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submit button
Browse filesadded a submit button and moved some code around so all the recipe data appears at once
app.py
CHANGED
@@ -277,6 +277,7 @@ st.sidebar.write("Upload an image and/or enter a query to get started! Explore o
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uploaded_image = st.sidebar.file_uploader("Choose an image:", type="jpg")
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query = st.sidebar.text_area("Enter your query:", height=100)
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# gap
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st.sidebar.markdown("<br><br><br>", unsafe_allow_html=True)
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@@ -307,7 +308,7 @@ with st.expander("**What is FOOD CHAIN?**"):
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#################
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# Image Classification Section
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-
if uploaded_image and
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with st.expander("**Food Classification**", expanded=True, icon=':material/search_insights:'):
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st.title("Results: Image Classification")
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# Open the image
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@@ -352,11 +353,11 @@ if uploaded_image and query:
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openAIresponse = llm.invoke(openAICall)
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print("AI CALL RESPONSE: ", openAIresponse.content)
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with st.expander("Recipe Generation", expanded=True, icon=':material/menu_book:'):
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st.title('Results: RAG')
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# RAG the openai response and display
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print("RAG INPUT", openAIresponse.content + " " + query)
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RAGresponse = get_response(openAIresponse.content + " " + query)
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display_response(RAGresponse)
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elif uploaded_image is not None:
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with st.expander("**Food Classification**", expanded=True, icon=':material/search_insights:'):
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@@ -382,10 +383,10 @@ elif uploaded_image is not None:
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st.markdown(f"*{class_name}*: {confidence:.2f}%")
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print(fpredictions)
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-
elif
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st.title("Results: RAG")
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response = get_response(query)
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display_response(response)
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else:
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st.warning("Please input an image and/or a prompt.", icon=':material/no_meals:')
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uploaded_image = st.sidebar.file_uploader("Choose an image:", type="jpg")
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query = st.sidebar.text_area("Enter your query:", height=100)
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+
recipe_submit = st.sidebar.button(label='Chain Recipe', icon=':material/link:', use_container_width=True)
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# gap
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st.sidebar.markdown("<br><br><br>", unsafe_allow_html=True)
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#################
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# Image Classification Section
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+
if uploaded_image and recipe_submit:
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with st.expander("**Food Classification**", expanded=True, icon=':material/search_insights:'):
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st.title("Results: Image Classification")
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# Open the image
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openAIresponse = llm.invoke(openAICall)
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print("AI CALL RESPONSE: ", openAIresponse.content)
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+
RAGresponse = get_response(openAIresponse.content + " " + query)
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with st.expander("Recipe Generation", expanded=True, icon=':material/menu_book:'):
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st.title('Results: RAG')
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# RAG the openai response and display
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print("RAG INPUT", openAIresponse.content + " " + query)
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display_response(RAGresponse)
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elif uploaded_image is not None:
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with st.expander("**Food Classification**", expanded=True, icon=':material/search_insights:'):
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st.markdown(f"*{class_name}*: {confidence:.2f}%")
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print(fpredictions)
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elif recipe_submit:
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response = get_response(query)
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with st.expander("**Recipe Generation**", expanded=True, icon=':material/menu_book:'):
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st.title("Results: RAG")
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display_response(response)
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else:
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st.warning("Please input an image and/or a prompt.", icon=':material/no_meals:')
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