Logging rows

app.py

@@ -3,6 +3,8 @@ from jinja2 import Template
 import openai
 import os
 import json
+from datasets import load_dataset, Dataset, DatasetDict
+import pandas as pd
 API_ENDPOINT = "https://txl0ptjvttfogwt9.us-east-1.aws.endpoints.huggingface.cloud/v1/"
 API_KEY = "NA"
 HF_TOKEN=os.getenv("HF_TOKEN")
@@ -16,7 +18,6 @@ def llama_guard_classify(conv_prefix, response):
         api_key=LLAMA_API_KEY
     )
     conv = conv_prefix
-    print(conv)
     conv.append(response)
     output = client.chat.completions.create(
         model=model_name,
@@ -69,25 +70,27 @@ Now, please output the following as a JSON object:
         return 'unsafe'
 
 def add_to_dataset(safe_text,unsafe_text,conv_prefix, response,llama_resp,collinear_resp):
-    dataset = load_dataset("collinear-ai/collinear-guard-demo-ds",token=HF_TOKEN)
+    dataset = load_dataset("collinear-ai/collinear-guard-demo")
     new_row = {'safe_text':safe_text,
-        'unsafe_text':unsafe_text,
-    'conv_prefix':conv_prefix,
-    'response':response,
-    'llama_resp':llama_resp,
-    'collinear_resp':collinear_resp
-    }
+            'unsafe_text':unsafe_text,
+            'conv_prefix':conv_prefix,
+            'response':response,
+            'llama_resp':{"output":llama_resp},
+            'collinear_resp':collinear_resp
+        }
     train_dataset = dataset['train']
 
     df = train_dataset.to_pandas()
-    df = df.append(new_row, ignore_index=True)
+    df2 = pd.DataFrame([new_row])
+    df = pd.concat([df, df2],ignore_index=True)
 
     new_train_dataset = Dataset.from_pandas(df)
 
     updated_dataset = DatasetDict({
-        'train': new_train_dataset
+            'train': new_train_dataset
     })
-    updated_dataset.push_to_hub("collinear-ai/collinear-guard-demo-ds", token=HF_TOKEN)
+    updated_dataset.push_to_hub("collinear-ai/collinear-guard-demo",token=HF_TOKEN)
+
 
 
 def process_inputs(safe_text,unsafe_text,conv_prefix, response_content):
@@ -95,6 +98,7 @@ def process_inputs(safe_text,unsafe_text,conv_prefix, response_content):
     conv_prefix = json.loads(conv_prefix)
     output = classify_prompt(safe_text,unsafe_text,conv_prefix, response)
     llama_output = llama_guard_classify(conv_prefix, response)
+    add_to_dataset(safe_text,unsafe_text,conv_prefix,response_content,llama_output,output)
     return output,llama_output
 
 with gr.Blocks() as demo: