# 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": 25,
"contextConfig": {
"charsBefore": 0,
"charsAfter": 0,
"sentencesBefore": 2,
"sentencesAfter": 2,
"startTag": "%START_SNIPPET%",
"endTag": "%END_SNIPPET%",
},
"rerankingConfig": {
"rerankerId": 272725718,
"mmrConfig": {
"diversityBias": 0.35
}
},
"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="""How To Use 😷MultiMed⚕️:
🗣️📝Interact with 😷MultiMed⚕️ in any language using audio or text!🗣️📝
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: 
🌟TeamTonic🌟 is always making cool demos!
Join our active builder's community on Discord: 
On Huggingface: TeamTonic & MultiTransformer On Github: Polytonic
& contribute to PolyGPT
""",
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()