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| import streamlit as st | |
| import requests | |
| import justext | |
| import pdfplumber | |
| import docx2txt | |
| import json | |
| import ast | |
| import os | |
| import re | |
| import openai | |
| import json | |
| from custom_prompt_template import InstructionGenerationTemplate, AnswerGenerationTemplate | |
| st.set_page_config(page_title="LLM instruction Generator") | |
| # sidebar content | |
| with st.sidebar: | |
| st.markdown(""" | |
| <style> | |
| [data-testid=stImage]{ | |
| display: block; | |
| margin-top: -20px; | |
| margin-left: auto; | |
| margin-right: auto; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| st.image(image="olive_farm.png", width=100) | |
| st.markdown(""" | |
| <style> | |
| .sidebar-text { | |
| text-align: justify; | |
| font-size: 14px; | |
| padding-bottom: 16px; | |
| } | |
| .list { | |
| font-size: 14px !important; | |
| } | |
| </style> | |
| <div class="sidebar-text"> | |
| OliveFarm is a cutting-edge web application crafted by the innovative minds at | |
| <a href="https://www.odiagenai.org/" target="_blank">OdiaGenAI.</a> | |
| It's designed to effortlessly generate LLM (Language Model) instruction sets in Indic languages. | |
| Presently, it offers support for Hindi and Odia, with seamless scalability to incorporate | |
| additional languages on the horizon. | |
| </div> | |
| <div class="sidebar-text"> | |
| This versatile tool accommodates inputs from a variety of sources, including (URLs, PDF documents, and plain text). | |
| </div> | |
| <div class="sidebar-text"> | |
| Additionally, OliveFarm features a collection of pre-existing templates, powered by ChatGPT, | |
| to streamline the process of generating instruction sets. Experience the future of | |
| Indic language instruction with OliveFarm! | |
| </div> | |
| <div> | |
| Please follow the | |
| <a href="https://github.com/OdiaGenAI/Olive_Farm/blob/main/README.md" target="_blank">GitHub README</a> | |
| instructions to generate the instruction set. | |
| </div> | |
| <div class="sidebar-text"> | |
| Contributors: | |
| </div> | |
| <ul> | |
| <li class="list">AR Kamaldeen</li> | |
| <li class="list">SK Shahid</li> | |
| <li class="list">Sambit Sekhar</li> | |
| <li class="list">Parul Agarwal</li> | |
| <li class="list">Dr. Shantipriya Parida</li> | |
| </ul> | |
| """, unsafe_allow_html=True) | |
| st.markdown( | |
| """ | |
| <style> | |
| .copyright { | |
| text-align: center; | |
| font-size: 14px; | |
| } | |
| </style> | |
| <div class="copyright"> | |
| © 2023 Odia Generative AI | |
| </div> | |
| """ | |
| , unsafe_allow_html=True) | |
| # 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) | |
| if response.status_code == 200: | |
| print("inside the response") | |
| 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"), 70, 140, 0.0, 0.02, 0.5, 150, False) | |
| 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 | |
| if para == "": | |
| st.error("Unable to extract data from the URL") | |
| return None | |
| else: | |
| return para | |
| else: | |
| st.error("Request failed ") | |
| return None | |
| except Exception as err: | |
| st.error(err) | |
| return None | |
| # 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 | |
| if "selected" not in st.session_state: | |
| st.session_state.selected = False | |
| if "answered" not in st.session_state: | |
| st.session_state.answered = 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") | |
| ) | |
| # input text for openAiKey | |
| openAiKey = st.text_input(label="Input the openai key", type="password") | |
| if "openAiKey" in st.session_state: | |
| st.session_state["openAiKey"] = openAiKey | |
| else: | |
| st.session_state["openAiKey"] = openAiKey | |
| 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) | |
| if extractedURLData is not None: | |
| extractedData = extractedURLData | |
| st.text_area("Extracted Text:", value=extractedData, height=200) | |
| else: | |
| extractedData = False | |
| 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 ----------------------------- | |
| if "extractedData" not in st.session_state: | |
| st.session_state["extractedData"] = extractedData | |
| else: | |
| st.session_state["extractedData"] = extractedData | |
| if "Initial" not in st.session_state: | |
| st.session_state.Initial=True | |
| if st.session_state.Initial == True: | |
| # running the prompt form here | |
| openai.api_key = st.session_state["openAiKey"] | |
| 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. | |
| """ | |
| try : | |
| 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}, | |
| ]) | |
| # if st.button("Generate Instructions"): | |
| print("Generate button") | |
| print("Checkpoint 1!") | |
| if "result" not in st.session_state: | |
| content = response.choices[0].message.content | |
| # content = "\n1. helloworld1.\n2. helloworld2" | |
| responses_list = content.split('\n') | |
| responses_list = [re.sub(r'^\s*\d+\.\s*', '', resp) for resp in responses_list if resp] | |
