Update app/graph/nodes/synthesizer.py

app/graph/nodes/synthesizer.py

@@ -1,36 +1,36 @@
-# app/graph/nodes/synthesizer.py
-
-from app.core.llm_engine import llm
-from app.core.prompts.rag_prompt import rag_prompt
-from langchain_core.output_parsers import StrOutputParser
-
-
-def synthesizer_node(state):
-    route = state.get("route")
-    general_answer = state.get("general_answer")
-
-    if route == ("general", "hybrid"):
-        return {
-            **state,
-            "final_answer": general_answer or "I couldn't find a relevant answer."
-        }
-
-    query = state["query"]
-    context = state.get("context", "")
-    history = state.get("history", "")
-
-
-    chain = rag_prompt | llm | StrOutputParser()
-    
-    answer = chain.invoke({
-        "context": context,
-        "query": query,
-        "history": history
-    })
-
-    return {
-        **state,
-        "final_answer": answer.strip()
-    }
-
-
+# app/graph/nodes/synthesizer.py
+
+from app.core.llm_engine import llm
+from app.core.prompts.rag_prompt import rag_prompt
+from langchain_core.output_parsers import StrOutputParser
+
+
+def synthesizer_node(state):
+    route = state.get("route")
+    general_answer = state.get("general_answer")
+
+    if route in ("general", "hybrid"):
+        return {
+            **state,
+            "final_answer": general_answer or "I couldn't find a relevant answer."
+        }
+
+    query = state["query"]
+    context = state.get("context", "")
+    history = state.get("history", "")
+
+
+    chain = rag_prompt | llm | StrOutputParser()
+    
+    answer = chain.invoke({
+        "context": context,
+        "query": query,
+        "history": history
+    })
+
+    return {
+        **state,
+        "final_answer": answer.strip()
+    }
+
+