diff --git a/libs/python/agent/agent/loops/gemini.py b/libs/python/agent/agent/loops/gemini.py
new file mode 100644
index 00000000..5ac4db51
--- /dev/null
+++ b/libs/python/agent/agent/loops/gemini.py
@@ -0,0 +1,391 @@
+"""
+Gemini 2.5 Computer Use agent loop
+
+Maps internal Agent SDK message format to Google's Gemini Computer Use API and back.
+
+Key features:
+- Lazy import of google.genai
+- Configure Computer Use tool with excluded browser-specific predefined functions
+- Optional custom function declarations hook for computer-call specific functions
+- Convert Gemini function_call parts into internal computer_call actions
+"""
+
+from __future__ import annotations
+
+import base64
+import io
+import uuid
+from typing import Any, Dict, List, Optional, Tuple
+
+from PIL import Image
+
+from ..decorators import register_agent
+from ..loops.base import AsyncAgentConfig
+from ..types import AgentCapability
+
+
+def _lazy_import_genai():
+    """Import google.genai lazily to avoid hard dependency unless used."""
+    try:
+        from google import genai  # type: ignore
+        from google.genai import types  # type: ignore
+        return genai, types
+    except Exception as e:  # pragma: no cover
+        raise RuntimeError(
+            "google.genai is required for the Gemini Computer Use loop. Install the Google Gemini SDK."
+        ) from e
+
+
+def _data_url_to_bytes(data_url: str) -> Tuple[bytes, str]:
+    """Convert a data URL to raw bytes and mime type."""
+    if not data_url.startswith("data:"):
+        # Assume it's base64 png payload
+        try:
+            return base64.b64decode(data_url), "image/png"
+        except Exception:
+            return b"", "application/octet-stream"
+    header, b64 = data_url.split(",", 1)
+    mime = "image/png"
+    if ";" in header:
+        mime = header.split(";")[0].split(":", 1)[1] or "image/png"
+    return base64.b64decode(b64), mime
+
+
+def _bytes_image_size(img_bytes: bytes) -> Tuple[int, int]:
+    try:
+        img = Image.open(io.BytesIO(img_bytes))
+        return img.size
+    except Exception:
+        return (1024, 768)
+
+
+def _find_last_user_text(messages: List[Dict[str, Any]]) -> List[str]:
+    texts: List[str] = []
+    for msg in reversed(messages):
+        if msg.get("type") in (None, "message") and msg.get("role") == "user":
+            content = msg.get("content")
+            if isinstance(content, str):
+                return [content]
+            elif isinstance(content, list):
+                for c in content:
+                    if c.get("type") in ("input_text", "output_text") and c.get("text"):
+                        texts.append(c["text"])  # newest first
+                if texts:
+                    return list(reversed(texts))
+    return []
+
+
+def _find_last_screenshot(messages: List[Dict[str, Any]]) -> Optional[bytes]:
+    for msg in reversed(messages):
+        if msg.get("type") == "computer_call_output":
+            out = msg.get("output", {})
+            if isinstance(out, dict) and out.get("type") in ("input_image", "computer_screenshot"):
+                image_url = out.get("image_url", "")
+                if image_url:
+                    data, _ = _data_url_to_bytes(image_url)
+                    return data
+    return None
+
+
+def _denormalize(v: int, size: int) -> int:
+    # Gemini returns 0-999 normalized
+    try:
+        return max(0, min(size - 1, int(round(v / 1000 * size))))
+    except Exception:
+        return 0
+
+
+def _map_gemini_fc_to_computer_call(
+    fc: Dict[str, Any],
+    screen_w: int,
+    screen_h: int,
+) -> Optional[Dict[str, Any]]:
+    name = fc.get("name")
+    args = fc.get("args", {}) or {}
+
+    action: Dict[str, Any] = {}
+    if name == "click_at":
+        x = _denormalize(int(args.get("x", 0)), screen_w)
+        y = _denormalize(int(args.get("y", 0)), screen_h)
+        action = {"type": "click", "x": x, "y": y, "button": "left"}
+    elif name == "type_text_at":
+        x = _denormalize(int(args.get("x", 0)), screen_w)
+        y = _denormalize(int(args.get("y", 0)), screen_h)
+        text = args.get("text", "")
+        if args.get("press_enter") == True:
+            text += "\n"
+        action = {"type": "type", "x": x, "y": y, "text": text}
+    elif name == "hover_at":
+        x = _denormalize(int(args.get("x", 0)), screen_w)
+        y = _denormalize(int(args.get("y", 0)), screen_h)
