docs: Update customizations how-to guides to use collections API and LLM factory - #2425
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anistark merged 3 commits intoNov 28, 2025
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Replace legacy LangChain wrapper pattern with llm_factory and
embedding_factory using LiteLLM provider for all cloud providers.
Changes:
Updated examples
- Removed LangChain dependencies (langchain_openai, langchain_google_vertexai,
langchain_aws) in favor of litellm
- Fixed Azure model naming to use deployment names (azure/{deployment-name})
- Removed unnecessary interface="modern" parameter (auto-detected)
Benefits:
- Consistent pattern across all cloud providers
- Simpler code with fewer dependencies
- No LangChain required
- Uses modern Ragas factory APIs with Instructor and LiteLLM
All syntax verified against LiteLLM and Instructor documentation.
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- Use litellm.completion (function) instead of litellm (module) - Pass Azure config directly to embedding_factory instead of global settings - Add clarifying comments about the correct patterns Tested with actual API calls via OpenAI/litellm integration.
anistark
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Nov 28, 2025
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Issue Link / Problem Description
Updates
customize_models.mdguide to use modernllm_factoryandembedding_factoryAPIs instead of legacy LangChain wrapper pattern.Changes Made
llm_factorywith litellm providerllm_factorywith litellm provider (major simplification)llm_factorywith litellm providerTesting
How to Test
References