fix: avoid duplicate references!

utils/query_engine/prepare_answer_sources.py

@@ -1,4 +1,5 @@
 import logging
+from collections import defaultdict
 
 from llama_index.core.schema import NodeWithScore
 from utils.globals import REFERENCE_SCORE_THRESHOLD
@@ -23,12 +24,8 @@ def __init__(
 
     def prepare_answer_sources(self, nodes: list[NodeWithScore | None]) -> str:
         """
-        Prepares a formatted string containing source URLs organized by tool name from the provided nodes.
-
-        This method processes a list of nodes, filtering them based on a score threshold and
-        organizing the URLs by their associated tool names. It creates a formatted output with
-        URLs numbered under their respective tool sections, limiting the number of references
-        per data source.
+        Prepares a formatted string containing unique source URLs organized by tool name
+        from the provided nodes, avoiding duplicate URLs.
 
         Parameters
         ----------
@@ -42,7 +39,7 @@ def prepare_answer_sources(self, nodes: list[NodeWithScore | None]) -> str:
 
         Returns
         -------
-        str
+        all_sources : str
             A formatted string containing numbered URLs organized by tool name, with the format:
             References:
             {tool_name}:
@@ -53,55 +50,60 @@ def prepare_answer_sources(self, nodes: list[NodeWithScore | None]) -> str:
             - The input nodes list is empty
             - No nodes meet the score threshold
             - No valid URLs are found in the nodes' metadata
-
-        Notes
-        -----
-        - URLs are only included if their node's score meets or exceeds the threshold
-          (default: 0.5)
-        - Each tool's sources are grouped together and prefixed with the tool name
-        - URLs are numbered sequentially within each tool's section
-        - Maximum number of references per data source is limited by max_refs_per_source
-          (default: 3)
-        - References are selected based on highest scores when limiting
-        - Logs error messages when no nodes are available or when all nodes are below
-          the threshold
         """
         if len(nodes) == 0:
             logging.error("No reference nodes available! returning empty string.")
             return ""
 
         cleaned_nodes = [n for n in nodes if n is not None]
 
-        # link of places that we got the answer from
-        all_sources: str = "References:\n"
+        # Group nodes by tool name while filtering by score and valid URL
+        tool_sources = defaultdict(list)
         for tool_nodes in cleaned_nodes:
-            # platform name
             tool_name = tool_nodes.sub_q.tool_name
+            for node in tool_nodes.sources:
+                if (
+                    node.score >= self.threshold
+                    and node.metadata.get("url") is not None
+                ):
+                    tool_sources[tool_name].append(node)
+
+        if not tool_sources:
+            logging.error(
+                f"All node scores are below threshold ({self.threshold}). Returning empty string!"
+            )
+            return ""
+
+        all_sources = "References:\n"
 
-            # Filter and sort nodes by score
-            valid_nodes = [
-                node
-                for node in tool_nodes.sources
-                if node.score >= self.threshold and node.metadata.get("url") is not None
-            ]
-            valid_nodes.sort(key=lambda x: x.score, reverse=True)
+        # Process each tool's nodes, remove duplicate URLs, sort and limit references
+        for tool_name, nodes_list in tool_sources.items():
+            unique_nodes = {}
+            for node in nodes_list:
+                url = node.metadata.get("url")
+                # If URL not seen yet or current node has a higher score, update it
+                if url not in unique_nodes or node.score > unique_nodes[url].score:
+                    unique_nodes[url] = node
 
-            # Limit the number of references
-            limited_nodes = valid_nodes[: self.max_refs_per_source]
+            # Sort nodes by score in descending order and limit references
+            sorted_nodes = sorted(
+                unique_nodes.values(), key=lambda x: x.score, reverse=True
+            )
+            limited_nodes = sorted_nodes[: self.max_refs_per_source]
 
             if limited_nodes:
-                urls = [node.metadata.get("url") for node in limited_nodes]
-                sources: list[str] = [
-                    f"[{idx + 1}] {url}" for idx, url in enumerate(urls)
+                sources = [
+                    f"[{idx + 1}] {node.metadata['url']}"
+                    for idx, node in enumerate(limited_nodes)
                 ]
-                sources_combined: str = "\n".join(sources)
+                sources_combined = "\n".join(sources)
                 all_sources += f"{tool_name}:\n{sources_combined}\n\n"
 
         if all_sources == "References:\n":
             logging.error(
-                f"All node scores are below threshold. threshold: {self.threshold}"
-                ". returning empty string!"
+                f"All node scores are below threshold ({self.threshold}). Returning empty string!"
             )
             return ""
 
+        # Remove trailing newlines
         return all_sources.removesuffix("\n\n")