Logger examples¶

Installation & set up¶

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!pip install lavague

import os
# Check if running in Google Colab
try:
    from google.colab import userdata
    IN_COLAB = True
except ImportError:
    IN_COLAB = False

if IN_COLAB:
    os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY')
else:
    os.environ["OPENAI_API_KEY"] = os.getenv('OPENAI_API_KEY')
!pip install lavague

import os
# Check if running in Google Colab
try:
    from google.colab import userdata
    IN_COLAB = True
except ImportError:
    IN_COLAB = False

if IN_COLAB:
    os.environ["OPENAI_API_KEY"] = userdata.get('OPENAI_API_KEY')
else:
    os.environ["OPENAI_API_KEY"] = os.getenv('OPENAI_API_KEY')

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Collecting starlette<0.38.0,>=0.37.2 (from fastapi->gradio==4.26.0->lavague-gradio<0.3.0,>=0.2.1->lavague)
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Collecting fastapi-cli>=0.0.2 (from fastapi->gradio==4.26.0->lavague-gradio<0.3.0,>=0.2.1->lavague)
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Collecting dnspython>=2.0.0 (from email_validator>=2.0.0->fastapi->gradio==4.26.0->lavague-gradio<0.3.0,>=0.2.1->lavague)
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Collecting fastapi-cli>=0.0.2 (from fastapi->gradio==4.26.0->lavague-gradio<0.3.0,>=0.2.1->lavague)
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INFO: pip is looking at multiple versions of lxml[html-clean] to determine which version is compatible with other requirements. This could take a while.
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Building wheels for collected packages: ffmpy
  Building wheel for ffmpy (setup.py) ... done
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    Found existing installation: packaging 24.0
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Successfully installed aiofiles-23.2.1 azure-core-1.30.2 azure-identity-1.16.0 colorama-0.4.6 courlan-1.2.0 dataclasses-json-0.6.6 dateparser-1.2.0 deprecated-1.2.14 dirtyjson-1.0.8 fastapi-0.110.3 ffmpy-0.3.2 gradio-4.26.0 gradio-client-0.15.1 h11-0.14.0 htmldate-1.8.1 httpcore-1.0.5 httpx-0.27.0 jedi-0.19.1 jsonpatch-1.33 jsonpointer-2.4 justext-3.0.1 langchain-0.1.20 langchain-community-0.0.38 langchain-core-0.1.52 langchain-text-splitters-0.0.2 langsmith-0.1.75 lavague-1.1.2 lavague-contexts-openai-0.2.0 lavague-core-0.2.12 lavague-drivers-selenium-0.2.2.post2 lavague-gradio-0.2.2 llama-index-0.10.43 llama-index-agent-openai-0.2.7 llama-index-cli-0.1.12 llama-index-core-0.10.43 llama-index-embeddings-openai-0.1.10 llama-index-indices-managed-llama-cloud-0.1.6 llama-index-legacy-0.9.48 llama-index-llms-azure-openai-0.1.8 llama-index-llms-openai-0.1.22 llama-index-multi-modal-llms-azure-openai-0.1.4 llama-index-multi-modal-llms-openai-0.1.6 llama-index-program-openai-0.1.6 llama-index-question-gen-openai-0.1.3 llama-index-readers-file-0.1.23 llama-index-readers-llama-parse-0.1.4 llama-index-retrievers-bm25-0.1.3 llama-parse-0.4.4 llamaindex-py-client-0.1.19 lxml-5.2.2 lxml-html-clean-0.1.1 marshmallow-3.21.3 msal-1.28.0 msal-extensions-1.1.0 mypy-extensions-1.0.0 openai-1.32.0 orjson-3.10.3 outcome-1.3.0.post0 packaging-23.2 portalocker-2.8.2 pydub-0.25.1 pypdf-4.2.0 python-multipart-0.0.9 rank-bm25-0.2.2 ruff-0.4.8 selenium-4.21.0 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.37.2 striprtf-0.0.26 tiktoken-0.7.0 tld-0.13 tomlkit-0.12.0 trafilatura-1.10.0 trio-0.25.1 trio-websocket-0.11.1 typing-inspect-0.9.0 uvicorn-0.30.1 websockets-11.0.3 wsproto-1.2.0

