Function _merge_report_payload

agents/reading-agent/main.py:4264–4311

(base: Dict[str, Any], llm_payload: Optional[Dict[str, Any]])

def _merge_report_payload(base: Dict[str, Any], llm_payload: Optional[Dict[str, Any]]) -> Dict[str, Any]:
    if not isinstance(llm_payload, dict):
        return base

    merged = dict(base)
    for key in (
        "one_sentence_summary",
        "clean_abstract_summary",
        "problem_analysis",
        "related_work",
        "solution_approach",
        "experiments",
        "experimental_observations",
        "future_directions",
        "paper_summary",
        "research_background",
        "core_method",
        "key_results",
        "institution",
        "affiliation",
    ):
        value = _clean_text(llm_payload.get(key))
        if value:
            merged["institution" if key == "affiliation" else key] = value

    analysis_note = _clean_text(llm_payload.get("analysis_note"))
    if analysis_note:
        merged["analysis_note"] = _append_analysis_note(merged.get("analysis_note"), analysis_note)

    for key in ("main_contributions", "limitations", "relevance_points", "reading_focus"):
        values = _normalize_string_list(llm_payload.get(key), max_chars=320)
        if values:
            merged[key] = values

    keyword_values = _normalize_string_list(llm_payload.get("keywords"), limit=8)
    if keyword_values:
        merged["keywords"] = keyword_values

    recommendation_label = _clean_text(llm_payload.get("recommendation_label"))
    if recommendation_label:
        merged["recommendation_label"] = recommendation_label

    for key in ("generation_provider", "generation_model"):
        value = _clean_text(llm_payload.get(key))
        if value:
            merged[key] = value

    return merged


def _resolve_doc_url_from_meta(doc_token: Optional[str]) -> Optional[str]: