Create app.py

app.py

@@ -0,0 +1,55 @@
+import gradio as gr
+import os
+os.system('CMAKE_ARGS="-DLLAMA_OPENBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python')
+import wget
+from llama_cpp import Llama
+import random
+url = 'https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGML/resolve/main/WizardLM-7B-uncensored.ggmlv3.q2_K.bin'
+filename = wget.download(url)
+llm2 = Llama(model_path=filename, seed=random.randint(1, 2**31))
+filename = wget.download(url)
+theme = gr.themes.Soft(
+    primary_hue=gr.themes.Color("#ededed", "#fee2e2", "#fecaca", "#fca5a5", "#f87171", "#ef4444", "#dc2626", "#b91c1c", "#991b1b", "#7f1d1d", "#6c1e1e"),
+    neutral_hue="red",
+)
+title = """<h1 align="center">Chat with awesome WizardLM 7b model!</h1><br>"""
+with gr.Blocks(theme=theme) as demo:
+    gr.HTML(title)
+    gr.HTML("This model is awesome for its size! It is only 20th the size of Chatgpt but is around 90% as good as Chatgpt. However, please don't rely on WizardLM to provide 100% true information as it might be wrong sometimes. ")
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox()
+    clear = gr.ClearButton([msg, chatbot])
+    #instruction = gr.Textbox(label="Instruction", placeholder=)
+
+    def user(user_message, history):
+        return gr.update(value="", interactive=True), history + [[user_message, None]]
+
+    def bot(history):
+        #instruction = history[-1][1] or ""
+        user_message = history[-1][0]
+        #token1 = llm.tokenize(b"### Instruction: ")
+        #token2 = llm.tokenize(instruction.encode())
+        #token3 = llm2.tokenize(b"USER: ")
+        tokens3 = llm2.tokenize(user_message.encode())
+        token4 = llm2.tokenize(b"\n\n### Response:")
+        tokens = tokens3 + token4
+        history[-1][1] = ""
+        count = 0
+        output = ""
+        for token in llm2.generate(tokens, top_k=50, top_p=0.73, temp=0.72, repeat_penalty=1.1):
+            text = llm2.detokenize([token])
+            output += text.decode()
+            count += 1
+            if count >= 500 or (token == llm2.token_eos()):
+                break
+            history[-1][1] += text.decode()
+            yield history
+
+    response = msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+        bot, chatbot, chatbot
+    )
+    response.then(lambda: gr.update(interactive=True), None, [msg], queue=False)
+    gr.HTML("Thanks for checking out this app!")
+
+demo.queue()
+demo.launch(debug=True)