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Update app.py
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app.py
CHANGED
@@ -571,19 +571,22 @@ def search_glossary(query): # 🔍Run------------------------------------------
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# 🔍Run PaperSummarizer
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PaperSummarizer = ' Create a paper summary as a markdown table with paper links clustering the features writing short markdown emoji outlines to extract three main ideas from each of the ten summaries. For each one create three simple points led by an emoji of the main three steps needed as method step process for implementing the idea as a single app.py streamlit python app. '
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# = str(result).replace('\n', ' ').replace('|', ' ')
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response2 = chat_with_model45(PaperSummarizer + str(response1))
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st.write('🔍Run 3 - Paper Summarizer is Complete.')
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# 🔍Run AppSpecifier
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AppSpecifier = ' Design and write a streamlit python code listing and specification that implements each scientific method steps as ten functions keeping specification in a markdown table in the function comments with original paper link to outline the AI pipeline ensemble implementing code as full plan to build.'
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#result = str(result).replace('\n', ' ').replace('|', ' ')
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response3 = chat_with_model45(AppSpecifier + str(response2))
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st.write('🔍Run 4 - AppSpecifier is Complete.')
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# 🔍Run PythonAppCoder
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PythonAppCoder = ' Complete this streamlit python app implementing the functions in detail using appropriate python libraries and streamlit user interface elements. Show full code listing for the completed detail app as full code listing with no comments or commentary. '
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#result = str(result).replace('\n', ' ').replace('|', ' ')
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response4 = chat_with_model45(PythonAppCoder + str(response3))
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st.write('🔍Run Python AppCoder is Complete.')
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# experimental 45 - - - - - - - - - - - - -<><><><><>
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@@ -972,7 +975,6 @@ def read_file_content(file,max_length):
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# 11. Chat with GPT - Caution on quota - now favoring fastest AI pipeline STT Whisper->LLM Llama->TTS
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@st.cache_resource
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def chat_with_model(prompt, document_section='', model_choice='gpt-3.5-turbo'): # gpt-4-0125-preview gpt-3.5-turbo
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#def chat_with_model(prompt, document_section='', model_choice='gpt-4-0125-preview'): # gpt-4-0125-preview gpt-3.5-turbo
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model = model_choice
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conversation = [{'role': 'system', 'content': 'You are a coder, inventor, and writer of quotes on wisdom as a helpful expert in all fields of health, math, development and AI using python.'}]
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conversation.append({'role': 'user', 'content': prompt})
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@@ -1003,7 +1005,6 @@ def chat_with_model(prompt, document_section='', model_choice='gpt-3.5-turbo'):
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# 11.1 45
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@st.cache_resource
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#def chat_with_model(prompt, document_section='', model_choice='gpt-3.5-turbo'): # gpt-4-0125-preview gpt-3.5-turbo
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def chat_with_model45(prompt, document_section='', model_choice='gpt-4-0125-preview'): # gpt-4-0125-preview gpt-3.5-turbo
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model = model_choice
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conversation = [{'role': 'system', 'content': 'You are a coder, inventor, and writer of quotes on wisdom as a helpful expert in all fields of health, math, development and AI using python.'}]
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# 🔍Run PaperSummarizer
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PaperSummarizer = ' Create a paper summary as a markdown table with paper links clustering the features writing short markdown emoji outlines to extract three main ideas from each of the ten summaries. For each one create three simple points led by an emoji of the main three steps needed as method step process for implementing the idea as a single app.py streamlit python app. '
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# = str(result).replace('\n', ' ').replace('|', ' ')
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# response2 = chat_with_model45(PaperSummarizer + str(response1))
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response2 = chat_with_model(PaperSummarizer + str(response1))
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st.write('🔍Run 3 - Paper Summarizer is Complete.')
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# 🔍Run AppSpecifier
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AppSpecifier = ' Design and write a streamlit python code listing and specification that implements each scientific method steps as ten functions keeping specification in a markdown table in the function comments with original paper link to outline the AI pipeline ensemble implementing code as full plan to build.'
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#result = str(result).replace('\n', ' ').replace('|', ' ')
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# response3 = chat_with_model45(AppSpecifier + str(response2))
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response3 = chat_with_model(AppSpecifier + str(response2))
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st.write('🔍Run 4 - AppSpecifier is Complete.')
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# 🔍Run PythonAppCoder
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PythonAppCoder = ' Complete this streamlit python app implementing the functions in detail using appropriate python libraries and streamlit user interface elements. Show full code listing for the completed detail app as full code listing with no comments or commentary. '
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#result = str(result).replace('\n', ' ').replace('|', ' ')
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# response4 = chat_with_model45(PythonAppCoder + str(response3))
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response4 = chat_with_model(PythonAppCoder + str(response3))
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st.write('🔍Run Python AppCoder is Complete.')
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# experimental 45 - - - - - - - - - - - - -<><><><><>
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# 11. Chat with GPT - Caution on quota - now favoring fastest AI pipeline STT Whisper->LLM Llama->TTS
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@st.cache_resource
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def chat_with_model(prompt, document_section='', model_choice='gpt-3.5-turbo'): # gpt-4-0125-preview gpt-3.5-turbo
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model = model_choice
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conversation = [{'role': 'system', 'content': 'You are a coder, inventor, and writer of quotes on wisdom as a helpful expert in all fields of health, math, development and AI using python.'}]
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conversation.append({'role': 'user', 'content': prompt})
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# 11.1 45
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@st.cache_resource
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def chat_with_model45(prompt, document_section='', model_choice='gpt-4-0125-preview'): # gpt-4-0125-preview gpt-3.5-turbo
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model = model_choice
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conversation = [{'role': 'system', 'content': 'You are a coder, inventor, and writer of quotes on wisdom as a helpful expert in all fields of health, math, development and AI using python.'}]
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