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import streamlit as st
from groq import Groq
from langchain_community.vectorstores import FAISS
from langchain_huggingface import HuggingFaceEmbeddings
def run_groq(prompt):
client = Groq(api_key = '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')
chat_completion = client.chat.completions.create(
messages = [
{
'role' : 'user' ,
'content' : prompt
}
] , model = 'llama3-70b-8192'
)
return chat_completion.choices[0].message.content
vc = FAISS.load_local(
'vc' ,
embeddings = HuggingFaceEmbeddings(model_name = 'all-MiniLM-L6-v2') ,
allow_dangerous_deserialization = True
)
def search(query) :
similar_docs = vc.similarity_search(query)
context = '\n'.join([doc.page_content for doc in similar_docs])
prompt = f'''
You are given a user query, some textual context and rules, all inside xml tags. You have to answer the query based on the context while respecting the rules.
<context>
{context}
</context>
<rules>
- If you don't know, just say so.
- If you are not sure, ask for clarification.
- Answer in the same language as the user query.
- If the context appears unreadable or of poor quality, tell the user then answer as best as you can.
- If the answer is not in the context but you think you know the answer, explain that to the user then answer with your own knowledge.
- Answer directly and without using xml tags.
- The context will contain some youtube video ids,
- Try to cite links using the ids each time you answer the query
- When citing the links , use the format https://www.youtube.com/watch?v=<id>
- DO not mention that you are using the context or the infromation is from the context or the information provided, treat the given context as your learned knowldge
- The context will also have yotube video_title at the end after the video_id, only mention the video in the citation if the title matches with the query. ALso mention the video title while giving citations
- Always provide the citations at the end with their title and link
- Try to strucutre your response in markdown format, use points, tables, bold formats and much more to beautify the response
</rules>
<user_query>
{query}
</user_query>
'''
response = run_groq(prompt)
return response
def check_prompt(prompt) :
try : prompt.replace('' , '') ; return True
except : return False
def check_mesaage() :
if 'messages' not in st.session_state : st.session_state.messages = []
check_mesaage()
for message in st.session_state.messages :
with st.chat_message(message['role']) : st.markdown(message['content'])
prompt = st.chat_input('Ask me anything')
if check_prompt(prompt) :
with st.chat_message('user'): st.markdown(prompt)
st.session_state.messages.append({
'role' : 'user' ,
'content' : prompt
})
if prompt != None or prompt != '' :
response = search(prompt)
with st.chat_message('assistant') : st.markdown(response)
st.session_state.messages.append({
'role' : 'assistant' ,
'content' : response
}) |