Update app.py
Browse files
app.py
CHANGED
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@@ -152,7 +152,7 @@ def add_witty_humor_buttons():
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if col7[0].button("More Funny Rhymes 🎙️"):
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StreamLLMChatResponse(descriptions["More Funny Rhymes 🎙️"])
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def
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documentHTML5='''
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<!DOCTYPE html>
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<html>
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@@ -180,7 +180,7 @@ def addDocumentHTML5(result):
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'''
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components.html(documentHTML5, width=1280, height=1024)
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return result
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# 3. Stream Llama Response
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@@ -220,7 +220,7 @@ def StreamLLMChatResponse(prompt):
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except:
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st.write('Stream llm issue')
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-
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return result
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except:
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st.write('Llama model is asleep. Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
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@@ -675,10 +675,8 @@ def main():
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if len(file_contents) > 0:
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if next_action=='open':
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file_content_area = st.text_area("File Contents:", file_contents, height=500)
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#addDocumentHTML5(file_contents)
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if next_action=='md':
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st.markdown(file_contents)
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#addDocumentHTML5(file_contents)
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if next_action=='search':
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file_content_area = st.text_area("File Contents:", file_contents, height=500)
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st.write('Reasoning with your inputs...')
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@@ -687,9 +685,7 @@ def main():
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response = StreamLLMChatResponse(file_contents)
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filename = generate_filename(user_prompt, ".md")
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create_file(filename, file_contents, response, should_save)
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-
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#addDocumentHTML5(file_contents)
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addDocumentHTML5(response)
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# old - gpt
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#response = chat_with_model(user_prompt, file_contents, model_choice)
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if col7[0].button("More Funny Rhymes 🎙️"):
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StreamLLMChatResponse(descriptions["More Funny Rhymes 🎙️"])
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+
def SpeechSynthesis(result):
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documentHTML5='''
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<!DOCTYPE html>
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<html>
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'''
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components.html(documentHTML5, width=1280, height=1024)
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#return result
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# 3. Stream Llama Response
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except:
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st.write('Stream llm issue')
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SpeechSynthesis(result)
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return result
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except:
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st.write('Llama model is asleep. Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
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if len(file_contents) > 0:
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if next_action=='open':
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file_content_area = st.text_area("File Contents:", file_contents, height=500)
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if next_action=='md':
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st.markdown(file_contents)
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if next_action=='search':
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file_content_area = st.text_area("File Contents:", file_contents, height=500)
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st.write('Reasoning with your inputs...')
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response = StreamLLMChatResponse(file_contents)
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filename = generate_filename(user_prompt, ".md")
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create_file(filename, file_contents, response, should_save)
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SpeechSynthesis(response)
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# old - gpt
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#response = chat_with_model(user_prompt, file_contents, model_choice)
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