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atomic_concepts_gradio/20250124_170625_aone.json

@@ -0,0 +1,28 @@
+{
+    "metrics_prompt": "Forget all of our past conversations and treat this as a new conversation.  As an expert Data Analyst in the Financial Securities Trading Industry,  parse the following question \"{question}\" and list all the metrics mentioned in the statement.  Do not list anything that is not a metric.  Do not include dimensions.  ",
+    "dimensions_prompt": " Forget all of our past conversations and treat this as a new conversation.  As an expert Data Analyst in the Financial Securities Trading Industry,  parse the following question \"{question}\" and identify all the dimensions that are not a metric.  List the dimensions including time period and list that only and nothing else.  Do not include metrics.",
+    "results": [
+        {
+            "question": "What is the MTD total order volume",
+            "metrics": [
+                "MTD total order volume"
+            ],
+            "dimensions": [
+                "MTD",
+                "order"
+            ]
+        },
+        {
+            "question": "Show total monthly order volume for the past 12 months.",
+            "metrics": [
+                "total monthly order volume"
+            ],
+            "dimensions": [
+                "total monthly order volume",
+                "past 12 months"
+            ]
+        }
+    ],
+    "llm_model": "gpt-4o",
+    "username": "achinta"
+}

atomic_concepts_gradio/20250124_170838_aone.json

@@ -0,0 +1,28 @@
+{
+    "metrics_prompt": "Forget all of our past conversations and treat this as a new conversation.  As an expert Data Analyst in the Financial Securities Trading Industry,  parse the following question \"{question}\" and list all the metrics mentioned in the statement.  Do not list anything that is not a metric.  Do not include dimensions.  ",
+    "dimensions_prompt": "Forget all of our past conversations and treat this as a new conversation.  As an expert Data Analyst in the Financial Securities Trading Industry,  parse the following question \"{question}\" and identify all the dimensions that are not a metric.  List the dimensions including time period and list that only and nothing else.  Do not include metrics.",
+    "results": [
+        {
+            "question": "What is the MTD total order volume",
+            "metrics": [
+                "MTD total order volume"
+            ],
+            "dimensions": [
+                "MTD (Month-to-Date)",
+                "Order"
+            ]
+        },
+        {
+            "question": "Show total monthly order volume for the past 12 months.",
+            "metrics": [
+                "total monthly order volume"
+            ],
+            "dimensions": [
+                "Order Volume",
+                "Time Period (Past 12 Months)"
+            ]
+        }
+    ],
+    "llm_model": "gpt-4o",
+    "username": "achinta"
+}

atomic_concepts_gradio/20250124_171034_aone.json

@@ -0,0 +1,28 @@
+{
+    "metrics_prompt": "Forget all of our past conversations and treat this as a new conversation.  As an expert Data Analyst in the Financial Securities Trading Industry,  parse the following question \"{question}\" and list all the metrics mentioned in the statement.  Do not list anything that is not a metric.  Do not include dimensions.",
+    "dimensions_prompt": "Forget all of our past conversations and treat this as a new conversation.  As an expert Data Analyst in the Financial Securities Trading Industry,  parse the following question \"{question}\" and identify all the dimensions that are not a metric.  List the dimensions including time period and list that only and nothing else.  Do not include metrics.",
+    "results": [
+        {
+            "question": "What is the MTD total order volume",
+            "metrics": [
+                "MTD total order volume"
+            ],
+            "dimensions": [
+                "MTD",
+                "order"
+            ]
+        },
+        {
+            "question": "Show total monthly order volume for the past 12 months.",
+            "metrics": [
+                "total monthly order volume"
+            ],
+            "dimensions": [
+                "total monthly order volume",
+                "past 12 months"
+            ]
+        }
+    ],
+    "llm_model": "gpt-4o",
+    "username": "achinta"
+}

evaluate_atomic_matching.py

@@ -256,8 +256,7 @@ with gr.Blocks(css="footer {visibility: hidden}") as iface:
                 download_btn = gr.Button("Download Results", interactive=False)
             
             def enable_download(message, filepath):
-                download_btn.interactive = True
-                return message, filepath
+                return message, filepath, gr.Button(value="Download Results", interactive=True)
             
             process_btn.click(
                 fn=process_questions,
@@ -267,11 +266,11 @@ with gr.Blocks(css="footer {visibility: hidden}") as iface:
             ).then(
                 fn=enable_download,
                 inputs=[result, file_output],
-                outputs=[result, file_output]
+                outputs=[result, file_output, download_btn]
             )
             
             download_btn.click(
-                fn=lambda filepath: filepath,
+                fn=lambda filepath: gr.File(value=filepath, label="Download JSON"),
                 inputs=[file_output],
                 outputs=gr.File(label="Download JSON")
             )