Adds png instead of lstlistings.

docs/final-report/report.tex

@@ -129,7 +129,7 @@
     entities. This ensures that the bot is able to understand intents and extract the entities
     inside the sentences. One example can be seen in listing \ref{nlu_example}.
 
-    \lstinputlisting[label={nlu_example}, caption={NLU example}]{nlu_example.md}
+    \includegraphics[width=\textwidth]{nlu_example}
 
     Rasa Core has been configured with \textit{stories} that contain example conversation flows as
     training data (listing \ref{stories_example}) and the \textit{domain} of the bot. The domain
@@ -139,7 +139,7 @@
     recognized physicist entity. According to the Rasa website\footnote{\url{https://rasa.com/docs/get_started_step2/}},
     the domain is \textit{the universe the bot is living in}. \\
 
-    \lstinputlisting[label={stories_example}, caption={Example Story}]{stories_example.md}
+    \includegraphics[width=\textwidth]{stories_example}
 
     The bot recognizes the intents shown in table \ref{table:intent_table}. It can be started by issuing \textit{MAKE}-commands. For further details,
     refer to the README