
||||
assert result_utf16["success"] is True
|
||||
assert test_file.read_text(encoding="utf-16") == content
|
||||
|
|
@ -71,8 +84,8 @@ def test_permission_error(mock_open_func, temp_test_dir):
|
|||
mock_open_func.side_effect = PermissionError("Permission denied")
|
||||
test_file = temp_test_dir / "noperm.txt"
|
||||
|
||||
result = write_file_tool.invoke(
|
||||
{"filepath": str(test_file), "content": "test content"}
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(test_file), "complete_file_contents": "test content"}
|
||||
)
|
||||
|
||||
assert result["success"] is False
|
||||
|
|
@ -86,8 +99,8 @@ def test_io_error(mock_open_func, temp_test_dir):
|
|||
mock_open_func.side_effect = IOError("IO Error occurred")
|
||||
test_file = temp_test_dir / "ioerror.txt"
|
||||
|
||||
result = write_file_tool.invoke(
|
||||
{"filepath": str(test_file), "content": "test content"}
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(test_file), "complete_file_contents": "test content"}
|
||||
)
|
||||
|
||||
assert result["success"] is False
|
||||
|
|
@ -99,12 +112,26 @@ def test_empty_content(temp_test_dir):
|
|||
"""Test writing empty content to a file."""
|
||||
test_file = temp_test_dir / "empty.txt"
|
||||
|
||||
result = write_file_tool.invoke({"filepath": str(test_file), "content": ""})
|
||||
result = put_complete_file_contents({"filepath": str(test_file)})
|
||||
|
||||
assert test_file.exists()
|
||||
assert test_file.read_text() == ""
|
||||
assert result["success"] is True
|
||||
assert result["bytes_written"] == 0
|
||||
assert "initialized empty file" in result["message"].lower()
|
||||
|
||||
|
||||
def test_write_empty_file_default(temp_test_dir):
|
||||
"""Test creating an empty file using default parameter."""
|
||||
test_file = temp_test_dir / "empty_default.txt"
|
||||
|
||||
result = put_complete_file_contents({"filepath": str(test_file)})
|
||||
|
||||
assert test_file.exists()
|
||||
assert test_file.read_text() == ""
|
||||
assert result["success"] is True
|
||||
assert result["bytes_written"] == 0
|
||||
assert "initialized empty file" in result["message"].lower()
|
||||
|
||||
|
||||
def test_overwrite_existing_file(temp_test_dir):
|
||||
|
|
@ -116,8 +143,8 @@ def test_overwrite_existing_file(temp_test_dir):
|
|||
|
||||
# Overwrite with new content
|
||||
new_content = "New content"
|
||||
result = write_file_tool.invoke(
|
||||
{"filepath": str(test_file), "content": new_content}
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(test_file), "complete_file_contents": new_content}
|
||||
)
|
||||
|
||||
assert test_file.read_text() == new_content
|
||||
|
|
@ -130,7 +157,9 @@ def test_large_file_write(temp_test_dir):
|
|||
test_file = temp_test_dir / "large.txt"
|
||||
content = "Large content\n" * 1000 # Create substantial content
|
||||
|
||||
result = write_file_tool.invoke({"filepath": str(test_file), "content": content})
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(test_file), "complete_file_contents": content}
|
||||
)
|
||||
|
||||
assert test_file.exists()
|
||||
assert test_file.read_text() == content
|
||||
|
|
@ -143,8 +172,8 @@ def test_invalid_path_characters(temp_test_dir):
|
|||
"""Test handling of invalid path characters."""
|
||||
invalid_path = temp_test_dir / "invalid\0file.txt"
|
||||
|
||||
result = write_file_tool.invoke(
|
||||
{"filepath": str(invalid_path), "content": "test content"}
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(invalid_path), "complete_file_contents": "test content"}
|
||||
)
|
||||
|
||||
assert result["success"] is False
|
||||
|
|
@ -161,8 +190,8 @@ def test_write_to_readonly_directory(temp_test_dir):
|
|||
os.chmod(readonly_dir, 0o444)
|
||||
|
||||
try:
|
||||
result = write_file_tool.invoke(
|
||||
{"filepath": str(test_file), "content": "test content"}
|
||||
result = put_complete_file_contents(
|
||||
{"filepath": str(test_file), "complete_file_contents": "test content"}
|
||||
)
|
||||
assert result["success"] is False
|
||||
assert "Permission" in result["message"]
|
||||
|
|
|
|||
|
|
@ -56,6 +56,102 @@ def sample_git_repo(empty_git_repo):
|
|||
return empty_git_repo
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def git_repo_with_untracked(sample_git_repo):
|
||||
"""Create a git repository with both tracked and untracked files."""
