Update app.py

app.py

@@ -212,6 +212,66 @@ class YouTubeQATool(PipelineTool):
         except Exception as exc:
             return f"Error generating answer: {exc}"
 
+# ---------------------------------------------------------------------------
+# NEW: Extract text from an image (OCR)
+# ---------------------------------------------------------------------------
+class ExtractTextFromImageTool(Tool):
+    """OCR helper using **pytesseract** + **Pillow** (if available)."""
+
+    name = "image_ocr"
+    description = "Extract visible text from a local image file via Tesseract OCR."
+    inputs = {"image_path": {"type": "string", "description": "Path to an image."}}
+    output_type = "string"
+
+    @lru_cache(maxsize=32)
+    def forward(self, image_path: str) -> str:  # type: ignore[override]
+        path = Path(image_path).expanduser().resolve()
+        if not path.is_file():
+            return f"Error: no such image file {path}"
+        try:
+            import pytesseract
+            from PIL import Image
+        except ModuleNotFoundError:
+            return "Error: pytesseract or Pillow not installed."
+        try:
+            with Image.open(path) as img:
+                text = pytesseract.image_to_string(img)
+            return text.strip() or "(No text detected)"
+        except Exception as exc:
+            return f"Error extracting text: {exc}"
+
+
+# ---------------------------------------------------------------------------
+# NEW: Analyze CSV file
+# ---------------------------------------------------------------------------
+class AnalyzeCSVFileTool(Tool):
+    """Quick CSV introspection & basic descriptive stats with pandas."""
+
+    name = "csv_analyzer"
+    description = "Load a CSV file and give column info + summary stats."
+    inputs = {
+        "file_path": {"type": "string", "description": "Path to CSV file."},
+        "query": {"type": "string", "description": "User question (unused for now)."},
+    }
+    output_type = "string"
+
+    @lru_cache(maxsize=16)
+    def forward(self, file_path: str, query: str) -> str:  # type: ignore[override]
+        path = Path(file_path).expanduser().resolve()
+        if not path.is_file():
+            return f"Error: no such CSV file {path}"
+        try:
+            import pandas as pd
+        except ModuleNotFoundError:
+            return "Error: pandas not installed."
+        try:
+            df = pd.read_csv(path)
+            desc = df.describe(include="all", datetime_is_numeric=True).T
+            buf = [f"Loaded CSV with {len(df)} rows × {len(df.columns)} columns", "Columns: " + ", ".join(df.columns), "", "Summary stats:", desc.to_markdown()]
+            return "\n".join(buf)
+        except Exception as exc:
+            return f"Error reading CSV: {exc}"
+
 
 # ---------------------------------------------------------------------------
 # Helper: download attachment (if any)