Update app.py

app.py

@@ -1,30 +1,18 @@
 import os
-import streamlit as st
 import networkx as nx
 import matplotlib.pyplot as plt
-from groq import Groq
-from langchain.prompts import PromptTemplate
+from langchain.llms import ChatGroq
 from langchain.chains import LLMChain
-from langchain.llms import OpenAI
+from langchain.prompts import PromptTemplate
+import gradio as gr
 
-# Set up Groq API
-api_key = st.secrets["GROQ_API_KEY"]
-os.environ['GROQ_API_KEY'] = api_key
-client = Groq()
+# Set up the ChatGroq API
+api_key = os.environ.get("GROQ_API_KEY")
+if not api_key:
+    raise ValueError("Please set the GROQ_API_KEY environment variable")
 
-def generate_response(prompt, context, max_tokens=1000):
-    messages = [
-        {"role": "system", "content": "You are a helpful coding assistant, specialized in code completion, debugging, and analysis. Provide concise and accurate responses."},
-        {"role": "user", "content": f"Context: {context}\n\nTask: {prompt}"}
-    ]
-    
-    chat_completion = client.chat.completions.create(
-        messages=messages,
-        model="llama2-70b-4096",
-        max_tokens=max_tokens
-    )
-    
-    return chat_completion.choices[0].message.content
+# Initialize the ChatGroq LLM
+llm = ChatGroq(temperature=0, model_name='llama-3.1-8b-instant', groq_api_key=api_key)
 
 # Define a prompt template for entity extraction
 entity_extraction_prompt = PromptTemplate(
@@ -33,12 +21,11 @@ entity_extraction_prompt = PromptTemplate(
 )
 
 # Create an LLMChain for entity extraction
-llm = OpenAI(temperature=0)
 entity_chain = LLMChain(llm=llm, prompt=entity_extraction_prompt)
 
 def create_knowledge_graph(text):
     # Extract entities and relationships
-    result = generate_response(entity_extraction_prompt.format(text=text), context="Entity extraction for knowledge graph")
+    result = entity_chain.run(text)
 
     # Parse the result and create a graph
     G = nx.Graph()
@@ -70,31 +57,32 @@ def visualize_graph(G):
     plt.tight_layout()
     return plt
 
-# Streamlit app
-def main():
-    st.title("Knowledge Graph Generator")
-    
-    text = st.text_area("Enter the text for analysis:", height=200)
-    
-    if st.button("Generate Knowledge Graph"):
-        if text:
-            with st.spinner("Generating knowledge graph..."):
-                knowledge_graph = create_knowledge_graph(text)
-                st.success("Knowledge graph generated!")
-                
-                st.subheader("Visualization")
-                fig = visualize_graph(knowledge_graph)
-                st.pyplot(fig)
-        else:
-            st.warning("Please enter some text for analysis.")
+def generate_knowledge_graph(text):
+    if text:
+        knowledge_graph = create_knowledge_graph(text)
+        fig = visualize_graph(knowledge_graph)
+        return fig
+    else:
+        return None
 
-    # Footer
-    st.markdown("""
-    <style>
+# Gradio interface
+iface = gr.Interface(
+    fn=generate_knowledge_graph,
+    inputs=gr.Textbox(lines=10, placeholder="Enter your text here..."),
+    outputs=gr.Plot(),
+    title="Knowledge Graph Generator",
+    description="Enter text to generate a knowledge graph.",
+    theme="default",
+    css="""
     footer {
         margin-top: 20px;
         text-align: center;
         color: #bb86fc;
+        position: fixed;
+        bottom: 0;
+        width: 100%;
+        background-color: white;
+        padding: 10px 0;
     }
     footer a {
         color: #bb86fc !important;
@@ -103,17 +91,12 @@ def main():
     footer a:hover {
         text-decoration: underline;
     }
-    </style>
-    """, unsafe_allow_html=True)
-
-    footer_text = """
-    <footer>
-        <p>If you enjoyed the functionality of the app, please leave a like!<br>
-        Check out more on <a href="https://www.linkedin.com/in/girish-wangikar/" target="_blank">LinkedIn</a> |
-        <a href="https://girishwangikar.github.io/Girish_Wangikar_Portfolio.github.io/" target="_blank">Portfolio</a></p>
-    </footer>
     """
-    st.markdown(footer_text, unsafe_allow_html=True)
+)
 
-if __name__ == "__main__":
-    main()
+# Custom footer
+footer_html = """
+<footer>
+    <p>If you enjoyed the functionality of the app, please leave a like!<br>
+    Check out more on <a href="https://www.linkedin.com/in/girish-wangikar/" target="_blank">LinkedIn</a> |
+    <a href="https://girishwangikar.github.io/Girish_Wangikar_Portfolio.github.io/" target="_blank">Portfolio</a></p>