prasadnu commited on
Commit
5bcd636
·
1 Parent(s): 46c743c

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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-
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-
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-
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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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-
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- # if chunk:
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-
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- # chunk_obj = json.loads(chunk.get('bytes').decode())
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-
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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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-
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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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-
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-
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-
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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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-
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-
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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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-
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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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-
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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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-
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-
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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:"):
@@ -396,11 +351,6 @@ def render_answer(question,answer,index,res_img):
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  with col_3:
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-
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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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-
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-
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-
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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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+
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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)