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from omegaconf import OmegaConf |
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from query import VectaraQuery |
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import os |
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import requests |
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import json |
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import uuid |
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import streamlit as st |
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from streamlit_pills import pills |
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from streamlit_feedback import streamlit_feedback |
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from PIL import Image |
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max_examples = 6 |
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languages = {'English': 'eng', 'Spanish': 'spa', 'French': 'frs', 'Chinese': 'zho', 'German': 'deu', 'Hindi': 'hin', 'Arabic': 'ara', |
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'Portuguese': 'por', 'Italian': 'ita', 'Japanese': 'jpn', 'Korean': 'kor', 'Russian': 'rus', 'Turkish': 'tur', 'Persian (Farsi)': 'fas', |
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'Vietnamese': 'vie', 'Thai': 'tha', 'Hebrew': 'heb', 'Dutch': 'nld', 'Indonesian': 'ind', 'Polish': 'pol', 'Ukrainian': 'ukr', |
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'Romanian': 'ron', 'Swedish': 'swe', 'Czech': 'ces', 'Greek': 'ell', 'Bengali': 'ben', 'Malay (or Malaysian)': 'msa', 'Urdu': 'urd'} |
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if 'device_id' not in st.session_state: |
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st.session_state.device_id = str(uuid.uuid4()) |
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headers = { |
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'Content-Type': 'application/json', |
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'Accept': '*/*' |
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} |
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amp_api_key = os.getenv('AMPLITUDE_TOKEN') |
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def thumbs_feedback(feedback, **kwargs): |
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""" |
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Sends feedback to Amplitude Analytics |
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""" |
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data = { |
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"api_key": amp_api_key, |
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"events": [{ |
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"device_id": st.session_state.device_id, |
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"event_type": "provided_feedback", |
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"event_properties": { |
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"Space Name": kwargs.get("title", "Unknown Space Name"), |
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"Demo Type": "chatbot", |
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"query": kwargs.get("prompt", "No user input"), |
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"response": kwargs.get("response", "No chat response"), |
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"feedback": feedback["score"], |
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"Response Language": st.session_state.language |
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} |
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}] |
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} |
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response = requests.post('https://api2.amplitude.com/2/httpapi', headers=headers, data=json.dumps(data)) |
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if response.status_code != 200: |
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print(f"Request failed with status code {response.status_code}. Response Text: {response.text}") |
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st.session_state.feedback_key += 1 |
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if "feedback_key" not in st.session_state: |
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st.session_state.feedback_key = 0 |
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def isTrue(x) -> bool: |
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if isinstance(x, bool): |
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return x |
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return x.strip().lower() == 'true' |
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def launch_bot(): |
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def generate_response(question): |
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response = vq.submit_query(question, languages[st.session_state.language]) |
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return response |
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def generate_streaming_response(question): |
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response = vq.submit_query_streaming(question, languages[st.session_state.language]) |
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return response |
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def show_example_questions(): |
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if len(st.session_state.example_messages) > 0 and st.session_state.first_turn: |
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selected_example = pills("Queries to Try:", st.session_state.example_messages, index=None) |
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if selected_example: |
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st.session_state.ex_prompt = selected_example |
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st.session_state.first_turn = False |
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return True |
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return False |
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if 'cfg' not in st.session_state: |
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corpus_keys = str(os.environ['corpus_keys']).split(',') |
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cfg = OmegaConf.create({ |
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'corpus_keys': corpus_keys, |
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'api_key': str(os.environ['api_key']), |
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'title': os.environ['title'], |
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'source_data_desc': os.environ['source_data_desc'], |
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'streaming': isTrue(os.environ.get('streaming', False)), |
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'prompt_name': os.environ.get('prompt_name', None), |
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'examples': os.environ.get('examples', None), |
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'language': 'English' |
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}) |
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st.session_state.cfg = cfg |
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st.session_state.ex_prompt = None |
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st.session_state.first_turn = True |
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st.session_state.language = cfg.language |
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example_messages = [example.strip() for example in cfg.examples.split(",")] |
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st.session_state.example_messages = [em for em in example_messages if len(em)>0][:max_examples] |
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st.session_state.vq = VectaraQuery(cfg.api_key, cfg.corpus_keys, cfg.prompt_name) |
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cfg = st.session_state.cfg |
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vq = st.session_state.vq |
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st.set_page_config(page_title=cfg.title, layout="wide") |
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with st.sidebar: |
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image = Image.open('Vectara-logo.png') |
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st.image(image, width=175) |
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st.markdown(f"## About\n\n" |
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f"This demo uses Retrieval Augmented Generation to ask questions about {cfg.source_data_desc}\n") |
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cfg.language = st.selectbox('Language:', languages.keys()) |
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if st.session_state.language != cfg.language: |
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st.session_state.language = cfg.language |
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print(f"DEBUG: Language changed to {st.session_state.language}") |
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st.rerun() |
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st.markdown("---") |
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st.markdown( |
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"## How this works?\n" |
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"This app was built with [Vectara](https://vectara.com).\n" |
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"Vectara's [Indexing API](https://docs.vectara.com/docs/api-reference/indexing-apis/indexing) was used to ingest the data into a Vectara corpus (or index).\n\n" |
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"This app uses Vectara [Chat API](https://docs.vectara.com/docs/console-ui/vectara-chat-overview) to query the corpus and present the results to you, answering your question.\n\n" |
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) |
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st.markdown("---") |
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st.markdown(f"<center> <h2> Vectara AI Assistant: {cfg.title} </h2> </center>", unsafe_allow_html=True) |
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if "messages" not in st.session_state.keys(): |
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st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}] |
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for message in st.session_state.messages: |
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with st.chat_message(message["role"]): |
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st.write(message["content"]) |
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example_container = st.empty() |
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with example_container: |
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if show_example_questions(): |
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example_container.empty() |
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st.rerun() |
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if st.session_state.ex_prompt: |
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prompt = st.session_state.ex_prompt |
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else: |
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prompt = st.chat_input() |
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if prompt: |
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st.session_state.messages.append({"role": "user", "content": prompt}) |
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with st.chat_message("user"): |
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st.write(prompt) |
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st.session_state.ex_prompt = None |
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if st.session_state.messages[-1]["role"] != "assistant": |
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with st.chat_message("assistant"): |
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if cfg.streaming: |
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stream = generate_streaming_response(prompt) |
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response = st.write_stream(stream) |
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else: |
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with st.spinner("Thinking..."): |
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response = generate_response(prompt) |
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st.write(response) |
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message = {"role": "assistant", "content": response} |
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st.session_state.messages.append(message) |
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data = { |
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"api_key": amp_api_key, |
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"events": [{ |
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"device_id": st.session_state.device_id, |
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"event_type": "submitted_query", |
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"event_properties": { |
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"Space Name": cfg["title"], |
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"Demo Type": "chatbot", |
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"query": st.session_state.messages[-2]["content"], |
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"response": st.session_state.messages[-1]["content"], |
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"Response Language": st.session_state.language |
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} |
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}] |
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} |
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response = requests.post('https://api2.amplitude.com/2/httpapi', headers=headers, data=json.dumps(data)) |
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if response.status_code != 200: |
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print(f"Amplitude request failed with status code {response.status_code}. Response Text: {response.text}") |
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st.rerun() |
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if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != "How may I help you?"): |
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streamlit_feedback(feedback_type="thumbs", on_submit = thumbs_feedback, key = st.session_state.feedback_key, |
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kwargs = {"prompt": st.session_state.messages[-2]["content"], |
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"response": st.session_state.messages[-1]["content"], |
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"title": cfg["title"]}) |
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if __name__ == "__main__": |
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launch_bot() |