f-string bugfix

app.py

@@ -360,9 +360,9 @@ def generate_response(question: str, dora: bool, rts: bool, news: bool):
     state = app.invoke({"question": question, "selected_sources": selected_sources})
     return (
         state["generation"],
-        ('\n\n'.join([f"***{doc.metadata["source"]} section {doc.metadata['section']}***: {doc.page_content}" for doc in state["dora_docs"]])) if "dora_docs" in state and state["dora_docs"] else 'No documents available.',
-        ('\n\n'.join([f"***{doc.metadata["source"]}, section {doc.metadata['section']}***: {doc.page_content}" for doc in state["dora_rts_docs"]])) if "dora_rts_docs" in state and state["dora_rts_docs"] else 'No documents available.',
-        ('\n\n'.join([f"***{doc.metadata["source"]}***: {doc.page_content}" for doc in state["dora_news_docs"]])) if "dora_news_docs" in state and state["dora_news_docs"] else 'No documents available.',
+        ('\n\n'.join([f"***{doc.metadata['source']} section {doc.metadata['section']}***: {doc.page_content}" for doc in state["dora_docs"]])) if "dora_docs" in state and state["dora_docs"] else 'No documents available.',
+        ('\n\n'.join([f"***{doc.metadata['source']}, section {doc.metadata['section']}***: {doc.page_content}" for doc in state["dora_rts_docs"]])) if "dora_rts_docs" in state and state["dora_rts_docs"] else 'No documents available.',
+        ('\n\n'.join([f"***{doc.metadata['source']}***: {doc.page_content}" for doc in state["dora_news_docs"]])) if "dora_news_docs" in state and state["dora_news_docs"] else 'No documents available.',
     )
 
 def show_loading(prompt: str):
@@ -392,7 +392,7 @@ def run_gradio():
         # Adding a sliding navbar
         with gr.Column(scale=1, elem_id='navbar'):
             gr.Image(
-                '..\\deployment\\logo.png', 
+                './logo.png', 
                 interactive=False, 
                 show_label=False, 
                 scale=1,
@@ -480,7 +480,7 @@ if __name__ == "__main__":
 
     dora_question_rewriter = IMPROVE_PROMPT | tool_llm | StrOutputParser()
     retrieval_grader = RELEVANCE_PROMPT | fast_llm.with_structured_output(GradeDocuments)
-    answer_chain = ANSWER_PROMPT | smart_llm | StrOutputParser() #former RAG chain
+    answer_chain = ANSWER_PROMPT | tool_llm | StrOutputParser() #former RAG chain
     hallucination_grader = HALLUCINATION_PROMPT | fast_llm.with_structured_output(GradeHallucinations)
     answer_grader = RESOLVER_PROMPT | fast_llm.with_structured_output(GradeAnswer)
     question_rewriter = REWRITER_PROMPT | rewrite_llm | StrOutputParser()