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."
# Welcome to Team Tonic's MultiMed
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 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()