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Browse files- pages/🦙_Alpaca.py +0 -201
pages/🦙_Alpaca.py
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##### `🦙_Alpaca.py`
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##### Alpaca Model
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##### https://github.com/seemanne/llamacpypy
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##### https://github.com/shaunabanana/llama.py
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##### https://github.com/thomasantony/llamacpp-python
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##### https://github.com/abetlen/llama-cpp-python
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##### Please reach out to [email protected] for any questions
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#### Loading needed Python libraries
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import streamlit as st
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#from llamacpypy import Llama
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#import llamacpp
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from llama_cpp import Llama
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import os
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import subprocess
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import sys
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#### Streamlit initial setup
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st.set_page_config(
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page_title = "🦙 Alpaca",
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page_icon = "images/Logo.png",
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layout = "centered",
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initial_sidebar_state = "expanded"
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)
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#### Functions of the Python Wrapper
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def llama_stream(
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prompt = '',
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skip_prompt = True,
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trim_prompt = 0,
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executable = 'pages/llama.cpp/main',
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model = 'models/7B/ggml-model-q4_0.bin',
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threads = 4,
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temperature = 0.7,
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top_k = 40,
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top_p = 0.5,
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repeat_last_n = 256,
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repeat_penalty = 1.17647,
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n = 4096,
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interactive = False,
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reverse_prompt = "User:"
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):
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command = [
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executable,
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'-m', model,
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'-t', str(threads),
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'--temp', str(temperature),
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'--top_k', str(top_k),
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'--top_p', str(top_p),
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'--repeat_last_n', str(repeat_last_n),
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'--repeat_penalty', str(repeat_penalty),
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'-n', str(n),
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'-p', prompt
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]
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if interactive:
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command += ['-i', '-r', reverse_prompt]
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process = subprocess.Popen(
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command,
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stdin = subprocess.PIPE,
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stdout = subprocess.PIPE,
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stderr = subprocess.PIPE,
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)
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token = b''
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generated = ''
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while True:
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token += process.stdout.read(1)
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if token: # neither empty string nor None
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try:
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decoded = token.decode('utf-8')
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trimmed_prompt = prompt
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if trim_prompt > 0:
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trimmed_prompt = prompt[:-trim_prompt]
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prompt_finished = generated.startswith(trimmed_prompt)
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reverse_prompt_encountered = generated.endswith(reverse_prompt)
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if not skip_prompt or prompt_finished:
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yield decoded
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if interactive and prompt_finished and reverse_prompt_encountered:
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user_input = input()
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process.stdin.write(user_input.encode('utf-8') + b'\n')
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process.stdin.flush()
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generated += decoded
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token = b''
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except UnicodeDecodeError:
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continue
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elif process.poll() is not None:
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return
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def llama(
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prompt = '',
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stream = False,
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skip_prompt = False,
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trim_prompt = 0,
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executable = 'pages/llama.cpp/main',
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model = 'models/7B/ggml-model-q4_0.bin',
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threads = 4,
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temperature = 0.7,
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top_k = 40,
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top_p = 0.5,
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repeat_last_n = 256,
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repeat_penalty = 1.17647,
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n = 4096,
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interactive = False,
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reverse_prompt = "User:"
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):
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streamer = llama_stream(
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prompt = prompt,
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skip_prompt = skip_prompt,
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trim_prompt = trim_prompt,
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executable = executable,
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model = model,
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threads = threads,
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temperature = temperature,
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top_k = top_k,
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top_p = top_p,
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repeat_last_n = repeat_last_n,
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repeat_penalty = repeat_penalty,
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n = n,
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interactive = interactive,
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reverse_prompt = reverse_prompt
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)
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if stream:
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return streamer
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else:
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return ''.join(list(streamer))
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### Python Wrapper (functions above)
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#text = []
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#for token in llama(prompt = 'What is your purpose?', repeat_penalty = 1.05, skip_prompt = False, interactive = False):
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# print(token, end = '', flush = True)
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# text.append(token)
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#st.subheader('Debug')
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#st.experimental_show(text[0])
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#st.experimental_show(text[1])
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#st.subheader('Answer')
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#st.write(''.join(text))
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### llamacpypy
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#llama = Llama(model_name = 'models/7B/ggml-model-q4_0.bin', warm_start = True)
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#llama.load_model()
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#var = llama.generate("This is the weather report, we are reporting a clown fiesta happening at backer street. The clowns ")
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#st.write(var)
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### llamacpp
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#model_path = "./models/7B/ggml-model-q4_0.bin"
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#params = llamacpp.gpt_params(model_path, 4096, 40, 0.1, 0.7, 2.0)
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#model = llamacpp.PyLLAMA(model_path, params)
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#text = model.predict("Hello, I'm a llama.", 10)
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#st.write(text)
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#params = llamacpp.gpt_params('./models/7B/ggml-model-q4_0.bin', # model,
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# 512, # ctx_size
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# 100, # n_predict
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# 40, # top_k
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# 0.95, # top_p
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# 0.85, # temp
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# 1.30, # repeat_penalty
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# -1, # seed
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# 8, # threads
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# 64, # repeat_last_n
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# 8, # batch_size
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#)
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#model = llamacpp.PyLLAMA(params)
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#model.add_bos() # Adds "beginning of string" token
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#model.update_input("A llama is a")
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#model.print_startup_stats()
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#model.prepare_context()
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#model.ingest_all_pending_input(True)
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#while not model.is_finished():
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# text, is_finished = model.infer_text()
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# print(text, end="")
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# if is_finished:
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# break
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# Flush stdout
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#sys.stdout.flush()
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#model.print_end_stats()
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### Llama cpp
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llm = Llama(model_path = "xfh/alpaca.cpp_65b_ggml")
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output = llm("Q: Name the planets in the solar system? A: ", max_tokens = 32, stop = ["Q:", "\n"], echo = True)
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st.write(output)
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