Akis Giannoukos commited on
Commit
8b938f4
·
1 Parent(s): e8b82b0

Refactor summary formatting in patient and clinician summaries to improve readability and consistency.

Browse files
Files changed (1) hide show
  1. app.py +6 -6
app.py CHANGED
@@ -298,9 +298,9 @@ def build_patient_summary(chat_history: List[Tuple[str, str]], meta: Dict[str, A
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  total = meta.get("Total_Score") or display_json.get("Total_Score")
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  transcript_text = transcript_to_text(chat_history)
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  return (
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- f"### Summary for You\n\n"
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- f"Thank you for your time. Here is a copy of our conversation so you can review it later.\n\n"
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- f"```") + transcript_text + "\n```"
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  )
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@@ -314,14 +314,14 @@ def build_clinician_summary(chat_history: List[Tuple[str, str]], meta: Dict[str,
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  scores_lines = "\n".join([f"- {k}: {v}" for k, v in scores.items()])
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  conf_str = ", ".join([f"{c:.2f}" for c in confidences]) if confidences else ""
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  return (
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- f"### Clinician Summary\n\n"
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  f"- Severity: **{severity}** \n"
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  f"- PHQ‑9 Total: **{total}** \n"
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  f"- High Risk: **{risk}**\n\n"
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  f"#### Item Scores\n{scores_lines}\n\n"
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  f"#### Item Confidences\n{conf_str}\n\n"
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- f"#### Conversation Transcript\n\n"
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- f"```") + transcript_text + "\n```"
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  )
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  def generate_recording_agent_reply(chat_history: List[Tuple[str, str]]) -> str:
 
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  total = meta.get("Total_Score") or display_json.get("Total_Score")
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  transcript_text = transcript_to_text(chat_history)
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  return (
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+ "### Summary for You\n\n"
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+ "Thank you for your time. Here is a copy of our conversation so you can review it later.\n\n"
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+ f"```\n{transcript_text}\n```"
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  )
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  scores_lines = "\n".join([f"- {k}: {v}" for k, v in scores.items()])
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  conf_str = ", ".join([f"{c:.2f}" for c in confidences]) if confidences else ""
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  return (
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+ "### Clinician Summary\n\n"
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  f"- Severity: **{severity}** \n"
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  f"- PHQ‑9 Total: **{total}** \n"
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  f"- High Risk: **{risk}**\n\n"
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  f"#### Item Scores\n{scores_lines}\n\n"
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  f"#### Item Confidences\n{conf_str}\n\n"
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+ "#### Conversation Transcript\n\n"
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+ f"```\n{transcript_text}\n```"
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  )
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  def generate_recording_agent_reply(chat_history: List[Tuple[str, str]]) -> str: