Update app.py

app.py

@@ -18,11 +18,11 @@ QUESTIONS_MODEL = "tiiuae/falcon-rw-1b"
 KEYWORDS_MODEL = "google/flan-t5-small"
 
 # Function to get LangChain LLM
-def get_llm(model_id):
+def get_llm(model_id, task):
     return HuggingFaceHub(
         repo_id=model_id,
         model_kwargs={"temperature": 0.5, "max_new_tokens": 150},
-        task="text2text-generation",
+        task=task,  # Changed to a generic task for text generation
         huggingfacehub_api_token=HUGGINGFACE_API_TOKEN
     )
 
@@ -40,17 +40,17 @@ if st.button("Run Multi-LLM Analysis"):
 
             # Step 1: Summary
             summary_prompt = f"Provide a short summary about: {topic}"
-            summary_model = get_llm(SUMMARY_MODEL)
+            summary_model = get_llm(SUMMARY_MODEL, task="text-generation")  # Corrected task
             summary = summary_model.predict(summary_prompt)
 
             # Step 2: Research Questions
             questions_prompt = f"Give three research questions about: {topic}"
-            questions_model = get_llm(QUESTIONS_MODEL)
+            questions_model = get_llm(QUESTIONS_MODEL, task="text-generation")  # Corrected task
             questions = questions_model.predict(questions_prompt)
 
             # Step 3: Keywords
             keywords_prompt = f"List five keywords related to: {topic}"
-            keywords_model = get_llm(KEYWORDS_MODEL)
+            keywords_model = get_llm(KEYWORDS_MODEL, task="text-generation")  # Corrected task
             keywords = keywords_model.predict(keywords_prompt)
 
         # Display results