|
||||
# Create untracked files
|
||||
untracked_files = ["untracked.txt", "src/untracked.py", "docs/draft.md"]
|
||||
|
||||
for file_path in untracked_files:
|
||||
full_path = sample_git_repo / file_path
|
||||
full_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
full_path.write_text(f"Untracked content of {file_path}")
|
||||
|
||||
return sample_git_repo
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def git_repo_with_ignores(git_repo_with_untracked):
|
||||
"""Create a git repository with .gitignore rules."""
|
||||
# Create .gitignore file
|
||||
gitignore_content = """
|
||||
# Python
|
||||
__pycache__/
|
||||
*.pyc
|
||||
|
||||
# Project specific
|
||||
*.log
|
||||
temp/
|
||||
ignored.txt
|
||||
docs/draft.md
|
||||
"""
|
||||
gitignore_path = git_repo_with_untracked / ".gitignore"
|
||||
gitignore_path.write_text(gitignore_content)
|
||||
|
||||
# Add and commit .gitignore first
|
||||
subprocess.run(["git", "add", ".gitignore"], cwd=git_repo_with_untracked)
|
||||
subprocess.run(
|
||||
["git", "commit", "-m", "Add .gitignore"],
|
||||
cwd=git_repo_with_untracked,
|
||||
env={
|
||||
"GIT_AUTHOR_NAME": "Test",
|
||||
"GIT_AUTHOR_EMAIL": "test@example.com",
|
||||
"GIT_COMMITTER_NAME": "Test",
|
||||
"GIT_COMMITTER_EMAIL": "test@example.com",
|
||||
},
|
||||
)
|
||||
|
||||
# Create some ignored files
|
||||
ignored_files = [
|
||||
"ignored.txt",
|
||||
"temp/temp.txt",
|
||||
"src/__pycache__/main.cpython-39.pyc",
|
||||
]
|
||||
|
||||
for file_path in ignored_files:
|
||||
full_path = git_repo_with_untracked / file_path
|
||||
full_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
full_path.write_text(f"Ignored content of {file_path}")
|
||||
|
||||
return git_repo_with_untracked
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def git_repo_with_aider_files(sample_git_repo):
|
||||
"""Create a git repository with .aider files that should be ignored."""
|
||||
# Create .aider files
|
||||
aider_files = [
|
||||
".aider.chat.history.md",
|
||||
".aider.input.history",
|
||||
".aider.tags.cache.v3/some_file",
|
||||
"src/.aider.local.settings",
|
||||
]
|
||||
|
||||
# Create regular files
|
||||
regular_files = ["main.cpp", "src/helper.cpp"]
|
||||
|
||||
# Create all files
|
||||
for file_path in aider_files + regular_files:
|
||||
full_path = sample_git_repo / file_path
|
||||
full_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
full_path.write_text(f"Content of {file_path}")
|
||||
|
||||
# Add all files (both .aider and regular) to git
|
||||
subprocess.run(["git", "add", "."], cwd=sample_git_repo)
|
||||
subprocess.run(
|
||||
["git", "commit", "-m", "Add files including .aider"],
|
||||
cwd=sample_git_repo,
|
||||
env={
|
||||
"GIT_AUTHOR_NAME": "Test",
|
||||
"GIT_AUTHOR_EMAIL": "test@example.com",
|
||||
"GIT_COMMITTER_NAME": "Test",
|
||||
"GIT_COMMITTER_EMAIL": "test@example.com",
|
||||
},
|
||||
)
|
||||
|
||||
return sample_git_repo
|
||||
|
||||
|
||||
def test_is_git_repo(sample_git_repo, tmp_path_factory):
|
||||
"""Test git repository detection."""
|
||||
# Create a new directory that is not a git repository
|
||||
|
|
@ -248,39 +344,200 @@ def mock_is_git_repo():
|
|||
yield mock
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_os_path(monkeypatch):
|
||||
"""Mock os.path functions."""
|
||||
|
||||
def mock_exists(path):
|
||||
return True
|
||||
|
||||
def mock_isdir(path):
|
||||
return True
|
||||
|
||||
monkeypatch.setattr(os.path, "exists", mock_exists)
|
||||
monkeypatch.setattr(os.path, "isdir", mock_isdir)
|
||||
return monkeypatch
|
||||
|
||||
|
||||
@pytest.mark.parametrize("test_case", FILE_LISTING_TEST_CASES, ids=lambda x: x["name"])
|
||||
def test_get_file_listing(test_case, mock_subprocess, mock_is_git_repo):
|
||||
def test_get_file_listing(test_case, mock_subprocess, mock_is_git_repo, mock_os_path):
|
||||
"""Test get_file_listing with various inputs."""