+        action = {"type": "move", "x": x, "y": y}
+    elif name == "key_combination":
+        keys = str(args.get("keys", ""))
+        action = {"type": "keypress", "keys": keys}
+    elif name == "scroll_document":
+        direction = args.get("direction", "down")
+        magnitude = 800
+        dx, dy = 0, 0
+        if direction == "down":
+            dy = magnitude
+        elif direction == "up":
+            dy = -magnitude
+        elif direction == "right":
+            dx = magnitude
+        elif direction == "left":
+            dx = -magnitude
+        action = {"type": "scroll", "scroll_x": dx, "scroll_y": dy, "x": int(screen_w / 2), "y": int(screen_h / 2)}
+    elif name == "scroll_at":
+        x = _denormalize(int(args.get("x", 500)), screen_w)
+        y = _denormalize(int(args.get("y", 500)), screen_h)
+        direction = args.get("direction", "down")
+        magnitude = int(args.get("magnitude", 800))
+        dx, dy = 0, 0
+        if direction == "down":
+            dy = magnitude
+        elif direction == "up":
+            dy = -magnitude
+        elif direction == "right":
+            dx = magnitude
+        elif direction == "left":
+            dx = -magnitude
+        action = {"type": "scroll", "scroll_x": dx, "scroll_y": dy, "x": x, "y": y}
+    elif name == "drag_and_drop":
+        x = _denormalize(int(args.get("x", 0)), screen_w)
+        y = _denormalize(int(args.get("y", 0)), screen_h)
+        dx = _denormalize(int(args.get("destination_x", x)), screen_w)
+        dy = _denormalize(int(args.get("destination_y", y)), screen_h)
+        action = {"type": "drag", "start_x": x, "start_y": y, "end_x": dx, "end_y": dy, "button": "left"}
+    elif name == "wait_5_seconds":
+        action = {"type": "wait"}
+    else:
+        # Unsupported / excluded browser-specific or custom function; ignore
+        return None
+
+    return {
+        "type": "computer_call",
+        "call_id": uuid.uuid4().hex,
+        "status": "completed",
+        "action": action,
+    }
+
+
+@register_agent(models=r"^gemini-2\.5-computer-use-preview-10-2025$")
+class GeminiComputerUseConfig(AsyncAgentConfig):
+    async def predict_step(
+        self,
+        messages: List[Dict[str, Any]],
+        model: str,
+        tools: Optional[List[Dict[str, Any]]] = None,
+        max_retries: Optional[int] = None,
+        stream: bool = False,
+        computer_handler=None,
+        use_prompt_caching: Optional[bool] = False,
+        _on_api_start=None,
+        _on_api_end=None,
+        _on_usage=None,
+        _on_screenshot=None,
+        **kwargs,
+    ) -> Dict[str, Any]:
+        genai, types = _lazy_import_genai()
+
+        client = genai.Client()
+
+        # Build excluded predefined functions for browser-specific behavior
+        excluded = [
+            "open_web_browser",
+            "search",
+            "navigate",
+            "go_forward",
+            "go_back",
+            "scroll_document",
+        ]
+        # Optional custom functions: can be extended by host code via `tools` parameter later if desired
+        CUSTOM_FUNCTION_DECLARATIONS: List[Any] = []
+
+        # Compose tools config
+        generate_content_config = types.GenerateContentConfig(
+            tools=[
+                types.Tool(
+                    computer_use=types.ComputerUse(
+                        environment=types.Environment.ENVIRONMENT_BROWSER,
+                        excluded_predefined_functions=excluded,
+                    )
+                ),
+                # types.Tool(function_declarations=CUSTOM_FUNCTION_DECLARATIONS),  # enable when custom functions needed
+            ]
+        )
+
+        # Prepare contents: last user text + latest screenshot
+        user_texts = _find_last_user_text(messages)
+        screenshot_bytes = _find_last_screenshot(messages)
+
+        parts: List[Any] = []
+        for t in user_texts:
+            parts.append(types.Part(text=t))
+
+        screen_w, screen_h = 1024, 768
+        if screenshot_bytes:
+            screen_w, screen_h = _bytes_image_size(screenshot_bytes)
+            parts.append(types.Part.from_bytes(data=screenshot_bytes, mime_type="image/png"))
+
+        # If we don't have any content, at least pass an empty user part to prompt reasoning
+        if not parts:
+            parts = [types.Part(text="Proceed to the next action.")]
