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feat(sample): add Dozer + LLM + Vector DB + LangChain credit card chatbot sample (#1690) - #2558

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properSkux:feat/issue-1690-llm-vector-langchain-sample
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properSkux wants to merge 1 commit into
getdozer:mainfrom
properSkux:feat/issue-1690-llm-vector-langchain-sample

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Summary

Implements a complete working sample for Dozer + LLM + Vector Database + LangChain hyper-personalized credit card recommendations (#1690):

  1. Multi-Dataset Dozer Pipeline (usecases/llm-credit-card-chatbot/dozer-config.yaml):

    • Ingests customers.csv, transactions.csv, and credit_cards.csv via Dozer LocalStorage.
    • Materializes a real-time customer_profiles view (total_spend, tx_count, credit_score, annual_income, preferred_category, kyc_verified) and exposes /customer_profiles and /credit_cards endpoints.
  2. Dozer REST Integration & Underwriting Filter (dozer_client.py):

    • Queries /customer_profiles/query and /credit_cards/query and enforces hard underwriting gates (kyc_verified, min_credit_score, min_annual_income) before vector retrieval.
  3. Vector Search & LangChain Advisor (vector_rag_chatbot.py, test_chatbot.py):

    • Indexes eligible credit card products into a semantic vector store, retrieves top matches aligned with the customer's question and spend category, and generates grounded recommendations via LangChain.

Fixes #1690
Fixes #1690
/claim #1690

Companion PR in getdozer/dozer-samples: getdozer/dozer-samples#149

…tbot sample (getdozer#1690)

- Add `dozer-config.yaml` joining `customers` and `transactions` into `customer_profiles` alongside `credit_cards` REST/gRPC endpoints
- Add `dozer_client.py` with REST query integration and hard credit-score/income/KYC underwriting gates
- Add `vector_rag_chatbot.py` indexing eligible credit card products for semantic retrieval and LangChain grounded generation
- Add unit test suite (`test_chatbot.py`) and setup documentation

Fixes getdozer#1690

Signed-off-by: Lucas Oliveira <kalopsia3445@gmail.com>
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Sample: Dozer + LLM + Vector database + Langchain sample

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