Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -90,9 +90,146 @@ def SpeechSynthesis(result):
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def parse_to_markdown(text):
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return text
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def search_arxiv(query):
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start_time = time.strftime("%Y-%m-%d %H:%M:%S")
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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@@ -107,19 +244,13 @@ def search_arxiv(query):
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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response1 = client.predict(
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query,
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-
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"Semantic Search - up to 10 Mar 2024", # Literal['Semantic Search - up to 10 Mar 2024', 'Arxiv Search - Latest - (EXPERIMENTAL)'] in 'Search Source' Dropdown component
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"mistralai/Mixtral-8x7B-Instruct-v0.1", # Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None'] in 'LLM Model' Dropdown component
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api_name="/update_with_rag_md"
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)
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#st.markdown(response1)
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lastpart=''
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totalparts=''
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#for parts in response1:
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# st.markdown(parts) # expect 2
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# lastpart=parts
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# totalparts=totalparts+parts
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results = response1[0] # Format for markdown display with links
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results2 = response1[1] # format for subquery without links
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st.markdown(results)
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@@ -127,13 +258,11 @@ def search_arxiv(query):
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RunSecondQuery = False
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if RunSecondQuery:
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# Search 2 - Retieve the Summary with Papers Context and Original Query
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#client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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#newquery='Create a summary as markdown outline with emojis for query: ' + query + ' ' + totalparts
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response2 = client.predict(
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query, # str in 'parameter_13' Textbox component
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#"mistralai/Mistral-7B-Instruct-v0.2",
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"google/gemma-7b-it",
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True, # bool in 'Stream output' Checkbox component
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api_name="/ask_llm"
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)
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@@ -148,7 +277,9 @@ def search_arxiv(query):
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st.write(f"Start time: {start_time}")
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st.write(f"Finish time: {end_time}")
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st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
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SpeechSynthesis(results) # Search History Reader / Writer IO Memory - Audio at Same time as Reading.
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filename=generate_filename(query, "md")
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create_file(filename, query, results, should_save)
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return results
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@@ -421,7 +552,7 @@ def compare_and_delete_files(files):
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if file != latest_file:
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os.remove(file)
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st.success(f"Deleted {file} as a duplicate.")
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-
st.
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# Function to get file size
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def get_file_size(file_path):
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@@ -456,7 +587,7 @@ def FileSidebar():
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if st.button("Delete", key=f"delete3_{file}"):
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os.remove(file)
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st.
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previous_size = size # Update previous size for the next iteration
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@@ -472,7 +603,7 @@ def FileSidebar():
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if st.button("๐ Delete All"):
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for file in all_files:
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os.remove(file)
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st.
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with Files2:
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if st.button("โฌ๏ธ Download"):
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zip_file = create_zip_of_files(all_files)
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@@ -511,7 +642,7 @@ def FileSidebar():
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if st.button("๐", key="delete_"+file):
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os.remove(file)
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file_name=file
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st.
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next_action='delete'
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st.session_state['next_action'] = next_action
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@@ -1271,7 +1402,7 @@ filekey = 'delall'
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if st.sidebar.button("๐ Delete All Audio", key=filekey):
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for file in all_files:
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os.remove(file)
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st.
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for file in all_files:
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col1, col2 = st.sidebar.columns([6, 1]) # adjust the ratio as needed
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@@ -1286,7 +1417,7 @@ for file in all_files:
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with col2:
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if st.button("๐", key="delete_" + file):
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os.remove(file)
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st.
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@@ -1333,7 +1464,7 @@ if 'action' in st.query_params:
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st.success("Showing a message because 'action=show_message' was found in the URL.")
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elif action == 'clear':
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clear_query_params()
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st.
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if 'query' in st.query_params:
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query = st.query_params['query'][0] # Get the query parameter
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def parse_to_markdown(text):
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return text
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+
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import re
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def extract_urls(text):
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# Regular expression patterns to find the required fields
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date_pattern = re.compile(r'### (\d{2} \w{3} \d{4})')
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abs_link_pattern = re.compile(r'\[(.*?)\]\((https://arxiv\.org/abs/\d+\.\d+)\)')
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pdf_link_pattern = re.compile(r'\[โฌ๏ธ\]\((https://arxiv\.org/pdf/\d+\.\d+)\)')
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title_pattern = re.compile(r'### \d{2} \w{3} \d{4} \| \[(.*?)\]')
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# Find all occurrences of the required fields using the regular expression patterns
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date_matches = date_pattern.findall(text)
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abs_link_matches = abs_link_pattern.findall(text)
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pdf_link_matches = pdf_link_pattern.findall(text)
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title_matches = title_pattern.findall(text)
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# Generate markdown string with the extracted fields
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markdown_text = ""
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for i in range(len(date_matches)):
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date = date_matches[i]
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title = title_matches[i]
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abs_link = abs_link_matches[i][1]
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pdf_link = pdf_link_matches[i]
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markdown_text += f"**Date:** {date}\n\n"
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markdown_text += f"**Title:** {title}\n\n"
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markdown_text += f"**Abstract Link:** [{abs_link}]({abs_link})\n\n"
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markdown_text += f"**PDF Link:** [{pdf_link}]({pdf_link})\n\n"
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markdown_text += "---\n\n"
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return markdown_text
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def download_pdfs(urls):
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local_files = []
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for url in urls:
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if url.endswith('.pdf'):
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local_filename = url.split('/')[-1]
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response = requests.get(url)
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with open(local_filename, 'wb') as f:
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f.write(response.content)
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local_files.append(local_filename)
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return local_files
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def generate_html(local_files):
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html = "<ul>"
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for file in local_files:
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link = f'<li><a href="{file}">{file}</a></li>'
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html += link
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html += "</ul>"
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return html
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def search_arxiv(query):