|
||||
mock_subprocess.return_value = create_mock_process(test_case["git_output"])
|
||||
files, total = get_file_listing(DUMMY_PATH, limit=test_case["limit"])
|
||||
|
||||
assert files == test_case["expected_files"]
|
||||
assert total == test_case["expected_total"]
|
||||
|
||||
|
||||
def test_get_file_listing_non_git_repo(mock_is_git_repo):
|
||||
def test_get_file_listing_non_git_repo(mock_is_git_repo, mock_os_path):
|
||||
"""Test get_file_listing with non-git repository."""
|
||||
mock_is_git_repo.return_value = False
|
||||
files, total = get_file_listing(DUMMY_PATH)
|
||||
assert files == EMPTY_FILE_LIST
|
||||
assert total == EMPTY_FILE_TOTAL
|
||||
assert files == []
|
||||
assert total == 0
|
||||
|
||||
|
||||
def test_get_file_listing_git_error(mock_subprocess, mock_is_git_repo):
|
||||
def test_get_file_listing_git_error(mock_subprocess, mock_is_git_repo, mock_os_path):
|
||||
"""Test get_file_listing when git command fails."""
|
||||
mock_subprocess.side_effect = GitCommandError("Git command failed")
|
||||
with pytest.raises(GitCommandError):
|
||||
get_file_listing(DUMMY_PATH)
|
||||
|
||||
|
||||
def test_get_file_listing_permission_error(mock_subprocess, mock_is_git_repo):
|
||||
def test_get_file_listing_permission_error(
|
||||
mock_subprocess, mock_is_git_repo, mock_os_path
|
||||
):
|
||||
"""Test get_file_listing with permission error."""
|
||||
mock_subprocess.side_effect = PermissionError("Permission denied")
|
||||
with pytest.raises(DirectoryAccessError):
|
||||
get_file_listing(DUMMY_PATH)
|
||||
|
||||
|
||||
def test_get_file_listing_unexpected_error(mock_subprocess, mock_is_git_repo):
|
||||
def test_get_file_listing_unexpected_error(
|
||||
mock_subprocess, mock_is_git_repo, mock_os_path
|
||||
):
|
||||
"""Test get_file_listing with unexpected error."""
|
||||
mock_subprocess.side_effect = Exception("Unexpected error")
|
||||
with pytest.raises(FileListerError):
|
||||
get_file_listing(DUMMY_PATH)
|
||||
|
||||
|
||||
def test_get_file_listing_with_untracked(git_repo_with_untracked):
|
||||
"""Test that file listing includes both tracked and untracked files."""
|
||||
files, count = get_file_listing(str(git_repo_with_untracked))
|
||||
|
||||
# Check tracked files are present
|
||||
assert "README.md" in files
|
||||
assert "src/main.py" in files
|
||||
|
||||
# Check untracked files are present
|
||||
assert "untracked.txt" in files
|
||||
assert "src/untracked.py" in files
|
||||
|
||||
# Verify count includes both tracked and untracked
|
||||
expected_count = 8 # 5 tracked + 3 untracked (excluding .gitignore)
|
||||
assert count == expected_count
|
||||
|
||||
|
||||
def test_get_file_listing_with_untracked_and_limit(git_repo_with_untracked):
|
||||
"""Test that file listing with limit works correctly with untracked files."""
|
||||
limit = 3
|
||||
files, count = get_file_listing(str(git_repo_with_untracked), limit=limit)
|
||||
|
||||
# Total count should still be full count
|
||||
assert count == 8 # 5 tracked + 3 untracked (excluding .gitignore)
|
||||
|
||||
# Only limit number of files should be returned
|
||||
assert len(files) == limit
|
||||
|
||||
# Files should be sorted, so we can check first 3
|
||||
assert files == sorted(files)
|
||||
|
||||
|
||||
def test_get_file_listing_respects_gitignore(git_repo_with_ignores):
|
||||
"""Test that file listing respects .gitignore rules."""
