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#import json
import os
#import shutil
#import requests
import gradio as gr
from transformers.utils import logging
from langchain.embeddings import HuggingFaceInstructEmbeddings, GooglePalmEmbeddings
import pinecone
from langchain.vectorstores import Pinecone
logging.set_verbosity_debug()
instructor_embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl", model_kwargs={"device": "cpu"})
HF_TOKEN = os.environ.get("HF_TOKEN", None)
PINECONE_API_KEY = os.environ.get("PINECONE_API_KEY", None)
PINECONE_ENV = os.environ.get("PINECONE_ENV", None)
GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY", None)
pinecone.init(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
from langchain.llms import GooglePalm
from langchain.chains import RetrievalQAWithSourcesChain
llm=GooglePalm(google_api_key=GOOGLE_API_KEY, temperature=1, max_output_tokens=2048)
vectorStore = Pinecone.from_existing_index('tennis', instructor_embeddings)
retriever = vectorStore.as_retriever(search_kwargs={"k": 3})
qa_chain_instrucEmbed = RetrievalQAWithSourcesChain.from_chain_type(llm=llm,
chain_type="stuff",
retriever=retriever,
return_source_documents=True,
verbose=True
)
theme = gr.themes.Monochrome(
primary_hue="indigo",
secondary_hue="blue",
neutral_hue="slate",
radius_size=gr.themes.sizes.radius_sm,
font=[
gr.themes.GoogleFont("Open Sans"),
"ui-sans-serif",
"system-ui",
"sans-serif",
],
)
def generate(question):
ret = qa_chain_instrucEmbed(question)
print(str(ret))
answer = ret['answer']
sources = ret['sources']
embed_video_html = ''
if sources is not None and len(sources) > 0:
sources = [s.strip() for s in sources.split(',')]
for source in sources:
embed_video_html += f'''
<iframe width="560" height="315" src="https://www.youtube.com/embed/{source}"
title="YouTube video player" frameborder="0" allow="accelerometer; autoplay;
clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
'''
return answer, embed_video_html
examples = [
"Tell me step by step how to find out my dominant eye when I play tennis.",
"hat do we look for in a great tennis player? Write out the essential attributes."
]
def process_example(args):
for x in generate(args):
pass
return x
css = ".generating {visibility: hidden}"
monospace_css = """
#q-input textarea {
font-family: monospace, 'Consolas', Courier, monospace;
}
"""
css += monospace_css + ".gradio-container {color: black}"
description = """
<div style="text-align: center;">
<h1>Ask Coach Patrick Mouratoglou</h1>
</div>
<div style="text-align: left;">
<p>This is a demo to answer some popular questions from tennis fans to Coach Patrick. The information is being extracted from his official <a href="https://www.youtube.com/@patrickmouratoglou_official" style='color: #e6b800;'>Youtube channel</a>. It's using the following technologies:</p>
<ul>
<li>Google PALM</li>
<li>Gradio</li>
<li>hkunlp/instructor-xl</li>
<li>HuggingFace</li>
<li>Langchain</li>
<li>Pinecone</li>
</ul>
</div>
"""
disclaimer = """⚠️<b>This is an unofficial website.</b>\
<br>**Intended Use**: this app for demonstration purposes; not to serve as replacement for Coach Patrick official media channels or personal expertise."""
with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:
with gr.Column():
gr.Markdown(description)
gr.Markdown(disclaimer)
with gr.Row():
with gr.Column():
instruction = gr.Textbox(
placeholder="Enter your question here",
lines=5,
label="Input",
elem_id="q-input",
)
submit = gr.Button("Ask", variant="primary")
output = gr.Code(elem_id="q-output", lines=10, label="Output")
video = gr.HTML('')
gr.Examples(
examples=examples,
inputs=[instruction],
cache_examples=False,
fn=process_example,
outputs=[output, video],
)
submit.click(
generate,
inputs=[instruction],
outputs=[output, video],
)
demo.queue(concurrency_count=16).launch(debug=True) |