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README.md

@@ -1,13 +1 @@
----
-title: TexGen
-emoji: 🦀
-colorFrom: indigo
-colorTo: red
-sdk: streamlit
-sdk_version: 1.29.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Build Feather AI

X_content_creation.py

@@ -1,83 +1,380 @@
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
+from langchain.llms import OpenAI
+
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
+
 
 class X_Generator:
+    
+    """
+    X_Generator: A class designed to generate various Twitter-related content using language models.
 
+    This class contains methods that leverage language models to generate diverse content
+    for Twitter campaigns, retweet comments, Twitter threads, bios, and converting articles
+    into coherent Twitter threads.
+    """
+    
+
+    def x_camp_gen(self, product_name:str, product_desc:str, goal:str, language='En', model_name='Google Palm 2', creativity='Original')->str:
         
-    def __init__(self, llm):
-        self.llm = llm
+        """
+        Generates a Twitter campaign prompt based on product information.
 
+        Parameters:
+        - product_name (str): Name of the product.
+        - product_desc (str): Description of the product.
+        - goal (str): Goal or objective of the campaign.
+        - language (str): Opitonal Parameter -> The language of the model.
+        - creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        - model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
 
-    def x_camp_gen(self, product_name, product_desc, goal):
-    
-        x_camp_prompt = f"Design a potent Twitter campaign for my product '{product_name}'. {product_name} is {product_desc} aiming to accomplish {goal} through the meticulous adoption of planning and content creation best practices.\n\nCampaign will include: Campaign Teaser, Educational Content Series, Customer Testimonials and Case Studies, Interactive Content, Limited-Time Offer Announcement, Call-to-Action for Consultation and  Recap and Thank You."
-        print(x_camp_prompt)
-        x_camp_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a Specialist in Twitter Copywriting\n\n{text_input}\n\nMake the tweets engaging, creative and coherent")
-        x_camp_extraction_chain = LLMChain(llm=self.llm, prompt=x_camp_promptTemp)
+        Returns:
+        - x_camp (str): Generated content for the Twitter campaign.
+        """
+
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        
+        if language == 'En':
+            
+            x_camp_prompt = f"Design a potent Twitter campaign for my product '{product_name}'. {product_name} is {product_desc} aiming to accomplish {goal} through the meticulous adoption of planning and content creation best practices.\n\nCampaign will include: Campaign Teaser, Educational Content Series, Customer Testimonials and Case Studies, Interactive Content, Limited-Time Offer Announcement, Call-to-Action for Consultation and  Recap and Thank You."
+            x_camp_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a Specialist in Twitter Copywriting\n\n{text_input}\n\nMake the tweets engaging, creative and coherent")
+        
+        elif language == 'Ar':
+            
+            x_camp_prompt = f"قم بتصميم حملة تويتر قوية لمنتجي '{product_name}'. {product_name} هو {product_desc} يهدف إلى تحقيق {goal} من خلال اعتماد دقيق على أفضل الممارسات في التخطيط وإنشاء المحتوى.\n\nستتضمن الحملة: العرض التشويقي للحملة، سلسلة محتوى تعليمي، شهادات العملاء ودراسات الحالة، محتوى تفاعلي، إعلان عن عرض لفترة محدودة، دعوة للعمل والاستشارة، وإعادة النظر والشكر."
+            x_camp_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت متخصص في كتابة التغريدات على تويتر\n\n{text_input}\n\nاجعل التغريدات جذابة وإبداعية ومترابطة")
+        
+        x_camp_extraction_chain = LLMChain(llm=llm, prompt=x_camp_promptTemp)
         x_camp = x_camp_extraction_chain.run(x_camp_prompt)
     
         return x_camp
 
-    def x_retweet_commenting_gen(self, tweet, tone_of_voice):
-    
-        x_retweet_comment_prompt = f"I'm planning to retweet the following tweet:\n“{tweet}”\nConstruct 5 varied comments I could append to this retweet. tone should be {tone_of_voice}"
-        x_retweet_comment_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are Specilaized Twitter Copywriter\n{text_input}\n\nRetweet Comment:")
-        x_retweet_comment_extraction_chain = LLMChain(llm=self.llm, prompt=x_retweet_comment_promptTemp)
+    def x_retweet_commenting_gen(self, tweet:str, tone_of_voice:str, language = 'En', model_name='Google Palm 2', creativity='Original')->str:
+        
+        """
+        Generates a X Retweet Commenting based on the quote or commenting tweet.
+
+        Parameters:
+        - tweet (str): The Quoted or commented tweet.
+        - tone_of_voice (str): tone of voice of the generated content.
+        - language (str): Opitonal Parameter -> The language of the model.
+        - creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        - model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
+        Returns:
+        - x_retweet_comment (str): Generated content for the Twitter campaign.
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            x_retweet_comment_prompt = f"I'm planning to retweet the following tweet:\n“{tweet}”\nConstruct 5 varied comments I could append to this retweet. tone should be {tone_of_voice}"
+            x_retweet_comment_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are Specilaized Twitter Copywriter\n{text_input}\n\nRetweet Comment:")
+
+        elif language == 'Ar':
+            
+            x_retweet_comment_prompt = f"أنا أخطط لإعادة نشر التغريدة التالية:\n“{tweet}”\nقم بصياغة 5 تعليقات متنوعة يمكنني إلحاقها بهذا الإعادة. يجب أن يكون النبرة {tone_of_voice}."
+            x_retweet_comment_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب نصوص تويتر متخصص\n{text_input}\n\nتعليق إعادة التغريد:")
+
+        x_retweet_comment_extraction_chain = LLMChain(llm=llm, prompt=x_retweet_comment_promptTemp)
         x_retweet_comment = x_retweet_comment_extraction_chain.run(x_retweet_comment_prompt)
         
         return x_retweet_comment
 
-    def X_thread_gen(self, topic, num_tweets, tone_of_voice):
-    
-        X_thread_prompt = f"Write a an engagging Twitter Thread  on '{topic}' consists of {num_tweets} tweets. Tone should be {tone_of_voice}"
-            
-        X_thread_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a Twitter Content Creator:\n{text_input}\n\nTwitter Thread:")
     
-        X_thread_extraction_chain = LLMChain(llm=self.llm, prompt=X_thread_promptTemp)
-        X_thread = X_thread_extraction_chain.run(X_thread_prompt)
+    def x_thread_gen_intro(self, topic:str, thread:str, tone_of_voice:str, language='En', model_name='Google Palm 2', creativity='Original')->str:
         
-        return X_thread
-    
-    def X_thread_gen_intro(self, topic, thread, tone_of_voice):
+        """
+        Generates a X Retweet Commenting based on the quote or commenting tweet.
+
+        Parameters:
+        - tweet (str): The Quoted or commented tweet.
+        - tone_of_voice (str): tone of voice of the generated content.
+        - language (str): Opitonal Parameter -> The language of the model.
+        - creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        - model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
     
-        X_thread_prompt = f"Write a an engagging and attractive Introduction head tweet for my twitter thread on {topic}. here is my twitter thread:\n{thread}\nTone should be {tone_of_voice}"
+        Returns:
+        - x_retweet_comment (str): Generated content for the Twitter campaign.
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
             
-        X_thread_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a Twitter Content Creator:\n{text_input}\n\nTweet:")
-    
-        X_thread_extraction_chain = LLMChain(llm=self.llm, prompt=X_thread_promptTemp)
-        X_thread = X_thread_extraction_chain.run(X_thread_prompt)
+            x_thread_intro_prompt = f"Write a an engagging and attractive Introduction head tweet for my twitter thread on {topic}. here is my twitter thread:\n{thread}\nTone should be {tone_of_voice}" 
+            x_thread_intro_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a Twitter Content Creator:\n{text_input}\n\nIntroduction Tweet:")
         
-        return X_thread
-    
-    def x_bio_gen(self, info, tone_of_voice):
+        elif language == 'Ar':
+            
+            x_thread_intro_prompt = f"اكتب تغريدة تعريفية جذابة وجذابة للثريد الخاص بي على تويتر {topic}. إليك الثريد الخاص بي على تويتر:\n{thread}\nيجب أن يكون الأسلوب {tone_of_voice}" 
+            x_thread_intro_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت مُنشئ محتوى على تويتر:\n{text_input}\n\n التغريدة التعريفية:")
+
+        x_thread_intro_extraction_chain = LLMChain(llm=llm, prompt=x_thread_intro_promptTemp)
+        x_thread_intro = x_thread_intro_extraction_chain.run(x_thread_intro_prompt)
+        
+        return x_thread_intro
+
+    def x_thread_gen(self, topic:str, num_tweets:int, tone_of_voice:str, language='En', model_name='Google Palm 2', creativity='Original')->str:
+        
+        """
+        Generates a X Retweet Commenting based on the quote or commenting tweet.
+
+        Parameters:
+        - tweet (str): The Quoted or commented tweet.
+        - tone_of_voice (str): tone of voice of the generated content.
+        - language (str): Opitonal Parameter -> The language of the model.
+        - creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        - model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
+        Returns:
+        - x_retweet_comment (str): Generated content for the Twitter campaign.
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            x_thread_prompt = f"Write a an engagging Twitter Thread  on '{topic}' consists of {num_tweets} tweets. Tone should be {tone_of_voice}"
+            x_thread_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a Twitter Content Creator:\n{text_input}\n\nTwitter Thread:")
+            
+        elif language == 'Ar':
+            
+            x_thread_prompt = f"اكتب سلسلة تغريدات جذابة (ثريد) عن '{topic}' تتكون من {num_tweets} الثريد. يجب أن يكون اللهجة {tone_of_voice}."
+            x_thread_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت مُنشئ محتوى على تويتر:\n{text_input}\n\n الثريد:")
+            
+        x_thread_extraction_chain = LLMChain(llm=llm, prompt=x_thread_promptTemp)
+        x_thread = x_thread_extraction_chain.run(x_thread_prompt)
+        
+        return x_thread
+
     
-        x_bio_prompt = f"Craft a personalized Twitter bio for me, based on the content I create, related to {info}. tone should be {tone_of_voice}, Produce 10 tailor-made Twitter bios for me."
-        x_bio_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a copywriter\n{text_input}\n\nTwitter Bios:")
-        x_bio_extraction_chain = LLMChain(llm=self.llm, prompt=x_bio_promptTemp)
+    def x_bio_gen(self, info:str, tone_of_voice:str, language='En', model_name = 'Google Palm 2', creativity = 'Original')->str:
+        
+        """
+        Generates an X Bio based on given Profile.
+
+        Parameters:
+        - info (str): Information about the X user.
+        - tone_of_voice (str): tone of voice of the generated X Bio.
+        - language (str): Opitonal Parameter -> The language of the model.
+        - creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        - model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
+        Returns:
+        - x_bio (str): Generated X Bio for The X user.
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            x_bio_prompt = f"Craft a personalized Twitter bio for me, based on the content I create, related to {info}. tone should be {tone_of_voice}, Produce 10 tailor-made Twitter bios for me."
+            x_bio_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a copywriter\n{text_input}\n\nTwitter Bios:")
+            
+        elif language == 'Ar':
+            
+            x_bio_prompt = f"قم بكتابة لي سيرة ذاتية شخصية على تويتر، مستندة إلى المحتوى الذي أنشئه، ذات صلة بـ {info}. يجب أن يكون النبرة {tone_of_voice}. أنتج ١٠ سير ذاتية مُصمَّمة خصيصًا لتويتر بالنسبة لي."
+            x_bio_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب نسخ\n{text_input}\n\n السير الذاتية لتويتر:")
+            
+        x_bio_extraction_chain = LLMChain(llm=llm, prompt=x_bio_promptTemp)
         x_bio = x_bio_extraction_chain.run(x_bio_prompt)
         
         return x_bio
     
-    def article_to_x_thread_gen(self, article):
-    
-        article_to_x_thread_prompt = f"Transform the ensuing article into a sequence of Twitter posts, creating a coherent Twitter thread between 5 to 20 tweets\nArticle: “{article}.“"
-        article_to_x_thread_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a twitter copywriter\n{text_input}\n\nCoherent Twitter Thread:")
-        article_to_x_thread_extraction_chain = LLMChain(llm=self.llm, prompt=article_to_x_thread_promptTemp)
-        article_to_x_thread = article_to_x_thread_extraction_chain.run(article_to_x_thread_prompt)
+    def article_to_x_thread_gen(self, article:str, language='En', model_name='Google Palm 2', creativity='Original')->str:
+        
+        """
+        Converts an article into a coherent Twitter thread.
+
+        Parameters:
+
+        - article (str): The article content to be transformed.
+        - language (str): Opitonal Parameter -> The language of the model.
+        - creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        - model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
+
+        Returns:
         
