Update app.py

app.py

@@ -1,5 +1,56 @@
+from transformers import GPTNeoForCausalLM, GPT2Tokenizer
 import gradio as gr
 
-demo = gr.load("RAIJAY/7B_QA_68348", src="models")
+model = PeftModel.from_pretrained("RAIJAY/7B_QA_68348")
+tokenizer = AutoTokenizer.from_pretrained("RAIJAY/7B_QA_68348")
 
-demo.launch()
+prompt = """This is a discussion between a person and Hassan Kane, an entrepreneur. 
+person: What are you working on?
+Hassan: This new AI community building the future of Africa
+person: Where are you?
+Hassan: In Lagos for a week, then Paris or London.
+person: How's it going? 
+Hassan: Not bad.. Just trying to hit EV (escape velocity) with my startup
+person: """
+
+def my_split(s, seps):
+    res = [s]
+    for sep in seps:
+        s, res = res, []
+        for seq in s:
+            res += seq.split(sep)
+    return res
+
+# input = "Who are you?"
+def chat_base(input):
+  p = prompt + input
+  input_ids = tokenizer(p, return_tensors="pt").input_ids
+  gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.7, max_length=150,)
+  gen_text = tokenizer.batch_decode(gen_tokens)[0]
+  # print(gen_text)
+  result = gen_text[len(p):]   
+  # print(">", result)
+  result = my_split(result, [']', '\n'])[1]
+  # print(">>", result)
+  if "Hassan: " in result:
+   result = result.split("Hassan: ")[-1]
+# print(">>>", result)
+  return result
+  
+import gradio as gr
+
+def chat(message):
+    history = gr.get_state() or []
+    print(history)
+    response = chat_base(message)
+    history.append((message, response))
+    gr.set_state(history)
+    html = "<div class='chatbot'>"
+    for user_msg, resp_msg in history:
+        html += f"<div class='user_msg'>{user_msg}</div>"
+        html += f"<div class='resp_msg'>{resp_msg}</div>"
+    html += "</div>"
+    return response
+
+iface = gr.Interface(chat_base, gr.inputs.Textbox(label="Ask Hassan a Question"), "text", allow_screenshot=False, allow_flagging=False)
+iface.launch()