Getting logs for Web Agent¶

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from lavague.drivers.selenium import SeleniumDriver
from lavague.core import ActionEngine, WorldModel
from lavague.core.agents import WebAgent

selenium_driver = SeleniumDriver(headless=True)
action_engine = ActionEngine(selenium_driver)
world_model = WorldModel()

agent = WebAgent(world_model, action_engine)

agent.get("https://huggingface.co/")
agent.run("Go to the first Model in the Models section")

# Retrieve pandas DataFrame with logs
df_logs = agent.logger.return_pandas()
from lavague.drivers.selenium import SeleniumDriver
from lavague.core import ActionEngine, WorldModel
from lavague.core.agents import WebAgent

selenium_driver = SeleniumDriver(headless=True)
action_engine = ActionEngine(selenium_driver)
world_model = WorldModel()

agent = WebAgent(world_model, action_engine)

agent.get("https://huggingface.co/")
agent.run("Go to the first Model in the Models section")

# Retrieve pandas DataFrame with logs
df_logs = agent.logger.return_pandas()

/usr/local/lib/python3.10/dist-packages/lavague/core/__init__.py:18: UserWarning: Telemetry is turned on. To turn off telemetry, set your LAVAGUE_TELEMETRY to 'NONE'
  warnings.warn(warning_message, UserWarning)
/usr/local/lib/python3.10/dist-packages/lavague/core/__init__.py:23: UserWarning: Security warning: This package executes LLM-generated code. Consider using this package in a sandboxed environment.
  warnings.warn(warning_message, UserWarning)
2024-06-07 09:26:22,872 - INFO - Screenshot folder cleared
2024-06-07 09:26:28,486 - INFO - Thoughts:
- The current screenshot shows the homepage of Hugging Face, a platform for AI models, datasets, and applications.
- The objective is to go to the first model in the Models section.
- The Models section is visible on the left side of the screen.
- The first model listed in the Models section is "OpenAI GPT-3".

Next engine: Navigation Engine
Instruction: Click on the 'OpenAI GPT-3' model in the Models section.
2024-06-07 09:26:50,021 - INFO - Thoughts:
- The current screenshot shows the page for the model "Codestarl-22B-v0.1" on Hugging Face.
- The objective is to go to the first model in the Models section.
- The previous instruction was to click on the 'OpenAI GPT-3' model, but it seems we are on a different model page.
- The best next step is to navigate back to the Models section to locate the 'OpenAI GPT-3' model.

Next engine: Navigation Controls
Instruction: BACK
2024-06-07 09:26:57,086 - INFO - Thoughts:
- The current screenshot shows the Hugging Face homepage with sections for Models, Spaces, and Datasets.
- The objective is to go to the first model in the Models section.
- The first model in the Models section is '2Noisy/ChatTTS'.
- The best next step is to click on the '2Noisy/ChatTTS' model to navigate to its page.

Next engine: Navigation Engine
Instruction: Click on the '2Noisy/ChatTTS' model in the Models section.
2024-06-07 09:27:16,192 - INFO - - The current screenshot shows the page for the '2Noisy/ChatTTS' model on Hugging Face.
- The objective is to go to the first model in the Models section.
- Previous instructions have attempted to navigate to specific models but have not achieved the objective.
- The best next step is to navigate back to the Models section and identify the first model.

Next engine: Navigation Controls
Instruction: BACK
2024-06-07 09:27:23,571 - INFO - Thoughts:
- The current screenshots show the Models section on the Hugging Face website.
- The objective is to go to the first model in the Models section.
- Previous attempts to click on specific models and navigate back were unsuccessful.
- The first model listed in the Models section is '2Noisy/ChatTTS'.
- The best next step is to click on the '2Noisy/ChatTTS' model.

