Spaces:
Sleeping
Sleeping
File size: 3,995 Bytes
cf9ec28 d7cd17a cf9ec28 992da9d 7ea7a0f d7cd17a 21e25fd d7cd17a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 |
import os
from groq import Groq
import gradio as gr
DESCRIPTION = '''
<div>
<h1 style="text-align: center;">Meta Llama3 8B</h1>
<p>This Space demonstrates the instruction-tuned model <a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct"><b>Meta Llama3 8b Chat</b></a>. Meta Llama3 is the new open LLM and comes in two sizes: 8b and 70b. Feel free to play with it, or duplicate to run privately!</p>
<p>🔎 For more details about the Llama3 release and how to use the model with <code>transformers</code>, take a look <a href="https://huggingface.co/blog/llama3">at our blog post</a>.</p>
<p>🦕 Looking for an even more powerful model? Check out the <a href="https://huggingface.co/chat/"><b>Hugging Chat</b></a> integration for Meta Llama 3 70b</p>
</div>
'''
LICENSE = """
<p/>
---
Built with Meta Llama 3
"""
PLACEHOLDER = """
<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
<img src="https://ysharma-dummy-chat-app.hf.space/file=/tmp/gradio/8e75e61cc9bab22b7ce3dec85ab0e6db1da5d107/Meta_lockup_positive%20primary_RGB.jpg" style="width: 80%; max-width: 550px; height: auto; opacity: 0.55; ">
<h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">Meta llama3</h1>
<p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Ask me anything related to Ayur Veda</p>
</div>
"""
css = """
h1 {
text-align: center;
display: block;
}
#duplicate-button {
margin: auto;
color: white;
background: #1565c0;
border-radius: 100vh;
}
"""
client = Groq(
api_key =os.getenv('api_key_gorq')
)
def response_from_llam3(query):
messages = [
{
"role" : "system",
"content": "You are an helpul Assistant who has plently of Knowledge on Ayur Veda. If the message is Hi or any greeting say namste how can i assist you "
},
{
"role": "user",
"content": "What is the answer to {}".format(query)
}
]
response = client.chat.completions.create(
messages = messages,
model = "llama3-70b-8192"
)
return response.choices[0].message.content
# iface = gr.Interface(
# fn=response_from_llam3,
# inputs="text",
# outputs="text",
# examples=[
# ['What is importance of fasting according to Ayurveda?'],
# ['What are the medicinal values of Tusli?'],
# ['What are the three different doshas?'],
# ['What is the ideal diet according to ayurveda?']
# ],
# cache_examples=False,
# )
# iface.launch()
# Gradio block
chatbot=gr.Chatbot(height=450, placeholder=PLACEHOLDER, label='Gradio ChatInterface')
with gr.Blocks(fill_height=True, css=css) as demo:
gr.Markdown(DESCRIPTION)
gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
gr.ChatInterface(
fn=response_from_llam3,
chatbot=chatbot,
fill_height=True,
additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
# additional_inputs=[
# gr.Slider(minimum=0,
# maximum=1,
# step=0.1,
# value=0.95,
# label="Temperature",
# render=False),
# gr.Slider(minimum=128,
# maximum=4096,
# step=1,
# value=512,
# label="Max new tokens",
# render=False ),
# ],
examples=[
['What is importance of fasting according to Ayurveda?'],
['What are the medicinal values of Tusli?'],
['What are the three different doshas?'],
['What is the ideal diet according to ayurveda?']
],
cache_examples=False,
)
gr.Markdown(LICENSE)
if __name__ == "__main__":
demo.launch() |