Update app.py

app.py

@@ -5,13 +5,18 @@ 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 typing import TypedDict
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
 # ✅ Load API keys from Hugging Face Secrets
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")  # Hugging Face Environment Variable
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")  
 LANGSMITH_API_KEY = os.getenv("LANGSMITH_API_KEY")
 
+# ✅ Set LangSmith Debugging
+os.environ["LANGCHAIN_TRACING_V2"] = "true"
+os.environ["LANGCHAIN_API_KEY"] = LANGSMITH_API_KEY
+
 # ✅ Initialize Groq LLM (for content generation)
 llm = ChatGroq(groq_api_key=GROQ_API_KEY, model_name="mixtral-8x7b-32768")
 
@@ -27,16 +32,18 @@ class State(TypedDict):
     language: str
 
 # ✅ Function to generate multiple blog titles using Groq
+@traceable(name="Generate Titles")  # ✅ Debugging with LangSmith
 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."
     
     response = llm([HumanMessage(content=prompt)])
-    titles = response.content.strip().split("\n")  # Get three titles as a list
+    titles = response.content.strip().split("\n")  
     
-    return {"titles": titles, "selected_title": titles[0]}  # Default to first title
+    return {"titles": titles, "selected_title": titles[0]}  
 
 # ✅ Function to generate blog content with tone using Groq
+@traceable(name="Generate Content")  # ✅ Debugging with LangSmith
 def generate_content(data):
     title = data.get("selected_title", "")
     tone = data.get("tone", "Neutral")
@@ -46,6 +53,7 @@ def generate_content(data):
     return {"content": response.content.strip()}
 
 # ✅ Function to generate summary using Groq
+@traceable(name="Generate Summary")  # ✅ Debugging with LangSmith
 def generate_summary(data):
     content = data.get("content", "")
     prompt = f"Summarize this blog post in a short and engaging way: {content}"
@@ -55,7 +63,7 @@ def generate_summary(data):
 
 # ✅ Load translation model (NLLB-200)
 def load_translation_model():
-    model_name = "facebook/nllb-200-distilled-600M"  # Efficient model for 200+ languages
+    model_name = "facebook/nllb-200-distilled-600M"
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
     return tokenizer, model
@@ -72,18 +80,19 @@ language_codes = {
 }
 
 # ✅ Function to translate blog content using NLLB-200
+@traceable(name="Translate Content")  # ✅ Debugging with LangSmith
 def translate_content(data):
     content = data.get("content", "")
     language = data.get("language", "English")
 
     if language == "English":
-        return {"translated_content": content}  # No translation needed
+        return {"translated_content": content}
 
-    tgt_lang = language_codes.get(language, "eng_Latn")  # Default to English if not found
+    tgt_lang = language_codes.get(language, "eng_Latn")  
 
     # ✅ Split content into smaller chunks (Avoids token limit issues)
-    max_length = 512  # Adjust based on model limitations
-    sentences = content.split(". ")  # Split at sentence level
+    max_length = 512  
+    sentences = content.split(". ")  
     chunks = []
     current_chunk = ""
 
@@ -105,7 +114,6 @@ 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}
@@ -119,19 +127,19 @@ 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)  # Ensures only blog content is translated
+    graph_workflow.add_node("translation", translate_content)  
 
     # 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")  # Summary only generated from content
-    graph_workflow.add_edge("content_generation", "translation")  # Translation happens for content only
+    graph_workflow.add_edge("content_generation", "summary_generation")
+    graph_workflow.add_edge("content_generation", "translation")
     graph_workflow.add_edge("summary_generation", END)
     graph_workflow.add_edge("translation", END)
 
     return graph_workflow.compile()
 
-# ✅ Function to generate blog content (Missing function added)
+# ✅ Function to generate blog content (Fixed)
 def generate_blog(topic, tone, language):
     try:
         if not topic:
@@ -146,16 +154,15 @@ def generate_blog(topic, tone, language):
         error_message = f"⚠️ Error: {str(e)}\n{traceback.format_exc()}"
         return error_message, "", "", "", ""
 
-# ✅ Gradio Interface with "Why Translate?" Section
+# ✅ Gradio UI
 with gr.Blocks() as app:
     gr.Markdown(
         """
         ### 🌍 Why Translate?  
-        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.  
+        - 🗣️ **Multilingual Support**  
+        - 🌎 **Expand Reach**  
+        - ✅ **Better Understanding**  
+        - 🤖 **AI-Powered Accuracy**  
         """
     )
 
@@ -167,14 +174,13 @@ 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 (Choose One)"),  # Displays multiple title suggestions
+            gr.Textbox(label="Suggested Blog Titles"),
             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 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!",
+        title="🚀 AI-Powered Blog Generator",
     )
 
 # ✅ Launch the Gradio App