Next engine: Navigation Engine
Instruction: Click on the '2Noisy/ChatTTS' model in the Models section.
2024-06-07 09:27:40,841 - INFO - Thoughts:
- The current screenshot shows the page for the '2Noisy/ChatTTS' model on Hugging Face.
- The objective is to go to the first model in the Models section.
- Previous attempts to click on specific models have not achieved the objective.
- A new approach should be used to navigate to the first model in the Models section.
- The best next step is to go back to the Models section and identify the first model.

Next engine: Navigation Controls
Instruction: BACK
2024-06-07 09:27:48,891 - INFO - Thoughts:
- The current screenshots show the main page of the Models section on Hugging Face.
- The objective is to go to the first model in the Models section.
- Previous attempts to click on specific models have failed, indicating that the approach might need adjustment.
- The first model listed in the Models section is '2Noisy/ChatTTS'.
- The best next step is to click on the '2Noisy/ChatTTS' model again, ensuring the correct element is targeted.

Next engine: Navigation Engine
Instruction: Click on the '2Noisy/ChatTTS' model in the Models section.
2024-06-07 09:28:02,958 - INFO - Thoughts:
- The current screenshot shows the page for the '2Noisy/ChatTTS' model on Hugging Face.
- The objective is to go to the first model in the Models section.
- Previous attempts to click on specific models have been unsuccessful.
- A new approach is needed to navigate to the first model in the Models section.
- The best next step is to navigate back to the Models section and identify the first model.

Next engine: Navigation Controls
Instruction: BACK
2024-06-07 09:28:11,150 - INFO - Thoughts:
- The current screenshots show the Models section of the Hugging Face website.
- The objective is to go to the first model in the Models section.
- Previous attempts to click on specific models have failed, indicating that the approach needs to be adjusted.
- The first model listed in the Models section is '2Noisy/ChatTTS'.
- The best next step is to click on the '2Noisy/ChatTTS' model again, ensuring that the interaction is correctly executed this time.

Next engine: Navigation Engine
Instruction: Click on the '2Noisy/ChatTTS' model in the Models section.
2024-06-07 09:28:25,878 - INFO - Thoughts:
- The current screenshot shows the page for the '2Noisy/ChatTTS' model on Hugging Face.
- The objective is to go to the first model in the Models section.
- Previous instructions have repeatedly tried to click on the '2Noisy/ChatTTS' model, which is not the first model in the Models section.
- A new approach should be used to navigate to the first model in the Models section.
- The best next step is to go back to the Models section and identify the first model.

Next engine: Navigation Controls
Instruction: BACK
2024-06-07 09:28:26,761 - WARNING - Telemetry failed with local variable 't' referenced before assignment

Exploring logs¶

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# Pandas option to ensure we show all text in column
import pandas as pd
pd.set_option('display.max_colwidth', None)

# Print the code generated for step 0 of our run
step = 0
print(df_logs.at[step, 'code'])
# Pandas option to ensure we show all text in column
import pandas as pd
pd.set_option('display.max_colwidth', None)

# Print the code generated for step 0 of our run
step = 0
print(df_logs.at[step, 'code'])

# Let's think step by step

# First, we notice that the query asks us to click on the "OpenAI GPT-3" model in the Models section.

# In the provided HTML, we need to identify the section that contains the models.

# We need to locate the specific model named "OpenAI GPT-3".

# Upon examining the HTML structure, we see that each model is represented by an article element with a specific class.

# We need to navigate through the hierarchy to accurately locate the "OpenAI GPT-3" model.

# The correct model is located within an article element with a specific class and contains a header with the model name.

# Specifically, for "OpenAI GPT-3", there is an article element with a unique class and contains a header with the text "OpenAI GPT-3".

