-
Notifications
You must be signed in to change notification settings - Fork 88
/
alwrity.py
328 lines (281 loc) · 14 KB
/
alwrity.py
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
import streamlit as st
import os
import json
import base64
from datetime import datetime
from lib.utils.config_manager import save_config
from lib.utils.ui_setup import setup_ui
from lib.utils.api_key_manager import check_all_api_keys
from dotenv import load_dotenv
from lib.utils.content_generators import ai_writers, content_planning_tools, blog_from_keyword, story_input_section, essay_writer, ai_news_writer, ai_finance_ta_writer, write_ai_prod_desc, do_web_research, competitor_analysis, ai_agents_content_planner
from lib.utils.seo_tools import ai_seo_tools
from lib.utils.ui_setup import setup_ui, setup_tabs
from lib.utils.alwrity_utils import ai_agents_team, ai_social_writer
from lib.utils.file_processor import load_image, read_prompts, write_prompts
from lib.utils.voice_processing import record_voice
def process_folder_for_rag(folder_path):
"""Placeholder for the process_folder_for_rag function."""
st.write(f"This is a placeholder for processing the folder: {folder_path}")
def save_config(config):
"""
Saves the provided configuration dictionary to a JSON file specified by the environment variable.
"""
try:
with open(os.getenv("ALWRITY_CONFIG"), "w") as config_file:
json.dump(config, config_file, indent=4)
except Exception as e:
st.error(f"An error occurred while saving the configuration: {e}")
# Sidebar configuration
def sidebar_configuration():
st.sidebar.title("🛠️ Personalization & Settings 🏗️")
with st.sidebar.expander("**👷 Content Personalization**"):
blog_length = st.text_input("**Content Length (words)**", value="2000",
help="Approximate word count for blogs. Note: Actual length may vary based on GPT provider and max token count.")
blog_tone_options = ["Casual", "Professional", "How-to", "Beginner", "Research", "Programming", "Social Media", "Customize"]
blog_tone = st.selectbox("**Content Tone**",
options=blog_tone_options,
help="Select the desired tone for the blog content.")
if blog_tone == "Customize":
custom_tone = st.text_input("Enter the tone of your content", help="Specify the tone of your content.")
if custom_tone:
blog_tone = custom_tone
else:
st.warning("Please specify the tone of your content.")
blog_demographic_options = ["Professional", "Gen-Z", "Tech-savvy", "Student", "Digital Marketing", "Customize"]
blog_demographic = st.selectbox("**Target Audience**",
options=blog_demographic_options,
help="Select the primary audience for the blog content.")
if blog_demographic == "Customize":
custom_demographic = st.text_input("Enter your target audience",
help="Specify your target audience.",
placeholder="Eg. Domain expert, Content creator, Financial expert etc..")
if custom_demographic:
blog_demographic = custom_demographic
else:
st.warning("Please specify your target audience.")
blog_type = st.selectbox("**Content Type**",
options=["Informational", "Commercial", "Company", "News", "Finance", "Competitor", "Programming", "Scholar"],
help="Select the category that best describes the blog content.")
blog_language = st.selectbox("**Content Language**",
options=["English", "Spanish", "German", "Chinese", "Arabic", "Nepali", "Hindi", "Hindustani", "Customize"],
help="Select the language in which the blog will be written.")
if blog_language == "Customize":
custom_lang = st.text_input("Enter the language of your choice", help="Specify the content language.")
if custom_lang:
blog_language = custom_lang
else:
st.warning("Please specify the language of your content.")
blog_output_format = st.selectbox("**Content Output Format**",
options=["markdown", "HTML", "plaintext"],
help="Select the format for the blog output.")
with st.sidebar.expander("**🩻 Images Personalization**"):
image_generation_model = st.selectbox("**Image Generation Model**",
options=["stable-diffusion", "dalle2", "dalle3"],
help="Select the model to generate images for the blog.")
number_of_blog_images = st.number_input("**Number of Blog Images**", value=1, help="Specify the number of images to include in the blog.")
with st.sidebar.expander("**🤖 LLM Personalization**"):
gpt_provider = st.selectbox("**GPT Provider**",
options=["google", "openai", "minstral"],
help="Select the provider for the GPT model.")
model = st.text_input("**Model**", value="gemini-1.5-flash-latest", help="Specify the model version to use from the selected provider.")
temperature = st.slider(
"Temperature",
min_value=0.1,
max_value=1.0,
value=0.7,
step=0.1,
format="%.1f",
help="""Temperature controls the 'creativity' or randomness of the text generated by GPT.
Greater determinism with higher values indicating more randomness."""
)
top_p = st.slider(
"Top-p",
min_value=0.0,
max_value=1.0,
value=0.9,
step=0.1,
format="%.1f",
help="Top-p sampling controls the level of diversity in the generated text."
)
# Selectbox for max tokens
max_tokens_options = [500, 1000, 2000, 4000, 16000, 32000, 64000]
max_tokens = st.selectbox(
"Max Tokens",
options=max_tokens_options,
index=max_tokens_options.index(4000),
help="Max tokens determine the maximum length of the output sequence generated by a model."
)
n = st.number_input("N",
value=1,
min_value=1,
max_value=10,
help="Defines the number of words or characters grouped together in a sequence when analyzing text.")
frequency_penalty = st.slider(
"Frequency Penalty",
min_value=0.0,
max_value=2.0,
value=1.0,
step=0.1,
format="%.1f",
help="Influences word selection during text generation, promoting diversity with higher values."
)
presence_penalty = st.slider(
"Presence Penalty",
min_value=0.0,
max_value=2.0,
value=1.0,
step=0.1,
format="%.1f",
help="Encourages the use of diverse words by discouraging repetition."
)
with st.sidebar.expander("**🕵️ Search Engine Personalization**"):
geographic_location = st.selectbox("**Geographic Location**",
options=["us", "in", "fr", "cn"],
help="Select the geographic location for tailoring search results.")
search_language = st.selectbox("**Search Language**",
options=["en", "zn-cn", "de", "hi"],
help="Select the language for the search results.")
number_of_results = st.number_input("**Number of Results**",
value=10,
max_value=20,
min_value=1,
help="Specify the number of search results to retrieve.")
time_range = st.selectbox("**Time Range**",
options=["anytime", "past day", "past week", "past month", "past year"],
help="Select the time range for filtering search results.")
include_domains = st.text_input("**Include Domains**", value="",
help="List specific domains to include in search results. Leave blank to include all domains.")
similar_url = st.text_input("**Similar URL**", value="", help="Provide a URL to find similar results. Leave blank if not needed.")
# Storing collected inputs in a dictionary
config = {
"Blog Content Characteristics": {
"Blog Length": blog_length,
"Blog Tone": blog_tone,
"Blog Demographic": blog_demographic,
"Blog Type": blog_type,
"Blog Language": blog_language,
"Blog Output Format": blog_output_format
},
"Blog Images Details": {
"Image Generation Model": image_generation_model,
"Number of Blog Images": number_of_blog_images
},
"LLM Options": {
"GPT Provider": gpt_provider,
"Model": model,
"Temperature": temperature,
"Top-p": top_p,
"Max Tokens": max_tokens,
"N": n,
"Frequency Penalty": frequency_penalty,
"Presence Penalty": presence_penalty
},
"Search Engine Parameters": {
"Geographic Location": geographic_location,
"Search Language": search_language,
"Number of Results": number_of_results,
"Time Range": time_range,
"Include Domains": include_domains,
"Similar URL": similar_url
}
}
# Writing the configuration to a file whenever a change is made
save_config(config)
def main():
#load_environment
load_dotenv()
setup_ui()
if check_all_api_keys():
setup_environment_paths()
sidebar_configuration()
setup_tabs()
modify_prompts_sidebar()
def setup_environment_paths():
"""Sets up environment paths for saving files and configurations."""
os.environ["SEARCH_SAVE_FILE"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_web_research",
f"web_research_report_{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}")
os.environ["IMG_SAVE_DIR"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_content")
os.environ["CONTENT_SAVE_DIR"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_content")
os.environ["PROMPTS_DIR"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_prompts")
os.environ["ALWRITY_CONFIG"] = os.path.join(os.getcwd(), "lib", "workspace", "alwrity_config", "main_config.json")
def modify_prompts_sidebar():
"""Provides a sidebar for modifying prompts."""
st.sidebar.title("📝 Modify Prompts")
prompts = read_prompts()
if prompts:
edited_prompts = []
for i, prompt in enumerate(prompts):
edited_prompt = st.sidebar.text_area(f"Prompt {i+1}", prompt)
edited_prompts.append(edited_prompt)
if st.sidebar.button("Save Prompts"):
write_prompts(edited_prompts)
st.sidebar.success("Prompts saved successfully!")
else:
st.sidebar.warning("No prompts found in the file.")
# Functions for the main options
def ai_writers():
options = [
"AI Blog Writer",
"Story Writer",
"Essay writer",
"Write News reports",
"Write Financial TA report",
"AI Product Description Writer",
"AI Copywriter",
"Quit"
]
choice = st.selectbox("**👇Select a content creation type:**", options, index=0, format_func=lambda x: f"📝 {x}")
if choice == "AI Blog Writer":
blog_from_keyword()
elif choice == "Story Writer":
story_input_section()
elif choice == "Essay writer":
essay_writer()
elif choice == "Write News reports":
ai_news_writer()
elif choice == "Write Financial TA report":
ai_finance_ta_writer()
elif choice == "AI Product Description Writer":
write_ai_prod_desc()
elif choice == "Quit":
st.subheader("Exiting, Getting Lost. But.... I have nowhere to go 🥹🥹")
def content_planning_tools():
st.markdown("""**Alwrity content Ideation & Planning** : Provide few keywords to do comprehensive web research.
Provide few keywords to get Google, Neural, pytrends analysis. Know keywords, blog titles to target.
Generate months long content calendar around given keywords.""")
options = [
"Keywords Researcher",
"Competitor Analysis",
"Content Calender Ideator"
]
choice = st.radio("Select a content planning tool:", options, index=0, format_func=lambda x: f"🔍 {x}")
if choice == "Keywords Researcher":
do_web_research()
elif choice == "Competitor Analysis":
competitor_analysis()
elif choice == "Content Calender Ideator":
plan_keywords = st.text_input(
"**Enter Your main Keywords to get 2 months content calendar:**",
placeholder="Enter 2-3 main keywords to generate AI content calendar with keyword researched blog titles",
help="The keywords are the ones where you would want to generate 50-60 blogs/articles on."
)
if st.button("**Ideate Content Calender**"):
if plan_keywords:
ai_agents_content_planner(plan_keywords)
else:
st.error("Come on, really, Enter some keywords to plan on..")
def alwrity_brain():
st.title("🧠 Alwrity Brain, Better than yours!")
st.write("Choose a folder to write content on. Alwrity will do RAG on these documents. The documents can of any type, pdf, pptx, docs, txt, cs etc. Video files and Audio files are also permitted.")
folder_path = st.text_input("**Enter folder path:**")
if st.button("**Process Folder**"):
if folder_path:
try:
process_folder_for_rag(folder_path)
st.success("Folder processed successfully!")
except Exception as e:
st.error(f"Error processing folder: {e}")
else:
st.warning("Please enter a valid folder path.")
if __name__ == "__main__":
main()