Update app.py
Browse files
app.py
CHANGED
@@ -2,6 +2,24 @@ import streamlit as st
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import requests
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import logging
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import json
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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@@ -31,7 +49,11 @@ with st.sidebar:
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system_message = st.text_area(
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"System Message",
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value=
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height=100
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)
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@@ -62,15 +84,84 @@ def query(payload, api_url):
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logger.error(f"Failed to decode JSON response: {response.text}")
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return None
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#
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def search_web(query):
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# Chat interface
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st.title("๐ค DeepSeek Chatbot")
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@@ -90,22 +181,22 @@ if prompt := st.chat_input("Type your message..."):
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try:
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with st.spinner("Generating response..."):
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#
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search_results = search_web(prompt)
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#
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if search_results and "results" in search_results:
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if 'organic' in search_results["results"]:
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search_content = "\n".join([f"**{item['title']}**: {item['snippet']}"
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search_content = f"Here are some search results related to your question:\n\n{search_content}\n\n"
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else:
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search_content = "Sorry, no relevant search results found.\n\n"
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# Combine the system message, search results, and user input into a single prompt
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full_prompt = f"{system_message}\n\n{search_content}User: {prompt}\nAssistant:"
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else:
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full_prompt = f"{system_message}\n\nUser: {prompt}\nAssistant:"
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payload = {
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"inputs": full_prompt,
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"parameters": {
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@@ -115,30 +206,28 @@ if prompt := st.chat_input("Type your message..."):
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"return_full_text": False
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}
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}
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#
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api_url = f"https://api-inference.huggingface.co/models/{selected_model}"
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logger.info(f"Selected model: {selected_model}, API URL: {api_url}")
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#
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output = query(payload, api_url)
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#
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if output is not None and isinstance(output, list) and len(output) > 0:
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if 'generated_text' in output[0]:
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# Extract the assistant's response
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assistant_response = output[0]['generated_text'].strip()
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#
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responses = assistant_response.split("\n</think>\n")
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unique_response = responses[0].strip()
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logger.info(f"Generated response: {unique_response}")
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# Append response to chat only once
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with st.chat_message("assistant"):
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st.markdown(unique_response)
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st.session_state.messages.append({"role": "assistant", "content": unique_response})
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else:
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logger.error(f"Unexpected API response structure: {output}")
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@@ -146,7 +235,7 @@ if prompt := st.chat_input("Type your message..."):
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else:
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logger.error(f"Empty or invalid API response: {output}")
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st.error("Error: Unable to generate a response. Please check the model and try again.")
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except Exception as e:
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logger.error(f"Application Error: {str(e)}", exc_info=True)
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st.error(f"Application Error: {str(e)}")
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import requests
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import logging
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import json
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from datetime import datetime, timedelta
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from requests.adapters import HTTPAdapter
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from urllib3.util.retry import Retry
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# --- Optional: translate_query ๋ฐ ๊ด๋ จ ์์ ์ ์ (์ค์ ๊ตฌํ์ ๋ง๊ฒ ์์ ) ---
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def translate_query(query, country):
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# ์ค์ ์ํฉ์์๋ ๋ฒ์ญ ๋ก์ง์ ๊ตฌํํ์ธ์.
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return query
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COUNTRY_LOCATIONS = {
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"United States": "United States",
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"South Korea": "South Korea"
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}
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COUNTRY_LANGUAGES = {
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"United States": "en",
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"South Korea": "ko"
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}
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# -------------------------------------------------------------------------
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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system_message = st.text_area(
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"System Message",
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value=(
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"You are a deep thinking AI, you may use extremely long chains of thought to deeply consider the problem and "
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"deliberate with yourself via systematic reasoning processes to help come to a correct solution prior to answering. "
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"You should enclose your thoughts and internal monologue inside tags, and then provide your solution or response to the problem."
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),
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height=100
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)
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logger.error(f"Failed to decode JSON response: {response.text}")
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return None
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# --- ์์ ๋ ์น์์น ๊ธฐ๋ฅ ---
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def search_web(query, country="United States", page=1, num_result=10):
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url = "https://api.serphouse.com/serp/live"
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# ์ต๊ทผ 24์๊ฐ ๊ธฐ๊ฐ ์ค์
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now = datetime.utcnow()
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yesterday = now - timedelta(days=1)
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date_range = f"{yesterday.strftime('%Y-%m-%d')},{now.strftime('%Y-%m-%d')}"
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# ์ฟผ๋ฆฌ ๋ฒ์ญ (ํ์์)
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translated_query = translate_query(query, country)
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payload = {
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"data": {
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"q": translated_query,
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"domain": "google.com",
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"loc": COUNTRY_LOCATIONS.get(country, "United States"),
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"lang": COUNTRY_LANGUAGES.get(country, "en"),
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"device": "desktop",
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"serp_type": "web", # ๊ฒ์ ์ ํ์ "web"์ผ๋ก ์ค์ (์ํ๋ ๊ฒฝ์ฐ "news" ๋ฑ์ผ๋ก ๋ณ๊ฒฝ ๊ฐ๋ฅ)
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"page": str(page),
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"num": str(num_result),
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"date_range": date_range,
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"sort_by": "date"
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}
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}
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# st.secrets์ SERPHOUSE_API_TOKEN์ด ์ ์ฅ๋์ด ์์ด์ผ ํฉ๋๋ค.
