Update app.py

app.py

@@ -6,50 +6,60 @@ def analyze_file(message, file):
     if not file:
         return "Please upload a file."
 
-    # Get file path string instead of using file.read()
     filepath = file.name
+    filename = filepath.split("/")[-1]
+    ext = filename.split(".")[-1].lower()
 
     try:
-        if filepath.endswith(".jsonl"):
+        # Known types
+        if ext == "jsonl":
             with open(filepath, "r", encoding="utf-8") as f:
                 lines = f.readlines()
                 data = [json.loads(line) for line in lines]
-            return f"📄 This is a JSONL file with *{len(data)}* entries."
+            return f"📄 JSONL file with *{len(data)}* entries."
 
-        elif filepath.endswith(".json"):
+        elif ext == "json":
             with open(filepath, "r", encoding="utf-8") as f:
                 content = json.load(f)
             if isinstance(content, dict):
-                return f"📁 JSON file with *{len(content.keys())}* top-level keys."
+                return f"📁 JSON with *{len(content.keys())}* top-level keys."
             elif isinstance(content, list):
-                return f"📁 JSON file with *{len(content)}* items in a list."
+                return f"📁 JSON with *{len(content)}* list items."
             else:
-                return f"🌀 JSON file with data type: {type(content)}"
+                return f"🌀 JSON with data type: {type(content)}"
 
-        elif filepath.endswith(".csv"):
+        elif ext == "csv":
             df = pd.read_csv(filepath)
-            return f"📊 CSV file with *{df.shape[0]}* rows and *{df.shape[1]}* columns."
+            return f"📊 CSV with *{df.shape[0]}* rows and *{df.shape[1]}* columns."
 
-        elif filepath.endswith(".py"):
+        elif ext == "py":
             with open(filepath, "r", encoding="utf-8") as f:
-                lines = f.readlines()
-            return f"💻 Python file with *{len(lines)}* lines of code."
+                code = f.read()
+            return f"💻 Python file with *{len(code.splitlines())}* lines of code."
 
+        # Unknown types – attempt plain text preview
         else:
-            return f"⚠ Unsupported file type: {filepath}. Try .jsonl, .json, .csv, or .py."
+            try:
+                with open(filepath, "r", encoding="utf-8") as f:
+                    content = f.read()
+                preview = content[:1000]
+                return f"📦 {ext} file preview:\n\n\n{preview}\n"
+            except Exception as e:
+                return f"❌ Cannot preview this {ext} file. Likely binary. Error: {e}"
 
     except Exception as e:
         return f"❌ Error processing file: {e}"
 
+# Gradio interface
 iface = gr.Interface(
     fn=analyze_file,
     inputs=[
-        gr.Textbox(label="Message (not used yet)", placeholder="e.g. How many questions?"),
-        gr.File(label="Upload a file", file_types=[".jsonl", ".json", ".csv", ".py"])
+        gr.Textbox(label="Message (not used yet)", placeholder="You can ask questions soon"),
+        gr.File(label="Upload any file")
     ],
     outputs="text",
-    title="AI Assistant – Multi-File Handler",
-    description="Upload a .jsonl, .json, .csv, or .py file and I’ll tell you what’s inside."
+    title="AI Assistant – Universal File Reader",
+    description="Upload any file (.json, .csv, .py, .txt, .docx, etc). I’ll preview what I can."
 )
 
 iface.launch()