Fix variables with GraphState

app.py

@@ -50,8 +50,8 @@ def process_query(query, architecture: Literal["A", "B", "C"]):
             "messages": [],
             "relevant_docs": [],
             "response": "",
-            "k": k,  
-            "alpha": alpha,
+            "k": k,
+            "similarity_threshold": similarity_threshold,
         }
 
     elif architecture in ["B", "C"]:

graph_agentA.py

@@ -31,16 +31,25 @@ def generate_response(state: GraphState) -> dict:
     response = llm.invoke(prompt)
     return {"response": response.content}
 
+def retrieve(state: GraphState) -> dict:
+    """Récupération sémantique : Pinecone (sémantique)"""
+
+    relevant_docs = retrieve_documents(
+        state["query"],
+        k=state.get("k"), 
+        similarity_threshold=state.get("similarity_threshold")
+    )
+    
+    return {"relevant_docs": relevant_docs}
+
 def post_process_response(state: GraphState) -> dict:
     """Post-process the response."""
     response = state["response"].strip() if isinstance(state["response"], str) else state["response"]
     return {"response": response}
 
-k = st.session_state.get("k", 30)  # Valeur par défaut 30
-similarity_threshold = st.session_state.get('similarity_threshold', 0.7)  # Valeur par défaut 0.7
 # Build the graph
 graph_builder = StateGraph(GraphState)
-graph_builder.add_node("retrieve", lambda state: {"relevant_docs": retrieve_documents(state["query"], k=k, similarity_threshold=similarity_threshold)})
+graph_builder.add_node("retrieve", retrieve)
 graph_builder.add_node("generate", generate_response)
 graph_builder.add_node("post_process", post_process_response)
 

graph_agentB.py

@@ -18,14 +18,14 @@ class GraphState(TypedDict):
 
 def retrieve_combined(state: GraphState) -> dict:
     """Récupération hybride : Pinecone (sémantique) + BM25 (mots-clés)."""
-    k = st.session_state.get("k", 30)  # Valeur par défaut 30
-    alpha = st.session_state.get("alpha", 0.5)  # Valeur par défaut 0.5
-    similarity_threshold = st.session_state.get('similarity_threshold', 0.7)  # Valeur par défaut 0.7
 
-    print(f"k: {k}")
-    print(f"similarity_threshold: {similarity_threshold}")
-    print(f"alpha: {alpha}")
-    relevant_docs = hybrid_search(state["query"], alpha=alpha, k=k, similarity_threshold=similarity_threshold)
+    relevant_docs = hybrid_search(
+        state["query"], 
+        alpha=state.get("alpha"), 
+        k=state.get("k"), 
+        similarity_threshold=state.get("similarity_threshold")
+    )
+    
     return {"relevant_docs": relevant_docs}
 
 def generate_response(state: GraphState) -> dict: