Spaces:
Running
on
T4
Running
on
T4
colpali fix
Browse files
pages/Multimodal_Conversational_Search.py
CHANGED
@@ -277,67 +277,22 @@ def render_answer(question,answer,index,res_img):
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with col2:
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ans_ = answer['answer']
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st.write(ans_)
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# def stream_():
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# #use for streaming response on the client side
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# for word in ans_.split(" "):
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# yield word + " "
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# time.sleep(0.04)
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# #use for streaming response from Llm directly
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# if(isinstance(ans_,botocore.eventstream.EventStream)):
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# for event in ans_:
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# chunk = event.get('chunk')
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# if chunk:
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# chunk_obj = json.loads(chunk.get('bytes').decode())
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# if('content_block' in chunk_obj or ('delta' in chunk_obj and 'text' in chunk_obj['delta'])):
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# key_ = list(chunk_obj.keys())[2]
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# text = chunk_obj[key_]['text']
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# clear_output(wait=True)
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# output.append(text)
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# yield text
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# time.sleep(0.04)
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# if(index == len(st.session_state.questions_)):
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# st.write_stream(stream_)
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# if(isinstance(st.session_state.answers_[index-1]['answer'],botocore.eventstream.EventStream)):
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# st.session_state.answers_[index-1]['answer'] = "".join(output)
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# else:
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# st.write(ans_)
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# polly_response = polly_client.synthesize_speech(VoiceId='Joanna',
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# OutputFormat='ogg_vorbis',
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# Text = ans_,
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# Engine = 'neural')
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# audio_col1, audio_col2 = st.columns([50,50])
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# with audio_col1:
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# st.audio(polly_response['AudioStream'].read(), format="audio/ogg")
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rdn_key_1 = ''.join([random.choice(string.ascii_letters)
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for _ in range(10)])
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def show_maxsim():
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st.session_state.show_columns = True
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st.session_state.maxSimImages = colpali.img_highlight(st.session_state.top_img, st.session_state.query_token_vectors, st.session_state.query_tokens)
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handle_input()
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with placeholder.container():
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render_all()
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if(st.session_state.input_is_colpali):
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st.button("Show similarity map",key=rdn_key_1,on_click = show_maxsim)
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#st.markdown("<div style='font-size:18px;padding:3px 7px 3px 7px;borderWidth: 0px;borderColor: red;borderStyle: solid;border-radius: 10px;'>"+ans_+"</div>", unsafe_allow_html = True)
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#st.markdown("<div style='color:#e28743';padding:3px 7px 3px 7px;borderWidth: 0px;borderColor: red;borderStyle: solid;width: fit-content;height: fit-content;border-radius: 10px;'><b>Relevant images from the document :</b></div>", unsafe_allow_html = True)
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#st.write("")
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colu1,colu2,colu3 = st.columns([4,82,20])
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with colu2:
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with st.expander("Relevant Sources:"):
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@@ -396,11 +351,6 @@ def render_answer(question,answer,index,res_img):
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with col_3:
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#st.markdown("<div style='color:#e28743;borderWidth: 0px;borderColor: red;borderStyle: solid;width: fit-content;height: fit-content;border-radius: 5px;'><b>"+",".join(st.session_state.input_rag_searchType)+"</b></div>", unsafe_allow_html = True)
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if(index == len(st.session_state.questions_)):
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rdn_key = ''.join([random.choice(string.ascii_letters)
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with col2:
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ans_ = answer['answer']
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st.write(ans_)
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rdn_key_1 = ''.join([random.choice(string.ascii_letters)
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for _ in range(10)])
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def show_maxsim():
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st.session_state.show_columns = True
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st.session_state.maxSimImages = colpali.img_highlight(st.session_state.top_img, st.session_state.query_token_vectors, st.session_state.query_tokens)
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st.session_state.input_query = st.session_state.questions_[-1]["question"]
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st.session_state.answers_.pop()
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st.session_state.questions_.pop()
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handle_input()
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with placeholder.container():
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render_all()
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if(st.session_state.input_is_colpali):
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st.button("Show similarity map",key=rdn_key_1,on_click = show_maxsim)
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+
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colu1,colu2,colu3 = st.columns([4,82,20])
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with colu2:
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with st.expander("Relevant Sources:"):
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with col_3:
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if(index == len(st.session_state.questions_)):
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rdn_key = ''.join([random.choice(string.ascii_letters)
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