-        return article_to_x_thread
+        - article_to_x_thread (str): Generated coherent Twitter thread based on the article.
+        """
+
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
 
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
 
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
 
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        
+        if language == 'En':
+            
+            article_to_x_thread_prompt = f"Transform the ensuing article into a sequence of Twitter posts, creating a coherent Twitter thread between 5 to 20 tweets\nArticle: “{article}.“"
+            article_to_x_thread_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a twitter copywriter\n{text_input}\n\nCoherent Twitter Thread:")
+        
+        elif language == 'Ar':
+            
+            article_to_x_thread_prompt = f"حوّل المقال الآتي إلى سلسلة من تغريدات تويتر، مكوّناً سلسلة تويتر مترابطة تتكون من 5 إلى 20 تغريدة. المقال : {article}"
+            article_to_x_thread_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب نصوص تويتر\n{text_input}\n\nسلسلة تويتر متناسقة:")
+
+        article_to_x_thread_extraction_chain = LLMChain(llm=llm, prompt=article_to_x_thread_promptTemp)
+        article_to_x_thread = article_to_x_thread_extraction_chain.run(article_to_x_thread_prompt)
+        
+        return article_to_x_thread

app.py

@@ -1,37 +1,22 @@
 from remove_astricks import remove_ast
 from load_model import call_palm
-from keywords_generation import keywords_generator, filter_keywords, process_keywords
+from keywords_generation import keywords_generator, keywords_generator_long_tail, filter_keywords, process_keywords
 from idea_generation import ideas_generator, filter_ideas
 from outline_generation import outlines_generator, filtered_outlines
-from article_generation import  full_article, rephrase
+from article_generation import  full_article
 from product_description_generation import product_description_gen
-from x_thread_generation import X_thread_gen, X_thread_gen_intro
-from linkedin_post_generation import linkedIn_post_gen
-from insta_image_caption_generation import img2text, generate_InstaCap
-from facebook_post_generation import facebook_post_gen
-from facebook_ads_generation import facebook_ads_gen
-from facebook_campaign import facbook_camp_gen, social_media_camp_gen
-from linkedIn_ads_generation import linkedIn_ads_gen
-from email_marketing_campaigns_generation import email_marketing_campaigns_gen
 from workout_plan_generation import workout_plan_gen
-from landing_page_generation import landing_page_gen
-from blog_post_generation import blog_post_gen
-from x_bio_creation import x_bio_gen
-from x_retweet_commenting_generation import x_retweet_commenting_gen
-from article_conversion_to_x_thread import article_to_x_thread_gen
-from x_campaign_generation import x_camp_gen
-from blog_ideas_generation import blog_idea_gen
-from blog_ideas_description_generation import blog_idea_desc_gen
-from blog_post_tags_generation import blog_tags_gen
+from linkedin_content_creation import linkedIn_content_gen
+
 import X_content_creation
 import blog_content_creation
 import meta_content_creation
 import email_writer
 
 import streamlit as st
+import spacy
 from dotenv import load_dotenv, find_dotenv
 import os
-import time
 
 load_dotenv(find_dotenv())
 google_api_key = os.environ['OPENAI_API_KEY']
@@ -42,12 +27,14 @@ if __name__ == '__main__':
     llm = call_palm(google_api_key) 
     
     tone_of_voice_list = ('Excited', 'Professional', 'Encouraging', 'Funny', 'Dramatic', 'Witty', 'Sarcastic', 'Engaging', 'Creative')
-    creativity_list = ('Original', 'Creative', 'Visionary')
+    languages = ('En', 'Ar', 'De', 'Fr', 'It', 'Es', 'Pt', 'Ru', 'Hi', 'Ja', 'Nl', 'Zh')
+    creativity_list = ('Original', 'Balanced', 'Creative', 'Spirited', 'Visionary')
+    models = ('Google Palm 2', 'GPT-3.5', 'GPT-4')
 
     with st.sidebar:
 
         st.image('Logo.png')
-        choice = st.radio("Navigation", ["Articles and Blogs", "Product Description", "LinkedIn Post", "LinkedIn Ads", "Gym Workout Plan", "Landing Page", "X Content Creation", "Meta Content", "Emails"])
+        choice = st.radio("Navigation", ["Articles and Blogs", "Product Description", "LinkedIn Content", "Gym Workout Plan", "Landing Page", "X Content Creation", "Meta Content", "Emails"])
         st.info("Generate your Content with Feather AI in Seconds..")
 
   
@@ -57,40 +44,57 @@ if __name__ == '__main__':
         product_name = st.text_input('Product Name')
         product_desc =  st.text_area('Product Description')
         tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
+        model = st.selectbox('Choose the Model', models)
+        creativity = st.selectbox('Creativity Level', creativity_list)
+        language = st.selectbox('Choose a language', languages)
 
-        if product_name and product_desc and tone_of_voice:
+        if product_name and product_desc and tone_of_voice and model and creativity and language:
 
             if st.button('Generate'):
 
-                product_description = product_description_gen(product_name, product_desc, tone_of_voice, llm)
+                product_description = product_description_gen(product_name, product_desc, tone_of_voice=tone_of_voice, model_name=model, creativity=creativity, language=language)
                 st.markdown(product_description)
 
-    elif choice == 'LinkedIn Post':
+    elif choice == 'LinkedIn Content':
 
-        topic = st.text_input("Topic")
-        tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
+        linkedIn_content_generation = linkedIn_content_gen()
+
+        linkedIn_choices_list = ('LinkedIn Post', 'LinkedIn Ads')
         
-        if topic and tone_of_voice:
+        linkedIn_choices = st.selectbox('Choose LinkedIn Template', linkedIn_choices_list)
+
+        if linkedIn_choices == linkedIn_choices_list[0]:
             
-            if st.button('Generate'):
 
-                linkedIn_post = linkedIn_post_gen(topic, tone_of_voice, llm)
-                st.markdown(linkedIn_post)
+            topic = st.text_input('Topic')
+            tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
+            if topic and tone_of_voice and model and creativity and language:
 
-    elif choice == "LinkedIn Ads":
+                if st.button('Generate'):
 
-        product_name = st.text_input("Product Name")
-        product_desc = st.text_area("Product Description")
-        target_audience = st.text_input("Target Audience")
-        target_keywords = st.text_input("Target Keywords")
+                    linkedIn_post = linkedIn_content_generation.linkedIn_post_gen(topic, tone_of_voice, language=language, model_name=model, creativity=creativity)
+                    st.markdown(linkedIn_post)
 
-        if product_name and product_desc and target_audience and target_keywords:
-            
-            if st.button("Generate"):
+        elif linkedIn_choices == linkedIn_choices_list[1]:
 
-                linkedIn_ad = linkedIn_ads_gen(product_name, product_desc, target_audience, target_keywords, llm)
-                st.markdown(linkedIn_ad)
+            product_name = st.text_input('Product Name')
+            product_desc = st.text_area('Product Description')
+            target_audience = st.text_input('Target Audience')
+            target_keywords = st.text_input('Target Keywords')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
+
+            if product_name and product_desc and target_audience and target_keywords and model and creativity and language:
+
+                if st.button('Generate'):
+
+                    linkedIn_ad = linkedIn_content_generation.linkedIn_ads_gen(product_name, product_desc, target_audience, target_keywords, language=language, model_name=model, creativity=creativity)
+                    st.markdown(linkedIn_ad)
 
 
     elif choice == "Gym Workout Plan":
@@ -106,11 +110,15 @@ if __name__ == '__main__':
         routine = st.selectbox("Preferred Routine", routine_list)
         my_goals = st.text_input('Goals')
 
-        if fitness_level  and days and hours and health_consd and routine and my_goals: 
+        model = st.selectbox('Choose a Model', models)
+        creativity = st.selectbox('Creativity Level', creativity_list)
+        language = st.selectbox('Select a Language', languages)
+
+        if fitness_level  and days and hours and health_consd and routine and my_goals and model and creativity and language: 
 
             if st.button('Generate'):
                 
-                workout_plan = workout_plan_gen(my_goals, fitness_level, days, hours, health_consd, routine, llm)
+                workout_plan = workout_plan_gen(my_goals, fitness_level, days, hours, health_consd, routine, model_name=model, creativity=creativity, language=language)
                 st.markdown(workout_plan)
 
     elif choice == "Landing Page":
@@ -130,7 +138,7 @@ if __name__ == '__main__':
     
     elif choice == 'X Content Creation':
 
-        X_content = X_content_creation.X_Generator(llm)
+        X_content = X_content_creation.X_Generator()
 
         x_choices_list = ('X thread', 'X Retweet Commenting', 'X Campaign', 'X Bio Creation', 'Article Conversion to X Thread')
         
@@ -141,13 +149,16 @@ if __name__ == '__main__':
             topic = st.text_input('Topic')
             num_tweets = st.slider('Number of Thread tweet', 1,10,5)
             tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if topic and num_tweets and tone_of_voice:
+            if topic and num_tweets and tone_of_voice and model and creativity and language:  
                 
                 if st.button('Generate'):
 
-                    X_thread = X_content.X_thread_gen(topic, num_tweets, tone_of_voice)
-                    intro = X_content.X_thread_gen_intro(topic, X_thread, tone_of_voice)
+                    X_thread = X_content.x_thread_gen(topic, num_tweets, tone_of_voice, language=language, model_name=model, creativity=creativity)
+                    intro = X_content.x_thread_gen_intro(topic, X_thread, tone_of_voice, language=language, model_name=model, creativity=creativity)
                     st.markdown(intro)
                     st.markdown(X_thread)
 
@@ -156,12 +167,15 @@ if __name__ == '__main__':
 
             tweet = st.text_area('Tweet')
             tone_of_voice = st.selectbox('Tone of voice', tone_of_voice_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if tweet and tone_of_voice:
+            if tweet and tone_of_voice and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    x_retweet_comment = X_content.x_retweet_commenting_gen(tweet, tone_of_voice)
+                    x_retweet_comment = X_content.x_retweet_commenting_gen(tweet, tone_of_voice, language=language, model_name=model, creativity=creativity)
                     st.markdown(x_retweet_comment)
 
         elif x_choices == x_choices_list[2]:
@@ -169,76 +183,99 @@ if __name__ == '__main__':
             product_name = st.text_input('Product Name')
             product_desc = st.text_area('Product Description')
             goal = st.text_input('Goal')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
 
-            if product_name and product_desc and goal:
+            if product_name and product_desc and goal and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    x_camp = X_content.x_camp_gen(product_name, product_desc, goal)
+                    x_camp = X_content.x_camp_gen(product_name, product_desc, goal, language=language, model_name=model, creativity=creativity)
                     st.markdown(x_camp)
 
         elif x_choices == x_choices_list[3]:
 
             info = st.text_area('info')
             tone_of_voice = st.selectbox('Tone of voice', tone_of_voice_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if info and tone_of_voice:
+            if info and tone_of_voice and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    x_bio = X_content.x_bio_gen(info, tone_of_voice, llm)
+                    x_bio = X_content.x_bio_gen(info, tone_of_voice, language=language, model_name=model, creativity=creativity)
                     st.markdown(x_bio)
 
         elif x_choices == x_choices_list[4]:
 
             article = st.text_area('Article')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if article:
+            if article and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    article_to_x_thread = X_content.article_to_x_thread_gen(article)
+                    article_to_x_thread = X_content.article_to_x_thread_gen(article, language=language, model_name=model, creativity=creativity)
                     st.markdown(article_to_x_thread)
 
     elif choice == 'Articles and Blogs':
 
-        blog_content = blog_content_creation.blog_content_generation(llm)
+        blog_content = blog_content_creation.blog_content_generation()
 
         blog_choices_list = ('Article Writer', 'Blog Post', 'Blog Ideas', 'Blog Tags', 'Blog Ideas description')
         
         blog_choices = st.selectbox('Choose Blog Template', blog_choices_list)
 
+        
+
         if blog_choices == blog_choices_list[0]:
             
             topic = st.text_input('Topic')
             tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if topic:
+            if topic and tone_of_voice and model and creativity and language:
+
+                keywords =  keywords_generator(topic, num_keywords=10, language=language, model_name=model, creativity=creativity)
+                keywords_gen_long_tail = keywords_generator_long_tail(topic, num_keywords=10, language=language, model_name=model, creativity=creativity)
 
-                keywords = keywords_generator(topic, llm)
                 filtered_keywords = filter_keywords(keywords)
+                filtered_keywords_long_tail = filter_keywords(keywords_gen_long_tail)
+
                 formatted_keywords = process_keywords(filtered_keywords)
+                formatted_keywords_long_tail = process_keywords(filtered_keywords_long_tail)
 
                 st.markdown('### Generated Keywords:\n')
                 st.markdown(formatted_keywords)
 
                 formatted_keywords = remove_ast(formatted_keywords)
+                formatted_keywords_long_tail = remove_ast(formatted_keywords_long_tail)
+
 
                 idea_numbers = st.slider("How many ideas you want?",1,10,5)
 
-                ideas = ideas_generator(topic, formatted_keywords, llm, tone_of_voice, idea_numbers)
+                ideas = ideas_generator(topic, formatted_keywords_long_tail, tone_of_voice=tone_of_voice, num_of_ideas=idea_numbers, language=language, model_name=model, creativity=creativity)
                 filtered_ideas = filter_ideas(ideas)
                 
                 index = 1
 
                 st.markdown("### Generated Ideas:\n")
+
                 for idea in filtered_ideas:
 
                     st.markdown(f"{index} - {idea}")
                     index+=1
 
                 st.text('\n')
+
                 num_idea = st.text_input("Choose the idea you want by number")
 
                 if num_idea:
@@ -247,73 +284,96 @@ if __name__ == '__main__':
                     idea = filtered_ideas[num_idea-1]
                     idea = remove_ast(idea)
 
-                    outline = outlines_generator(idea,formatted_keywords, llm)
+                    outline = outlines_generator(idea,formatted_keywords_long_tail, language=language, model_name=model, creativity=creativity)
+
                     st.text('\n')
                     st.markdown("### Generated Outline:\n")
                     st.markdown(outline)
                     outline_list = filtered_outlines(outline)
 
+                    outline_list2=[]
+
+                    for section in outline_list:
+                        
+                        cleaned_section = remove_ast(section)
+                        outline_list2.append(cleaned_section)
 
                     if st.button('Generate'):
 
-                        article = full_article(idea, outline_list, tone_of_voice, llm)
+                        article = full_article(idea, outline_list2, tone_of_voice=tone_of_voice, language=language, model_name=model, creativity=creativity)
 
                         st.markdown("# Your Article:\n")
                         st.markdown(f"{idea}\n")
                         st.markdown('\n\n'.join(article))
                         st.text('\n\n')
-                        num_art_chars = len('\n'.join(article))
-                        num_art_words = len('\n'.join(article).split(' '))
 
-                        st.markdown(f"{num_art_chars} Characters")
-                        st.markdown(f"{num_art_words} Words")
+                        num_full_art_chars = len('\n'.join(article))
+                        nlp = spacy.load('en_core_web_sm')
+                        doc = nlp('\n'.join(article))
+                        num_full_art_words = len(doc)
+
+                        st.markdown(f"{num_full_art_chars} Characters")
+                        st.markdown(f"{num_full_art_words} Words")
 
         elif blog_choices == blog_choices_list[1]:
 
             topic = st.text_input('Topic')
+            tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if topic:
+            if topic and tone_of_voice and model and creativity and language:
 
                 if st.button('Generate'):
-                    blog_post = blog_content.blog_post_gen(topic)
+                    blog_post = blog_content.blog_post_gen(topic, tone_of_voice=tone_of_voice, language=language, creativity=creativity, model_name=model)
                     st.markdown(blog_post)
 
         elif blog_choices == blog_choices_list[2]:
 
             topic = st.text_input('Topic')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
             if topic:
 
                 if st.button('Generate'):
 
-                    blog_idea = blog_content.blog_idea_gen(topic)
+                    blog_idea = blog_content.blog_idea_gen(topic, model_name=model, creativity=creativity, language=language)
                     st.markdown(blog_idea)
 
         elif blog_choices == blog_choices_list[4]:
 
-            blog = st.text_area('Blog')
+            topic = st.text_input('topic')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if blog:
+            if topic and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    blog_idea_desc = blog_content.blog_idea_desc_gen(blog)
+                    blog_idea_desc = blog_content.blog_idea_desc_gen(topic, model_name=model, creativity=creativity, language=language)
                     st.markdown(blog_idea_desc)
 
         elif blog_choices == blog_choices_list[3]:
 
             blog = st.text_area('Blog')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if blog:
+            if blog and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    blog_tags = blog_content.blog_tags_gen(blog)
+                    blog_tags = blog_content.blog_tags_gen(blog, model_name=model, creativity=creativity, language=language)
                     st.markdown(blog_tags)
 
     elif choice == 'Meta Content':
         
-        meta_content_gen = meta_content_creation.meta_content_generation(llm)
+        meta_content_gen = meta_content_creation.meta_content_generation()
 
         meta_choices_list = ('Facebook Post', 'Facebook Ads', 'Facebook Campaign', 'Insta Image Captioning')
         
@@ -323,14 +383,16 @@ if __name__ == '__main__':
         if meta_choices == meta_choices_list[0]:
 
             topic = st.text_input("Topic")
-
             tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if topic and tone_of_voice:
+            if topic and tone_of_voice and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    facebook_post = meta_content_gen.facebook_post_gen(tone_of_voice, topic)
+                    facebook_post = meta_content_gen.facebook_post_gen(tone_of_voice, topic, language=language, model_name=model, creativity=creativity)
                     st.markdown(facebook_post)
 
         elif meta_choices == meta_choices_list[1]:
@@ -339,15 +401,16 @@ if __name__ == '__main__':
             product_desc = st.text_area('Description')
             targeted_audience = st.text_input('Target Audience')
             plans_proms = st.text_input('Plan and Promotions')
-
             tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
-            creativity = st.selectbox('Creativity', creativity_list)
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if product_name and product_desc and tone_of_voice:
+            if product_name and product_desc and tone_of_voice and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    face_ad__prom = meta_content_gen.facebook_ads_gen(product_name, product_desc, tone_of_voice, targeted_audience, plans_proms)
+                    face_ad__prom = meta_content_gen.facebook_ads_gen(product_name, product_desc, tone_of_voice, targeted_audience, plans_proms, language=language, model_name=model, creativity=creativity)
                     st.markdown(face_ad__prom)
 
         elif meta_choices == meta_choices_list[2]:
@@ -356,13 +419,16 @@ if __name__ == '__main__':
             product_desc = st.text_area('Product Description')
             days = st.selectbox('Days', (10,15,20,25,30))
             goal = st.text_input('Goal')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if product_name and product_desc and goal and days:
+            if product_name and product_desc and goal and days and model and creativity and language:
 
                 if st.button('Generate'):
 
-                    facbook_camp = meta_content_gen.facbook_camp_gen(product_name, product_desc, days, goal)
-                    st.markdown(facbook_camp)
+                    facebook_camp = meta_content_gen.facbook_camp_gen(product_name, product_desc, days, goal, language=language, model_name=model, creativity=creativity)
+                    st.markdown(facebook_camp)
 
         elif meta_choices == meta_choices_list[3]:
 
@@ -385,16 +451,21 @@ if __name__ == '__main__':
 
                     tone_of_voice = st.selectbox('Tone of Voice', tone_of_voice_list)
                     form = st.selectbox('Caption Form', ('Short Form', 'Medium Form', 'Long Form'))
+                    model = st.selectbox('Choose a model', models)
+                    creativity = st.selectbox('Choose a creativity', creativity_list)
+                    language = st.selectbox('Choose a language', languages)
 
-                    if st.button('Generate'):
+                    if tone_of_voice and form and model and creativity and language:
+
+                        if st.button('Generate'):
 
-                        st.subheader("Generated Instagram Image according to the scenario:")                    
-                        instaCap = meta_content_gen.generate_InstaCap(scenario, tone_of_voice, form)
-                        st.markdown(instaCap)
+                            st.subheader("Generated Instagram Image according to the scenario:")                    
+                            instaCap = meta_content_gen.generate_InstaCap(scenario, tone_of_voice, form, language=language, model_name=model, creativity=creativity)
+                            st.markdown(instaCap)
 
     elif choice == 'Emails':
 
-        email_content_gen = email_writer.email_writing(llm)
+        email_content_gen = email_writer.email_writing()
 
         email_choices_list = ('Email Writer', 'Email Marketing Campaign')
         
@@ -407,12 +478,15 @@ if __name__ == '__main__':
             sender_name = st.text_input('Sender Name')
             position_sender = st.text_input('Sender Position')
             description = st.text_area('Description')
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if recipient and recipient_position and sender_name and position_sender and description:
+            if recipient and recipient_position and sender_name and position_sender and description and model and creativity and language:
 
                 if st.button('Generate'):
                     
-                    email = email_content_gen.email_gen(recipient, recipient_position, sender_name, position_sender, description)
+                    email = email_content_gen.email_gen(recipient, recipient_position, sender_name, position_sender, description, language=language, model_name=model, creativity=creativity)
                     email_subject = email_content_gen.email_subject_gen(email)
                     st.markdown(f'Subject: {email_subject}')
                     st.markdown(email)
@@ -423,12 +497,15 @@ if __name__ == '__main__':
             product_description = st.text_area("Product Description")
             target_audience = st.text_input("Target Audience")
             goal = st.text_input("Goal")
+            model = st.selectbox('Choose a model', models)
+            creativity = st.selectbox('Choose a creativity', creativity_list)
+            language = st.selectbox('Choose a language', languages)
 
-            if product_name and product_description and target_audience and goal:
+            if product_name and product_description and target_audience and goal and model and creativity and language:
                 
                 if st.button("Generate"):
 
-                    email_marketing_camp = email_content_gen.email_marketing_campaigns_gen(product_name, product_description, target_audience, goal)
+                    email_marketing_camp = email_content_gen.email_marketing_campaigns_gen(product_name, product_description, target_audience, goal, language=language, model_name=model, creativity=creativity)
                     st.markdown(email_marketing_camp)
 
 

article_generation.py

@@ -1,53 +1,104 @@
+from typing import List
+
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
+from langchain.llms import OpenAI
+
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
 
-def article_generator(idea, outline, section, llm, tone_of_voice):
+def article_generator(idea : str, outline : str, section : str, tone_of_voice : str, language='En', model_name='Google Palm 2', creativity='Original') -> str:
     
     '''
-    Description:
-        This function generates paragraphs for an article based on provided inputs such as the main idea, outline, specific section, Long Language Model (LLM), and desired tone of voice. 
-        It uses a language model to create content either for a catchy introduction paragraph or to expand the article based on an existing outline.
+    Description
+
+        This function generates paragraphs for an article based on provided parameters such as the main idea, outline, section, language model, and tone of voice. It utilizes a PromptTemplate and an LLMChain for content creation.
 
     Parameters:
-        idea (str) -> Required: The main idea or topic of the article.
-        outline (str) -> Required: The existing outline (if any) that has been covered in the article.
-        section (str) -> Required: The specific section or point that needs content creation or elaboration.
-        llm -> Required: The Long Language Model (LLM) used for generating article content.
-        tone_of_voice (str) -> Required: The intended tone of the article (e.g., professional, conversational, persuasive).
-
-    Return Value:
-        article (str): The generated article paragraph based on the provided inputs.
+
+        idea -> Required: (str) Represents the main idea or topic of the article.
+        outline -> Required: (str) Indicates the existing outline content (if any) for the article.
+        section -> Required: (str) Specifies the main point or section that requires content generation.
+        tone_of_voice -> Required: (str) Defines the desired tone for the article (e.g., formal, informal, technical).
+        language (str): Opitonal Parameter -> The language of the model.
+        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
+
+    Return:
+    - `article`: (str) The generated article paragraph based on the provided parameters and content prompts.
     '''
+    
+    temp = 0
+
+    if creativity == 'Original':
+        temp = 0
+    elif creativity == 'Balanced':
+        temp = 0.25
+    elif creativity == 'Creative':
+        temp = 0.5
+    elif creativity == 'Spirited':
+        temp = 0.75
+    elif creativity == 'Visionary':
+        temp = 1
+
+
+    if model_name == 'Google Palm 2':
+        llm = call_palm(google_api_key, temperature=temp)
+
+    elif model_name == 'GPT-3.5':
+        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
 
-    if len(outline) == 0:
-        article_prompt = f"Generate Catchy Introduction paragraph for my article on {idea} using the following main point: {section}\nThe tone should be {tone_of_voice}."
-    else:
-        article_prompt = f"Generate well-organized paragraph for my article on {idea}. I have already covered: {outline} in the outline. I need help with the following main point: {section}. Please ensure the paragraphs are connected logically and provide a smooth transition between main topics. The tone should be {tone_of_voice}."
+    elif model_name == 'GPT-4':
+        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
 
-    article_promptTemp = PromptTemplate(
-    input_variables=["text_input"],
-    template="You are a Professional content creator and article Writer:\n\n{text_input}\n\nParagraph:")
+
+    if language == 'En':
+        
+        if len(outline) == 0:
+            article_prompt = f"Generate Catchy Introduction paragraph for my article on {idea} using the following main point: {section}\nThe tone should be {tone_of_voice}."
+        else:
+            article_prompt = f"Generate well-organized paragraph for my article on {idea}. I have already covered: {outline} in the outline. I need help with the following main point: {section}. Please ensure the paragraphs are connected logically and provide a smooth transition between main topics. The tone should be {tone_of_voice}."
+
+        article_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="You are a Professional content creator and article Writer:\n\n{text_input}\n\nParagraph:")
     
-    print(article_prompt)
+    elif language == 'Ar':
+        
+        if len(outline) == 0:
+            article_prompt = f"أنشئ فقرة مثيرة للاهتمام لمقالي عن {idea} باستخدام النقطة الرئيسية التالية: {section}\nيجب أن يكون اللهجة {tone_of_voice}."
+        else:
+            article_prompt = f"انشئ فقرة منظمة تماماً لمقالي حول {idea}. لقد غطيت بالفعل: {outline} في الخطة العريضة. أحتاج مساعدة في النقطة الرئيسية التالية: {section}. يرجى التأكد من أن الفقرات متصلة منطقياً وتوفير انتقال سلس بين المواضيع الرئيسية. يجب أن يكون اللهجة {tone_of_voice}."
+
+        article_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="أنت مبدع محترف للمحتوى وكاتب مقالات:\n\n{text_input}\n\nالفقرة:")
+
     article_extraction_chain = LLMChain(llm=llm, prompt=article_promptTemp)
     article = article_extraction_chain.run(article_prompt)
     
     return article
 
-def full_article(idea, outline_list, tone_of_voice, llm):
+
+def full_article(idea : str, outline_list : List[str], tone_of_voice : str, language='En', model_name='Google Palm 2', creativity='Original') -> List[str]:
     
     '''
     Description:
-        This function generates a full article by iteratively calling the article_generator function for each section in the provided outline list. It accumulates paragraphs generated for each section to construct a complete article based on the specified idea, outline, tone of voice, and Long Language Model (LLM).
+        This function generates a full article by iteratively creating paragraphs for each section in an outline list using the `article_generator` function. It accumulates the generated paragraphs into a list representing the complete article.
 
     Parameters:
-        idea (str) -> Required: The main idea or topic for the article.
-        outline_list (list) -> Required: A list containing sections or subsections for the article's structure.
-        tone_of_voice (str) -> Required: The desired tone of the article (e.g., professional, conversational, persuasive).
-        llm -> Required: The Long Language Model (LLM) used for generating article content.
+        - `idea` -> Required: (str) Represents the main idea or topic of the article.
+        - `outline_list` -> Required: (list) Contains sections or main points forming the outline structure of the article.
+        - `tone_of_voice` -> Required: (str) Defines the desired tone for the article (e.g., formal, informal, technical).
+        - `llm` -> Required: (object) Represents the language model used for generating the article content.
+        language (str): Opitonal Parameter -> The language of the model.
+        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
 
-    Return Value:
-        article (list): A list of paragraphs representing the article content for each section in the provided outline.
+    Return:
+        - `article`: (list) A list containing paragraphs generated for each section in the `outline_list`.
     '''
     
     article = []
@@ -57,7 +108,7 @@ def full_article(idea, outline_list, tone_of_voice, llm):
         
         for section in outline_list:
 
-            para = article_generator(idea, ' '.join(outline), section, llm, tone_of_voice)
+            para = article_generator(idea, ' '.join(outline), section, tone_of_voice, language=language, model_name=model_name, creativity=creativity)
             outline.append(section)
             article.append(para)
             
@@ -65,16 +116,3 @@ def full_article(idea, outline_list, tone_of_voice, llm):
         pass
     
     return article
-
-def rephrase(par, llm):
-    
-    paraCheck_prompt = f"Rephrase the following paragraph and make it more unique and excited: {par}"
-
-    paraCheck_promptTemp = PromptTemplate(
-    input_variables=["text_input"],
-    template="You are a content creator.\n{text_input}")
-   
-    paraCheck_extraction_chain = LLMChain(llm=llm, prompt=paraCheck_promptTemp)
-    rephrased_paragraph = paraCheck_extraction_chain.run(paraCheck_prompt)
-    
-    return rephrased_paragraph

blog_content_creation.py

@@ -1,5 +1,10 @@
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
+from langchain.llms import OpenAI
+
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
+
 
 class blog_content_generation:
 
@@ -12,87 +17,238 @@ class blog_content_generation:
         __init__(self, llm)
 
             Description: Initializes the blog_content_generation class by setting the language model (llm) to be used for content generation.
-            Parameters:
-            llm: The language model instance used for generating content.
         
         blog_idea_desc_gen(self, blog)
 
             Description: Generates SEO-friendly titles and meta descriptions for a given blog post topic.
+
             Parameters:
-            blog: The title or topic of the blog post.
+
+                topic: The title or topic of the blog post.
+                language (str): Opitonal Parameter -> The language of the model.
+                creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+                model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+                
+
             Returns:
             blog_idea_desc: A list of suggested titles and meta descriptions.
             
         blog_idea_gen(self, topic)
 
             Description: Creates a list of SEO-friendly blog post ideas with emotional and persuasive titles based on a specific topic.
+
             Parameters:
-            topic: The subject or theme for which blog post ideas are requested.
+                topic: The subject or theme for which blog post ideas are requested.
+                language (str): Opitonal Parameter -> The language of the model.
+                creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+                model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+                
             Returns:
-            blog_idea: A list containing at least 10 suggested blog post ideas.
+                blog_idea: A list containing at least 10 suggested blog post ideas.
             
         blog_post_gen(self, topic)
 
             Description: Generates a blog post on a given topic.
+
             Parameters:
-            topic: The subject or theme for the blog post content.
+                topic: The subject or theme for the blog post content.
+                language (str): Opitonal Parameter -> The language of the model.
+                creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+                model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+                
             Returns:
             blog_post: The generated blog post content.
             
         blog_tags_gen(self, blog)
 
             Description: Suggests tags for a specific blog post.
+            
             Parameters:
-            blog: The title or topic of the blog post for which tags are needed.
+                blog: The title or topic of the blog post for which tags are needed.
+                language (str): Opitonal Parameter -> The language of the model.
+                creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+                model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+                
             Returns:
             blog_tags_desc: A list of suggested tags related to the provided blog post.
     '''
-    
-    def __init__(self, llm):
-        self.llm = llm
 
 
-    def blog_idea_desc_gen(self, blog):
-    
-        blog_idea_desc_prompt = f"Suggest at least 5 SEO-friendly titles and meta descriptions for the following blog post {blog}. Use a persuasive and intriguing tone."
-        blog_idea_desc_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are my blogger writter\n\n{text_input}\n\nSEO blog post ideas:")
-        blog_idea_desc_extraction_chain = LLMChain(llm=self.llm, prompt=blog_idea_desc_promptTemp)
+    def blog_idea_desc_gen(self, topic, language='En',creativity='Original', model_name='Google Palm 2'):
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            blog_idea_desc_prompt = f"Suggest at least 5 SEO-friendly titles and meta descriptions for blog post topic delimeted by three backtick. Use a persuasive and intriguing tone.\n```{topic}```"
+            blog_idea_desc_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are my blogger writter\n\n{text_input}\n\nSEO blog post ideas:")
+            
+        elif language == 'Ar':
+            
+            blog_idea_desc_prompt = f"اقترح على الأقل 5 عناوين ووصفات ودية لمحركات البحث (SEO) لمقالة الويب التالية {topic}. استخدم نبرة مقنعة ومثيرة للاهتمام."
+            blog_idea_desc_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب مدونتي\n\n{text_input}\n\nأفكار مقالات مدونة حول تحسين محركات البحث:")
+            
+        blog_idea_desc_extraction_chain = LLMChain(llm=llm, prompt=blog_idea_desc_promptTemp)
         blog_idea_desc = blog_idea_desc_extraction_chain.run(blog_idea_desc_prompt)
         
         return blog_idea_desc
 
-    def blog_idea_gen(self, topic):
-    
+    def blog_idea_gen(self, topic, language='En', creativity='Original', model_name='Google Palm 2'):
     
-        blog_idea_prompt = f"Create a list of at least 10 blog post ideas on the following topic: {topic}. Suggest SEO-Friendly title and use an emotional and persuasive tone in blog post titles."
-        blog_idea_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are my blogger writter\n\n{text_input}\n\nSEO blog post ideas:")
-        blog_idea_extraction_chain = LLMChain(llm=self.llm, prompt=blog_idea_promptTemp)
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            blog_idea_prompt = f"Create a list of at least 10 blog post ideas on the following topic: {topic}. Suggest SEO-Friendly title and use an emotional and persuasive tone in blog post titles."
+            blog_idea_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are my blogger writter\n\n{text_input}\n\nSEO blog post ideas:")
+            
+        elif language == 'Ar':
+            blog_idea_prompt = f"أنشئ قائمة تحتوي على على الأقل 10 أفكار لمقالات في موضوع: {topic}. اقترح عناوين صديقة لمحركات البحث واستخدم نبرة عاطفية ومقنعة في عناوين مقالات البلوج"
+            blog_idea_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب مدونتي\n\n{text_input}\n\nأفكار مقالات مدونة تحسين محركات البحث:")
+            
+        blog_idea_extraction_chain = LLMChain(llm=llm, prompt=blog_idea_promptTemp)
         blog_idea = blog_idea_extraction_chain.run(blog_idea_prompt)
         
         return blog_idea
 
-    def blog_post_gen(self, topic):
-    
-        blog_post_prompt = f"Write a blog Plost about {topic}."
-        blog_post_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a Professional Content Creator and Blog Writer:\n{text_input}\nBlog Post:")
-        blog_post_extraction_chain = LLMChain(llm=self.llm, prompt=blog_post_promptTemp)
+    def blog_post_gen(self, topic, tone_of_voice='Excited', language='En', creativity='Original', model_name='Google Palm 2'):
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            blog_post_prompt = f"""Write a well organized and attractive blog Plost about the topic delimited by triple backticks.
+            The tone should be {tone_of_voice}.
+              ```{topic}```."""
+            blog_post_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a Professional Content Creator and Blog Writer:\n{text_input}\nBlog Post:")
+        
+        elif language == 'Ar':
+            
+            blog_post_prompt = f"اكتب مقالة في المدونة حول {topic}."
+            blog_post_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت مبدع محترف للمحتوى وكاتب للمدوّنات:\n{text_input}\nمقال المدوّنة:")
+        
+        blog_post_extraction_chain = LLMChain(llm=llm, prompt=blog_post_promptTemp)
         blog_post = blog_post_extraction_chain.run(blog_post_prompt)
         
         return blog_post
         
-    def blog_tags_gen(self, blog):
-    
-        blog_tags_desc_prompt = f" Suggest at least 5 tags for the following blog post.\n{blog}"
-        blog_tags_desc_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are my blogger writter\n\n{text_input}\n\nSEO blog post ideas:")
-        blog_tags_desc_extraction_chain = LLMChain(llm=self.llm, prompt=blog_tags_desc_promptTemp)
+    def blog_tags_gen(self, blog, language='En', creativity='Original', model_name='Google Palm 2'):
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            blog_tags_desc_prompt = f" Suggest at least 5 tags for the following blog post.\n{blog}"
+            blog_tags_desc_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are my blogger writter\n\n{text_input}\n\nSEO blog post ideas:")
+            
+        elif language == 'Ar':
+            blog_tags_desc_prompt = f"اقترح ما لا يقل عن 5 علامات لمنشور المدونة التالي.\n{blog}"
+            blog_tags_desc_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب مدونتي\n\n{text_input}\n\nأفكار مقالات مدونة محركات البحث:")
+            
+        blog_tags_desc_extraction_chain = LLMChain(llm=llm, prompt=blog_tags_desc_promptTemp)
         blog_tags_desc = blog_tags_desc_extraction_chain.run(blog_tags_desc_prompt)
         
         return blog_tags_desc

calling_apis.py

@@ -0,0 +1,8 @@
+from dotenv import find_dotenv, load_dotenv
+import os
+
+load_dotenv(find_dotenv())
+
+google_api_key = os.environ['GOOGLE_API_KEY']
+openai_api_key = os.environ['OPENAI_API_KEY']
+

email_writer.py

@@ -1,46 +1,191 @@
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
+from langchain.llms import OpenAI
+
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
 
 class email_writing:
+    
+    """
+        A class for generating emails and email marketing campaigns using a language model.
+
+    """
 
-    def __init__(self, llm):
-        self.llm = llm
+    def email_gen(self, recipient:str, recipient_position:str, sender_name:str, position_sender:str, desc:str, language='En', model_name='Google Palm 2', creativity='Original') -> str:
+        
+         """
+        Generates an email based on provided details.
 
-    def email_gen(self, recipient, recipient_position, sender_name, position_sender, desc):
         
-        email_prompt = f"Write a professional and well organized Email on {desc}.\nThe name of the Recipient is {recipient} and the recipient position is {recipient_position}.\nMy Name is {sender_name} and my Position is {position_sender}."
+        Args:
+            recipient (str): Name of the email recipient.
+            recipient_position (str): Position of the email recipient.
+            sender_name (str): Name of the email sender.
+            position_sender (str): Position of the email sender.
+            desc (str): Description or context for the email.
+            language (str): the language of the generated content (optional, default value is 'EN').
+            creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+            model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
             
-        email_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a professional email writer:\n{text_input}\nEmail:")
-    
-        email_extraction_chain = LLMChain(llm=self.llm, prompt=email_promptTemp)
-        email = email_extraction_chain.run(email_prompt)
+
+        Returns:
+            email (str): Generated email content.
+        """
+         
+         temp = 0
+
+         if creativity == 'Original':
+            temp = 0
+         elif creativity == 'Balanced':
+            temp = 0.25
+         elif creativity == 'Creative':
+            temp = 0.5
+         elif creativity == 'Spirited':
+            temp = 0.75
+         elif creativity == 'Visionary':
+            temp = 1
+
+
+         if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+         elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+         elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+         if language == 'En':
+            email_prompt = f"Write a professional and well organized Email on {desc}.\nThe name of the Recipient is {recipient} and the recipient position is {recipient_position}.\nMy Name is {sender_name} and my Position is {position_sender}."
+            email_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a professional email writer:\n{text_input}\nEmail:")
+        
+         elif language == 'Ar':
+            email_prompt = f"اكتب بريدًا إلكترونيًا احترافيًا ومنظمًا حول {desc}.\nاسم المستلم هو {recipient} وموقع المستلم هو {recipient_position}.\nاسمي هو {sender_name} وموقعي هو {position_sender}."
+            email_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب بريد إلكتروني محترف:\n{text_input}\nالبريد الإلكتروني:")
+
+         email_extraction_chain = LLMChain(llm=llm, prompt=email_promptTemp)
+         email = email_extraction_chain.run(email_prompt)
         
-        return email
+         return email
 
-    def email_subject_gen(self, email):
+    def email_subject_gen(self, email:str, language='En', model_name='Google Palm 2', creativity='Original')->str:
+        
+        """
+        Generates a subject for a given email.
 
-        email_subject_prompt = f"Generate a subject for the following email:\n{email}\n"
+        Args:
+            email (str): Email content for which the subject needs to be generated.
+            language (str): the language of the generated content (optional, default value is 'EN').
+            creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+            model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
             
-        email_subject_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a professional email writer:\n{text_input}\nEmail Subject:")
-    
-        email_subject_extraction_chain = LLMChain(llm=self.llm, prompt=email_subject_promptTemp)
+
+        Returns:
+            email_subject (str): Generated email subject.
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            email_subject_prompt = f"Generate a subject for the following email:\n{email}\n"
+            email_subject_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a professional email writer:\n{text_input}\nEmail Subject:")
+        
+        elif language == 'Ar':
+            email_subject_prompt = f"أنشئ موضوعًا للبريد الإلكتروني التالي:\n{email}\n"
+            email_subject_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب بريد إلكتروني محترف:\n{text_input}\nعنوان البريد الإلكتروني:")
+            
+        email_subject_extraction_chain = LLMChain(llm=llm, prompt=email_subject_promptTemp)
         email_subject = email_subject_extraction_chain.run(email_subject_prompt)
         
         return email_subject
     
-    def email_marketing_campaigns_gen(self, product_name, product_description, target_audience, goal):
-    
-        email_prompt = f"Generate a high-converting email marketing campaign for {product_name}. {product_name} is {product_description}. that is targeted at {target_audience} and has the goal of {goal}. The campaign should include a welcome email, a nurture sequence, and a promotional email."
+    def email_marketing_campaigns_gen(self, product_name:str, product_description:str, target_audience:str, goal:str, language='En', model_name='Google Palm 2', creativity='Original')->str:
+        
+        """
+        Generates a subject for a given email.
+
+        Args:
+            product_name (str): Name of the product.
+            product_description (str): Description of the product.
+            target_audience (str): Targeted audience for the campaign.
+            goal (str): Goal of the Campaign.
+            language (str): the language of the generated content (optional, default value is 'EN').
+
+        Returns:
+            email (str): Generated emails marketing campaigns.
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
             
-        email_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a Professional Email Marketing Copywriter:\n{text_input}\nEmail Marketing Campaign:")
-    
-        email_extraction_chain = LLMChain(llm=self.llm, prompt=email_promptTemp)
+            email_prompt = f"Generate a high-converting email marketing campaign for {product_name}. {product_name} is {product_description}. that is targeted at {target_audience} and has the goal of {goal}. The campaign should include a welcome email, a nurture sequence, and a promotional email."
+            email_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a Professional Email Marketing Copywriter:\n{text_input}\nEmail Marketing Campaign:")
+        
+        elif language == 'Ar':
+            
+            email_prompt = f"أنشئ حملة تسويق بريد إلكتروني فعّالة لـ {product_name}. {product_name} هو {product_description}. مستهدفة لـ {target_audience} ولها هدف {goal}. يجب أن تتضمن الحملة رسالة ترحيب، سلسلة تغذية، ورسالة ترويجية."
+            email_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب نصوص تسويق البريد الإلكتروني المحترف:\n{text_input}\nحملة تسويق البريد الإلكتروني:")
+        
+        email_extraction_chain = LLMChain(llm=llm, prompt=email_promptTemp)
         email = email_extraction_chain.run(email_prompt)
         
         return email

idea_generation.py

@@ -1,8 +1,14 @@
+import re
+from typing import List
+
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
-import re
+from langchain.llms import OpenAI
 
-def ideas_generator(topic, keywords, llm, tone_of_voice='Professional', num_of_ideas=3):
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
+
+def ideas_generator(topic : str, keywords : str, tone_of_voice='Professional', num_of_ideas=3, language = 'En', creativity='Original', model_name='Google Palm 2') -> str:
     
     '''
     Description:
@@ -18,9 +24,12 @@ def ideas_generator(topic, keywords, llm, tone_of_voice='Professional', num_of_i
     
         topic (str, required): The topic or subject matter of the article for which you want to generate titles.
         keywords (str, required): A list of keywords that should be used to help generate catchy titles relevant to the topic. These keywords can provide context and improve the quality of the titles.
-        llm (langchain.llms object, required): An instance of a pre-trained language model (e.g., GPT-3 or GPT-4) that will be used to generate the titles. This model should be provided by the user.
         num_of_ideas (int, optional): The number of long-form titles to generate. If num is set to 1, the function will produce a single title. If num is greater than 1, it will generate multiple titles. Default is 3.
-        tone_of_voice (str, optional): A String to determine the tone of voice of the title. Default Value Professional
+        tone_of_voice (str, optional): A String to determine the tone of voice of the title. Default Value Professional.
+        language (str): Opitonal Parameter -> The language of the model.
+        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
     '''
     
     '''
@@ -29,16 +38,57 @@ def ideas_generator(topic, keywords, llm, tone_of_voice='Professional', num_of_i
         ideas (str): Functions returns a text with number of ideas numbered with roman numerals   
     '''
     
-    if num_of_ideas == 1:
+    temp = 0
+
+    if creativity == 'Original':
+        temp = 0
+    elif creativity == 'Balanced':
+        temp = 0.25
+    elif creativity == 'Creative':
+        temp = 0.5
+    elif creativity == 'Spirited':
+        temp = 0.75
+    elif creativity == 'Visionary':
+        temp = 1
+
+
+    if model_name == 'Google Palm 2':
+        llm = call_palm(google_api_key, temperature=temp)
+
+    elif model_name == 'GPT-3.5':
+        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+    elif model_name == 'GPT-4':
+        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+    if language == 'En':
         
-            ideas_prompt = f"Generate only 1 {tone_of_voice} and catchy Innovation title for my article about {topic} topic.\n\nuse this keywords to help you generate {tone_of_voice} catchy title: {keywords}."
+        if num_of_ideas == 1:
+
+                ideas_prompt = f"Generate only 1 {tone_of_voice} and catchy Innovation title for my article about {topic} topic.\n\nuse this keywords to help you generate {tone_of_voice} catchy title: {keywords}."
+
+        else:
+                ideas_prompt = f"Generate only {num_of_ideas} {tone_of_voice} and catchy Innovation titles for my article about {topic} topic.\n\nuse this keywords to help you generate {tone_of_voice} catchy titles: {keywords}."
+
+        ideas_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="You are a professional content creator and Title Generator:\n\n{text_input}\n\n:Titles (number them with roman numerals):")
+    
+    elif language == 'Ar':
+        
+        if num_of_ideas == 1:
+        
+            ideas_prompt = f"تولّد عنوان واحد فقط بنبرة {tone_of_voice} وجاذبية لمقالتي حول موضوع {topic}.\n\nاستخدم هذه الكلمات الرئيسية للمساعدة في إنشاء عنوان جذّاب وبنبرة {tone_of_voice}: {keywords}"
+
+        else:
+            
+            ideas_prompt = f"توليد فقط {num_of_ideas} {tone_of_voice} وعناوين جذابة للابتكارات لمقالتي حول موضوع {topic}.\n\nاستخدم هذه الكلمات الرئيسية لمساعدتك في إنشاء عناوين جذابة بنفس {tone_of_voice}: {keywords}."
 
-    else:
-            ideas_prompt = f"Generate only {num_of_ideas} {tone_of_voice} and catchy Innovation titles for my article about {topic} topic.\n\nuse this keywords to help you generate {tone_of_voice} catchy titles: {keywords}."
+        ideas_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="أنت صانع محتوى احترافي ومولّد عناوين\n\n{text_input}\nالعناوين (عدّها باستخدام الأرقام الرومانية):")
 
-    ideas_promptTemp = PromptTemplate(
-    input_variables=["text_input"],
-    template="You are a professional content creator and Title Generator:\n\n{text_input}\n\n:Titles (number them with roman numerals):")
 
     ideas_extraction_chain = LLMChain(llm=llm, prompt=ideas_promptTemp)
     ideas = ideas_extraction_chain.run(ideas_prompt)
@@ -46,7 +96,7 @@ def ideas_generator(topic, keywords, llm, tone_of_voice='Professional', num_of_i
     return ideas
 
 
-def filter_ideas(ideas):
+def filter_ideas(ideas : str) -> List[str]:
     
     '''
     Description:
@@ -70,7 +120,7 @@ def filter_ideas(ideas):
     return filtered_ideas
 
 
-def pick_idea(list_ideas):
+def pick_idea(list_ideas : List[str]) -> str:
     
     """
     Description:
@@ -98,7 +148,7 @@ def pick_idea(list_ideas):
         c = counter+1
         print(f"{c}. {idea}")
         
-    x = int(input("Type the number of the idea: "))
+    x = int(input("\nType the number of the idea: "))
     idea = list_ideas[x-1]
     
     return idea

keywords_generation.py

@@ -1,34 +1,75 @@
+import re
+from typing import List
+
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
-import re
+from langchain.llms import OpenAI
+
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
 
-def keywords_generator(topic, llm, num_keywords=10):
+def keywords_generator(topic : str,num_keywords=10, language='En', creativity='Original', model_name='Google Palm 2') -> str:
     
     '''
     Description: 
     
-        Generates a list of keywords for a given topic using a large language model (LLM).
+        Generates a list of short-tail keywords for a given topic using a large language model (LLM).
     '''
     
     '''
     Parameters:
     
         topic (str): Required Parameter -> The topic for which to generate keywords.
-        llm (langchain.llms object): Required Parameter -> The LLM to use for generating keywords.
         num_keywords (int): Optional Parameter -> The number of keywords to generate. Default Value is 10
-        long_tail_keywords (bool): Optional Parameter -> A boolean flag indicating whether to generate long-tail keywords. Default Value is False
+        language (str): Opitonal Parameter -> The language of the model.
+        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
     '''
     
     '''
     Returns:
         Keywords (str): A Text of list of keywords numbered with roman numerals for the given topic -> str datatype.
     '''
-    
-    keywords_prompt = f"Identify {num_keywords} SEO keywords related to '{topic}'."
+    temp = 0
+
+    if creativity == 'Original':
+        temp = 0
+    elif creativity == 'Balanced':
+        temp = 0.25
+    elif creativity == 'Creative':
+        temp = 0.5
+    elif creativity == 'Spirited':
+        temp = 0.75
+    elif creativity == 'Visionary':
+        temp = 1
+
+
+    if model_name == 'Google Palm 2':
+        llm = call_palm(google_api_key, temperature=temp)
+
+    elif model_name == 'GPT-3.5':
+        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+    elif model_name == 'GPT-4':
+        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+    if language == 'En':
+
+        keywords_prompt = f"Generate {num_keywords} SEO keywords related to '{topic}'."
 
-    keywords_promptTemp = PromptTemplate(
-    input_variables=["text_input"],
-    template="You are a professional content creator and SEO Keywords Generator:\n\n{text_input}\n\nKeywords (number them with roman numerals):")
+        keywords_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="You are a professional content creator and SEO Keywords Generator:\n\n{text_input}\n\nKeywords (number them with roman numerals):")
+
+    elif language == 'Ar':
+
+        keywords_prompt = f"قم بإنشاء {num_keywords} كلمة أساسية SEO متعلقة بـ '{topic}'."
+
+        keywords_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت منشئ محتوى محترف ومولد كلمات أساسية SEO:\n\n{text_input}\n\nالكلمات الأساسية (قم بترقيمها بالأرقام الرومانية):")
 
     keywords_extraction_chain = LLMChain(llm=llm, prompt=keywords_promptTemp)
     keywords = keywords_extraction_chain.run(keywords_prompt)
@@ -36,7 +77,75 @@ def keywords_generator(topic, llm, num_keywords=10):
     return keywords
 
 
-def filter_keywords(keywords):
+def keywords_generator_long_tail(topic : str, num_keywords=10, language='En', creativity='Original', model_name='Google Palm 2') -> str:
+    
+    '''
+    Description: 
+    
+        Generates a list of long-tail keywords for a given topic using a large language model (LLM).
+    '''
+    
+    '''
+    Parameters:
+    
+        topic (str): Required Parameter -> The topic for which to generate keywords.
+        num_keywords (int): Optional Parameter -> The number of keywords to generate. Default Value is 10
+        language (str): Opitonal Parameter -> The language of the model.
+        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
+    '''
+    
+    '''
+    Returns:
+        Keywords (str): A Text of list of keywords numbered with roman numerals for the given topic -> str datatype.
+    '''
+    
+    temp = 0
+
+    if creativity == 'Original':
+        temp = 0
+    elif creativity == 'Balanced':
+        temp = 0.25
+    elif creativity == 'Creative':
+        temp = 0.5
+    elif creativity == 'Spirited':
+        temp = 0.75
+    elif creativity == 'Visionary':
+        temp = 1
+
+
+    if model_name == 'Google Palm 2':
+        llm = call_palm(google_api_key, temperature=temp)
+
+    elif model_name == 'GPT-3.5':
+        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+    elif model_name == 'GPT-4':
+        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+    if language == 'En':
+        
+        keywords_prompt = f"Generate {num_keywords} long-tail SEO keywords related to '{topic}'."
+
+        keywords_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="You are a professional content creator and SEO Keywords Generator:\n\n{text_input}\n\nKeywords (number them with roman numerals):")
+    
+    elif language == 'Ar':
+        
+        keywords_prompt = f"قم بإنشاء {num_keywords} كلمة أساسية SEO طويلة الذيل متعلقة بـ '{topic}'."
+
+        keywords_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="أنت منشئ محتوى محترف ومولد كلمات أساسية SEO:\n\n{text_input}\n\nالكلمات الأساسية (قم بترقيمها بالأرقام الرومانية):")
+
+    keywords_extraction_chain = LLMChain(llm=llm, prompt=keywords_promptTemp)
+    keywords = keywords_extraction_chain.run(keywords_prompt)
+
+    return keywords
+
+def filter_keywords(keywords : str) -> List[str]:
     '''
     Description: 
     
@@ -61,7 +170,7 @@ def filter_keywords(keywords):
     return filtered_keywords
 
 
-def process_keywords(list_keywords):
+def process_keywords(list_keywords : List[str]) -> str:
     
     '''
     Description: 

linkedin_content_creation.py

@@ -0,0 +1,137 @@
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+from langchain.llms import OpenAI
+
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
+
+class linkedIn_content_gen:
+    
+    """
+        A class for generating linkedIn Content.
+
+    """
+        
+
+    def linkedIn_post_gen(self, topic: str, tone_of_voice:str, language='En', model_name='Google Palm 2', creativity='Original') -> str:
+        
+        """
+        Generate an engaging LinkedIn post based on the provided topic and tone of voice.
+
+        Parmaeters:
+            - self: The instance of the class containing this method.
+            - topic (str): The topic for the LinkedIn post.
+            - tone_of_voice (str): The desired tone of voice for the post.
+            - language (str): the language of the generated content (optional, default value is 'EN').
+            - creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+            - model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+            
+
+        Returns:
+        - linkedIn_post (str): The generated LinkedIn post.
+
+        """
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            linkedIn_post_prompt = f"Write an engagging LinkedIn Post on {topic}. The tone should be {tone_of_voice}."
+            linkedIn_post_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a content creator and LinkedIn Posts writer :\n{text_input}\nLinkedIn Post:")
+        
+        elif language == 'Ar':
+            
+            linkedIn_post_prompt = f"اكتب منشورًا جذابًا على LinkedIn حول {topic}. يجب أن يكون النبرة {tone_of_voice}."
+            linkedIn_post_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت مُنشئ محتوى وكاتب لمنشورات LinkedIn :\n{text_input}\nمنشور LinkedIn:")
+
+            
+        linkedIn_post_extraction_chain = LLMChain(llm=llm, prompt=linkedIn_post_promptTemp)
+        linkedIn_post = linkedIn_post_extraction_chain.run(linkedIn_post_prompt)
+
+        return linkedIn_post
+     
+        
+    def linkedIn_ads_gen(self, product_name:str, product_desc:str, target_audience:str, target_keywords:str, language='En', model_name='Google Palm 2', creativity='Original'):
+    
+        """
+        Generates a LinkedIn ad based on the provided product information and target details.
+
+        Args:
+        - product_name (str): The name of the product being advertised.
+        - product_desc (str): A description of the product being advertised.
+        - target_audience (str): The intended audience or demographic for the product.
+        - target_keywords (str): Keywords relevant to the product or its marketing strategy.
+        - language (str): the language of the generated content (optional, default value is 'EN').
+
+        Returns:
+        - linkedIn_ad (str): The generated LinkedIn ad copy based on the provided parameters.
+
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            linkedIn_ads_prompt = f"Generate a LinkedIn ad for {product_name}. {product_name} is {product_desc} that is targeted at {target_audience} and uses the keywords {target_keywords}. The ad should be persuasive and engaging, and it should include a call to action."
+            linkedIn_ads_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a Professional LinkedIn Ad Copywriter:\n{text_input}\nFacebook Ad:")
+        
+        elif language == 'Ar':
+            
+            linkedIn_ads_prompt = f"أنشئ إعلانًا على LinkedIn لـ {product_name}. {product_name} هو {product_desc} المستهدف نحو {target_audience} ويستخدم الكلمات الرئيسية {target_keywords}. يجب أن يكون الإعلان مقنعًا وجذابًا، ويجب أن يتضمن دعوة للعمل."
+            linkedIn_ads_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت كاتب إعلانات محترف على LinkedIn:\n{text_input}\nإعلان على فيسبوك:")
+        
+        linkedIn_ad_extraction_chain = LLMChain(llm=llm, prompt=linkedIn_ads_promptTemp)
+        linkedIn_ad = linkedIn_ad_extraction_chain.run(linkedIn_ads_prompt)
+
+        return linkedIn_ad

meta_content_creation.py

@@ -1,94 +1,292 @@
+from transformers import pipeline
+
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
-from transformers import pipeline
+from langchain.llms import OpenAI
+
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
 
 class meta_content_generation:
+    
+    """
+    Class meta_content_generation:
+    Provides methods to generate content for social media platforms using Language Models (LLMs) and prompt templates.
+    """
+        
+
 
+    def facebook_ads_gen(self, product_name:str, product_description:str, tone_of_voice:str, targeted_audience="", plans_promotions="", language='En', model_name='Google Palm 2', creativity='Original')->str:
         
-    def __init__(self, llm):
-        self.llm = llm
+        """
+        Generates a Facebook ad based on the provided product details and parameters.
 
+        Parameters:
+            - product_name (str): Name of the product for the ad.
+            - product_description (str): Description of the product for the ad.
+            - tone_of_voice (str): Tone of the ad.
+            - targeted_audience (str): Target audience for the ad (optional).
+            - plans_promotions (str): Plans and promotions for the ad (optional).
+
+        Returns:
+            - Generated Facebook ad text.
+        """
+
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
 
-    def facebook_ads_gen(self, product_name, product_description, tone_of_voice, targeted_audience="", plans_promotions=""):
-    
-        if targeted_audience != "" and plans_promotions != "":
-            facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Our Target Audience is {targeted_audience}. Our plans and promotions is {plans_promotions}. Tone of the ad should be {tone_of_voice}"
 
-        elif targeted_audience == "" and plans_promotions != "":
-            facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Our plans and promotions is {plans_promotions}. Tone of the ad should be {tone_of_voice}"
         
-        elif targeted_audience != "" and plans_promotions == "":
-            facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Our Target Audience is {targeted_audience}. Tone of the ad should be{tone_of_voice}."
+        if language == 'En':
+            
+            if targeted_audience != "" and plans_promotions != "":
+                facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Our Target Audience is {targeted_audience}. Our plans and promotions is {plans_promotions}. Tone of the ad should be {tone_of_voice}"
+
+            elif targeted_audience == "" and plans_promotions != "":
+                facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Our plans and promotions is {plans_promotions}. Tone of the ad should be {tone_of_voice}"
+
+            elif targeted_audience != "" and plans_promotions == "":
+                facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Our Target Audience is {targeted_audience}. Tone of the ad should be{tone_of_voice}."
+
+            else:
+                facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Tone of the ad Should be {tone_of_voice}."
         
-        else:
-            facebook_ads_prompt = f"Generate a Facebook ad for {product_name} Product. {product_name} is {product_description}. Tone of the ad Should be {tone_of_voice}."
+        elif language == 'Ar':
+            
+            if targeted_audience != "" and plans_promotions != "":
+                facebook_ads_prompt = f"انشئ إعلانًا على فيسبوك لمنتج {product_name}. {product_name} هو {product_description}. جمهورنا المستهدف هو {targeted_audience}. خططنا وعروضنا هي {plans_promotions}. يجب أن يكون توجه الإعلان {tone_of_voice}."
 
+            elif targeted_audience == "" and plans_promotions != "":
+                facebook_ads_prompt = f"قم بإنشاء إعلان على فيسبوك لـ {product_name} المنتج. {product_name} هو {product_description}. خططنا وعروضنا هي {plans_promotions}. يجب أن يكون تون الإعلان {tone_of_voice}"
+
+            elif targeted_audience != "" and plans_promotions == "":
+                facebook_ads_prompt = f"أنشئ إعلانًا على فيسبوك لمنتج {product_name}. {product_name} هو {product_description}. جمهورنا المستهدف هو {targeted_audience}. يجب أن يكون طابع الإعلان {tone_of_voice}"
+
+            else:
+                facebook_ads_prompt = f"انشئ إعلانًا على فيسبوك لـ {product_name} المنتج. {product_name} هو {product_description}. يجب أن يكون نبرة الإعلان {tone_of_voice}."
+
+                
         facebook_ads_promptTemp = PromptTemplate(
         input_variables=["text_input"],
         template="You are a Professional Facebook Ad Copywriter:\n{text_input}\nFacebook Ad:")
     
-        facebook_ad_extraction_chain = LLMChain(llm=self.llm, prompt=facebook_ads_promptTemp)
+        facebook_ad_extraction_chain = LLMChain(llm=llm, prompt=facebook_ads_promptTemp)
         facebook_ad = facebook_ad_extraction_chain.run(facebook_ads_prompt)
         
         return facebook_ad
     
-    def facbook_camp_gen(self, product_name, product_desc, days, goal):
+    def facbook_camp_gen(self, product_name:str, product_desc:str, days:int, goal:str, language='En', model_name='Google Palm 2', creativity='Original') -> str:
         
+         """
+        Generates a Facebook Campign based on the provided product details and goals.
+
+        Parameters:
+            - product_name (str): Name of the product for the ad.
+            - product_desc (str): Description of the product for the ad.
+            - days (int): Number of campaign days.
+            - goal (str): Goal of the campaign.
+            - language (str): the language of the generated content (optional, default value is 'EN').
+
+        Returns:
+            - Facebook_ad (str): Generated Facebook Campaign .
+        """
+         temp = 0
+
+         if creativity == 'Original':
+            temp = 0
+         elif creativity == 'Balanced':
+            temp = 0.25
+         elif creativity == 'Creative':
+            temp = 0.5
+         elif creativity == 'Spirited':
+            temp = 0.75
+         elif creativity == 'Visionary':
+            temp = 1
+
+
+         if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+         elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+         elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+         if language == 'En':
+            
+            facebook_ads_prompt = f"Generate a {days} days Persuative Facebook campaign (don't mention any budget) calendar for our {product_name}. {product_name} is {product_desc}. with the goal to {goal}."
+            facebook_ads_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="""You are a Professional Facebook Digital Marketer:\n{text_input}\nFacebook Campaign:""")
         
-        facebook_ads_prompt = f"Generate a {days} days Facebook campaign (no budget included) calendar for our {product_name}. {product_name} is {product_desc}. with the goal to {goal}."
-        print(facebook_ads_prompt)
-        facebook_ads_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="""You are a Professional Facebook Digital Marketer:\n{text_input}\nGenerate only the Facebook campaign Calender without any details and don't mention any budgets:\nExample to emulate it:\nWeek 1: Getting Started and Teasers
+         elif language == 'Ar':
+            
+            facebook_ads_prompt = f"قم بإنشاء حملة فايسبوك قائمة لمدة {days} يومًا (دون الإشارة إلى أي ميزانية) لـ {product_name} الخاص بنا. {product_name} هو {product_desc}. بهدف {goal}."
+            facebook_ads_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت مسوّق رقمي محترف على فيسبوك:\n{text_input}\nحملة فيسبوك:")
+        
+         facebook_ad_extraction_chain = LLMChain(llm=llm, prompt=facebook_ads_promptTemp)
+         facebook_ad = facebook_ad_extraction_chain.run(facebook_ads_prompt)
+        
+         return facebook_ad
 
-    Day 1-2: Introduction to FAQGenius, share its features and benefits.
-    Day 3-4: Teaser posts about how FAQGenius can save time and improve customer satisfaction.
-    Day 5-7: User testimonials and success stories with FAQGenius." and so on..
-    """)
-        facebook_ad_extraction_chain = LLMChain(llm=self.llm, prompt=facebook_ads_promptTemp)
-        facebook_ad = facebook_ad_extraction_chain.run(facebook_ads_prompt)
+    def facebook_post_gen(self, tone_of_voice:str, topic:str, language='En', model_name='Google Palm 2', creativity='Original') -> str:
         
-        return facebook_ad
+        """
+        Generates a Facebook Post based on the provided topic.
 
-    def facebook_post_gen(self, tone_of_voice, topic):
-    
-        productDesc_prompt = f"Write an attractive facebook post on {topic}. Tone should be {tone_of_voice}. Post dosen't include any photos or videos."
+        Parameters:
+            - tone_of_voice (str): The tone of the facebook post.
+            - topic (str): The facebook post topic
+            - language (str): the language of the generated content (optional, default value is 'EN').
+
+        Returns:
+            - Facebook_post (str): Generated Facebook Post .
+        """
+        
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
+
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
+
