fix vision prompt discounted max_cost calculation

pyproject.toml

@@ -19,6 +19,7 @@ dependencies = [
     "websockets>=12.0",
     "nostr>=0.0.2",
     "mdurl==0.1.2",
+    "pillow>=10",
 ]
 
 [dependency-groups]

routstr/payment/helpers.py

@@ -1,9 +1,13 @@
+import base64
 import json
 import math
+from io import BytesIO
 from typing import Any
 
+import httpx
 from fastapi import HTTPException, Response
 from fastapi.requests import Request
+from PIL import Image
 from sqlmodel.ext.asyncio.session import AsyncSession
 
 from ..core import get_logger
@@ -172,6 +176,18 @@ async def calculate_discounted_max_cost(
 
     if messages := body.get("messages"):
         prompt_tokens = estimate_tokens(messages)
+
+        image_tokens = await estimate_image_tokens_in_messages(messages)
+        if image_tokens > 0:
+            logger.debug(
+                "Found images in request",
+                extra={
+                    "model": model,
+                    "image_tokens": image_tokens,
+                },
+            )
+            prompt_tokens += image_tokens
+
         estimated_prompt_delta_sats = (
             max_prompt_allowed_sats - prompt_tokens * model_pricing.prompt
         )
@@ -215,6 +231,157 @@ def estimate_tokens(messages: list) -> int:
     return len(str(messages)) // 3
 
 
+def _get_image_dimensions(image_data: bytes) -> tuple[int, int]:
+    """Extract image dimensions from image bytes."""
+    try:
+        img = Image.open(BytesIO(image_data))
+        return img.size
+    except Exception as e:
+        logger.warning(
+            "Failed to get image dimensions, using default",
+            extra={"error": str(e)},
+        )
+        return (512, 512)
+
+
+async def _fetch_image_from_url(url: str) -> bytes | None:
+    """Fetch image from URL."""
+    try:
+        async with httpx.AsyncClient(timeout=10.0) as client:
+            response = await client.get(url)
+            response.raise_for_status()
+            return response.content
+    except Exception as e:
+        logger.warning(
+            "Failed to fetch image from URL",
+            extra={"error": str(e), "url": url[:100]},
+        )
+        return None
+
+
+def _calculate_image_tokens(width: int, height: int, detail: str = "auto") -> int:
+    """Calculate image tokens based on OpenAI's vision pricing.
+
+    For low detail: 85 tokens
+    For high detail/auto: 85 base tokens + 170 tokens per 512px tile
+    """
+    if detail == "low":
+        return 85
+
+    if width > 2048 or height > 2048:
+        aspect_ratio = width / height
+        if width > height:
+            width = 2048
+            height = int(width / aspect_ratio)
+        else:
+            height = 2048
+            width = int(height * aspect_ratio)
+
+    if width > 768 or height > 768:
+        aspect_ratio = width / height
+        if width > height:
+            width = 768
+            height = int(width / aspect_ratio)
+        else:
+            height = 768
+            width = int(height * aspect_ratio)
+
+    tiles_width = (width + 511) // 512
+    tiles_height = (height + 511) // 512
+    num_tiles = tiles_width * tiles_height
+
+    return 85 + (170 * num_tiles)
+
+
+async def estimate_image_tokens_in_messages(messages: list) -> int:
+    """Estimate total tokens for all images in messages.
+
+    Supports both base64 encoded images and image URLs.
+    """
+    total_image_tokens = 0
+
+    for message in messages:
+        if not isinstance(message, dict):
+            continue
+
+        content = message.get("content")
+        if not content:
+            continue
+
+        if isinstance(content, str):
+            continue
+
+        if not isinstance(content, list):
+            continue
+
+        for content_item in content:
+            if not isinstance(content_item, dict):
+                continue
+
+            content_type = content_item.get("type")
+            if content_type not in ("image_url", "input_image"):
+                continue
+
+            image_url_data = content_item.get("image_url")
+            if not image_url_data:
+                continue
+
+            if isinstance(image_url_data, str):
+                url = image_url_data
+                detail = "auto"
+            elif isinstance(image_url_data, dict):
+                url = image_url_data.get("url", "")
+                detail = image_url_data.get("detail", "auto")
+            else:
+                continue
+
+            if not url:
+                continue
+
+            if url.startswith("data:image/"):
+                try:
+                    header, base64_data = url.split(",", 1)
+                    image_bytes = base64.b64decode(base64_data)
+                    width, height = _get_image_dimensions(image_bytes)
+                    tokens = _calculate_image_tokens(width, height, detail)
+                    total_image_tokens += tokens
+                    logger.debug(
+                        "Calculated tokens for base64 image",
+                        extra={
+                            "width": width,
+                            "height": height,
+                            "detail": detail,
+                            "tokens": tokens,
+                        },
+                    )
+                except Exception as e:
+                    logger.warning(
+                        "Failed to process base64 image",
+                        extra={"error": str(e)},
+                    )
+                    total_image_tokens += 85
+            else:
+                image_bytes_or_none = await _fetch_image_from_url(url)
+                if image_bytes_or_none:
+                    width, height = _get_image_dimensions(image_bytes_or_none)
+                    tokens = _calculate_image_tokens(width, height, detail)
+                    total_image_tokens += tokens
+                    logger.debug(
+                        "Calculated tokens for URL image",
+                        extra={
+                            "url": url[:100],
+                            "width": width,
+                            "height": height,
+                            "detail": detail,
+                            "tokens": tokens,
+                        },
+                    )
+                else:
+                    total_image_tokens += 85
+
+    return total_image_tokens
+
+
 def create_error_response(
     error_type: str,
     message: str,

tests/integration/conftest.py

@@ -512,7 +512,7 @@ async def integration_app(
         from routstr.core.settings import settings as _settings
 
