Update app.py

app.py

@@ -5,15 +5,17 @@ import torch
 from langgraph.graph import StateGraph, START, END
 from langchain.schema import HumanMessage
 from langchain_groq import ChatGroq
-from langsmith import traceable  # ✅ Added LangSmith for Debugging
+from langsmith import traceable
 from typing import TypedDict
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from google.colab import userdata  # Only needed in Google Colab
 
-# ✅ Load API keys from Hugging Face Secrets
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")  
-LANGSMITH_API_KEY = os.getenv("LANGSMITH_API_KEY")
+# ✅ Load API keys from Google Colab secrets
+GROQ_API_KEY = userdata.get('GROQ_API_KEY')  # Ensure this is set in Colab
+LANGSMITH_API_KEY = userdata.get('LANGSMITH_API_KEY')
 
-# ✅ Set LangSmith Debugging
+# ✅ Set environment variables
+os.environ["GROQ_API_KEY"] = GROQ_API_KEY
 os.environ["LANGCHAIN_TRACING_V2"] = "true"
 os.environ["LANGCHAIN_API_KEY"] = LANGSMITH_API_KEY
 
@@ -32,18 +34,18 @@ class State(TypedDict):
     language: str
 
 # ✅ Function to generate multiple blog titles using Groq
-@traceable(name="Generate Titles")  # ✅ Debugging with LangSmith
+@traceable(name="Generate Titles")
 def generate_titles(data):
     topic = data.get("topic", "")
-    prompt = f"Generate three short and catchy blog titles for the topic: {topic}. Each title should be under 10 words. Separate them with new lines."
+    prompt = f"Generate **three short and catchy blog titles** for the topic: {topic}. Each title should be under 10 words. Separate them with new lines."
     
     response = llm([HumanMessage(content=prompt)])
-    titles = response.content.strip().split("\n")  
+    titles = response.content.strip().split("\n")  # Get three titles as a list
     
-    return {"titles": titles, "selected_title": titles[0]}  
+    return {"titles": titles, "selected_title": titles[0]}  # Default to first title
 
 # ✅ Function to generate blog content with tone using Groq
-@traceable(name="Generate Content")  # ✅ Debugging with LangSmith
+@traceable(name="Generate Content")
 def generate_content(data):
     title = data.get("selected_title", "")
     tone = data.get("tone", "Neutral")
@@ -53,7 +55,7 @@ def generate_content(data):
     return {"content": response.content.strip()}
 
 # ✅ Function to generate summary using Groq
-@traceable(name="Generate Summary")  # ✅ Debugging with LangSmith
+@traceable(name="Generate Summary")
 def generate_summary(data):
     content = data.get("content", "")
     prompt = f"Summarize this blog post in a short and engaging way: {content}"
@@ -63,7 +65,7 @@ def generate_summary(data):
 
 # ✅ Load translation model (NLLB-200)
 def load_translation_model():
-    model_name = "facebook/nllb-200-distilled-1.3B"
+    model_name = "facebook/nllb-200-distilled-600M"  # Efficient model for 200+ languages
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
     return tokenizer, model
@@ -80,19 +82,19 @@ language_codes = {
 }
 
 # ✅ Function to translate blog content using NLLB-200
-@traceable(name="Translate Content")  # ✅ Debugging with LangSmith
+@traceable(name="Translate Content")
 def translate_content(data):
     content = data.get("content", "")
     language = data.get("language", "English")
 
     if language == "English":
-        return {"translated_content": content}
+        return {"translated_content": content}  # No translation needed
 
-    tgt_lang = language_codes.get(language, "eng_Latn")  
+    tgt_lang = language_codes.get(language, "eng_Latn")  # Default to English if not found
 
     # ✅ Split content into smaller chunks (Avoids token limit issues)
-    max_length = 512  
-    sentences = content.split(". ")  
+    max_length = 512  # Adjust based on model limitations
+    sentences = content.split(". ")  # Split at sentence level
     chunks = []
     current_chunk = ""
 
@@ -114,6 +116,7 @@ def translate_content(data):
         translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
         translated_chunks.append(translated_text.strip())
 
+    # ✅ Combine all translated chunks into final text
     full_translation = " ".join(translated_chunks)
 
     return {"translated_content": full_translation}
@@ -127,42 +130,28 @@ def make_blog_generation_graph():
     graph_workflow.add_node("title_generation", generate_titles)
     graph_workflow.add_node("content_generation", generate_content)
     graph_workflow.add_node("summary_generation", generate_summary)
-    graph_workflow.add_node("translation", translate_content)  
+    graph_workflow.add_node("translation", translate_content)  # Ensures only blog content is translated
 
     # Define Execution Order
     graph_workflow.add_edge(START, "title_generation")
     graph_workflow.add_edge("title_generation", "content_generation")
-    graph_workflow.add_edge("content_generation", "summary_generation")
-    graph_workflow.add_edge("content_generation", "translation")
+    graph_workflow.add_edge("content_generation", "summary_generation")  # Summary only generated from content
+    graph_workflow.add_edge("content_generation", "translation")  # Translation happens for content only
     graph_workflow.add_edge("summary_generation", END)
     graph_workflow.add_edge("translation", END)
 
     return graph_workflow.compile()
 
-# ✅ Function to generate blog content (Fixed)
-def generate_blog(topic, tone, language):
-    try:
-        if not topic:
-            return "⚠️ Please enter a topic.", "", "", "", ""
-
-        blog_agent = make_blog_generation_graph()
-        result = blog_agent.invoke({"topic": topic, "tone": tone, "language": language})
-
-        return result["titles"], result["selected_title"], result["content"], result["summary"], result["translated_content"]
-
-    except Exception as e:
-        error_message = f"⚠️ Error: {str(e)}\n{traceback.format_exc()}"
-        return error_message, "", "", "", ""
-
-# ✅ Gradio UI
+# ✅ Gradio Interface with "Why Translate?" Section
 with gr.Blocks() as app:
     gr.Markdown(
         """
         ### 🌍 Why Translate?  
-        - 🗣️ **Multilingual Support**  
-        - 🌎 **Expand Reach**  
-        - ✅ **Better Understanding**  
-        - 🤖 **AI-Powered Accuracy**  
+        We provide translation to make the blog content **accessible to a global audience**.  
+        - 🗣️ **Multilingual Support** – Read blogs in your preferred language.  
+        - 🌎 **Expand Reach** – Reach international readers.  
+        - ✅ **Better Understanding** – Enjoy content in a language you're comfortable with.  
+        - 🤖 **AI-Powered Accuracy** – Uses advanced AI models for precise translation.  
         """
     )
 
@@ -174,13 +163,14 @@ with gr.Blocks() as app:
             gr.Dropdown(["English", "Hindi", "Telugu", "Spanish", "French"], label="Translate Blog To", value="English"),
         ],
         outputs=[
-            gr.Textbox(label="Suggested Blog Titles"),
+            gr.Textbox(label="Suggested Blog Titles (Choose One)"),  # Displays multiple title suggestions
             gr.Textbox(label="Selected Blog Title"),
             gr.Textbox(label="Generated Blog Content"),
             gr.Textbox(label="Blog Summary"),
             gr.Textbox(label="Translated Blog Content"),
         ],
-        title="🚀 AI-Powered Blog Generator",
+        title="🚀 AI-Powered Blog Generator with Multi-Title Suggestions",
+        description="Generate high-quality blogs using Groq AI, customize tone, translate using NLLB-200, and get interactive summaries. Select from multiple title suggestions!",
     )
 
 # ✅ Launch the Gradio App