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| from openai import OpenAI | |
| import streamlit as st | |
| from st_multimodal_chatinput import multimodal_chatinput | |
| ##hack to make sure that chatinput is always at the bottom of the page | |
| ##will only work if multimodal_chatinput is called inside the first st.container of the page | |
| ############################################################################## | |
| def reconfig_chatinput(): | |
| st.markdown( | |
| """ | |
| <style> | |
| div[data-testid="stVerticalBlock"] div[data-testid="stVerticalBlock"]:first-of-type { | |
| position: fixed; | |
| bottom: 0; | |
| background-color: #0E117; | |
| z-index: 1000; | |
| /* Other styles as needed */ | |
| } | |
| </style> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| return | |
| reconfig_chatinput() | |
| ############################################################################## | |
| st.title("ChatGPT with Vision") | |
| client = OpenAI(api_key=st.secrets["OPENAI_KEY"]) | |
| if "openai_model" not in st.session_state: | |
| st.session_state["openai_model"] = "gpt-3.5-turbo" | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| chatbox = st.container() | |
| for message in st.session_state.messages: | |
| with chatbox.chat_message(message["role"]): | |
| contents = message["content"] | |
| for content in contents: | |
| if content["type"] == "text": | |
| chatbox.markdown(content["text"]) | |
| elif content["type"] == "image_url": | |
| chatbox.image(content["image_url"]["url"]) | |
| def push_message(role, content, images=None): | |
| contents = [] | |
| contents.append({"type": "text", "text": content}) | |
| if images: | |
| for image in images: | |
| obj = { | |
| "type": "image_url", | |
| "image_url": { | |
| "url": image, | |
| }, | |
| } | |
| contents.append(obj) | |
| print("pushing message", role, contents) | |
| message = {"role": role, "content": contents} | |
| st.session_state.messages.append(message) | |
| return message | |
| with st.container(): | |
| multimodal_prompt = multimodal_chatinput() | |
| if multimodal_prompt: | |
| prompt = multimodal_prompt["text"] | |
| push_message("user", prompt) | |
| # with st.chat_message("user"): | |
| # st.markdown(prompt) | |
| # with st.chat_message("assistant"): | |
| messages = [ | |
| {"role": m["role"], "content": m["content"]} | |
| for m in st.session_state.messages | |
| ] | |
| print("api call", messages) | |
| stream = client.chat.completions.create( | |
| model="gpt-4-vision-preview", | |
| messages=messages, | |
| # stream=True, | |
| max_tokens=1024, | |
| ) | |
| # response = st.write_stream(stream) | |
| # print("api response", stream) | |
| stream = stream.choices[0].message.content | |
| # response = st.markdown(stream) | |
| response = stream | |
| push_message("assistant", response) | |
| # chat_placeholder = st.empty() | |
| # with chat_placeholder.container(): | |