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# Welcome to Team Tonic's MultiMed | |
import gradio as gr | |
import requests | |
import json | |
from decouple import Config | |
config = Config('.env') | |
def query_vectara(question): | |
user_message = question | |
# Read authentication parameters from the .env file | |
CUSTOMER_ID = config('CUSTOMER_ID') | |
CORPUS_ID = config('CORPUS_ID') | |
API_KEY = config('API_KEY') | |
# Define the headers | |
api_key_header = { | |
"customer-id": CUSTOMER_ID, | |
"x-api-key": API_KEY | |
} | |
# Define the request body in the structure provided in the example | |
request_body = { | |
"query": [ | |
{ | |
"query": user_message, | |
"queryContext": "", | |
"start": 1, | |
"numResults": 10, | |
"contextConfig": { | |
"charsBefore": 0, | |
"charsAfter": 0, | |
"sentencesBefore": 2, | |
"sentencesAfter": 2, | |
"startTag": "%START_SNIPPET%", | |
"endTag": "%END_SNIPPET%", | |
}, | |
"rerankingConfig": { | |
"rerankerId": 272725718, | |
"mmrConfig": { | |
"diversityBias": 0.27 | |
} | |
}, | |
"corpusKey": [ | |
{ | |
"customerId": CUSTOMER_ID, | |
"corpusId": CORPUS_ID, | |
"semantics": 0, | |
"metadataFilter": "", | |
"lexicalInterpolationConfig": { | |
"lambda": 0 | |
}, | |
"dim": [] | |
} | |
], | |
"summary": [ | |
{ | |
"maxSummarizedResults": 5, | |
"responseLang": "eng", | |
"summarizerPromptName": "vectara-summary-ext-v1.2.0" | |
} | |
] | |
} | |
] | |
} | |
# Make the API request using Gradio | |
response = requests.post( | |
"https://api.vectara.io/v1/query", | |
json=request_body, # Use json to automatically serialize the request body | |
verify=True, | |
headers=api_key_header | |
) | |
if response.status_code == 200: | |
query_data = response.json() | |
if query_data: | |
sources_info = [] | |
# Extract the summary. | |
summary = query_data['responseSet'][0]['summary'][0]['text'] | |
# Iterate over all response sets | |
for response_set in query_data.get('responseSet', []): | |
# Extract sources | |
for source in response_set.get('response', [])[:5]: # Limit to top 5 sources. | |
source_metadata = source.get('metadata', []) | |
source_info = {} | |
for metadata in source_metadata: | |
metadata_name = metadata.get('name', '') | |
metadata_value = metadata.get('value', '') | |
if metadata_name == 'title': | |
source_info['title'] = metadata_value | |
elif metadata_name == 'author': | |
source_info['author'] = metadata_value | |
elif metadata_name == 'pageNumber': | |
source_info['page number'] = metadata_value | |
if source_info: | |
sources_info.append(source_info) | |
result = {"summary": summary, "sources": sources_info} | |
return f"{json.dumps(result, indent=2)}" | |
else: | |
return "No data found in the response." | |
else: | |
return f"Error: {response.status_code}" | |
def convert_to_markdown(vectara_response_json): | |
vectara_response = json.loads(vectara_response_json) | |
if vectara_response: | |
summary = vectara_response.get('summary', 'No summary available') | |
sources_info = vectara_response.get('sources', []) | |
# Format the summary as Markdown | |
markdown_summary = f'**Summary:** {summary}\n\n' | |
# Format the sources as a numbered list | |
markdown_sources = "" | |
for i, source_info in enumerate(sources_info): | |
author = source_info.get('author', 'Unknown author') | |
title = source_info.get('title', 'Unknown title') | |
page_number = source_info.get('page number', 'Unknown page number') | |
markdown_sources += f"{i+1}. {title} by {author}, Page {page_number}\n" | |
return f"{markdown_summary}**Sources:**\n{markdown_sources}" | |
else: | |
return "No data found in the response." | |
iface = gr.Interface( | |
fn=lambda text: convert_to_markdown(query_vectara(text)), | |
inputs=[gr.Textbox(label="Input Text")], | |
outputs=[gr.Markdown(label="Output Text")], | |
title="👋🏻Welcome to Team🚀Tonic's 😷MultiMed⚕️", | |
description="""<h3>How To Use 😷MultiMed⚕️:</h3><h5>🗣️📝Interact with 😷MultiMed⚕️ in any language using audio or text!🗣️📝</h5> | |
<h5>This is an educational and accessible conversational tool to improve wellness and sanitation in support of public health. 📚🌟💼 You can use 😷MultiMed⚕️ on your own data & in your own way by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/TeamTonic/MultiMed?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHY dmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h5> | |
<p>🌟TeamTonic🌟 is always making cool demos!</p> | |
<p>Join our active builder's community on Discord: <a href="https://discord.gg/GWpVpekp"><img src="https://discordapp.com/api/guilds/1109943800132010065/widget.png"></a> On Huggingface: <a href="https://huggingface.co/TeamTonic">TeamTonic</a> & <a href="https://huggingface.co/MultiTransformer">MultiTransformer</a> On Github: <a href="https://github.com/tonic-ai">Polytonic<img src="https://img.shields.io/github/followers/Tonic-AI.svg?style=social&label=Follow&maxAge=2592000"></a> & contribute to <a href="https://github.com/tonic-ai/polygpt-alpha">PolyGPT</a>""", | |
examples=[ | |
["What is the proper treatment for buccal herpes?"], | |
["Male, 40 presenting with swollen genitals and a rash"], | |
["How does cellular metabolism work TCA cycle"], | |
["What special care must be provided to children with chicken pox?"], | |
["When and how often should I wash my hands ?"], | |
["بکل ہرپس کا صحیح علاج کیا ہے؟"], | |
["구강 헤르페스의 적절한 치료법은 무엇입니까?"], | |
["Je, ni matibabu gani sahihi kwa herpes ya buccal?"] | |
] | |
) | |
iface.launch() |