add text summarization.py

src/apps/pages/programs/ApiPrograms/text_summarization.py

@@ -0,0 +1,71 @@
+import os
+import streamlit as st
+from langchain_groq import ChatGroq
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import JsonOutputParser
+import json
+
+# Function to check if the Groq API key exists
+def API_Exists():
+    if "GROQ_API_KEY" in st.secrets["api_key"] and st.secrets["api_key"]["GROQ_API_KEY"]:
+        return True
+    elif "GROQ_API_KEY" in os.environ and os.environ["GROQ_API_KEY"]:
+        return True
+    return False
+
+# Streamlit app
+def text_summarization():
+    st.title("Text Summarization using Groq")
+    st.markdown("Enter text to generate a concise summary using the Groq LLM.")
+
+    # Check if API key exists
+    if not API_Exists():
+        st.error("Groq API key is missing. Please add it to Streamlit secrets or environment variables.")
+        return
+
+    # Retrieve the API key
+    GROQ_API_KEY = st.secrets["api_key"].get("GROQ_API_KEY", os.environ.get("GROQ_API_KEY"))
+
+    # Initialize the Groq LLM
+    llm = ChatGroq(
+        model_name="llama-3.3-70b-versatile",
+        api_key=GROQ_API_KEY,
+        temperature=0.7
+    )
+
+    # Define the summarization prompt
+    summarization_prompt = ChatPromptTemplate.from_messages([
+        ("system", """Summarize the given text into a concise and coherent paragraph.
+        Return the summary in the following JSON format:
+        {{
+            "summary": "your summary here"
+        }}
+        """),
+        ("user", "{input}")
+    ])
+
+    # Define a JSON output parser
+    parser = JsonOutputParser(pydantic_object={
+        "type": "object",
+        "properties": {
+            "summary": {"type": "string"}
+        }
+    })
+
+    # Create the summarization chain
+    chain = summarization_prompt | llm | parser
+
+    # Input text for summarization
+    input_text = st.text_area("Enter Text to Summarize", placeholder="Paste your text here...")
+
+    if st.button("Generate Summary"):
+        if not input_text.strip():
+            st.warning("Please enter some text to summarize.")
+        else:
+            try:
+                # Summarize the text
+                result = chain.invoke({"input": input_text})
+                st.success("Summary Generated!")
+                st.json(result)
+            except Exception as e:
+                st.error(f"Error during summarization: {e}")