codeant-ai-for-open-source[bot] commented on code in PR #43556:
URL: https://github.com/apache/superset/pull/43556#discussion_r3864193075


##########
superset/jinja_context.py:
##########
@@ -1302,7 +1302,7 @@ def get_dataset_id_from_context(metric_key: str) -> int:
     )
 
     if has_request_context():
-        if payload := request.get_json(cache=True) if request.is_json else 
None:
+        if payload := get_request_json_body():
             if dataset_id := payload.get("datasource", {}).get("id"):

Review Comment:
   **Suggestion:** Normalize the nested JSON values before dereferencing or 
merging them. `get_request_json_body()` guarantees only that the top-level 
value is a dictionary; a valid payload such as `{"datasource": null}` makes 
`.get("id")` raise `AttributeError`, while a non-dictionary `form_data` can 
make `form_data.update(...)` raise `TypeError` instead of reaching the intended 
fallback exception. [type error]
   
   <details>
   <summary><b>Severity Level:</b> Major ⚠️</summary>
   
   ```mdx
   - ❌ MCP chart rendering can fail on malformed nested payloads.
   - ⚠️ Metric resolution bypasses existing form-data fallbacks.
   - ⚠️ Users receive runtime errors instead of dataset guidance.
   ```
   </details>
   
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   <details>
   <summary><b>Prompt for AI Agent 🤖 </b></summary>
   
   ```mdx
   This is a comment left during a code review.
   
   **Path:** superset/jinja_context.py
   **Line:** 1305:1306
   **Comment:**
        *Type Error: Normalize the nested JSON values before dereferencing or 
merging them. `get_request_json_body()` guarantees only that the top-level 
value is a dictionary; a valid payload such as `{"datasource": null}` makes 
`.get("id")` raise `AttributeError`, while a non-dictionary `form_data` can 
make `form_data.update(...)` raise `TypeError` instead of reaching the intended 
fallback exception.
   
   Validate the correctness of the flagged issue. If correct, How can I resolve 
this? If you propose a fix, implement it and please make it concise.
   Once fix is implemented, also check other comments on the same PR, and ask 
user if the user wants to fix the rest of the comments as well. if said yes, 
then fetch all the comments validate the correctness and implement a minimal fix
   ```
   </details>
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href='https://app.codeant.ai/feedback?pr_url=https%3A%2F%2Fgithub.com%2Fapache%2Fsuperset%2Fpull%2F43556&comment_hash=05fbcdb15d89a9161a48542846b568ddffbe20dcff842ad6be7137757ea8c34a&reaction=like'>👍</a>
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