Upload 2 files

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+import copy
+import time
+import ctypes #to run on C api directly 
+import llama_cpp
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download #load from huggingfaces 
+
+
+llm = Llama(model_path= hf_hub_download(repo_id="TheBloke/Llama-2-70B-GGML", filename="llama-2-70b.ggmlv3.q4_K_M.bin"), n_ctx=2048) #download model from hf/ n_ctx=2048 for high ccontext length
+
+history = []
+
+pre_prompt = " The user and the AI are having a conversation : <|endoftext|> \n "
+
+def generate_text(input_text, history):
+    print("history ",history)
+    print("input ", input_text)
+    temp =""
+    if history == []:
+        input_text_with_history = f"SYSTEM:{pre_prompt}"+ "\n" + f"USER: {input_text} " + "\n" +" ASSISTANT:"
+    else:
+        input_text_with_history = f"{history[-1][1]}"+ "\n"
+        input_text_with_history += f"USER: {input_text}" + "\n" +" ASSISTANT:"
+    print("new input", input_text_with_history)
+    output = llm(input_text_with_history, max_tokens=1024, stop=["<|prompter|>", "<|endoftext|>", "<|endoftext|> \n","ASSISTANT:","USER:","SYSTEM:"], stream=True)
+    for out in output:
+     stream = copy.deepcopy(out)
+     print(stream["choices"][0]["text"])
+     temp += stream["choices"][0]["text"]
+     yield temp
+
+
+    history =["init",input_text_with_history]
+        
+
+
+demo = gr.ChatInterface(generate_text,
+    title="LLM on CPU",
+    description="Running LLM with https://github.com/abetlen/llama-cpp-python. btw the text streaming thing was the hardest thing to impliment",
+    examples=["Hello", "Am I cool?", "Are tomatoes vegetables?"],
+    cache_examples=True,
+    retry_btn=None,
+    undo_btn="Delete Previous",
+    clear_btn="Clear",)
+demo.queue(concurrency_count=1, max_size=5)
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+llama-cpp-python
+huggingface_hub
+gradio_client