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Update app.py
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app.py
CHANGED
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import streamlit as st
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import requests
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import asyncio
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import time
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from ast import literal_eval
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import urllib.parse
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from dacite import from_dict
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from together_web3.computer import LanguageModelInferenceRequest
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from together_web3.together import TogetherWeb3
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st.title("GPT-JT")
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if 'together_web3' not in st.session_state:
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st.session_state.together_web3 = TogetherWeb3()
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if 'loop' not in st.session_state:
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st.session_state.loop = asyncio.new_event_loop()
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async def _inference(prompt, max_tokens, stop, top_p, temperature, seed):
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result = await st.session_state.together_web3.language_model_inference(
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from_dict(
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data_class=LanguageModelInferenceRequest,
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data={
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"model": "Together-gpt-JT-6B-v1",
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"max_tokens": max_tokens,
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"prompt": prompt,
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"stop": stop,
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"top_p": top_p,
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"temperature": temperature,
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"seed": seed,
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}
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),
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)
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return result
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@st.cache
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def infer(prompt,
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model_name,
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max_new_tokens=10,
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temperature=
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top_p=1.0,
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num_completions=1,
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seed=42,
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stop="\n"):
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col1, col2 = st.columns([1, 3])
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with col1:
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model_name = st.selectbox("Model", ["GPT-JT-6B-v1"])
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max_new_tokens = st.text_input('Max new tokens', "10")
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temperature = st.text_input('temperature', "
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top_p = st.text_input('top_p', "1.0")
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num_completions = st.text_input('num_completions (only the best one will be returend)', "1")
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stop = st.text_input('stop, split by;', r'\n')
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prompt, model_name=model_name, max_new_tokens=max_new_tokens, temperature=temperature, top_p=top_p,
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num_completions=num_completions, seed=seed, stop=literal_eval("'''"+stop+"'''"),
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)
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generated_area.text(prompt + report_text)
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import streamlit as st
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import requests
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import time
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from ast import literal_eval
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@st.cache
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def infer(prompt,
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model_name,
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max_new_tokens=10,
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temperature=0.0,
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top_p=1.0,
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num_completions=1,
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seed=42,
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stop="\n"):
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model_name_map = {
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"GPT-JT-6B-v1": "Together-gpt-JT-6B-v1",
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}
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my_post_dict = {
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"model": "Together-gpt-JT-6B-v1",
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"prompt": prompt,
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"top_p": float(top_p),
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"temperature": float(temperature),
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"max_tokens": int(max_new_tokens),
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"stop": stop.split(";")
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}
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response = requests.get("https://staging.together.xyz/api/inference", params=my_post_dict).json()
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return response['output']['choices'][0]['text']
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st.title("GPT-JT")
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col1, col2 = st.columns([1, 3])
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with col1:
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model_name = st.selectbox("Model", ["GPT-JT-6B-v1"])
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max_new_tokens = st.text_input('Max new tokens', "10")
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temperature = st.text_input('temperature', "0.0")
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top_p = st.text_input('top_p', "1.0")
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num_completions = st.text_input('num_completions (only the best one will be returend)', "1")
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stop = st.text_input('stop, split by;', r'\n')
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prompt, model_name=model_name, max_new_tokens=max_new_tokens, temperature=temperature, top_p=top_p,
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num_completions=num_completions, seed=seed, stop=literal_eval("'''"+stop+"'''"),
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)
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generated_area.text(prompt + report_text)
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