deploy: auto-deploy 17:59:57

app/services/csv_analysis_service.py

@@ -105,6 +105,7 @@ with open(r"{blocks_path}", "r") as _f:
 
 _results = {{"analyze": [], "visualization": []}}
 _ns = {{"df": df, "pd": pd, "np": np, "plt": plt, "sns": sns}}
+_EXCLUDED = {{"pd", "np", "plt", "sns", "df", "json", "sys", "io", "base64", "traceback", "matplotlib", "seaborn"}}
 
 for _b in _data.get("analyze", []):
     _code = (_b.get("python_code") or "").strip()
@@ -113,9 +114,25 @@ for _b in _data.get("analyze", []):
         continue
     _old = sys.stdout
     sys.stdout = io.StringIO()
+    _pre = {{k for k in _ns if not k.startswith("_")}} - _EXCLUDED
     try:
         exec(_code, _ns)
-        _results["analyze"].append({{"success": True, "output": sys.stdout.getvalue(), "error": None}})
+        _output = sys.stdout.getvalue()
+        if not _output:
+            _post = {{k for k in _ns if not k.startswith("_")}} - _EXCLUDED
+            _new = sorted(_post - _pre)
+            if "final_result" in _ns:
+                _output += f"final_result = {{repr(_ns['final_result'])}}\\n"
+            for _k in _new:
+                if _k == "final_result":
+                    continue
+                _v = _ns[_k]
+                try:
+                    _s = repr(_v)
+                except Exception:
+                    _s = "<unrepresentable>"
+                _output += f"{{_k}} = {{_s}}\\n"
+        _results["analyze"].append({{"success": True, "output": _output, "error": None}})
     except Exception:
         _results["analyze"].append({{"success": False, "output": sys.stdout.getvalue(), "error": traceback.format_exc()}})
     finally:

app/services/prompts/csv_system_prompt.py

@@ -10,7 +10,7 @@ _JSON_EXAMPLE = (
     '  "analyze": [\n'
     '    {\n'
     '      "description": "Short explanation of the math",\n'
-    '      "python_code": "# Clean data first\\ndf[\'col\'] = ...\\n\\n# Perform analysis\\nresult = df.groupby..."\n'
+    '      "python_code": "# Clean data first\\ndf[\'col\'] = ...\\n\\n# Perform analysis\\nfinal_result = df.groupby..."\n'
     '    }\n'
     '  ],\n'
     '  "visualization": [\n'
@@ -84,12 +84,13 @@ VISUALIZATION STANDARDS:
 VARIABLE ASSIGNMENT RULES:
 1. Every operation must store its result in a variable.
 2. Variable names should be descriptive and snake_case.
-3. For DataFrame operations: result_df = df.operation()
-4. For statistical results: summary_stats = df.describe(include='all')
-5. For filtered data: filtered_data = df[df['column'] > value]
-6. For grouped analysis: revenue_by_region = df.groupby('region')['revenue'].sum().reset_index()
-7. For correlation matrices: correlation_matrix = df.corr(numeric_only=True)
-8. For visualizations: fig, ax = plt.subplots(...)
+3. For the final/primary result of an analysis block, ALWAYS use the variable name `final_result`.
+4. For DataFrame operations: result_df = df.operation()
+5. For statistical results: summary_stats = df.describe(include='all')
+6. For filtered data: filtered_data = df[df['column'] > value]
+7. For grouped analysis: revenue_by_region = df.groupby('region')['revenue'].sum().reset_index()
+8. For correlation matrices: correlation_matrix = df.corr(numeric_only=True)
+9. For visualizations: fig, ax = plt.subplots(...)
 
 EXAMPLES: