Spaces:
Runtime error
Runtime error
File size: 15,222 Bytes
89c010a |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 |
import streamlit as st
import pandas as pd
from groq_llms import LLMHandler
#from openrouter_llms import LLMHandler
import tempfile
import os
from dotenv import load_dotenv
load_dotenv()
# Initialize LLMHandler
llm_handler = LLMHandler()
def process_csv(file, user_prompt):
"""Read CSV, generate responses using LLMHandler, and return processed DataFrame."""
df = pd.read_csv(file)
responses = []
for _, row in df.iterrows():
try:
response = llm_handler.generate_response(user_prompt, row.to_dict())
responses.append(response)
except Exception as e:
responses.append(f"Error: {e}")
df["Generated Text"] = responses
return df
def initialize_session_state():
"""Initialize session state variables"""
if 'prompt_creation_method' not in st.session_state:
st.session_state.prompt_creation_method = None
if 'current_step' not in st.session_state:
st.session_state.current_step = 'choose_method'
if 'context' not in st.session_state:
st.session_state.context = ""
if 'questions' not in st.session_state:
st.session_state.questions = []
if 'answers' not in st.session_state:
st.session_state.answers = {}
if 'multiselect_answers' not in st.session_state:
st.session_state.multiselect_answers = {}
if 'custom_options' not in st.session_state:
st.session_state.custom_options = {}
if 'final_prompt' not in st.session_state:
st.session_state.final_prompt = ""
if 'direct_prompt' not in st.session_state:
st.session_state.direct_prompt = ""
def display_progress_tracker():
"""Display current progress and previous responses"""
with st.expander("π View Progress", expanded=True):
if st.session_state.prompt_creation_method:
st.write(f"**Method chosen:** {st.session_state.prompt_creation_method.title()}")
if st.session_state.context:
st.write("**Initial Context:**")
st.info(st.session_state.context)
if st.button("Edit Context", key="edit_context"):
st.session_state.current_step = 'initial_context'
st.rerun()
if st.session_state.answers:
st.write("**Your Responses:**")
for i, question in enumerate(st.session_state.questions):
if i in st.session_state.multiselect_answers:
answers = ", ".join(st.session_state.multiselect_answers[i])
st.success(f"Q: {question['question']}\nA: {answers}")
elif i in st.session_state.answers:
st.success(f"Q: {question['question']}\nA: {st.session_state.answers[i]}")
if st.button("Edit Responses", key="edit_responses"):
st.session_state.current_step = 'answer_questions'
st.rerun()
if st.session_state.direct_prompt:
st.write("**Your Direct Prompt:**")
st.info(st.session_state.direct_prompt)
if st.button("Edit Prompt", key="edit_direct_prompt"):
st.session_state.current_step = 'direct_prompt'
st.rerun()
if st.session_state.final_prompt:
st.write("**Final Generated Prompt:**")
st.info(st.session_state.final_prompt)
if st.button("Edit Final Prompt", key="edit_final_prompt"):
st.session_state.current_step = 'edit_prompt'
st.rerun()
# Streamlit UI
st.set_page_config(page_title="Invite AI", page_icon="π¬", layout="wide")
# Header
st.title("Invite AI")
st.markdown(
"""
Welcome to the Invitation Generator! This tool helps you create personalized invitations using the power of AI.
"""
)
# Initialize session state
initialize_session_state()
# Display progress tracker (always visible)
display_progress_tracker()
# Sidebar with instructions
st.sidebar.title("Instructions")
st.sidebar.markdown(
"""
### Template Download
[Click here to download the suggested CSV template](http://surl.li/ptvzzv) π₯
### Suggested Requirements
- **Unique Identifier for each receiver**
- **Name of the receiver**
- **Designation/Job title of the receiver**
- **Company/Organisation where the receiver works**
- **Areas the receiver is interested in / has expertise in**
- **Categorize receivers into groups**
[Note: The above template is for your reference, you are free to submit your own data.]
"""
)
# Main content area with steps
st.markdown("---") # Separator between progress tracker and current step
if st.session_state.current_step == 'choose_method':
st.subheader("Choose Your Prompt Creation Method")
col1, col2 = st.columns(2)
with col1:
st.markdown("""
### Guided Prompt Builder
- Step-by-step assistance
- AI-generated questions
- Structured approach
""")
if st.button("Use Guided Builder"):
st.session_state.prompt_creation_method = 'guided'
st.session_state.current_step = 'initial_context'
st.rerun()
with col2:
st.markdown("""
### Direct Prompt Entry
- Write your own prompt
- Complete control
- Quick setup
""")
if st.button("Use Direct Entry"):
st.session_state.prompt_creation_method = 'direct'
st.session_state.current_step = 'direct_prompt'
st.rerun()
elif st.session_state.current_step == 'direct_prompt':
st.subheader("Enter Your Prompt")
st.markdown(
"Write your complete prompt for generating invitations. Include all necessary details and requirements.")
direct_prompt = st.text_area(
"Your Prompt:",
value=st.session_state.direct_prompt,
placeholder="Example: Generate a professional invitation for a product launch...",
height=200
)
col1, col2 = st.columns([1, 5])
with col1:
if st.button("β Back"):
st.session_state.current_step = 'choose_method'
st.rerun()
with col2:
if st.button("Continue β"):
if direct_prompt:
st.session_state.direct_prompt = direct_prompt
st.session_state.final_prompt = direct_prompt
st.session_state.current_step = 'upload_process'
st.rerun()
else:
st.error("Please enter a prompt before continuing.")
elif st.session_state.prompt_creation_method == 'guided':
if st.session_state.current_step == 'initial_context':
st.subheader("Step 1: Provide Initial Context")
st.markdown("Briefly describe what your invitation is about (e.g., 'Launching a new GPU product')")
context = st.text_area(
"Context:",
value=st.session_state.context,
placeholder="Example: Launching a new GPU product for AI and HPC applications",
height=100
)
col1, col2 = st.columns([1, 5])
with col1:
if st.button("β Back"):
st.session_state.current_step = 'choose_method'
st.rerun()
with col2:
if st.button("Generate Questions β"):
if context:
st.session_state.context = context
st.session_state.questions = llm_handler.generate_questions(context)
st.session_state.current_step = 'answer_questions'
st.rerun()
else:
st.error("Please provide context before proceeding.")
