updated

app.py

@@ -8,6 +8,10 @@ import os
 # Load environment variables from .env file
 load_dotenv()
 
+# Ensure API key is loaded correctly
+api_key = os.getenv("HUGGINGFACE_API_KEY")
+print(f"Hugging Face API Key: {api_key}")
+
 async def process_csv(file):
     print("Reading CSV file...")
     df = pd.read_csv(file, header=None)  # Read the CSV file without a header
@@ -35,6 +39,7 @@ async def process_csv(file):
     df['predictions'] = results
     df.columns = df.columns.astype(str)  # Convert column names to strings to avoid warnings
     print("Results assigned to DataFrame successfully.")
+    print(df.head())  # Print first few rows of the DataFrame to verify
     return df
 
 st.title("Finance Model Deployment")

llama_models.py

@@ -1,5 +1,5 @@
 import os
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM  # Ensure correct model class
 import aiohttp
 
 HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
@@ -11,7 +11,7 @@ def load_model(model_name):
     if not tokenizer or not model:
         print("Loading model and tokenizer...")
         tokenizer = AutoTokenizer.from_pretrained(model_name)
-        model = AutoModelForCausalLM.from_pretrained(model_name)
+        model = AutoModelForSeq2SeqLM.from_pretrained(model_name)  # Ensure correct model class
         print("Model and tokenizer loaded successfully.")
     return tokenizer, model