|
||||
# First test with hidden files excluded (default)
|
||||
files, count = get_file_listing(str(git_repo_with_ignores))
|
||||
|
||||
# These files should be included (tracked or untracked but not ignored)
|
||||
assert "README.md" in files
|
||||
assert "src/main.py" in files
|
||||
assert "untracked.txt" in files
|
||||
assert "src/untracked.py" in files
|
||||
|
||||
# .gitignore should be excluded as it's hidden
|
||||
assert ".gitignore" not in files
|
||||
|
||||
# These files should be excluded (ignored)
|
||||
assert "ignored.txt" not in files
|
||||
assert "temp/temp.txt" not in files
|
||||
assert "src/__pycache__/main.cpython-39.pyc" not in files
|
||||
assert "docs/draft.md" not in files # Explicitly ignored in .gitignore
|
||||
|
||||
# Count should include non-ignored, non-hidden files
|
||||
expected_count = 7 # 4 tracked + 2 untracked (excluding .gitignore)
|
||||
assert count == expected_count
|
||||
|
||||
# Now test with hidden files included
|
||||
files, count = get_file_listing(str(git_repo_with_ignores), include_hidden=True)
|
||||
|
||||
# .gitignore should now be included
|
||||
assert ".gitignore" in files
|
||||
|
||||
# Count should include non-ignored files plus .gitignore
|
||||
expected_count = 8 # 5 tracked + 2 untracked + .gitignore
|
||||
assert count == expected_count
|
||||
|
||||
|
||||
def test_aider_files_excluded(git_repo_with_aider_files):
|
||||
"""Test that .aider files are excluded from the file listing."""
|
||||
files, count = get_file_listing(str(git_repo_with_aider_files))
|
||||
|
||||
# Regular files should be included
|
||||
assert "main.cpp" in files
|
||||
assert "src/helper.cpp" in files
|
||||
|
||||
# .aider files should be excluded
|
||||
assert ".aider.chat.history.md" not in files
|
||||
assert ".aider.input.history" not in files
|
||||
assert ".aider.tags.cache.v3/some_file" not in files
|
||||
assert "src/.aider.local.settings" not in files
|
||||
|
||||
# Only the regular files should be counted
|
||||
expected_count = 7 # 5 original files from sample_git_repo + 2 new regular files
|
||||
assert count == expected_count
|
||||
assert len(files) == expected_count
|
||||
|
||||
|
||||
def test_hidden_files_excluded_by_default(git_repo_with_aider_files):
|
||||
"""Test that hidden files are excluded by default."""
|
||||
# Create some hidden files
|
||||
hidden_files = [".config", ".env", "src/.local", ".gitattributes"]
|
||||
|
||||
# Create regular files
|
||||
regular_files = ["main.cpp", "src/helper.cpp"]
|
||||
|
||||
# Create all files
|
||||
for file_path in hidden_files + regular_files:
|
||||
full_path = git_repo_with_aider_files / file_path
|
||||
full_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
full_path.write_text(f"Content of {file_path}")
|
||||
|
||||
# Add all files to git
|
||||
subprocess.run(["git", "add", "."], cwd=git_repo_with_aider_files)
|
||||
subprocess.run(
|
||||
["git", "commit", "-m", "Add files including hidden files"],
|
||||
cwd=git_repo_with_aider_files,
|
||||
env={
|
||||
"GIT_AUTHOR_NAME": "Test",
|
||||
"GIT_AUTHOR_EMAIL": "test@example.com",
|
||||
"GIT_COMMITTER_NAME": "Test",
|
||||
"GIT_COMMITTER_EMAIL": "test@example.com",
|
||||
},
|
||||
)
|
||||
|
||||
# Test default behavior (hidden files excluded)
|
||||
files, count = get_file_listing(str(git_repo_with_aider_files))
|
||||
|
||||
# Regular files should be included
|
||||
assert "main.cpp" in files
|
||||
assert "src/helper.cpp" in files
|
||||
|
||||
# Hidden files should be excluded
|
||||
for hidden_file in hidden_files:
|
||||
assert hidden_file not in files
|
||||
|
||||
# Only regular files should be counted
|
||||
assert count == 7 # 5 original files + 2 new regular files
|
||||
|
||||
# Test with include_hidden=True
|
||||
files, count = get_file_listing(str(git_repo_with_aider_files), include_hidden=True)
|
||||
|
||||
# Both regular and hidden files should be included
|
||||
assert "main.cpp" in files
|
||||
assert "src/helper.cpp" in files
|
||||
for hidden_file in hidden_files:
|
||||
assert hidden_file in files
|
||||
|
||||
# All files should be counted
|
||||
assert count == 11 # 5 original + 2 regular + 4 hidden
|
||||
|
|
|
|||
Loading…
Reference in New Issue