digiteinfotech / kairon

Conversational AI Platform to build effective Proactive Digital Assistants using Visual LLM Chaining
https://kairon.nimblework.com/bots
Apache License 2.0
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Separated llm_metadata from system_metadata and added API to fetch the same #1421

Closed himanshugt16 closed 1 month ago

himanshugt16 commented 1 month ago

Summary by CodeRabbit

coderabbitai[bot] commented 1 month ago

Walkthrough

The recent changes transform the API for managing large language model (LLM) metadata, enhancing clarity and functionality. Key updates include renaming endpoints and functions to better reflect their purposes, shifting to a metadata-driven approach, and introducing new YAML configurations for LLM parameters. The modifications aim to improve usability and flexibility, enabling users to customize model behaviors more effectively.

Changes

Files Change Summary
kairon/api/app/.../bot.py Renamed endpoint from "/llm/models" to "/metadata/llm"; function updated to reflect metadata retrieval instead of model listing.
kairon/shared/llm/.../processor.py Renamed method from get_llm_models to fetch_llm_metadata; updated logic to retrieve metadata directly from Utility.llm_metadata.
kairon/shared/utils.py Introduced new class attributes for LLM metadata management; added method for loading metadata from a YAML file.
metadata/integrations.yml Removed OpenAI model configuration block, simplifying model interaction settings.
metadata/llm_metadata.yml New file defining a JSON schema for LLM configurations, enhancing customization of model behavior.
tests/integration_test/services_test.py Renamed test functions to align with metadata retrieval; updated test cases for new LLM types and response validation.
tests/testing_data/system.yaml Added llm_metadata_file parameter to specify path for LLM metadata configuration.
tests/unit_test/utility_test.py Updated test case to focus on "gemini" LLM hyperparameters instead of "claude", reflecting updated testing priorities.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant API
    participant LLMProcessor
    participant Utility

    User->>API: Request metadata for LLM
    API->>LLMProcessor: Fetch LLM metadata
    LLMProcessor->>Utility: Load metadata from file
    Utility-->>LLMProcessor: Return loaded metadata
    LLMProcessor-->>API: Return LLM metadata
    API-->>User: Respond with LLM metadata

πŸ‡ In the meadow, changes bloom,
New endpoints sprout, dispel the gloom.
With metadata fresh and bright,
Models dance in pure delight!
Hop, hop, cheer, let’s celebrate,
For every change, we elevate! πŸŽ‰


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