chatbot code to summarize and give insight

app.py

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+import os
+import torch
+from huggingface_hub import InferenceClient
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from langchain_core.prompts import PromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+
+# Load HF_TOKEN securely 
+hf_token = os.getenv("HF_TOKEN") 
+
+# Set up the Hugging Face Inference Client with the Bearer token
+client = InferenceClient(api_key=f"Bearer {hf_token}")
+
+# Model paths and IDs
+model_id = "mistralai/Mistral-7B-Instruct-v0.3"
+bart_model_path = "ChijoTheDatascientist/summarization-model"
+
+# Load BART model for summarization
+device = torch.device('cpu')
+bart_tokenizer = AutoTokenizer.from_pretrained(bart_model_path)
+bart_model = AutoModelForSeq2SeqLM.from_pretrained(bart_model_path).to(device)
+
+@st.cache_data
+def summarize_review(review_text):
+    inputs = bart_tokenizer(review_text, max_length=1024, truncation=True, return_tensors="pt")
+    summary_ids = bart_model.generate(inputs["input_ids"], max_length=40, min_length=10, length_penalty=2.0, num_beams=8, early_stopping=True)
+    summary = bart_tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+def generate_response(system_message, user_input, chat_history, max_new_tokens=128):
+    try:
+        # Prepare the messages for the Hugging Face Inference API
+        messages = [{"role": "user", "content": user_input}]
+        
+        # Call the Inference API
+        completion = client.chat.completions.create(
+            model=model_id, 
+            messages=messages, 
+            max_tokens=max_new_tokens,
+        )
+
+        # Get the response from the API
+        response = completion.choices[0].message["content"]
+        return response
+
+    except Exception as e:
+        return f"Error generating response: {e}"
+
+# Streamlit app configuration
+st.set_page_config(page_title="Insight Snap & Summarizer")
+st.title("Insight Snap & Summarizer")
+
+st.markdown("""
+- Use specific keywords in your queries to get targeted responses:
+    - **"summarize"**: To summarize customer reviews.
+    - **"Feedback or insights"**: Get actionable business insights based on feedback.
+""")
+
+# Initialize session state for chat history
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+
+# Chat interface
+user_input = st.text_area("Enter customer reviews or a question:")
+
+if st.button("Submit"):
+    if user_input:
+        # Summarize if the query is feedback-related
+        if "summarize" in user_input.lower():
+            summary = summarize_review(user_input)
+            st.markdown(f"**Summary:** \n{summary}")
+        elif "insight" in user_input.lower() or "feedback" in user_input.lower():
+            system_message = (
+                "You are a helpful assistant providing actionable insights "
+                "from customer feedback to help businesses improve their services."
+            )
+            # Use the last summarized text if available
+            last_summary = st.session_state.get("last_summary", "")
+            query_input = last_summary if last_summary else user_input
+            response = generate_response(system_message, query_input, st.session_state.chat_history)
+            
+            if response:
+                # Update chat history
+                st.session_state.chat_history.append({"role": "user", "content": user_input})
+                st.session_state.chat_history.append({"role": "assistant", "content": response})
+                st.markdown(f"**Insight:** \n{response}")
+            else:
+                st.warning("No response generated. Please try again later.")
+        else:
+            st.warning("Please specify if you want to 'summarize' or get 'insights'.")
+
+        # Store the last summary for insights
+        if "summarize" in user_input.lower():
+            st.session_state["last_summary"] = summary
+    else:
+        st.warning("Please enter customer reviews or ask for insights.")
+
+