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api_key = st.secrets.get("SERPHOUSE_API_TOKEN")
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if not api_key:
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logger.error("SERPHOUSE_API_TOKEN not found in st.secrets")
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return {"error": "API token not configured."}
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headers = {
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"accept": "application/json",
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"content-type": "application/json",
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"authorization": f"Bearer {api_key}"
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}
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try:
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# ์ธ์
๊ณผ ์ฌ์๋ ์ค์
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session = requests.Session()
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retries = Retry(
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total=5,
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backoff_factor=1,
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status_forcelist=[500, 502, 503, 504, 429],
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allowed_methods=["POST"]
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)
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adapter = HTTPAdapter(max_retries=retries)
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session.mount('http://', adapter)
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session.mount('https://', adapter)
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# ์ฐ๊ฒฐ ๋ฐ ์ฝ๊ธฐ ํ์์์ 30์ด์ฉ ์ค์
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response = session.post(
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url,
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json=payload,
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headers=headers,
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timeout=(30, 30)
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)
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response.raise_for_status()
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return {"results": response.json(), "translated_query": translated_query}
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except requests.exceptions.Timeout:
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return {
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"error": "๊ฒ์ ์๊ฐ์ด ์ด๊ณผ๋์์ต๋๋ค. ์ ์ ํ ๋ค์ ์๋ํด์ฃผ์ธ์.",
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"translated_query": query
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}
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except requests.exceptions.RequestException as e:
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return {
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"error": f"๊ฒ์ ์ค ์ค๋ฅ๊ฐ ๋ฐ์ํ์ต๋๋ค: {str(e)}",
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"translated_query": query
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}
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except Exception as e:
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return {
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"error": f"์๊ธฐ์น ์์ ์ค๋ฅ๊ฐ ๋ฐ์ํ์ต๋๋ค: {str(e)}",
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"translated_query": query
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}
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# --- ๋ ---
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# Chat interface
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st.title("๐ค DeepSeek Chatbot")
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try:
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with st.spinner("Generating response..."):
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# ์
๋ฐ์ดํธ๋ ์น์์น ๊ธฐ๋ฅ์ ์ฌ์ฉํ์ฌ ๊ฒ์ ์ํ
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search_results = search_web(prompt, country="United States", page=1, num_result=10)
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# ๊ฒ์ ๊ฒฐ๊ณผ ์ฒ๋ฆฌ (API ์๋ต ๊ตฌ์กฐ์ ๋ฐ๋ผ ์ ์ ํ ์์ ํ์)
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if search_results and "results" in search_results:
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if 'organic' in search_results["results"]:
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search_content = "\n".join([f"**{item['title']}**: {item['snippet']}"
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for item in search_results["results"]["organic"]])
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search_content = f"Here are some search results related to your question:\n\n{search_content}\n\n"
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else:
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search_content = "Sorry, no relevant search results found.\n\n"
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full_prompt = f"{system_message}\n\n{search_content}User: {prompt}\nAssistant:"
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else:
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full_prompt = f"{system_message}\n\nUser: {prompt}\nAssistant:"
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payload = {
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"inputs": full_prompt,
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"parameters": {
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"return_full_text": False
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}
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}
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# ์ ํํ ๋ชจ๋ธ์ ๋ฐ๋ฅธ API URL ๋์ ๊ตฌ์ฑ
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api_url = f"https://api-inference.huggingface.co/models/{selected_model}"
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logger.info(f"Selected model: {selected_model}, API URL: {api_url}")
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# Hugging Face API์ ์ฟผ๋ฆฌ ์ ์ก
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output = query(payload, api_url)
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# ์๋ต ์ฒ๋ฆฌ
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if output is not None and isinstance(output, list) and len(output) > 0:
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if 'generated_text' in output[0]:
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assistant_response = output[0]['generated_text'].strip()
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# ์ค๋ณต ์๋ต ์ ๊ฑฐ (๋ด๋ถ ์ฒด์ธ ์ค ์ผ๋ถ ์ ๊ฑฐ)
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responses = assistant_response.split("\n</think>\n")
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unique_response = responses[0].strip()
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logger.info(f"Generated response: {unique_response}")
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with st.chat_message("assistant"):
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st.markdown(unique_response)
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st.session_state.messages.append({"role": "assistant", "content": unique_response})
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else:
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logger.error(f"Unexpected API response structure: {output}")
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else:
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logger.error(f"Empty or invalid API response: {output}")
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st.error("Error: Unable to generate a response. Please check the model and try again.")
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except Exception as e:
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logger.error(f"Application Error: {str(e)}", exc_info=True)
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st.error(f"Application Error: {str(e)}")
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