create

app.py

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+import gradio as gr
+import random
+
+text_to_text_gm130b = gr.Blocks.load(name="spaces/THUDM/GLM-130B")
+
+def block_inference(prompt):
+  #thudm glm 130 b space 
+  generated_text = text_to_text_gm130b(model_input=prompt, seed=1234, out_seq_length=256, min_gen_length=0, sampling_strategy='BeamSearchStrategy', num_beams=2, length_penalty=1, no_repeat_ngram_size=3, temperature=0.7, topk=1, topp=0)
+  return generated_text
+  
+def chat(message, history):
+  history = history or []
+  message = message.lower()
+  response = block_inference(message)
+  #if message.startswith("how many"):
+  #    response = random.randint(1, 10)
+  #elif message.startswith("how"):
+  #    response = random.choice(["Great", "Good", "Okay", "Bad"])
+  #elif message.startswith("where"):
+  #    response = random.choice(["Here", "There", "Somewhere"])
+  #else:
+  #    response = "I don't know"
+  history.append((message, response))
+  return history, history
+
+chatbot = gr.Chatbot().style(color_map=("green", "pink"))
+demo = gr.Interface(
+    chat,
+    ["text", "state"],
+    [chatbot, "state"],
+    allow_flagging="never",
+)
+if __name__ == "__main__":
+    demo.launch()