fixs

app.py

@@ -92,7 +92,7 @@ reranker = get_reranker("nano")
 
 # Create vectorstore and retriever
 vectorstore = get_pinecone_vectorstore(embeddings_function)
-vectorstore_graphs = Chroma(persist_directory="/home/tim/ai4s/climate_qa/dora/climate-question-answering-graphs/climate-question-answering-graphs/vectorstore_owid", embedding_function=embeddings_function)
+vectorstore_graphs = Chroma(persist_directory="/home/tim/ai4s/climate_qa/climate-question-answering/data/vectorstore_owid", embedding_function=embeddings_function)
 
 # agent = make_graph_agent(llm,vectorstore,reranker)
 agent = make_graph_agent(llm=llm, vectorstore_ipcc=vectorstore, vectorstore_graphs=vectorstore_graphs, reranker=reranker)

climateqa/engine/chains/graph_retriever.py

@@ -50,7 +50,7 @@ def make_graph_retriever_node(vectorstore, reranker, rerank_by_question=True, k_
             print("---- Retrieving graphs ----")
             
             POSSIBLE_SOURCES = ["IEA", "OWID"]
-            questions = state["questions"] if state["questions"] is not None else [state["query"]]
+            questions = state["remaining_questions"] if state["remaining_questions"] is not None and state["remaining_questions"]!=[]  else [state["query"]]
             sources_input = state["sources_input"]
 
             auto_mode = "auto" in sources_input
@@ -90,7 +90,7 @@ def make_graph_retriever_node(vectorstore, reranker, rerank_by_question=True, k_
                     docs_question = retriever.get_relevant_documents(question)
                     
                     # Rerank
-                    if reranker is not None:
+                    if reranker is not None and docs_question!=[]:
                         with suppress_output():
                             docs_question = rerank_docs(reranker,docs_question,question)
                     else:

climateqa/engine/graph.py

@@ -18,6 +18,9 @@ from .chains.translation import make_translation_node
 from .chains.intent_categorization import make_intent_categorization_node
 from .chains.retrieve_documents import make_retriever_node
 from .chains.answer_rag import make_rag_node
+from .chains.graph_retriever import make_graph_retriever_node
+from .chains.chitchat_categorization import make_chitchat_intent_categorization_node
+from .chains.set_defaults import set_defaults
 
 class GraphState(TypedDict):
     """
@@ -89,8 +92,8 @@ def make_graph_agent(llm, vectorstore_ipcc, vectorstore_graphs, reranker, thresh
     transform_query = make_query_transform_node(llm)
     translate_query = make_translation_node(llm)
     answer_chitchat = make_chitchat_node(llm)
-    answer_ai_impact = make_ai_impact_node(llm)
-    retrieve_documents = make_retriever_node(vectorstore_ipcc, reranker)
+    # answer_ai_impact = make_ai_impact_node(llm)
+    retrieve_documents = make_retriever_node(vectorstore_ipcc, reranker, llm)
     retrieve_graphs = make_graph_retriever_node(vectorstore_graphs, reranker)
     # answer_rag_graph = make_rag_graph_node(llm)
     answer_rag = make_rag_node(llm, with_docs=True)
@@ -108,7 +111,7 @@ def make_graph_agent(llm, vectorstore_ipcc, vectorstore_graphs, reranker, thresh
     # workflow.add_node("translate_query_ai", translate_query)
     workflow.add_node("answer_chitchat", answer_chitchat)
     workflow.add_node("chitchat_categorize_intent", chitchat_categorize_intent)
-    workflow.add_node("answer_ai_impact", answer_ai_impact)
+    # workflow.add_node("answer_ai_impact", answer_ai_impact)
     workflow.add_node("retrieve_graphs", retrieve_graphs)
     workflow.add_node("retrieve_graphs_chitchat", retrieve_graphs)
     # workflow.add_node("retrieve_graphs_ai", retrieve_graphs)
@@ -162,7 +165,7 @@ def make_graph_agent(llm, vectorstore_ipcc, vectorstore_graphs, reranker, thresh
     workflow.add_edge("answer_rag_no_docs", END)
     workflow.add_edge("answer_chitchat", "chitchat_categorize_intent")
     # workflow.add_edge("answer_chitchat", END)
-    workflow.add_edge("answer_ai_impact", END)
+    # workflow.add_edge("answer_ai_impact", END)
     workflow.add_edge("retrieve_graphs_chitchat", END)
     # workflow.add_edge("answer_ai_impact", "translate_query_ai")
     # workflow.add_edge("translate_query_ai", "transform_query_ai")