IBM/api-integrated-llm-experiment
Mar 2025 – Mar 2025
1 Month active
Languages Used
JSONPythonShell
Technical Skills
AI IntegrationAI Model ConfigurationAPI IntegrationBackend DevelopmentCode RefactoringConfiguration Management
Anupama Murthi
PROFILE
Anupama Murthi
Anupama Murthi developed a robust LLM experimentation workflow within the IBM/api-integrated-llm-experiment repository, focusing on prompt refinement, automated evaluation, and scalable configuration management. She enhanced prompt engineering by updating prompts.json to improve response quality and flexibility, and introduced new Python modules for parsing and scoring, increasing reliability in model evaluation. Her work included scripting to automate data preparation, scoring, and aggregation, streamlining the experimental process for LLM-based agent research. Through code refactoring, linting, and backend development, Anupama established a stable foundation that accelerated experimentation cycles and enabled repeatable, data-driven decisions, demonstrating depth in AI integration and backend engineering.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
3
Lines of code
2,699
Activity Months1
Your Network
841 people
Work History
March 2025
11 Commits • 3 Features
Mar 1, 2025March 2025 remained focused on delivering a robust LLM experimentation workflow within IBM/api-integrated-llm-experiment, aligning prompt management, parsing/scoring reliability, and automation to accelerate evaluation cycles and business decisions. The team shipped three primary feature areas, targeted fixes to improve stability, and established a scalable foundation for future experiments.
11 Commits • 3 Features
Mar 1, 2025March 2025 remained focused on delivering a robust LLM experimentation workflow within IBM/api-integrated-llm-experiment, aligning prompt management, parsing/scoring reliability, and automation to accelerate evaluation cycles and business decisions. The team shipped three primary feature areas, targeted fixes to improve stability, and established a scalable foundation for future experiments.
March 2025
Activity
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Quality Metrics
Correctness76.4%
Maintainability78.2%
Architecture69.2%
Performance63.6%
AI Usage47.4%
Skills & Technologies
Programming Languages
JSONPythonShell
Technical Skills
AI IntegrationAI Model ConfigurationAPI IntegrationBackend DevelopmentCode RefactoringConfiguration ManagementData CleaningData ParsingData ProcessingExperiment ManagementExperimentationLLMLLM DevelopmentLLM IntegrationLLM Operations
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