Update app.py

app.py

@@ -1,7 +1,7 @@
+import streamlit as st
 from langchain.llms import CTransformers
 from langchain.chains import LLMChain
 from langchain import PromptTemplate
-import streamlit as st 
 import os
 from docx import Document
 from docx.shared import Inches
@@ -9,21 +9,17 @@ import io
 from PIL import Image
 import requests
 
-#Loading the model
-def load_llm(max_tokens, prompt_template):
+# Loading the model
+def load_llm(max_tokens, prompt_template, temperature):
     # Load the locally downloaded model here
     llm = CTransformers(
-        model = "llama-2-7b-chat.ggmlv3.q8_0.bin",
+        model="llama-2-7b-chat.ggmlv3.q8_0.bin",
         model_type="llama",
-        max_new_tokens = max_tokens,
-        temperature = 0.7
+        max_new_tokens=max_tokens,
+        temperature=temperature,
     )
-    
-    llm_chain = LLMChain(
-        llm=llm,
-        prompt=PromptTemplate.from_template(prompt_template)
-    )
-    print(llm_chain)
+
+    llm_chain = LLMChain(llm=llm, prompt=PromptTemplate.from_template(prompt_template))
     return llm_chain
 
 def get_src_original_url(query):
@@ -75,54 +71,51 @@ st.set_page_config(layout="wide")
 def main():
     st.title("GeniusWords: Unleash Your Imagination")
 
+    prompt_template = st.text_area("Please enter the prompt template:")
+    max_tokens = st.number_input("Please enter the maximum tokens:", min_value=1, value=800)
+    temperature = st.slider("Select the temperature:", min_value=0.1, max_value=1.0, value=0.7, step=0.1)
     user_input = st.text_input("Please enter the idea/topic for the article you want to generate!")
-
     image_input = st.text_input("Please enter the topic for the image you want to fetch!")
 
-    if len(user_input) > 0 and len(image_input) > 0:
-
-        col1, col2, col3 = st.columns([1,2,1])
-
-        with col1:
-            st.subheader("Generated Content")
-            st.write("Topic of the article is: " + user_input)
-            st.write("Image of the article is: " + image_input)
-            prompt_template = """You are a digital marketing and SEO expert and your task is to write article so write an article on the given topic: {user_input}. The article must be under 800 words. The article should be be lengthy.               
-            """
-            llm_call = load_llm(max_tokens=800, prompt_template=prompt_template)
-            print(llm_call)
-            result = llm_call(user_input)
-            if len(result) > 0:
-                st.info("Your article has been been generated successfully!")
-                st.write(result)
-            else:
-                st.error("Your article couldn't be generated!")
-
-        with col2:
-            st.subheader("Fetched Image")
-            image_url = get_src_original_url(image_input)
-            st.image(image_url)
-
-        with col3:
-            st.subheader("Final Article to Download")
-            #image_input = "temp_image.jpg"
-            image_response=requests.get(image_url)
-            img=Image.open(io.BytesIO(image_response.content))
-            doc = create_word_docx(user_input, result['text'], img)
-
-            # Save the Word document to a BytesIO buffer
-            doc_buffer = io.BytesIO()
-            doc.save(doc_buffer)
-            doc_buffer.seek(0)
-
-            # Prepare the download link
-            st.download_button(
-                label='Download Word Document',
-                data=doc_buffer,
-                file_name='document.docx',
-                mime='application/vnd.openxmlformats-officedocument.wordprocessingml.document'
-            )
-
+    if st.button("Generate Article"):
+        if len(user_input) > 0 and len(image_input) > 0 and len(prompt_template) > 0:
+            col1, col2, col3 = st.columns([1, 2, 1])
+            with col1:
+                st.subheader("Generated Content")
+                st.write("Topic of the article is: " + user_input)
+                st.write("Image of the article is: " + image_input)
+
+                llm_call = load_llm(max_tokens=max_tokens, prompt_template=prompt_template, temperature=temperature)
+                result = llm_call(user_input)
+                if len(result) > 0:
+                    st.info("Your article has been generated successfully!")
+                    st.write(result)
+                else:
+                    st.error("Your article couldn't be generated!")
+
+            with col2:
+                st.subheader("Fetched Image")
+                image_url = get_src_original_url(image_input)
+                st.image(image_url)
+
+            with col3:
+                st.subheader("Final Article to Download")
+                image_response = requests.get(image_url)
+                img = Image.open(io.BytesIO(image_response.content))
+                doc = create_word_docx(user_input, result['text'], img)
+
+                # Save the Word document to a BytesIO buffer
+                doc_buffer = io.BytesIO()
+                doc.save(doc_buffer)
+                doc_buffer.seek(0)
+
+                # Prepare the download link
+                st.download_button(
+                    label='Download Word Document',
+                    data=doc_buffer,
+                    file_name='document.docx',
+                    mime='application/vnd.openxmlformats-officedocument.wordprocessingml.document'
+                )
 
 if __name__ == "__main__":
-    main()
+    main()