+
+        contents = [types.Content(role="user", parts=parts)]
+
+        api_kwargs = {
+            "model": model,
+            "contents": contents,
+            "config": generate_content_config,
+        }
+
+        if _on_api_start:
+            await _on_api_start({
+                "model": api_kwargs["model"],
+                # "contents": api_kwargs["contents"], # Disabled for now
+                "config": api_kwargs["config"],
+            })
+
+        response = client.models.generate_content(**api_kwargs)
+
+        if _on_api_end:
+            await _on_api_end({
+                "model": api_kwargs["model"],
+                # "contents": api_kwargs["contents"], # Disabled for now
+                "config": api_kwargs["config"],
+            }, response)
+
+        # Usage (Gemini SDK may not always provide token usage; populate when available)
+        usage: Dict[str, Any] = {}
+        try:
+            # Some SDKs expose response.usage; if available, copy
+            if getattr(response, "usage_metadata", None):
+                md = response.usage_metadata
+                usage = {
+                    "prompt_tokens": getattr(md, "prompt_token_count", None) or 0,
+                    "completion_tokens": getattr(md, "candidates_token_count", None) or 0,
+                    "total_tokens": getattr(md, "total_token_count", None) or 0,
+                }
+        except Exception:
+            pass
+
+        if _on_usage and usage:
+            await _on_usage(usage)
+
+        # Parse output into internal items
+        output_items: List[Dict[str, Any]] = []
+
+        candidate = response.candidates[0]
+        # Text parts from the model (assistant message)
+        text_parts: List[str] = []
+        function_calls: List[Dict[str, Any]] = []
+        for p in candidate.content.parts:
+            if getattr(p, "text", None):
+                text_parts.append(p.text)
+            if getattr(p, "function_call", None):
+                # p.function_call has name and args
+                fc = {
+                    "name": getattr(p.function_call, "name", None),
+                    "args": dict(getattr(p.function_call, "args", {}) or {}),
+                }
+                function_calls.append(fc)
+
+        if text_parts:
+            output_items.append(
+                {
+                    "type": "message",
+                    "role": "assistant",
+                    "content": [{"type": "output_text", "text": "\n".join(text_parts)}],
+                }
+            )
+
+        # Map function calls to internal computer_call actions
+        for fc in function_calls:
+            item = _map_gemini_fc_to_computer_call(fc, screen_w, screen_h)
+            if item is not None:
+                output_items.append(item)
+
+        return {"output": output_items, "usage": usage}
+
+    async def predict_click(
+        self,
+        model: str,
+        image_b64: str,
+        instruction: str,
+        **kwargs,
+    ) -> Optional[Tuple[float, float]]:
+        """Ask Gemini CUA to output a single click action for the given instruction.
+
+        Excludes all predefined tools except `click_at` and sends the screenshot.
+        Returns pixel (x, y) if a click is proposed, else None.
+        """
+        genai, types = _lazy_import_genai()
+
+        client = genai.Client()
+
+        # Exclude all but click_at
+        exclude_all_but_click = [
+            "open_web_browser",
+            "wait_5_seconds",
+            "go_back",
+            "go_forward",
+            "search",
+            "navigate",
+            "hover_at",
+            "type_text_at",
+            "key_combination",
+            "scroll_document",
+            "scroll_at",
+            "drag_and_drop",
+        ]
+
+        config = types.GenerateContentConfig(
+            tools=[
+                types.Tool(
+                    computer_use=types.ComputerUse(
+                        environment=types.Environment.ENVIRONMENT_BROWSER,
+                        excluded_predefined_functions=exclude_all_but_click,
+                    )
+                )
+            ]
+        )
+
+        # Prepare prompt parts
+        try:
+            img_bytes = base64.b64decode(image_b64)
+        except Exception:
+            img_bytes = b""
+
+        w, h = _bytes_image_size(img_bytes) if img_bytes else (1024, 768)
+
+        parts: List[Any] = [types.Part(text=f"Click {instruction}.")]
+        if img_bytes:
+            parts.append(types.Part.from_bytes(data=img_bytes, mime_type="image/png"))
+
+        contents = [types.Content(role="user", parts=parts)]
+
+        response = client.models.generate_content(
+            model=model,
+            contents=contents,
+            config=config,
+        )
+
+        # Parse first click_at
+        try:
+            candidate = response.candidates[0]
+            for p in candidate.content.parts:
+                fc = getattr(p, "function_call", None)
+                if fc and getattr(fc, "name", None) == "click_at":
+                    args = dict(getattr(fc, "args", {}) or {})
+                    x = _denormalize(int(args.get("x", 0)), w)
+                    y = _denormalize(int(args.get("y", 0)), h)
+                    return float(x), float(y)
+        except Exception:
+            return None
+
+        return None
+
+    def get_capabilities(self) -> List[AgentCapability]:
+        return ["click", "step"]