# We observe that this article element has the following XPath:
# /html/body/div/main/div[2]/div[2]/div[2]/div/article[2]/a

# Thus, we believe this is the correct element to be interacted with:
openai_gpt3_model = driver.find_element(By.XPATH, "/html/body/div/main/div[2]/div[2]/div[2]/div/article[2]/a")

# Then we can click on the model
openai_gpt3_model.click()

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from IPython.display import display

step = 0
image = 0
display(df_logs["screenshots"][step][image])
from IPython.display import display

step = 0
image = 0
display(df_logs["screenshots"][step][image])

No description has been provided for this image

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# Print the World Model thoughts generated for step 0 of our run
step = 0
print(df_logs.at[step, 'world_model_output'])
# Print the World Model thoughts generated for step 0 of our run
step = 0
print(df_logs.at[step, 'world_model_output'])

Thoughts:
- The current screenshot shows the homepage of Hugging Face, a platform for AI models, datasets, and applications.
- The objective is to go to the first model in the Models section.
- The Models section is visible on the left side of the screen.
- The first model listed in the Models section is "OpenAI GPT-3".

Next engine: Navigation Engine
Instruction: Click on the 'OpenAI GPT-3' model in the Models section.

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# Print the code generated for step 0 of our run
attempt = 0
from IPython.display import display, HTML, Code

# We need to index the engine log at 0 to access further data due to an on-going update from a legacy feature - this index will be removed in the future
sub_instruction = 0
x = 0
for node in df_logs.at[attempt, 'engine_log'][sub_instruction]['retrieved_html']:
    print(f"node {x}")
    x = x + 1
    display(HTML(node)) # Display node as visual element
    display(Code(node, language="html")) # Display code
# Print the code generated for step 0 of our run
attempt = 0
from IPython.display import display, HTML, Code

# We need to index the engine log at 0 to access further data due to an on-going update from a legacy feature - this index will be removed in the future
sub_instruction = 0
x = 0
for node in df_logs.at[attempt, 'engine_log'][sub_instruction]['retrieved_html']:
    print(f"node {x}")
    x = x + 1
    display(HTML(node)) # Display node as visual element
    display(Code(node, language="html")) # Display code

node 0

Updated 3 days ago • 3.24k • 817

stabilityai/stable-audio-open-1.0

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node 1

Updated 3 days ago • 3.24k • 817

stabilityai/stable-audio-open-1.0

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node 2

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FineWeb: decanting the web for the finest text data at scale

342

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ToonCrafter

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</a>
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node 3

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Advanced example: Logging lower level modules¶

In [13]:

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from lavague.drivers.selenium import SeleniumDriver
from lavague.core.logger import AgentLogger
from lavague.core import ActionEngine

selenium_driver = SeleniumDriver(headless=True, url="https://huggingface.co/")
action_engine = ActionEngine(
    driver=selenium_driver,
)

# Initialize your logger
logger = AgentLogger()
from lavague.drivers.selenium import SeleniumDriver
from lavague.core.logger import AgentLogger
from lavague.core import ActionEngine

selenium_driver = SeleniumDriver(headless=True, url="https://huggingface.co/")
action_engine = ActionEngine(
    driver=selenium_driver,
)

# Initialize your logger
logger = AgentLogger()

In [14]:

Copied!

# Start a new logging run
logger.new_run()

# Add logging to NavigationEngine
action_engine.navigation_engine.set_logger(logger)

obs = selenium_driver.get_obs()
# Start a new logging run
logger.new_run()

# Add logging to NavigationEngine
action_engine.navigation_engine.set_logger(logger)

obs = selenium_driver.get_obs()

In [15]:

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# Engine & instruction
engine_name = "Navigation Engine"
instruction = "Show me the top model"

# Execute the instruction
ret = action_engine.dispatch_instruction(engine_name, instruction)

# Add required driver info to logs and end the logging step
logger.add_log(obs)
logger.end_step()

# Retrieve and print logs as a pandas DataFrame
df_logs = logger.return_pandas()
# Engine & instruction
engine_name = "Navigation Engine"
instruction = "Show me the top model"

# Execute the instruction
ret = action_engine.dispatch_instruction(engine_name, instruction)

# Add required driver info to logs and end the logging step
logger.add_log(obs)
logger.end_step()

# Retrieve and print logs as a pandas DataFrame
df_logs = logger.return_pandas()