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12.9 kB
| import streamlit as st | |
| import requests | |
| import justext | |
| import pdfplumber | |
| import docx2txt | |
| import json | |
| import os | |
| import openai | |
| from custom_prompt_template import InstructionGenerationTemplate | |
| st.set_page_config(page_title="LLM instruction") | |
| st.sidebar.success("Select a page above") | |
| # function for the odia stoplists justext | |
| def odia_stoplist(): | |
| odia_stopwords = [ | |
| "ଏହି", "ଏକ", "ଏକାଉଣଟ", "ମୁଁ", "ମୋର", "ମୁଁ ନିଜେ", "ଆମେ", "ଆମର", "ଆମର", "ଆମେ ନିଜେ", "ତୁମେ", "ତୁମର", "ତୁମର", | |
| "ନିଜେ", "ନିଜେ", "ସେ", "ତାଙ୍କୁ", "ତାଙ୍କର", | |
| "ନିଜେ", "ସେ", "ତାଙ୍କୁ", "ତାଙ୍କର", "ନିଜେ", "ଏହା", "ଏହାର", "ନିଜେ |", "ସେମାନେ", "ସେଗୁଡିକ", "ସେମାନଙ୍କର", | |
| "ସେମାନଙ୍କର", "ନିଜେ |", "କଣ", "ଯାହା", "କିଏ", "କାହାକୁ", | |
| "ଏହା", "ତାହା", "ଏଗୁଡ଼ିକ", "ସେଗୁଡ଼ିକ", "ମୁଁ", "ହେଉଛି", "ହେଉଛି |", "ଥିଲା", "ଥିଲା |", "ହୁଅ", "ହୋଇସାରିଛି |", "ହେବା", | |
| "ଅଛି", "ଅଛି", "ଥିଲା", "ଅଛି", "କର", "କରେ |", | |
| "କରିଛନ୍ତି", "କରିବା", "ଏବଂ", "କିନ୍ତୁ", "ଯଦି", "କିମ୍ବା", "କାରଣ", "ଯେପରି", "ପର୍ଯ୍ୟନ୍ତ", "ଯେତେବେଳେ", "ର", "ପାଇଁ", | |
| "ସହିତ", "ବିଷୟରେ", "ବିପକ୍ଷରେ", "ମଧ୍ୟରେ", "ଭିତରକୁ", "ମାଧ୍ୟମରେ", | |
| "ସମୟରେ", "ପୂର୍ବରୁ", "ପରେ", "ଉପରେ", "ନିମ୍ନରେ |", "କୁ", "ଠାରୁ", "ଅପ୍", "ତଳକୁ", "ଭିତରେ", "ବାହାରେ", "ଉପରେ", "ବନ୍ଦ", | |
| "ସମାପ୍ତ", "ତଳେ |", "ପୁନର୍ବାର", "ଆଗକୁ", | |
| "ତାପରେ", "ଥରେ |", "ଏଠାରେ", "ସେଠାରେ", "କେବେ", "କେଉଁଠାରେ", "କିପରି", "ସମସ୍ତ", "ଉଭୟ", "ପ୍ରତ୍ୟେକ", "ଅଳ୍ପ", "ଅଧିକ", | |
| "ଅଧିକାଂଶ", "ଅନ୍ୟ", "କେତେକ", "ଏହିପରି", | |
| "ନୁହେଁ |", "କେବଳ", "ନିଜର", "ସମାନ", "ତେଣୁ", "ଅପେକ୍ଷା", "ମଧ୍ୟ", "ବହୁତ", "କରିପାରିବେ |", "ଇଚ୍ଛା", "କେବଳ", | |
| "କରିବା ଉଚିତ", "ବର୍ତ୍ତମାନ" | |
| ] | |
| return frozenset(odia_stopwords) | |
| # function to extract data from url using justext | |
| def extract_data_from_url(url, language): | |
| try: | |
| response = requests.get(url) | |
| response.raise_for_status() | |
| page = response.content | |
| para = "" | |
| if language == "English": | |
| paragraphs = justext.justext(page, justext.get_stoplist("English")) | |
| elif language == "Hindi": | |
| paragraphs = justext.justext(page, justext.get_stoplist("Hindi")) | |
| elif language == "Odia": | |
| paragraphs = justext.justext( | |
| page, odia_stoplist(), 70, 140, 0.0, 0.02, 0.5, 150, False | |
| ) | |
| for paragraph in paragraphs: | |
| if not paragraph.is_boilerplate: | |
| para = para + "\n" + paragraph.text | |
| # returning the extracted data i.e para as string | |
| return para | |
| except Exception as e: | |
| st.error(e) | |
| # function to extract data from documents | |
| def extract_data_from_documents(documents): | |
| data = "" | |
| if documents is not None: | |
| for document in documents: | |
| document_details = { | |
| "filename": document.name, | |
| "filetype": document.type, | |
| "filesize": document.size, | |
| } | |
| st.write(document_details) | |
| # Extract content from the txt file | |
| if document.type == "text/plain": | |
| # Read as bytes | |
| data += str(document.read(), "utf-8") | |
| # Extract content from the pdf file | |
| elif document.type == "application/pdf": | |
| # using pdfplumber | |
| try: | |
| with pdfplumber.open(document) as pdf: | |
| all_text = "" | |
| for page in pdf.pages: | |
| text = page.extract_text() | |
| all_text += text + "\n" | |
| data += all_text | |
| except requests.exceptions.RequestException as e: | |
| st.write("None") | |
