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feat: prompt - #7

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TeoCalvo merged 1 commit into
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feat/guardrails
Jun 10, 2026
Merged

feat: prompt#7
TeoCalvo merged 1 commit into
mainfrom
feat/guardrails

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Copilot AI review requested due to automatic review settings June 10, 2026 13:09
@TeoCalvo
TeoCalvo merged commit c77f7d8 into main Jun 10, 2026
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Pull request overview

This PR tweaks the RAG chat experience (retrieval size + prompt wording) and adjusts the data ingestion/training configuration that supports the guardrails and vector DB pipeline.

Changes:

  • Increase Qdrant ColBERT query limit and refine the assistant prompt text in the /predict endpoint.
  • Adjust ingestion chunk size (max_tokens) for document chunking.
  • Update guardrails training configuration (notably RandomForestClassifier.n_estimators) and a final summary print.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 3 comments.

File Description
ragia/app.py Updates retrieval limit and refines the LLM prompt used to answer user queries.
ragia/03_train.py Modifies guardrails model training settings and adjusts the end-of-notebook output.
ragia/01_ingest.py Changes document chunking size used before uploading vectors to Qdrant.

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Comment thread ragia/app.py
---

Sumarize o contexto e responda de forma clara, objetiva e descontraída com no máximo 300 caracteres.
Sumarize a resposta com o contexto e responda de forma clara, objetiva e descontraída com no máximo 300 caracteres. Lembre-se que se trata de uma live aberta.
Comment thread ragia/03_train.py
Comment on lines 56 to 60
clf = ensemble.RandomForestClassifier(
n_estimators=100,
n_estimators=500,
min_samples_leaf=3,
random_state=42,
)
Comment thread ragia/03_train.py
# %%

print(np.mean(y))
print(np.mean(y_train))
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2 participants