Add satellite image summarization tool (#7)

* Add dspy & jupyterlab as dependency

* Add image summarizer agent tool

* Add test for summarize tool

* Remove try except

---------

Co-authored-by: Daniel Wiesmann <yellowcap@users.noreply.github.com>

src/geo_assistant/tools/summarize.py

@@ -0,0 +1,97 @@
+"""Tools for summarizing satellite images using LLM-based analysis."""
+
+from typing import Annotated, Optional
+import dspy
+from langchain_core.tools import tool
+from langgraph.types import Command
+from langchain_core.messages import ToolMessage
+from langchain_core.tools.base import InjectedToolCallId
+
+
+class SatImgSummary(dspy.Signature):
+    "Describe things you see in the satellite image."
+
+    img: dspy.Image = dspy.InputField(desc="A satellite image")
+    answer: str = dspy.OutputField(desc="Description of the image")
+
+
+class SatImgSummaryAgent(dspy.Module):
+    """Agent for generating summaries of satellite images using an LLM."""
+
+    def __init__(
+        self,
+        model: str = "ministral-3:14b-cloud",
+        api_base: str = "http://localhost:11434",
+        temperature: float = 0.5,
+        max_tokens: int = 4_096,
+    ) -> None:
+        """Initialize the satellite image summary agent.
+
+        Args:
+            model: The Ollama model to use for summarization
+            api_base: Base URL for the Ollama API
+            temperature: Sampling temperature (0-1)
+            max_tokens: Maximum tokens to generate
+        """
+        super().__init__()
+        self.ollama_model = dspy.LM(
+            model=f"ollama/{model}",
+            api_base=api_base,
+            api_key="",
+            temperature=temperature,
+            max_tokens=max_tokens,
+        )
+        dspy.configure(lm=self.ollama_model)
+        self.summarizer = dspy.Predict(SatImgSummary)
+
+    def forward(self, img_url: str) -> dspy.Prediction:
+        """Generate a summary for the given image URL.
+
+        Args:
+            img_url: URL of the image to summarize
+
+        Returns:
+            dspy.Prediction containing the image summary
+        """
+        return self.summarizer(img=dspy.Image(img_url))
+
+
+# Singleton instance to avoid repeated initialization
+_SUMMARIZER_AGENT = SatImgSummaryAgent()
+
+
+@tool
+def summarize_sat_img(
+    img_url: str,
+    tool_call_id: Annotated[Optional[str], InjectedToolCallId] = None,
+) -> Command:
+    """Summarize the contents of a satellite image using an LLM.
+
+    Args:
+        img_url: URL of the satellite image to analyze
+        tool_call_id: Optional ID for tracking the tool call
+
+    Returns:
+        Command containing the image summary and metadata
+
+    Raises:
+        ValueError: If the image URL is invalid or the image cannot be processed
+    """
+    if not img_url or not isinstance(img_url, str):
+        raise ValueError("img_url must be a non-empty string")
+
+    summary = _SUMMARIZER_AGENT(img_url)
+    message_content = summary.answer
+    artifact = {"img_url": img_url}
+
+    return Command(
+        update={
+            "messages": [
+                ToolMessage(
+                    content=message_content,
+                    artifact=artifact,
+                    tool_call_id=tool_call_id,
+                )
+            ]
+        }
+    )