Spaces:
Running
Running
update
Browse files- Makefile +1 -0
- README.md +54 -3
- src/proxy_lite/environments/webbrowser.py +5 -2
Makefile
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@@ -1,6 +1,7 @@
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.PHONY: proxy
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proxy:
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uv venv --python 3.11 --python-preference managed
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uv sync
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uv pip install -e .
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.PHONY: proxy
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proxy:
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pip install uv
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uv venv --python 3.11 --python-preference managed
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uv sync
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uv pip install -e .
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README.md
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@@ -6,9 +6,8 @@ A mini, open-weights version of our Proxy assistant.
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---
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## Getting Started
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-
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Clone the repository:
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@@ -25,6 +24,7 @@ make proxy
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Or do it manually:
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```bash
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uv venv --python 3.11 --python-preference managed
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uv sync
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uv pip install -e .
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@@ -32,7 +32,7 @@ playwright install
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```
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-
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```bash
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proxy --help
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export PROXY_LITE_API_BASE=http://localhost:8008/v1
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```
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---
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## Installation
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Clone the repository:
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Or do it manually:
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```bash
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pip install uv
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uv venv --python 3.11 --python-preference managed
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uv sync
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uv pip install -e .
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```
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## Usage
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```bash
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proxy --help
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export PROXY_LITE_API_BASE=http://localhost:8008/v1
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```
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### Scaffolding Proxy-Lite in Python
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We use the `RunnerConfig` to control the setup of the task.
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The library is designed to be modular and extendable, you can easily swap the environment, solver, or agent.
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Example:
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```python
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import asyncio
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from proxy_lite import Runner, RunnerConfig
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config = RunnerConfig.from_dict(
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{
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"environment": {
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"name": "webbrowser",
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"homepage": "https://www.google.com",
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"headless": True, # Don't show the browser
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},
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"solver": {
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"name": "simple",
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"agent": {
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"name": "proxy_lite",
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"client": {
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"name": "convergence",
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"model_id": "convergence-ai/proxy-lite",
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"api_base": "https://convergence-ai-demo-api.hf.space/v1",
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},
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},
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},
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"max_steps": 50,
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"action_timeout": 1800,
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"environment_timeout": 1800,
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"task_timeout": 18000,
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"logger_level": "DEBUG",
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},
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)
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proxy = Runner(config=config)
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result = asyncio.run(
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proxy.run("Book a table for 2 at an Italian restaurant in Kings Cross tonight at 7pm.")
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)
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```
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### Webbrowser Environment
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The `webbrowser` environment is a simple environment that uses the `playwright` library to navigate the web.
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We launch a Chromium browser and navigate to the `homepage` provided in the `RunnerConfig`.
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Actions in an environment are defined through available tool calls, which in the browser case are set as default in the `BrowserTool` class. This allows the model to click, type, etc. at relevant `mark_id` elements on the page. These elements are extracted using JavaScript injected into the page in order to make interaction easier for the models.
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If you want to not use this set-of-marks approach, you can set the `no_pois_in_image` flag to `True`, and the `include_poi_text` flag to `False` in the `EnvironmentConfig`. This way the model will only see the original image, and not the annotated image with these points-of-interest (POIs). In this case, you would want to update the `BrowserTool` to interact with pixel coordinates instead of the `mark_id`s.
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src/proxy_lite/environments/webbrowser.py
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@@ -28,6 +28,7 @@ class WebBrowserEnvironmentConfig(BaseEnvironmentConfig):
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browserbase_timeout: int = 7200
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headless: bool = True
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keep_original_image: bool = False
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@Environments.register_environment("webbrowser")
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original_img, annotated_img = await self.browser.screenshot(
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delay=self.config.screenshot_delay,
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)
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html_content = await self.browser.current_page.content() if self.config.include_html else None
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browserbase_timeout: int = 7200
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headless: bool = True
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keep_original_image: bool = False
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no_pois_in_image: bool = False
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@Environments.register_environment("webbrowser")
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original_img, annotated_img = await self.browser.screenshot(
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delay=self.config.screenshot_delay,
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)
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if self.config.no_pois_in_image:
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base64_image = base64.b64encode(original_img).decode("utf-8")
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else:
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base64_image = base64.b64encode(annotated_img).decode("utf-8")
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html_content = await self.browser.current_page.content() if self.config.include_html else None
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