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ClearML
 Contents 
Installation and Setup
Getting API Credentials
Callbacks
Scenario 1: Just an LLM
Scenario 2: Creating an agent with tools
Tips and Next Steps
ClearML#
ClearML is a ML/DL development and production suite, it contains 5 main modules:
Experiment Manager - Automagical experiment tracking, environments and results
MLOps - Orchestration, Automation & Pipelines solution for ML/DL jobs (K8s / Cloud / bare-metal)
Data-Management - Fully differentiable data management & version control solution on top of object-storage (S3 / GS / Azure / NAS)
Model-Serving - cloud-ready Scalable model serving solution!
Deploy new model endpoints in under 5 minutes
Includes optimized GPU serving support backed by Nvidia-Triton
with out-of-the-box Model Monitoring
Fire Reports - Create and share rich MarkDown documents supporting embeddable online content
In order to properly keep track of your langchain experiments and their results, you can enable the ClearML integration. We use the ClearML Experiment Manager that neatly tracks and organizes all your experiment runs.
Installation and Setup#
!pip install clearml
!pip install pandas
!pip install textstat
!pip install spacy
!python -m spacy download en_core_web_sm
Getting API Credentials#
We’ll be using quite some APIs in this notebook, here is a list and where to get them:
ClearML: https://app.clear.ml/settings/workspace-configuration
OpenAI: https://platform.openai.com/account/api-keys
SerpAPI (google search): https://serpapi.com/dashboard
import os
os.environ["CLEARML_API_ACCESS_KEY"] = ""
os.environ["CLEARML_API_SECRET_KEY"] = ""
os.environ["OPENAI_API_KEY"] = ""
os.environ["SERPAPI_API_KEY"] = ""
rtdocs_stable/api.python.langchain.com/en/stable/integrations/clearml_tracking.html