Update app.py

app.py

@@ -17,9 +17,11 @@ from huggingface_hub import InferenceClient
 # Bhashini API translation function
 api_key = getenv('API_KEY')
 user_id = getenv('USER_ID')
-
-def bhashini_translate(text: str, from_code: str = "en", to_code: str = "te") -> dict:
+def bhashini_translate(text: str, from_code: str = "en", to_code: str = "hi") -> dict:
     """Translates text from source language to target language using the Bhashini API."""
+    print(f'Starting translation process from {from_code} to {to_code}...')
+    gr.Warning(f'Translating to {to_code}...')
+    
     url = 'https://meity-auth.ulcacontrib.org/ulca/apis/v0/model/getModelsPipeline'
     headers = {
         "Content-Type": "application/json",
@@ -30,14 +32,21 @@ def bhashini_translate(text: str, from_code: str = "en", to_code: str = "te") ->
         "pipelineTasks": [{"taskType": "translation", "config": {"language": {"sourceLanguage": from_code, "targetLanguage": to_code}}}],
         "pipelineRequestConfig": {"pipelineId": "64392f96daac500b55c543cd"}
     }
+    
+    print('Sending initial request to get the pipeline...')
     response = requests.post(url, json=payload, headers=headers)
     
     if response.status_code != 200:
+        print(f'Error in initial request: {response.status_code}')
         return {"status_code": response.status_code, "message": "Error in translation request", "translated_content": None}
 
+    print('Initial request successful, processing response...')
     response_data = response.json()
     service_id = response_data["pipelineResponseConfig"][0]["config"][0]["serviceId"]
     callback_url = response_data["pipelineInferenceAPIEndPoint"]["callbackUrl"]
+    
+    print(f'Service ID: {service_id}, Callback URL: {callback_url}')
+    
     headers2 = {
         "Content-Type": "application/json",
         response_data["pipelineInferenceAPIEndPoint"]["inferenceApiKey"]["name"]: response_data["pipelineInferenceAPIEndPoint"]["inferenceApiKey"]["value"]
@@ -47,13 +56,18 @@ def bhashini_translate(text: str, from_code: str = "en", to_code: str = "te") ->
         "inputData": {"input": [{"source": text}], "audio": [{"audioContent": None}]}
     }
     
+    print(f'Sending translation request with text: "{text}"')
     compute_response = requests.post(callback_url, json=compute_payload, headers=headers2)
+    
     if compute_response.status_code != 200:
+        print(f'Error in translation request: {compute_response.status_code}')
         return {"status_code": compute_response.status_code, "message": "Error in translation", "translated_content": None}
     
+    print('Translation request successful, processing translation...')
     compute_response_data = compute_response.json()
     translated_content = compute_response_data["pipelineResponse"][0]["output"][0]["target"]
     
+    print(f'Translation successful. Translated content: "{translated_content}"')
     return {"status_code": 200, "message": "Translation successful", "translated_content": translated_content}