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import streamlit as st | |
from together import Together | |
import os | |
from typing import Iterator | |
from PIL import Image | |
import base64 | |
from PyPDF2 import PdfReader | |
API_KEY = os.getenv("TOGETHER_API_KEY") | |
if not API_KEY: | |
raise ValueError("API key is missing! Make sure TOGETHER_API_KEY is set in the Secrets.") | |
def get_client(): | |
return Together(api_key=API_KEY) | |
def process_file(file) -> str: | |
if file is None: | |
return "" | |
try: | |
if file.type == "application/pdf": | |
text = "" | |
pdf_reader = PdfReader(file) | |
for page in pdf_reader.pages: | |
text += page.extract_text() + "\n" | |
return text | |
elif file.type.startswith("image/"): | |
return base64.b64encode(file.getvalue()).decode("utf-8") | |
else: | |
return file.getvalue().decode('utf-8') | |
except Exception as e: | |
st.error(f"νμΌ μ²λ¦¬ μ€ μ€λ₯ λ°μ: {str(e)}") | |
return "" | |
def generate_response( | |
message: str, | |
history: list[tuple[str, str]], | |
system_message: str, | |
max_tokens: int, | |
temperature: float, | |
top_p: float, | |
files=None | |
) -> Iterator[str]: | |
client = get_client() | |
try: | |
# λ©μμ§ λ°°μ΄ μ΄κΈ°ν | |
messages = [] | |
# μμ€ν λ©μμ§κ° μλ κ²½μ°μλ§ μΆκ° | |
if system_message.strip(): | |
messages.append({ | |
"role": "system", | |
"content": system_message | |
}) | |
# λν νμ€ν 리 μΆκ° | |
for user_msg, assistant_msg in history: | |
messages.append({ | |
"role": "user", | |
"content": user_msg | |
}) | |
messages.append({ | |
"role": "assistant", | |
"content": assistant_msg | |
}) | |
# νμ¬ λ©μμ§μ νμΌ λ΄μ© μ€λΉ | |
current_content = message | |
if files: | |
file_contents = [] | |
for file in files: | |
content = process_file(file) | |
if content: | |
file_contents.append(f"νμΌ λ΄μ©:\n{content}") | |
if file_contents: | |
current_content = current_content + "\n\n" + "\n\n".join(file_contents) | |
# νμ¬ λ©μμ§ μΆκ° | |
messages.append({ | |
"role": "user", | |
"content": current_content | |
}) | |
# API μμ² μ€μ | |
request_params = { | |
"model": "deepseek-ai/DeepSeek-R1", | |
"messages": messages, | |
"max_tokens": max_tokens, | |
"temperature": temperature, | |
"top_p": top_p, | |
"stream": True | |
} | |
# API νΈμΆ | |
try: | |
stream = client.chat.completions.create(**request_params) | |
for chunk in stream: | |
if hasattr(chunk.choices[0].delta, 'content') and chunk.choices[0].delta.content: | |
yield chunk.choices[0].delta.content | |
except Exception as e: | |
if "rate limit" in str(e).lower(): | |
yield "API νΈμΆ νλμ λλ¬νμ΅λλ€. μ μ ν λ€μ μλν΄μ£ΌμΈμ." | |
else: | |
error_message = str(e) | |
# Together.aiμ μ€λ₯ μλ΅ λΆμ | |
if "Input validation error" in error_message: | |
yield "μ λ ₯ νμμ΄ μ¬λ°λ₯΄μ§ μμ΅λλ€. μμ€ν κ΄λ¦¬μμκ² λ¬Έμν΄μ£ΌμΈμ." | |
else: | |
yield f"API νΈμΆ μ€ μ€λ₯κ° λ°μνμ΅λλ€: {error_message}" | |
except Exception as e: | |
yield f"μ€λ₯κ° λ°μνμ΅λλ€: {str(e)}" | |
def main(): | |
st.set_page_config(page_title="DeepSeek μ±ν ", page_icon="π", layout="wide") | |
if "messages" not in st.session_state: | |
st.session_state.messages = [] | |
st.title("DeepSeek μ±ν ") | |
st.markdown("DeepSeek AI λͺ¨λΈκ³Ό λννμΈμ. νμν κ²½μ° νμΌμ μ λ‘λν μ μμ΅λλ€.") | |
with st.sidebar: | |
st.header("μ€μ ") | |
system_message = st.text_area( | |
"μμ€ν λ©μμ§", | |
value="λΉμ μ κΉμ΄ μκ² μκ°νλ AIμ λλ€. λ¬Έμ λ₯Ό κΉμ΄ κ³ λ €νκ³ μ²΄κ³μ μΈ μΆλ‘ κ³Όμ μ ν΅ν΄ μ¬λ°λ₯Έ ν΄κ²°μ± μ λμΆνμΈμ. λ°λμ νκΈλ‘ λ΅λ³νμΈμ.", | |
height=100 | |
) | |
max_tokens = st.slider("μ΅λ ν ν° μ", 1, 4096, 2048) # ν ν° μ ν μ‘°μ | |
temperature = st.slider("μ¨λ", 0.0, 2.0, 0.7, 0.1) # μ¨λ λ²μ μ‘°μ | |
top_p = st.slider("Top-p", 0.0, 1.0, 0.7, 0.1) # top_p λ²μ μ‘°μ | |
uploaded_file = st.file_uploader( | |
"νμΌ μ λ‘λ (μ νμ¬ν)", | |
type=['txt', 'py', 'md', 'pdf', 'png', 'jpg', 'jpeg'], | |
accept_multiple_files=True | |
) | |
for message in st.session_state.messages: | |
with st.chat_message(message["role"]): | |
st.markdown(message["content"]) | |
if prompt := st.chat_input("무μμ μκ³ μΆμΌμ κ°μ?"): | |
st.session_state.messages.append({"role": "user", "content": prompt}) | |
with st.chat_message("user"): | |
st.markdown(prompt) | |
with st.chat_message("assistant"): | |
response_placeholder = st.empty() | |
full_response = "" | |
history = [(msg["content"], next_msg["content"]) | |
for msg, next_msg in zip(st.session_state.messages[::2], st.session_state.messages[1::2])] | |
for response_chunk in generate_response( | |
prompt, | |
history, | |
system_message, | |
max_tokens, | |
temperature, | |
top_p, | |
uploaded_file | |
): | |
full_response += response_chunk | |
response_placeholder.markdown(full_response + "β") | |
response_placeholder.markdown(full_response) | |
st.session_state.messages.append({"role": "assistant", "content": full_response}) | |
if __name__ == "__main__": | |
main() |