Create data_insights.py

utils/data_insights.py

@@ -0,0 +1,50 @@
+import pyvo as vo
+import pandas as pd
+
+def fetch_exoplanet_data():
+    # Connect to NASA Exoplanet Archive TAP Service
+    tap_service = vo.dal.TAPService("https://exoplanetarchive.ipac.caltech.edu/TAP")
+
+    # Query to fetch all columns from the pscomppars table
+    ex_query = """
+        SELECT TOP 10 pl_name, hostname, sy_snum, sy_pnum, discoverymethod, disc_year, disc_facility, pl_controv_flag, pl_orbper, pl_orbsmax, pl_rade, pl_bmasse, pl_orbeccen, pl_eqt, st_spectype, st_teff, st_rad, st_mass, ra, dec, sy_vmag
+        FROM pscomppars
+    """
+    # Execute the query
+    qresult = tap_service.search(ex_query)
+
+    # Convert to a Pandas DataFrame
+    ptable = qresult.to_table()
+    exoplanet_data = ptable.to_pandas()
+
+    return exoplanet_data
+
+def generate_data_insights(user_input, client, exoplanet_data, max_tokens=500, temperature=0.3):
+    """
+    Generate insights by passing the user's input along with the exoplanet data to GPT-4.
+    """
+    # Convert the dataframe to a readable format for GPT (e.g., CSV-style text)
+    data_as_text = exoplanet_data.to_csv(index=False)  # CSV-style for better readability
+
+    # Create a prompt with the user query and the data sample
+    insights_prompt = (
+        f"Analyze the following user query and provide relevant insights based on the provided exoplanet data.\n\n"
+        f"User Query: {user_input}\n\n"
+        f"Exoplanet Data:\n{data_as_text}\n\n"
+        f"Please provide insights that are relevant to the user's query."
+    )
+    
+    # Call GPT-4 to generate insights based on the data and user input
+    response = client.chat.completions.create(
+        model="gpt-4o",
+        messages=[
+            {"role": "system", "content": "You are an expert in analyzing astronomical data and generating insights."},
+            {"role": "user", "content": insights_prompt}
+        ],
+        max_tokens=max_tokens,
+        temperature=temperature
+    )
+    
+    # Extract and return GPT-4's insights
+    insights_from_data = response.choices[0].message.content.strip()
+    return insights_from_data