| # Extract content from the docx file | |
| elif ( | |
| document.type | |
| == "application/vnd.openxmlformats-officedocument.wordprocessingml.document" | |
| ): | |
| data += docx2txt.process(document) | |
| # return extract data | |
| return data | |
| else: | |
| st.error("Error: An error occurred while fetching content.") | |
| # return extract status, and the data extracted | |
| return None | |
| # function for the keyboard | |
| # Check the inputs for language, promptType | |
| def valid_drop_down(language, promptType, noOfQuestions, instructionFormat): | |
| langFlag = False | |
| promptFlag = False | |
| noOfQuestionFlag = False | |
| instructionFormatFlag = False | |
| if language: | |
| langFlag = True | |
| if promptType: | |
| promptFlag = True | |
| if noOfQuestions: | |
| noOfQuestionFlag = True | |
| if instructionFormat: | |
| instructionFormatFlag = True | |
| # checking for the compalsory inputs and return true only if all are set | |
| return langFlag & promptFlag & noOfQuestionFlag & instructionFormatFlag | |
| def main(): | |
| # setting up the initial session_states | |
| if "extract_button" not in st.session_state: | |
| st.session_state.extract_button = False | |
| if "submit" not in st.session_state: | |
| st.session_state.submit = False | |
| if "generated" not in st.session_state: | |
| st.session_state.generated = False | |
| st.subheader("LLM Instructions") | |
| # form to get the inputs | |
| with st.form(key="form1"): | |
| st.write("#") | |
| # dropdown for language | |
| language = st.selectbox("Select a language", ("", "English", "Hindi", "Odia")) | |
| # dropdown for prompt type | |
| promptType = st.selectbox( | |
| "Select the Prompt type", ("", "Input text", "Url", "Document") | |
| ) | |
| # inputs for number | |
| noOfQuestions = st.number_input( | |
| "Number of questions to generate:", min_value=1, max_value=20, value=10 | |
| ) | |
| # dropdown for language | |
| instructionFormat = st.selectbox( | |
| "Format of instruction:", ("Imperative sentence", "Question") | |
| ) | |
| # checkbox for additional info bool val | |
| addInfoCheckbox = st.checkbox("Input Additional Instructions", value=False) | |
| st.write("##") | |
| # form submit button and setting up the session_state | |
| if st.form_submit_button(): | |
| st.session_state.submit = True | |
| if st.session_state.submit: | |
| # extends the prompt form to extract the data | |
| with st.expander(label="prompt"): | |
| with st.form(key="form2"): | |
| # calling the function inside if to check valid drop down inputs | |
| if valid_drop_down( | |
| language, promptType, noOfQuestions, instructionFormat | |
| ): | |
| if promptType == "Input text": | |
| inputText = st.text_area( | |
| label="For Instructions", | |
| placeholder="Please enter your text here", | |
| ) | |
| elif promptType == "Url": | |
| url = st.text_input( | |
| label="For URL", placeholder="Please enter your text here" | |
| ) | |
| elif promptType == "Document": | |
| documents = st.file_uploader( | |
| label="For Documents ( pdf / txt / docx )", | |
| type=["pdf", "txt", "docx"], | |
| accept_multiple_files=True, | |
| ) | |
| if addInfoCheckbox: | |
| additionalInfo = st.text_input( | |
| label="Additional Instructions", | |
| placeholder="Please enter your text here", | |
| ) | |
| if st.form_submit_button(): | |
| st.session_state.extract_button = True | |
