Update src/streamlit_app.py

src/streamlit_app.py

@@ -379,40 +379,48 @@ def evaluate_dataset_with_gpt(subtask: str, df: pd.DataFrame, client=openai_clie
     sample_rows = df.head(3)[selected_cols].to_dict(orient="records")   # take 3 example rows
 
     prompt = f"""
-You are a data‑validation assistant. Decide whether the dataset below is useful for the research subtask.
+You are a data-validation assistant. Your job is to determine whether the dataset below is useful for the research subtask.
 
-===== TASK =====
+===== TASK =====  
 Subtask: "{{subtask}}"
 
-===== DATASET PREVIEW =====
-Schema (first {{len(selected_cols)}} columns):
-{{json.dumps(column_info, indent=20)}}
-Sample rows (20 max):
-{{json.dumps(sample_rows, indent=20)}}
+===== DATASET PREVIEW =====  
+Schema: {{schema}}  
+Example Rows: {{example_rows}}
 
 ===== OUTPUT INSTRUCTIONS (follow strictly) =====
-First, begin your response with one of the following labels on its own line:
-Relevant
-or
-Irrelevant
 
-Then follow the appropriate instruction below based on your decision.
+Case A – Relevant:
+• Write exactly two sentences, each no more than 30 words.  
+• Sentence 1: summarize what the dataset contains.  
+• Sentence 2: explain why it helps answer the subtask.  
+• Do not mention specific column names or list individual rows.  
+• Do NOT generate any additional explanation or markdown formatting.
 
---- 
+Case B – Not Relevant:  
+• Write one or two sentences, each no more than 30 words, describing **only what the dataset contains**.  
+• Do **NOT** mention the subtask, usefulness, relevance, or missing information.  
+• Do **NOT** use words like “irrelevant,” “not related,” “not useful,” “not sufficient,” etc.  
+• After the sentence(s), output the exact header:
 
-If you choose "Relevant":
-• Write exactly two sentences, each no more than 30 words.  
-• Summarize what the dataset contains and why it helps the subtask.  
-• Do not mention column names or list individual rows.
+**Additionally, here are some external resources you might find helpful:**
 
----
+• Then output 2–3 **real** resources in Markdown link format. Each must:
+   - Have a **real source name** (e.g., “MatWeb”, not “Name of Source”)
+   - Contain a **real, working URL** to a page or dataset related to the subtask  
+   - Be formatted exactly like: `- [Source Name](https://example.com)`
 
-If you choose "Irrelevant":
-• Write one or two sentences, each no more than 30 words, **describing only what the dataset contains**.
-• After the sentences, output the header **Additionally, here are some external resources you might find helpful:** on a new line. Format your output in markdown as:
-- [Name of Source](URL)
-• Then list 2–3 bullet points, each on its own line, starting with “- ” followed immediately by a URL likely to contain the needed data.
-• No additional commentary.
+• Do NOT use placeholder text like “Name of Source” or “URL”.  
+• Do NOT generate any commentary after the list.
+
+Example for Case B:
+
+The dataset contains technical specifications of commercial vehicles, such as engine types and dimensions.  
+
+**Additionally, here are some external resources you might find helpful:**  
+- [Polymer Property Database](https://polymerdatabase.com/)  
+- [MatWeb Materials Data Sheets](https://www.matweb.com/)  
+- [NIST Thermophysical Properties of Polymers](https://www.nist.gov/srd/nist-standard-reference-database-147)
 """
 
     rsp = client.chat.completions.create(