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app.py

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+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import time
+import gradio as gr
+
+model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-xl")
+tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-xl")
+
+
+
+
+prompt=''' Review the Following text as a human, who is tasked to Extract `Code Snippets` ,if any. If there are no Code Snippets in the below Text then return No CODE HIDDEN:
+
+"{}"
+'''
+def reply(message, history):
+    m=message.replace('\n','')
+    m=m.replace('\t','')
+    inputs = tokenizer(prompt.format(m), return_tensors="pt")
+    outputs = model.generate(**inputs)
+    code=tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    for i in range(len(code)):
+        time.sleep(0.3)
+        yield  code[: i+1]
+
+gr.ChatInterface(slow_echo).queue().launch()

requirements.txt

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+transformers
+time
+gradio