Model Changed

app.py

@@ -1,74 +1,83 @@
-import streamlit as st
-from langchain.prompts import PromptTemplate
-from langchain.chains import LLMChain
-from langchain_community.llms import HuggingFaceHub
-from huggingface_hub import login
-from dotenv import load_dotenv
-import os
-
-load_dotenv()
-
-# Authenticate with Hugging Face Hub
-hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
-login(hf_token)
-
-# Initialize LLM using HuggingFaceHub
-llm = HuggingFaceHub(
-    repo_id="caffsean/t5-base-finetuned-keyword-to-text-generation",
-    model_kwargs={
-        "temperature": 0.7,  # Adjust for creativity
-        "max_length": 512,  # Adjust for desired output length
-    }
-)
-
-# Define a function to generate responses
-def get_blog_response(keywords: str, no_words: str, blog_style: str) -> str:
-    # Define a prompt template
-    template = "Generate a blog for {blog_style} job profile based on the keywords '{keywords}' within {no_words} words."
-    prompt = PromptTemplate(
-        input_variables=["keywords", "no_words", "blog_style"],
-        template=template
-    )
-    
-    # Use LangChain LLMChain for structured interaction
-    chain = LLMChain(llm=llm, prompt=prompt)
-    response = chain.run(keywords=keywords, no_words=no_words, blog_style=blog_style)
-    return response
-
-# Streamlit UI
-st.set_page_config(
-    page_title="Blog Generation Using LangChain and Hugging Face",
-    layout="centered",
-    initial_sidebar_state="collapsed"
-)
-
-st.header("Blog Generation App :earth_americas:")
-
-st.write("This app uses LangChain and a fine-tuned T5 model for generating blogs. Please provide your inputs below:")
-
-# Input fields
-keywords = st.text_input("Enter the Blog Keywords")
-
-col1, col2 = st.columns([5, 5])
-with col1:
-    no_words = st.text_input("Number of Words")
-with col2:
-    blog_style = st.selectbox(
-        "Writing the blog for",
-        ["Researchers", "Engineers", "Doctors", "Content Creators", "Sportsman", "Businessman", "Common People"],
-        index=0
-    )
-
-submit = st.button("Generate Blog")
-
-# Generate response
-if submit:
-    if keywords and no_words.isdigit() and int(no_words) > 0:
-        try:
-            st.write("Generating blog...")
-            response = get_blog_response(keywords, no_words, blog_style)
-            st.markdown(f"### Generated Blog:\n\n{response}")
-        except Exception as e:
-            st.error(f"An error occurred: {e}")
-    else:
-        st.warning("Please provide valid inputs for all fields.")
+import streamlit as st
+import google.generativeai as genai
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+
+st.set_page_config(
+    page_title="Blog Generation Using Google Gemini",
+    layout="centered",
+    initial_sidebar_state="collapsed"
+)
+
+# Configure the Google Gemini API
+api_key = os.getenv("GOOGLE_API_KEY")
+genai.configure(api_key=api_key)
+
+# Function to list available models
+def list_available_models():
+    try:
+        models = genai.list_models()
+        return [model.name for model in models if "generateContent" in model.supported_generation_methods]
+    except Exception as e:
+        st.error(f"Error listing models: {e}")
+        return []
+
+# Generate blog content using Gemini
+def generate_blog(keywords, no_words, blog_style):
+    try:
+        available_models = list_available_models()
+        
+        if not available_models:
+            return "Unable to retrieve available models. Please check your API key and network connection."
+        
+        # Select the first available generative model
+        model_name = available_models[6]
+        model = genai.GenerativeModel(model_name)
+        
+        prompt = f"Generate a blog for {blog_style} job profile based on the keywords '{keywords}' within {no_words} words."
+        
+        response = model.generate_content(prompt)
+        return response.text
+    except Exception as e:
+        return f"Error generating content: {e}"
+
+
+
+st.header("Blog Generation App :earth_americas:")
+st.write("This app uses Google's Gemini AI for generating blogs. Please provide your inputs below:")
+
+# Input fields
+keywords = st.text_input("Enter the Blog Keywords")
+col1, col2 = st.columns([5, 5])
+with col1:
+    no_words = st.text_input("Number of Words")
+with col2:
+    blog_style = st.selectbox(
+        "Writing the blog for",
+        ["Researchers", "Engineers", "Doctors", "Content Creators", "Sportsman", "Businessman", "Common People"],
+        index=0
+    )
+
+# Display available models
+# if st.checkbox("Show available models"):
+#     models = list_available_models()
+#     if models:
+#         st.write("Available models:")
+#         for model in models:
+#             st.write(f"- {model}")
+#     else:
+#         st.write("No models available or unable to retrieve models.")
+
+submit = st.button("Generate Blog")
+
+# Generate response
+if submit:
+    if keywords and no_words.isdigit() and int(no_words) > 0:
+        st.write("Generating blog...")
+        response = generate_blog(keywords, no_words, blog_style)
+        st.markdown(f"### Generated Blog:\n\n{response}")
+    else:
+        st.warning("Please provide valid inputs for all fields.")