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from openai import OpenAI
import crawl_the_site
import create_database
import streamlit as st
import time
api_key = "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"
openai_client = OpenAI(base_url="https://openrouter.ai/api/v1",api_key=api_key)
prompt_template = """Answer the question only according to the information provided below. Answer only the user's question, dont give additional information.
## Information :
{}
## Question :
# {}"""
if not "messages" in st.session_state:
st.session_state.messages = []
if not "stage" in st.session_state:
st.session_state.stage = "crawl-input"
elif st.session_state.stage == "remove-crawl-input-widgets":
st.session_state.stage = "prompt-input"
if st.session_state.stage == "crawl-input":
config = st.text_area("Enter the start URL and the limit of crawling (in this format : URL,limit) :")
config_btn = st.button("Start crawling!")
if config and config_btn:
start = config.split(",")[0]
limit = int(config.split(",")[1])
txt = crawl_the_site.crawl(start,limit)
st.session_state.collection = create_database.create_database(txt)
st.write("Crawling is done. Click \"Start Crawling!\" again to start chatting!")
st.session_state.stage = "remove-crawl-input-widgets"
if st.session_state.stage == "prompt-input":
prompt = st.chat_input("Ask the documentation a question!")
if prompt:
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["message"])
with st.chat_message("user"):
st.markdown(prompt)
st.session_state.messages.append({"role":"user","message":prompt})
results = st.session_state.collection.query(query_texts=[prompt],n_results=5)
infos = results["documents"][0]
info_text = ""
for info in infos:
info_text += info + "\n---\n"
info_text = info_text.strip()
prompt = prompt_template.format(info_text,prompt)
completion = openai_client.chat.completions.create(
extra_headers={},
extra_body={},
model="deepseek/deepseek-r1:free",
messages=[{"role":"user","content":prompt}])
with st.chat_message("assistant"):
full_response = ""
message_placeholder = st.empty()
for chunk in completion.choices[0].message.content.split():
full_response += chunk + " "
time.sleep(0.05)
message_placeholder.markdown(full_response + "▌")
message_placeholder.markdown(full_response)
st.session_state.messages.append({"role":"assistant","message":full_response}) |