# In the answer_questions section of your code, replace the multiselect implementation with this:
elif st.session_state.current_step == 'answer_questions':
st.subheader("Step 2: Answer Questions")
for i, question in enumerate(st.session_state.questions):
if 'choices' in question:
# Get previously selected options
previous_selections = st.session_state.multiselect_answers.get(i, [])
# Initialize base choices
base_choices = question['choices'].copy()
if "Custom" not in base_choices:
base_choices.append("Custom")
# Add any previous custom value to the choices if it exists
custom_values = [x for x in previous_selections if x not in question['choices'] and x != "Custom"]
all_choices = base_choices + custom_values
# Handle word count questions differently
if any(word in question['question'].lower() for word in ['word count', 'words', 'length']):
selected_options = st.multiselect(
question['question'],
options=all_choices,
default=previous_selections,
key=f"multiselect_{i}"
)
if "Custom" in selected_options:
# Pre-fill with previous custom value if exists
default_custom = next((x for x in previous_selections if x not in base_choices), "")
custom_value = st.text_input(
"Enter custom word count:",
value=default_custom,
key=f"custom_{i}"
)
if custom_value:
try:
word_count = int(custom_value)
if word_count > 0:
selected_options = [opt for opt in selected_options if opt != "Custom"]
if str(word_count) not in selected_options:
selected_options.append(str(word_count))
else:
st.error("Please enter a positive number")
except ValueError:
st.error("Please enter a valid number")
else:
# Regular non-numeric multiselect handling
selected_options = st.multiselect(
question['question'],
options=all_choices,
default=previous_selections,
key=f"multiselect_{i}"
)
if "Custom" in selected_options:
# Pre-fill with previous custom value if exists
default_custom = next((x for x in previous_selections if x not in base_choices), "")
custom_value = st.text_input(
"Enter your custom response:",
value=default_custom,
key=f"custom_{i}"
)
if custom_value:
selected_options = [opt for opt in selected_options if opt != "Custom"]
if custom_value not in selected_options:
selected_options.append(custom_value)
# Update session state
st.session_state.multiselect_answers[i] = selected_options
st.session_state.answers[i] = ", ".join(selected_options) if selected_options else ""
else:
# Handle non-choice questions
st.session_state.answers[i] = st.text_input(
question['question'],
value=st.session_state.answers.get(i, ""),
key=f"question_{i}"
)
col1, col2 = st.columns([1, 5])
with col1:
if st.button("β Back"):
st.session_state.current_step = 'initial_context'
st.rerun()
with col2:
if st.button("Generate Prompt β"):
if all(st.session_state.answers.values()):
st.session_state.final_prompt = llm_handler.generate_final_prompt(
st.session_state.context,
st.session_state.questions,
st.session_state.answers
)
st.session_state.current_step = 'edit_prompt'
st.rerun()
else:
st.error("Please answer all questions before proceeding.")
elif st.session_state.current_step == 'edit_prompt':
st.subheader("Step 3: Review and Edit Final Prompt")
edited_prompt = st.text_area(
"Edit your prompt if needed:",
value=st.session_state.final_prompt,
height=200
)
col1, col2 = st.columns([1, 5])
with col1:
if st.button("β Back"):
st.session_state.current_step = 'answer_questions'
st.rerun()
with col2:
if st.button("Continue to Upload β"):
st.session_state.final_prompt = edited_prompt
st.session_state.current_step = 'upload_process'
st.rerun()
# Common upload and processing section for both paths
if st.session_state.current_step == 'upload_process':
st.subheader("Upload and Process")
uploaded_file = st.file_uploader("π Upload CSV File", type=["csv"])
col1, col2 = st.columns([1, 5])
with col1:
if st.button("β Back"):
if st.session_state.prompt_creation_method == 'guided':
st.session_state.current_step = 'edit_prompt'
else:
st.session_state.current_step = 'direct_prompt'
st.rerun()
if uploaded_file is not None and st.session_state.final_prompt:
st.write("β³ Processing your file... Please wait.")
processed_df = process_csv(uploaded_file, st.session_state.final_prompt)
st.write("### Generated Invitations")
st.dataframe(processed_df, use_container_width=True)
with tempfile.NamedTemporaryFile(delete=False, suffix=".csv") as temp_file:
processed_df.to_csv(temp_file.name, index=False)
temp_file.close()
st.download_button(
label="π₯ Download Results CSV",
data=open(temp_file.name, "rb"),
file_name="generated_invitations.csv",
mime="text/csv",
)
os.unlink(temp_file.name)
# Reset button (moved to sidebar)
st.sidebar.markdown("---")
if st.sidebar.button("π Start Over"):
st.session_state.prompt_creation_method = None
st.session_state.current_step = 'choose_method'
st.session_state.context = ""
st.session_state.questions = []
st.session_state.answers = {}
st.session_state.multiselect_answers = {}
st.session_state.custom_options = {}
st.session_state.final_prompt = ""
st.session_state.direct_prompt = ""
st.rerun()
st.markdown("---")
st.markdown("π‘ **Tip:** Ensure your data aligns with the provided template for accurate results.") |