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start_time = time.strftime("%Y-%m-%d %H:%M:%S")
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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search_query = query
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search_source = "Arxiv Search - Latest - (EXPERIMENTAL)"
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llm_model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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st.markdown('### ๐ ' + query)
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# Search 1 - Retrieve the Papers
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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response1 = client.predict(
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query,
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20,
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"Semantic Search - up to 10 Mar 2024",
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"mistralai/Mixtral-8x7B-Instruct-v0.1",
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api_name="/update_with_rag_md"
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)
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lastpart = ''
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totalparts = ''
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results = response1[0] # Format for markdown display with links
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results2 = response1[1] # format for subquery without links
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st.markdown(results)
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# Extract URLs from the response
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urls = extract_urls(results)
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# Download PDFs and generate HTML5 code for local links
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# local_links_html = download_pdfs_and_generate_html(urls)
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st.markdown(urls)
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RunSecondQuery = False
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if RunSecondQuery:
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# Search 2 - Retrieve the Summary with Papers Context and Original Query
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response2 = client.predict(
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query,
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"mistralai/Mixtral-8x7B-Instruct-v0.1",
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True,
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api_name="/ask_llm"
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)
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st.markdown(response2)
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results = results + response2
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st.write('๐Run of Multi-Agent System Paper Summary Spec is Complete')
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end_time = time.strftime("%Y-%m-%d %H:%M:%S")
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start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
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end_timestamp = time.mktime(time.strptime(end_time, "%Y-%m-%d %H:%M:%S"))
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elapsed_seconds = end_timestamp - start_timestamp
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st.write(f"Start time: {start_time}")
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st.write(f"Finish time: {end_time}")
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st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
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SpeechSynthesis(results)
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filename = generate_filename(query, "md")
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create_file(filename, query, results, should_save)
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# Display local links HTML
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st.markdown(local_links_html, unsafe_allow_html=True)
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return results
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def download_pdfs_and_generate_html(urls):
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pdf_links = []
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for url in urls:
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if url.endswith('.pdf'):
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pdf_filename = os.path.basename(url)
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download_pdf(url, pdf_filename)
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pdf_links.append(pdf_filename)
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local_links_html = '<ul>'
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for link in pdf_links:
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local_links_html += f'<li><a href="{link}">{link}</a></li>'
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local_links_html += '</ul>'
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return local_links_html
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def download_pdf(url, filename):
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response = requests.get(url)
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with open(filename, 'wb') as file:
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file.write(response.content)
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# Show ArXiv Scholary Articles! ----------------*************----โถ๏ธ Semantic and Episodic Memory System
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def search_arxiv_old(query):
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start_time = time.strftime("%Y-%m-%d %H:%M:%S")
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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response1 = client.predict(
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query,
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20,
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"Semantic Search - up to 10 Mar 2024", # Literal['Semantic Search - up to 10 Mar 2024', 'Arxiv Search - Latest - (EXPERIMENTAL)'] in 'Search Source' Dropdown component
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"mistralai/Mixtral-8x7B-Instruct-v0.1", # Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None'] in 'LLM Model' Dropdown component
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api_name="/update_with_rag_md"
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)
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lastpart=''
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totalparts=''
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results = response1[0] # Format for markdown display with links
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results2 = response1[1] # format for subquery without links
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st.markdown(results)
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RunSecondQuery = False
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if RunSecondQuery:
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# Search 2 - Retieve the Summary with Papers Context and Original Query
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response2 = client.predict(
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query, # str in 'parameter_13' Textbox component
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"mistralai/Mixtral-8x7B-Instruct-v0.1",
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#"mistralai/Mistral-7B-Instruct-v0.2",
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#"google/gemma-7b-it",
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True, # bool in 'Stream output' Checkbox component
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api_name="/ask_llm"
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)
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st.write(f"Start time: {start_time}")
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st.write(f"Finish time: {end_time}")
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st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
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SpeechSynthesis(results) # Search History Reader / Writer IO Memory - Audio at Same time as Reading.
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filename=generate_filename(query, "md")
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create_file(filename, query, results, should_save)
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return results
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if file != latest_file:
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os.remove(file)
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st.success(f"Deleted {file} as a duplicate.")
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st.rerun()
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# Function to get file size
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def get_file_size(file_path):
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if st.button("Delete", key=f"delete3_{file}"):
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os.remove(file)
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st.rerun()
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previous_size = size # Update previous size for the next iteration
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if st.button("๐ Delete All"):
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for file in all_files:
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os.remove(file)
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st.rerun()
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with Files2:
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if st.button("โฌ๏ธ Download"):
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zip_file = create_zip_of_files(all_files)
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if st.button("๐", key="delete_"+file):
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os.remove(file)
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file_name=file
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st.rerun()
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next_action='delete'
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st.session_state['next_action'] = next_action
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if st.sidebar.button("๐ Delete All Audio", key=filekey):
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for file in all_files:
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os.remove(file)
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st.rerun()
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for file in all_files:
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col1, col2 = st.sidebar.columns([6, 1]) # adjust the ratio as needed
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with col2:
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if st.button("๐", key="delete_" + file):
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os.remove(file)
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st.rerun()
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st.success("Showing a message because 'action=show_message' was found in the URL.")
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elif action == 'clear':
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clear_query_params()
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st.rerun()
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if 'query' in st.query_params:
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query = st.query_params['query'][0] # Get the query parameter
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