Update app.py

app.py

@@ -8,15 +8,15 @@ from langchain.chains import LLMChain
 
 api_key = os.environ['openai_api_key']
 
-def get_insurance_heading(data):
+def get_insurance_heading(data,insurance_prompt):
 
     llm = OpenAI(temperature=0,openai_api_key=api_key)
 
-    prompt_template = """this is article content and my user is insurance industry now give me user specific or we can personalize heading hook line for article, which can include something related to the industry with respect to the content and need only article heading nothing else
+    # prompt_template = """this is article content and my user is insurance industry now give me user specific or we can personalize heading hook line for article, which can include something related to the industry with respect to the content and need only article heading nothing else
 
-    article content: {text} """
+    # article content: {text} """
     PROMPT = PromptTemplate(
-        template=prompt_template, input_variables=["text"]
+        template=insurance_prompt, input_variables=["text"]
     )
     chain = LLMChain(llm=llm, prompt=PROMPT)
     resp = chain.run(text=data)
@@ -24,15 +24,15 @@ def get_insurance_heading(data):
     return resp
 
 
-def get_sports_heading(data):
+def get_sports_heading(data,sports_prompt):
 
     llm = OpenAI(temperature=0,openai_api_key=api_key)
 
-    prompt_template = """this is article content and my user is sports industry now give me user specific or we can personalize heading hook line for article, which can include something related to the industry with respect to the content and need only article heading nothing else
+    # prompt_template = """this is article content and my user is sports industry now give me user specific or we can personalize heading hook line for article, which can include something related to the industry with respect to the content and need only article heading nothing else
 
-    article content: {text} """
+    # article content: {text} """
     PROMPT = PromptTemplate(
-        template=prompt_template, input_variables=["text"]
+        template=sports_prompt, input_variables=["text"]
     )
     chain = LLMChain(llm=llm, prompt=PROMPT)
     resp = chain.run(text=data)
@@ -40,9 +40,9 @@ def get_sports_heading(data):
     return resp
 
 
-def process_article_content(content):
+def process_article_content(content,insurance_prompt,sports_prompt):
 
-    return get_insurance_heading(content), get_sports_heading(content)
+    return get_insurance_heading(content,insurance_prompt), get_sports_heading(content,sports_prompt)
 
 # Streamlit app
 def main():
@@ -50,12 +50,16 @@ def main():
 
     # Input field for article content
     article_content = st.text_area("Enter Article Content:", "")
+    insurance_prompt = st.text_area("insurance prompt", "")
+    sports_prompt = st.text_area("sports prompt", "")
+    
+
 
     # Process button
     if st.button("Process"):
         # Process the article content
         if article_content:
-            insurance_user, sports_user = process_article_content(article_content)
+            insurance_user, sports_user = process_article_content(article_content,insurance_prompt,sports_prompt)
 
             # Display the output
             st.subheader("Processed Output:")