| # st.experimental_rerun() | |
| # extracting data | |
| if st.session_state.extract_button: | |
| # extracting data | |
| if promptType == "Input text": | |
| extractedData = inputText | |
| elif promptType == "Url": | |
| extractedURLData = extract_data_from_url(url, language) | |
| extractedData = extractedURLData | |
| elif promptType == "Document": | |
| if not documents: | |
| documents = None | |
| else: | |
| for doc in documents: | |
| if doc.name.split(".")[-1].lower() not in ["pdf", "txt", "docx"]: | |
| # if documents is not the relevant type | |
| st.error("Unsupported file: " + doc.name) | |
| extractedDocumentData = extract_data_from_documents(documents) | |
| extractedData = extractedDocumentData | |
| # if the values are extracted running the custom prompt by creating an instance | |
| if extractedData: | |
| # ----------------------------- RUNNING THE PROMPT ----------------------------- | |
| # running the prompt form here | |
| openai.api_key = "GET_YOUR_KEY" | |
| my_prompt_template = InstructionGenerationTemplate() | |
| # providing the rules for the instructions to be generated | |
| additional_rules = """ | |
| - You do not need to provide a response to the generated examples. | |
| - You must return the response in the specified language. | |
| - Each generated instruction can be either an imperative sentence or a question. | |
| - Return the result in dictionary , where the key is the serial number and the value is an instruction. | |
| """ | |
| if st.button("Generate Instructions"): | |
| prompt = my_prompt_template.format( | |
| num_questions=noOfQuestions, | |
| context=extractedData, | |
| instruction_format=instructionFormat, | |
| lang=language, | |
| additional_rules=additional_rules | |
| ) | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": prompt}, | |
| # {"role": "user", "content": f"Generate {num_questions} diverse questions based on the context provided below in the form of {instruction_format}.\n\n{context}\n\n{additional_rules}"}, | |
| ]) | |
| if "result" not in st.session_state: | |
| st.session_state["result"] = response.choices[0].message.content | |
| st.session_state.generated = True | |
| if st.session_state.generated: | |
| # displaying the generated instructions | |
| st.write("Generated Insuctions") | |
| # st.write(result) | |
| result = st.session_state["result"] | |
| print(type(result)) | |
| print(result) | |
| # cleaned_result=result.replace("<example>","").replace("</example>","").replace("\\n","\n") | |
| result_dict=json.loads(result) | |
| print(type(result_dict)) | |
| print(result_dict) | |
| # print(result_dict) | |
| # for key,value in result_dict.items(): | |
| # print(f"{key}:{value}") | |
| # including the questions as checkboxes for generating further solutions | |
| # Creating list to display the selected instructions | |
| selected_items = [f"{value} " for key, value in result_dict.items() if st.checkbox(f"Q{key} : {value}")] | |
| # Display the selected items as a list | |
| if selected_items: | |
| st.write("Selected Items:") | |
| st.write(selected_items) | |
| else: | |
| st.write("No items selected.") | |
| if st.button("clear"): | |
| st.session_state.extract_button = False | |
| st.session_state.submit = False | |
| st.session_state.generated = True | |
| del st.session_state["result"] | |
| st.experimental_rerun() | |
| if __name__ == "__main__": | |
| main() | |