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
             
-        productDesc_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are a professional facebook content creator:\n{text_input}\n\nFacebook Post:")
+            productDesc_prompt = f"Generate an attractive and persuasive facebook post on {topic}. Tone should be {tone_of_voice}. Post dosen't include any photos or videos."
+            productDesc_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are a professional facebook content creator:\n{text_input}\n\nFacebook Post:")
     
-        productDesc_extraction_chain = LLMChain(llm=self.llm, prompt=productDesc_promptTemp)
+        
+        elif language == 'Ar':
+            
+            productDesc_prompt = f"انشر منشورًا جذابًا ومقنعًا على فيسبوك حول {topic}. يجب أن يكون النبرة {tone_of_voice}. لا يتضمن المنشور أي صور أو مقاطع فيديو."
+            productDesc_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت مبدع محترف في إنشاء محتوى على فيسبوك:\n{text_input}\n\nمنشور فيسبوك:")
+
+        productDesc_extraction_chain = LLMChain(llm=llm, prompt=productDesc_promptTemp)
         product_desc = productDesc_extraction_chain.run(productDesc_prompt)
         
         return product_desc
 
-    def img2text(self, url):
+    def img2text(self, url:str) -> str:
+        
+         """
+        Function to extract text from an image using a pre-trained image captioning model.
+
+        Parameters:
+            self: The instance of a class (if this function is part of a class).
+            url (str): The URL pointing to the image for which text extraction is required.
 
-        image_to_text = pipeline("image-to-text", model='Salesforce/blip-image-captioning-base')
+        Returns:
+            out (str): The extracted text from the provided image.
+        """
+            
+         image_to_text = pipeline("image-to-text", model='Salesforce/blip-image-captioning-base')
 
-        text = image_to_text(url)
+         text = image_to_text(url)
 
-        out = text[0]['generated_text']
+         out = text[0]['generated_text']
         
-        return out
+         return out
 
 
-    def generate_InstaCap(self, scenario, tone_of_voice, form):
+    def generate_InstaCap(self, scenario:str, tone_of_voice:str, form:str, language='En', model_name='Google Palm 2', creativity='Original') -> str:
         
-        instaCap_prompt = f"Craft a {form} Caption on my Instagram Image Here is the description of my Instagram Image: {scenario}.\nThe tone should be {tone_of_voice}"
-            
-        instaCap_promptTemp = PromptTemplate(
-        input_variables=["text_input"],
-        template="You are infulencer:\n{text_input}\nInstagram Caption:")
-    
-        instaCap_extraction_chain = LLMChain(llm=self.llm, prompt=instaCap_promptTemp)
-        instaCap = instaCap_extraction_chain.run(instaCap_prompt)
-        
-        return instaCap
+        """
+        Generates a Instagram Caption based on the image description.
+
+        Parameters:
+            - tone_of_voice (str): The tone of the facebook post.
+            - scenario (str): The description of the image
+            - form (str): the form of the caption (short - long) forms
+
+        Returns:
+            - instaCap (str): Generated Image Caption.
+        """
         
-    
-    
+        temp = 0
+
+        if creativity == 'Original':
+            temp = 0
+        elif creativity == 'Balanced':
+            temp = 0.25
+        elif creativity == 'Creative':
+            temp = 0.5
+        elif creativity == 'Spirited':
+            temp = 0.75
+        elif creativity == 'Visionary':
+            temp = 1
+
 
+        if model_name == 'Google Palm 2':
+            llm = call_palm(google_api_key, temperature=temp)
 
+        elif model_name == 'GPT-3.5':
+            llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
 
+        elif model_name == 'GPT-4':
+            llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+        if language == 'En':
+            
+            instaCap_prompt = f"Craft a {form} Caption on my Instagram Image Here is the description of my Instagram Image: {scenario}.\nThe tone should be {tone_of_voice}"
+            instaCap_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="You are infulencer:\n{text_input}\nInstagram Caption:")
+        
+        elif language == 'Ar':
+            
+            instaCap_prompt = f"صياغة توضيح {form} على صورة إنستغرام الخاصة بي. إليك وصف صورة إنستغرامي: {scenario}.يجب أن يكون التون {tone_of_voice}."
+            instaCap_promptTemp = PromptTemplate(
+            input_variables=["text_input"],
+            template="أنت مؤثر: \n{text_input}\n وصف بوست الانستغرام:")
+            
+        instaCap_extraction_chain = LLMChain(llm=llm, prompt=instaCap_promptTemp)
+        instaCap = instaCap_extraction_chain.run(instaCap_prompt)
+        
+        return instaCap
+        

outline_generation.py

@@ -1,10 +1,16 @@
-from langchain.prompts import PromptTemplate
-from langchain.chains import LLMChain
 import re
 from remove_astricks import remove_ast
+from typing import List
 
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+from langchain.llms import OpenAI
 
-def outlines_generator(idea, keywords, llm):
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
+
+
+def outlines_generator(idea : str, keywords : str, language='En', creativity='Original', model_name='Google Palm 2') -> str:
     
     '''
     Description:
@@ -18,7 +24,10 @@ def outlines_generator(idea, keywords, llm):
     
         idea (str): The main idea or topic of the article for which you want to generate an outline.
         keywords (str): A set of keywords or topic-related terms that will be used as section headings in the outline. These headings help organize the content and provide a structure for the article.
-        llm (langchain.llms object): An instance of a pre-trained language model (e.g., Google Palm or llama2) that will be used to generate the article outline.
+        language (str): Opitonal Parameter -> The language of the model.
+        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+        
     '''
     
     '''
@@ -27,41 +36,63 @@ def outlines_generator(idea, keywords, llm):
         outlines (str): The generated outline for the article, including section headings and placeholders for content under each heading.
     '''
     
-    outlines_prompt = f"Generate an table of contents with at least 10 main points for an article on {idea}. Include key points related to {keywords}.\nBe creative and innovation in each main topic"
-            
-    outlines_promptTemp = PromptTemplate(
-    input_variables=["text_input"],
-    template="You are a content creator\n{text_input}\n\nTable of Content (number each main point with roman numerals):")
-   
+    temp = 0
+
+    if creativity == 'Original':
+        temp = 0
+    elif creativity == 'Balanced':
+        temp = 0.25
+    elif creativity == 'Creative':
+        temp = 0.5
+    elif creativity == 'Spirited':
+        temp = 0.75
+    elif creativity == 'Visionary':
+        temp = 1
+
+
+    if model_name == 'Google Palm 2':
+        llm = call_palm(google_api_key, temperature=temp)
+
+    elif model_name == 'GPT-3.5':
+        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+    elif model_name == 'GPT-4':
+        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+    if language == 'En':
+        outlines_prompt = f"Generate an outline with at least 10 main points for an article on {idea}. Include key points related to {keywords}.\nBe creative and innovation in each main topic"
+
+        outlines_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="You are a professional writer\n\n{text_input}\n\nOutline (number each main point with roman numerals):")
+
+    elif language == 'Ar':
+        outlines_prompt = f"قم بتوليد مخطط تفصيلي يحتوي على ما لا يقل عن ١٠ نقاط رئيسية لمقال حول {idea}. وضمّن النقاط الرئيسية المتعلقة بـ {keywords}.\nكن مبدعًا ومبتكرًا في كل موضوع رئيسي."
+
+        outlines_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="أنت كاتب محترف\n\n{text_input}\n\nالخطوط العريضة (عد كل نقطة رئيسية بأرقام رومانية):")
+
     outlines_extraction_chain = LLMChain(llm=llm, prompt=outlines_promptTemp)
     outlines = outlines_extraction_chain.run(outlines_prompt)
     
     return outlines
 
 
-def filtered_outlines(outline):
-    
+def filtered_outlines(outline : str) -> List[str]:
     '''
     Description:
-        This function processes an outline text containing Roman numeral formatted section headers, 
-        splitting the input into sections and filtering out asterisks ('*') within each section. 
-        The resulting output is a list of cleaned outline sections.
-   
+        This function processes an outline text by splitting it into sections based on Roman numeral patterns followed by a dot and space. It then generates a list of formatted sections.
+
     Parameters:
-        outline (str) -> Required: The input outline text containing Roman numeral formatted section headers.
-        
+         `outline` -> Required: (str) The input outline text to be processed.
+
     Return:
-        outline_list (list): A list containing cleaned sections of the input outline, with asterisks removed.
+        `sections`: (list) A list containing sections of the outline formatted with Arabic numerals (1, 2, 3, ...) and concatenated with their corresponding section content.
     '''
-
-    sections = re.split(r'\b[IVXLCDM]+\.\s', outline)[1:]
+    
+    sections = re.split(r'\b[IVXL]+\.\s', outline)[1:]
     sections = [f"{i}. {section}" for i, section in enumerate(sections, start=1)]
 
-    outline_list = []
-
-    for section in sections:
-        cleaned_section = remove_ast(section)
-        outline_list.append(cleaned_section)
-
-    return outline_list
-
+    return sections

product_description_generation.py

@@ -1,7 +1,11 @@
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
+from langchain.llms import OpenAI
 
-def product_description_gen(product_name, product_desc, tone_of_voice, llm):
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
+
+def product_description_gen(product_name:str, product_desc:str, tone_of_voice:str, language='En', model_name = 'Google Palm 2', creativity = 'Original') -> str:
     
     '''
     Description:
@@ -14,19 +18,54 @@ def product_description_gen(product_name, product_desc, tone_of_voice, llm):
         product_name (str) -> Required: The name of the product for which the description is generated.
         product_desc (str) -> Required: A brief description of the product.
         tone_of_voice (str) -> Required: The intended tone of the product description (e.g., professional, friendly, persuasive).
-        llm -> Required: The Long Language Model (LLM) used for generating the description.
+        language (str): Opitonal Parameter -> The language of the model.
+        creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+        model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
     '''
 
     '''
     Return Value:
         product_desc (str): The generated Amazon product description.
     '''
-    productDesc_prompt = f"Write an engagging and {tone_of_voice} Amazon product description of {product_name} Product here is a short description of my product:\n\n{product_desc}\n"
+    
+    temp = 0
+
+    if creativity == 'Original':
+        temp = 0
+    elif creativity == 'Balanced':
+        temp = 0.25
+    elif creativity == 'Creative':
+        temp = 0.5
+    elif creativity == 'Spirited':
+        temp = 0.75
+    elif creativity == 'Visionary':
+        temp = 1
+
+
+    if model_name == 'Google Palm 2':
+        llm = call_palm(google_api_key, temperature=temp)
+
+    elif model_name == 'GPT-3.5':
+        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+    elif model_name == 'GPT-4':
+        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+    if language == 'En':
         
-    productDesc_promptTemp = PromptTemplate(
-    input_variables=["text_input"],
-    template="You are a content creator and product description writer who helps clients to write their product description on amazon:\n{text_input}\nAmazon Product Description:")
-   
+        productDesc_prompt = f"Write an engagging and {tone_of_voice} Amazon product description of {product_name} Product here is a short description of my product:\n\n{product_desc}\n"
+        productDesc_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="You are a content creator and product description writer who helps clients to write their product description on amazon:\n{text_input}\nAmazon Product Description:")
+    
+    elif language == 'Ar':
+        
+        productDesc_prompt = f"اكتب وصفًا جذابًا و{tone_of_voice} عن منتج {product_name} في أمازون. هنا وصف قصير لمنتجي:\n\n{product_desc}\n"
+        productDesc_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="أنت كاتب محتوى وكاتب وصف المنتجات الذي يساعد العملاء في كتابة وصف منتجاتهم على أمازون:\n{text_input}\nوصف منتج أمازون:")
+
     productDesc_extraction_chain = LLMChain(llm=llm, prompt=productDesc_promptTemp)
     product_desc = productDesc_extraction_chain.run(productDesc_prompt)
     

workout_plan_generation.py

@@ -1,25 +1,88 @@
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
+from langchain.llms import OpenAI
 
-def workout_plan_gen(my_goals, fitness_level, days, hours, helth_cosnd, routine, llm):
-    
-    
-    
+from load_model import call_palm
+from calling_apis import google_api_key, openai_api_key
 
-    workout_plan_prompt = f"""Generate a workout plan with diversity and creative exercises.
-Please note the following details:
-* My Goals: I'm looking to {my_goals}
-* Fitness Level: {fitness_level}.
-* Available Equipment: I have access to a gym with various equipment.
-* Time Commitment: I'm dedicated to working out {days} days a week, and I have {hours} hours a day I can spend during each session.
-* Health Considerations: I'm in the {helth_cosnd}.
-* Preferred Routine: I like to follow {routine} routine.\nWorkout Plan:"""
+def workout_plan_gen(my_goals:str, fitness_level:str, days:int, hours:int, helth_cosnd:str, routine:str, language='En', model_name='Google Palm 2', creativity='Original')->str:
+
+    """
+        Generates a Gym Workout Plan based on user's goal, fiteness_level, days and hours avaliable, his routine and health considiration.
+
+        Parameters:
         
-  
+            my_goals (str): Trainee Goal from the Gym Workout.
+            fitness_level (str): Level of the trainee Fitness.
+            days (int): Avaliable Days.
+            hours (int): Avaliable Hours.
+            helth_cosnd (str): Health Considiration.
+            routine (str): Trainee Routine.
+            language (str): the language of the generated content (optional, default value is 'EN').
+            creativity (str): Optional Parameter -> Controling the randomness of the model. Default value is Original
+            model_name (str): Optional Parameter -> select the LLM model. Default Value is Google Palm 2
+            
+
+        Returns:
+            workout_plan (str): Generated Workout Plan.
+    
+    """
+
+    temp = 0
+
+    if creativity == 'Original':
+        temp = 0
+    elif creativity == 'Balanced':
+        temp = 0.25
+    elif creativity == 'Creative':
+        temp = 0.5
+    elif creativity == 'Spirited':
+        temp = 0.75
+    elif creativity == 'Visionary':
+        temp = 1
+
+
+    if model_name == 'Google Palm 2':
+        llm = call_palm(google_api_key, temperature=temp)
 
-    workout_plan_promptTemp = PromptTemplate(
-    input_variables=["text_input"],
-    template="You are a Professional Fitness Trainer:\n{text_input}")
+    elif model_name == 'GPT-3.5':
+        llm = OpenAI(model_name='gpt-3.5-turbo', openai_api_key=openai_api_key, temperature=temp)
+
+    elif model_name == 'GPT-4':
+        llm = OpenAI(model_name='gpt-4', openai_api_key=openai_api_key, temperature=temp)
+
+
+    
+    if language == 'En':
+        
+        workout_plan_prompt = f"""Generate a workout plan with diversity and creative exercises.
+    Please note the following details:
+    * My Goals: I'm looking to {my_goals}
+    * Fitness Level: {fitness_level}.
+    * Available Equipment: I have access to a gym with various equipment.
+    * Time Commitment: I'm dedicated to working out {days} days a week, and I have {hours} hours a day I can spend during each session.
+    * Health Considerations: I'm in the {helth_cosnd}.
+    * Preferred Routine: I like to follow {routine} routine.\nWorkout Plan:"""
+        workout_plan_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="You are a Professional Fitness Trainer:\n{text_input}")
+        
+    elif language == 'Ar':
+        
+        workout_plan_prompt = f"""قم بإنشاء خطة تمارين رياضية متنوعة ومبتكرة.
+يرجى مراعاة التفاصيل التالية:
+* أهدافي: أنا أسعى لـ {my_goals}.
+* مستوى اللياقة: {fitness_level}.
+* المعدات المتاحة: لدي الوصول إلى صالة ألعاب رياضية بها معدات متنوعة.
+* الالتزام الزمني: أنا ملتزم بممارسة التمارين {days} أيام في الأسبوع، ولدي {hours} ساعة يوميًا يمكنني قضائها خلال كل جلسة.
+* اعتبارات الصحة: أنا في حالة {helth_cosnd}.
+* الروتين المفضل: أحب اتباع الروتين {routine}.\nخطة التمارين:"""
+        
+        workout_plan_promptTemp = PromptTemplate(
+        input_variables=["text_input"],
+        template="أنت مدرب لياقة مهني:\n{text_input}")
+        
+        
     workout_plan_extraction_chain = LLMChain(llm=llm, prompt=workout_plan_promptTemp)
     workout_plan = workout_plan_extraction_chain.run(workout_plan_prompt)