| st.session_state["result"]=responses_list | |
| st.session_state.generated = True | |
| st.session_state.Initial = False | |
| except Exception as err: | |
| st.error(err) | |
| if st.session_state.generated: | |
| # displaying the generated instructions | |
| st.write("Generated Instructions") | |
| result = st.session_state["result"] | |
| # print(type(result)) | |
| # print(result) | |
| result_dict = {i+1: value for i,value in enumerate(result)} | |
| selected_items = [f" {value} " for key, value in result_dict.items() if st.checkbox(f"Q{key} : {value}")] | |
| # print(type(result_dict)) | |
| # print(result_dict) | |
| print("Checked point 2!") | |
| # Display the selected items as a list | |
| if selected_items: | |
| st.write("Selected Items:") | |
| st.write(selected_items) | |
| if "selected_items" not in st.session_state: | |
| st.session_state["selected_items"] = selected_items | |
| st.session_state["selected_items"] = selected_items | |
| st.session_state.selected = True | |
| else: | |
| st.write("No items selected.") | |
| # ----------------------------- RUNNING THE PROMPT FOR ANSWER GENERATION ----------------------------- | |
| if st.session_state.selected: | |
| if "Initial2" not in st.session_state: | |
| st.session_state.Initial2=True | |
| if st.session_state.Initial2: | |
| # running the prompt form here | |
| openai.api_key = st.session_state["openAiKey"] | |
| my_prompt_template2 = AnswerGenerationTemplate() | |
| # providing the rules for the answers to be generated | |
| additional_rules = """ | |
| Each generated answer should be within the <ans>Answer</ans> tag and the question should be within the <ques>Question</ques> tag. | |
| """ | |
| question = st.session_state["selected_items"] | |
| try: | |
| if st.button("Generate Answers"): | |
| prompt = my_prompt_template2.format( | |
| questions=question, | |
| additional_rules = additional_rules | |
| ) | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": prompt}, | |
| ]) | |
| # if st.button("Generate Answers"): | |
| # print("\n\n\n\nInside Answersss:\n\n\n\n") | |
| # print(st.session_state["selected_items"]) | |
| # print("Generate button") | |
| # print("Checkpoint 3!") | |
| if "answers" not in st.session_state: | |
| content = response.choices[0].message.content | |
| # content = "\n1. Answer1.\n2. Answer2" | |
| print("\n\n\n\n\nAnswerss before regex\n\n\n\n") | |
| print(content) | |
| # print("Answer Type:" + str(type(content))) | |
| # responses_list = content.split('\n') | |
| # print("\n\n\n\n\nAnswerss before regex after splitting\n\n\n\n") | |
| # print(responses_list) | |
| # print("Answer Type:" + str(type(responses_list))) | |
| # responses_list = [re.sub(r'^\s*\d+\.\s*', '', resp) for resp in responses_list if resp] | |
| responses_list = re.findall(r'<ans>(.*?)</ans>', content, re.DOTALL) | |
| st.session_state["answers"]=responses_list | |
| st.session_state.answered = True | |
| st.session_state.Initial2 = False | |
| except Exception as e: | |
| st.error(e) | |
| if st.session_state.answered: | |
| # displaying the generated Answers | |
| questions = st.session_state["selected_items"] | |
| answers = st.session_state["answers"] | |
| # print("\n\n\n\n\nAnswerss after regex\n\n\n\n") | |
| # print(answers) | |
| # print("Answer Type:" + str(type(answers))) | |
| answers_dict = {i+1: value for i,value in enumerate(answers)} | |
| # print(type(answers_dict)) | |
| # print(answers_dict) | |
| # print("Checked point 4!") | |
| # st.write("answers") | |
| # st.write(answers_dict) | |
| # Create a list to hold the JSON-like data | |
| st.write("Generated Questions and Answers") | |
| # Create a list of dictionaries | |
| jsonl_data = [{"Instruction": question, "Output": answers_dict.get(i, 'No answer found'), "Input":""} for i, question in enumerate(questions, start=1)] | |
| st.write(jsonl_data) | |
| jsonl_string = '\n'.join(json.dumps(item, ensure_ascii=False) for item in jsonl_data) | |
| # Display the JSONL data | |
| print(jsonl_string) | |
| if st.download_button(label="Save as jsonl", data=jsonl_string, mime="application/json"): | |
| st.success("Successfully saved") | |
| if st.button("Clear"): | |
| st.session_state.extract_button = False | |
| st.session_state.submit = False | |
| st.session_state.generated = False | |
| st.session_state.selected = False | |
| st.session_state.answered = False | |
| if "Initial" in st.session_state: | |
| st.session_state.Initial = True | |
| if "Initial2" in st.session_state: | |
| st.session_state.Initial2 = True | |
| if "openAiKey" in st.session_state: | |
| del st.session_state["openAiKey"] | |
| if "extractedData" in st.session_state: | |
| del st.session_state["extractedData"] | |
| if "result" in st.session_state: | |
| del st.session_state["result"] | |
| if "selected_items" in st.session_state: | |
| del st.session_state["selected_items"] | |
| if "answers" in st.session_state: | |
| del st.session_state["answers"] | |
| st.experimental_rerun() | |
| if __name__ == "__main__": | |
| main() | |