Create app.py

app.py

@@ -0,0 +1,79 @@
+import gradio as gr
+import requests
+import os 
+import json
+
+API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
+headers = {"Authorization": f"Bearer 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"}
+
+def translate(prompt_ , from_lang, to_lang, input_prompt = "translate this", seed = 42):
+    
+
+    prompt =  f"To say \"{prompt_}\" in {to_lang}, you would say " 
+    print(prompt)
+    if len(prompt) == 0:
+        prompt = input_prompt 
+
+    json_ = {
+            "inputs": prompt,
+            "parameters": {
+                            "top_p": 0.9,
+                            "top_k": 100,
+                            "temperature": 1.1,
+                            "max_new_tokens": 250,
+                            "return_full_text": True,
+                            "do_sample": True,
+                            "num_beams": 3,
+                            "seed": seed,
+                            "early_stopping": False,
+                            "length_penalty": 0.0,
+                            "eos_token_id": None,
+                            "repetition_penalty": 3.0,
+                          }, 
+          "options": {
+              "use_cache": True,
+              "wait_for_model": True,
+                     },
+        }
+    response = requests.post(API_URL,  json=json_, headers=headers)
+    print(f"Response  is : {response}")
+    output = response.json()
+    print(f"output is : {output}") 
+    #output = json.loads(response.content.decode("utf-8"))
+    output_tmp = output[0]['generated_text']
+    print(f"output_tmp is: {output_tmp}")
+    
+    solution = output_tmp.split(f"\n{to_lang}:")[0]  
+
+
+    if '\n\n' in solution:
+        final_solution = solution.split("\n\n")[0] 
+    else:
+        final_solution = solution
+        
+    return final_solution
+
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown("<h1><center>Bloom Translation</center></h1>")
+
+    with gr.Row():
+        from_lang = gr.Dropdown(['English', 'Spanish', 'Hindi' , 'Bangla'], 
+                                value='English', 
+                                label='select From language : ')
+        to_lang = gr.Dropdown(['English', 'Spanish', 'Hindi'], 
+                              value='Hindi', 
+                              label= 'select to Language : ')
+
+    input_prompt = gr.Textbox(label="Enter the sentence : ", 
+                            value=f"Instruction: ... \ninput: \"from sentence\" \n{to_lang} :",
+                            lines=6)
+
+    generated_txt = gr.Textbox(lines=3)
+
+    b1 = gr.Button("translate")
+    b1.click(translate,inputs=[ input_prompt, from_lang, to_lang], outputs=generated_txt) 
+    
+demo.launch(enable_queue=True, debug=True)
+