Update app.py

app.py

@@ -38,30 +38,30 @@ class StopOnTokens(StoppingCriteria):
         return False
 
 def getProductDetails(history, image):
-    product_description=getImageDescription(image)
-    clients = InferenceClient("google/gemma-7b")
-    rand_val = random.randint(1, 1111111111111111)
+    # product_description=getImageDescription(image)
+    # clients = InferenceClient("google/gemma-7b")
+    # rand_val = random.randint(1, 1111111111111111)
     if not history:
         history = []
-    generate_kwargs = dict(
-        temperature=temp,
-        max_new_tokens=tokens,
-        top_p=top_p,
-        repetition_penalty=rep_p,
-        do_sample=True,
-        seed=seed,
-    )
-    system_prompt="you're a helpful e-commerce marketting assitant"
-    prompt="Write me a poem"
-    formatted_prompt = self.format_prompt(f"{system_prompt}, {prompt}", history)
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=stream_output, details=True, return_full_text=False)
-    output = ""
+    # generate_kwargs = dict(
+    #     temperature=temp,
+    #     max_new_tokens=tokens,
+    #     top_p=top_p,
+    #     repetition_penalty=rep_p,
+    #     do_sample=True,
+    #     seed=seed,
+    # )
+    # system_prompt="you're a helpful e-commerce marketting assitant"
+    # prompt="Write me a poem"
+    # formatted_prompt = self.format_prompt(f"{system_prompt}, {prompt}", history)
+    # stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=stream_output, details=True, return_full_text=False)
+    # output = ""
     
-    for response in stream:
-        output += response.token.text
-        yield [(prompt, output)]
-    gr.Info('Gemma:' + output)
-    history.append((prompt, output))
+    # for response in stream:
+    #     output += response.token.text
+    #     yield [(prompt, output)]
+    # gr.Info('Gemma:' + output)
+    # history.append((prompt, output))
     yield history
 
 @torch.no_grad()