Quickstart¶
Python API¶
Use evidence_fetcher.fetch_evidence() to retrieve normalized
evidence_fetcher.Evidence results:
from evidence_fetcher import fetch_evidence
results = fetch_evidence("retrieval augmented generation evaluation")
for evidence in results:
print(evidence.title)
print(evidence.url)
print(evidence.snippet)
CLI¶
Readable text output:
evidence-fetcher "retrieval augmented generation evaluation"
JSON output:
evidence-fetcher "retrieval augmented generation evaluation" --format json
Use --limit to control the maximum number of results.
Streamlit UI¶
Launch the Streamlit review app:
evidence-fetcher-ui
The UI uses the same Brave-backed retrieval, local reranking, relevance feedback, and explicit expansion workflow as the CLI.
For a step-by-step walkthrough, see Streamlit UI sample.