I need a step-by-step guide on automating resume screening workflows with Python and OpenAI for a class project.
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
I need a step-by-step guide on automating resume screening workflows with Python and OpenAI for a class project.
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
site:platform.openai.com/docs/guides/structured-outputs OpenAI Python structured outputs Responses API Google ↗
site:platform.openai.com/docs/api-reference/responses OpenAI Python Responses API Google ↗
- OpenAI API dashboard · platform.openai.com
- Assistants migration guide · platform.openai.com
- Assistants migration guide · platform.openai.com
- OpenAI API documentation · platform.openai.com
- OpenAI Python SDK · github.com
- PyPDF documentation · pypdf.readthedocs.io
- Streamlit documentation · docs.streamlit.io
- Pandas documentation · pandas.pydata.org
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
site:platform.openai.com/docs/guides/structured-outputs OpenAI Python structured outputs Responses API OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
site:platform.openai.com/docs/api-reference/responses OpenAI Python Responses API OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 |