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f34a2c8 1a44acf f34a2c8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 | 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()
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