         # Passthrough discounted max cost to avoid dependence on MODELS in tests
-        def _passthrough_discount(
+        async def _passthrough_discount(
             max_cost_for_model: int,
             body: dict,
             model_obj: Any = None,

tests/unit/test_image_tokens.py

@@ -0,0 +1,189 @@
+import base64
+from io import BytesIO
+
+import pytest
+from PIL import Image
+
+from routstr.payment.helpers import (
+    _calculate_image_tokens,
+    _get_image_dimensions,
+    estimate_image_tokens_in_messages,
+)
+
+
+def create_test_image(width: int, height: int) -> bytes:
+    """Create a test image with specified dimensions."""
+    img = Image.new("RGB", (width, height), color="red")
+    buffer = BytesIO()
+    img.save(buffer, format="JPEG")
+    return buffer.getvalue()
+
+
+def test_calculate_image_tokens_low_detail() -> None:
+    """Test that low detail images always return 85 tokens."""
+    assert _calculate_image_tokens(100, 100, "low") == 85
+    assert _calculate_image_tokens(1000, 1000, "low") == 85
+    assert _calculate_image_tokens(2048, 2048, "low") == 85
+
+
+def test_calculate_image_tokens_high_detail_small() -> None:
+    """Test token calculation for small images."""
+    tokens = _calculate_image_tokens(512, 512, "high")
+    assert tokens == 85 + 170
+
+
+def test_calculate_image_tokens_high_detail_large() -> None:
+    """Test token calculation for large images that need tiling."""
+    tokens = _calculate_image_tokens(768, 768, "high")
+    assert tokens > 85
+
+
+def test_calculate_image_tokens_auto() -> None:
+    """Test that auto detail behaves like high detail."""
+    width, height = 512, 512
+    auto_tokens = _calculate_image_tokens(width, height, "auto")
+    high_tokens = _calculate_image_tokens(width, height, "high")
+    assert auto_tokens == high_tokens
+
+
+def test_get_image_dimensions() -> None:
+    """Test extracting dimensions from image bytes."""
+    image_bytes = create_test_image(800, 600)
+    width, height = _get_image_dimensions(image_bytes)
+    assert width == 800
+    assert height == 600
+
+
+def test_get_image_dimensions_invalid() -> None:
+    """Test that invalid image data returns default dimensions."""
+    invalid_bytes = b"not an image"
+    width, height = _get_image_dimensions(invalid_bytes)
+    assert width == 512
+    assert height == 512
+
+
+@pytest.mark.asyncio
+async def test_estimate_image_tokens_base64() -> None:
+    """Test estimating tokens for base64 encoded images."""
+    image_bytes = create_test_image(512, 512)
+    base64_image = base64.b64encode(image_bytes).decode("utf-8")
+
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What's in this image?"},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
+                },
+            ],
+        }
+    ]
+
+    tokens = await estimate_image_tokens_in_messages(messages)
+    assert tokens > 0
+
+
+@pytest.mark.asyncio
+async def test_estimate_image_tokens_multiple_images() -> None:
+    """Test estimating tokens for multiple images."""
+    image_bytes = create_test_image(512, 512)
+    base64_image = base64.b64encode(image_bytes).decode("utf-8")
+
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Compare these images"},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
+                },
+            ],
+        }
+    ]
+
+    tokens = await estimate_image_tokens_in_messages(messages)
+    assert tokens > 0
+
+
+@pytest.mark.asyncio
+async def test_estimate_image_tokens_with_detail() -> None:
+    """Test that detail parameter affects token calculation."""
+    image_bytes = create_test_image(512, 512)
+    base64_image = base64.b64encode(image_bytes).decode("utf-8")
+
+    messages_low = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": f"data:image/jpeg;base64,{base64_image}",
+                        "detail": "low",
+                    },
+                },
+            ],
+        }
+    ]
+
+    messages_high = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": f"data:image/jpeg;base64,{base64_image}",
+                        "detail": "high",
+                    },
+                },
+            ],
+        }
+    ]
+
+    tokens_low = await estimate_image_tokens_in_messages(messages_low)
+    tokens_high = await estimate_image_tokens_in_messages(messages_high)
+
+    assert tokens_low == 85
+    assert tokens_high > tokens_low
+
+
+@pytest.mark.asyncio
+async def test_estimate_image_tokens_no_images() -> None:
+    """Test that messages without images return 0 tokens."""
+    messages = [
+        {"role": "user", "content": "Hello, how are you?"},
+        {"role": "assistant", "content": "I'm doing well, thank you!"},
+    ]
+
+    tokens = await estimate_image_tokens_in_messages(messages)
+    assert tokens == 0
+
+
+@pytest.mark.asyncio
+async def test_estimate_image_tokens_input_image_type() -> None:
+    """Test that input_image type is also supported."""
+    image_bytes = create_test_image(512, 512)
+    base64_image = base64.b64encode(image_bytes).decode("utf-8")
+
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "input_image",
+                    "image_url": f"data:image/jpeg;base64,{base64_image}",
+                },
+            ],
+        }
+    ]
+
+    tokens = await estimate_image_tokens_in_messages(messages)
+    assert tokens > 0

uv.lock

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 name = "pluggy"
 version = "1.6.0"
@@ -1783,7 +1878,7 @@ wheels = [
 
 [[package]]
 name = "routstr"
-version = "0.2.0"
+version = "0.2.0b0"
 source = { editable = "." }
 dependencies = [
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@@ -1795,6 +1890,7 @@ dependencies = [
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     { name = "mdurl" },
     { name = "nostr" },
+    { name = "pillow" },
     { name = "python-json-logger" },
     { name = "secp256k1" },
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