Deploy explorer to Hugging Face Spaces

evals/interactive_explorer.py

@@ -1448,7 +1448,26 @@ Return a single JSON object containing:
     client = OpenAI(api_key=api_key)
 
     def _judge(img_path: Path) -> dict:
-        b64 = base64.b64encode(img_path.read_bytes()).decode("utf-8")
+        from PIL import Image
+        import io
+
+        # Open image using Pillow to normalize color space and remove transparency
+        with Image.open(img_path) as img:
+            # Create a solid white background image matching the size
+            background = Image.new("RGB", img.size, (255, 255, 255))
+
+            # If the image has an alpha channel, use it as a mask when pasting
+            if img.mode in ("RGBA", "LA") or (img.mode == "P" and "transparency" in img.info):
+                background.paste(img, mask=img.convert("RGBA").split()[3])
+            else:
+                background.paste(img)
+
+            # Save the flattened RGB image as a JPEG to a byte buffer
+            buffer = io.BytesIO()
+            background.save(buffer, format="JPEG", quality=90)
+            jpeg_bytes = buffer.getvalue()
+
+        b64 = base64.b64encode(jpeg_bytes).decode("utf-8")
         response = client.chat.completions.create(
             model="gpt-4o",
             response_format={"type": "json_object"},
@@ -1461,7 +1480,7 @@ Return a single JSON object containing:
                     "role": "user",
                     "content": [
                         {"type": "text", "text": audit_prompt},
-                        {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64}"}}
+                        {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64}"}}
                     ]
                 }
             ],

pyproject.toml

@@ -16,14 +16,23 @@ dependencies = [
   "pydantic-settings>=2.0.0",
   "python-dotenv>=1.0.0",
   "draco @ git+https://github.com/avsolatorio/draco2.git@data360-mcp",
+  "opencensus-ext-azure>=1.1.13",
+  "azure-monitor-opentelemetry>=1.6.0",
   "pandas>=3.0.0",
   "cachetools>=6.2.4",
   "scikit-learn>=1.8.0",
+  "opentelemetry-instrumentation-httpx>=0.50b0",
+  "opentelemetry-sdk>=1.28.0",
+  "opentelemetry-exporter-otlp>=1.28.0",
   "vl-convert-python>=1.9.0.post1",
   "huggingface-hub",
-  "openai",
+  "Pillow>=10.0.0",
 ]
 
+[project.optional-dependencies]
+# LangChain / LangGraph client (workspace package); use: uv sync --extra agent
+agent = ["data360-mcp-agent"]
+
 [build-system]
 requires = ["setuptools>=42", 'setuptools-scm']
 build-backend = "setuptools.build_meta"
@@ -34,6 +43,26 @@ where = ["src"]
 [tool.setuptools.package-data]
 data360 = ["tool_contract_version.json", "databases.json", "ref_area_groups.json"]
 
+[tool.uv.workspace]
+members = ["packages/data360-mcp-agent"]
+
+[dependency-groups]
+dev = [
+  "data360-mcp-agent",
+  "pre-commit>=4.5.0",
+  "pyright>=1.1.407",
+  "ruff>=0.14.8",
+  "poethepoet>=0.27.0",
+  "pytest>=8.0.0",
+  "pytest-asyncio>=0.23.0",
+  "pytest-httpx>=0.27.0",
+  "pytest-cov>=4.1.0",
+  "pip-licenses>=5.0.0",
+  "pip-audit>=2.10.0",
+  "requests>=2.32.0",
+  "deepeval>=4.1.0",
+]
+
 [tool.ruff.lint]
 select = ['I', 'UP', 'PL', 'F401']
 
@@ -42,6 +71,9 @@ name = "pypi"
 url = "https://pypi.org/simple"
 default = true
 
+[tool.uv.sources]
+data360-mcp-agent = { workspace = true }
+
 [tool.pyright]
 typeCheckingMode = "standard"
 extraPaths = ["packages/data360-mcp-agent/src"]