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Update app.py
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app.py
CHANGED
@@ -1,5 +1,6 @@
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import io
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import os
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from contextlib import closing
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from typing import Optional, Tuple
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import datetime
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@@ -30,17 +31,31 @@ from openai.error import AuthenticationError, InvalidRequestError, RateLimitErro
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from langchain.prompts import PromptTemplate
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from polly_utils import PollyVoiceData, NEURAL_ENGINE
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news_api_key = os.environ["NEWS_API_KEY"]
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tmdb_bearer_token = os.environ["TMDB_BEARER_TOKEN"]
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TOOLS_LIST = ['serpapi', 'wolfram-alpha', 'pal-math', 'pal-colored-objects', 'news-api', 'tmdb-api',
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'open-meteo-api'] # 'google-search'
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TOOLS_DEFAULT_LIST = ['serpapi', 'pal-math']
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BUG_FOUND_MSG = "Congratulations, you've found a bug in this application!"
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AUTH_ERR_MSG = "Please paste your OpenAI key. It is not necessary to hit a button or key after pasting it."
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MAX_TOKENS = 512
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# Pertains to Express-inator functionality
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NUM_WORDS_DEFAULT = 0
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MAX_WORDS = 400
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@@ -51,11 +66,13 @@ LANG_LEVEL_DEFAULT = "N/A"
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TRANSLATE_TO_DEFAULT = "N/A"
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LITERARY_STYLE_DEFAULT = "N/A"
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PROMPT_TEMPLATE = PromptTemplate(
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input_variables=["original_words", "num_words", "formality", "emotions", "lang_level", "translate_to",
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template="Restate {num_words}{formality}{emotions}{lang_level}{translate_to}{literary_style}the following: \n{original_words}\n",
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)
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POLLY_VOICE_DATA = PollyVoiceData()
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# Pertains to WHISPER functionality
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WHISPER_DETECT_LANG = "Detect language"
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@@ -87,6 +104,29 @@ def transcribe(aud_inp, whisper_lang):
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return result_text
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# Pertains to Express-inator functionality
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def transform_text(desc, express_chain, num_words, formality,
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anticipation_level, joy_level, trust_level,
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@@ -143,12 +183,15 @@ def transform_text(desc, express_chain, num_words, formality,
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translate_to_str = ""
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if translate_to != TRANSLATE_TO_DEFAULT:
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translate_to_str = "translated to " + (
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literary_style_str = ""
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if literary_style != LITERARY_STYLE_DEFAULT:
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if literary_style == "Prose":
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literary_style_str = "as prose, "
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elif literary_style == "Summary":
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literary_style_str = "as a summary, "
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elif literary_style == "Outline":
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literary_style_str = "as a haiku, "
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elif literary_style == "Limerick":
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literary_style_str = "as a limerick, "
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elif literary_style == "Joke":
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literary_style_str = "as a very funny joke with a setup and punchline, "
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elif literary_style == "Knock-knock":
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literary_style_str = "as a very funny knock-knock joke, "
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formatted_prompt = PROMPT_TEMPLATE.format(
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original_words=desc,
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def load_chain(tools_list, llm):
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chain = None
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express_chain = None
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if llm:
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print("\ntools_list", tools_list)
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tool_names = tools_list
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chain = initialize_agent(tools, llm, agent="conversational-react-description", verbose=True, memory=memory)
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express_chain = LLMChain(llm=llm, prompt=PROMPT_TEMPLATE, verbose=True)
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return chain, express_chain
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def set_openai_api_key(api_key):
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"""Set the api key and return chain.
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If no api_key, then None is returned.
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"""
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if api_key and api_key.startswith("sk-") and len(api_key) > 50:
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llm = OpenAI(temperature=0, max_tokens=MAX_TOKENS)
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os.environ["OPENAI_API_KEY"]
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def run_chain(chain, inp, capture_hidden_text):
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try:
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output = chain.run(input=inp)
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except AuthenticationError as ae:
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error_msg = AUTH_ERR_MSG
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except RateLimitError as rle:
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error_msg = "\n\nRateLimitError: " + str(rle)
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except ValueError as ve:
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try:
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output = chain.run(input=inp)
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except AuthenticationError as ae:
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output = AUTH_ERR_MSG
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except RateLimitError as rle:
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output = "\n\nRateLimitError: " + str(rle)
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except ValueError as ve:
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return output, hidden_text
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class ChatWrapper:
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def __init__(self):
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def __call__(
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self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain: Optional[ConversationChain],
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trace_chain: bool, speak_text: bool, monologue: bool, express_chain: Optional[LLMChain],
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num_words, formality, anticipation_level, joy_level, trust_level,
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fear_level, surprise_level, sadness_level, disgust_level, anger_level,
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lang_level, translate_to, literary_style
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):
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"""Execute the chat functionality."""
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self.lock.acquire()
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print("inp: " + inp)
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print("trace_chain: ", trace_chain)
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print("speak_text: ", speak_text)
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print("monologue: ", monologue)
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history = history or []
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# If chain is None, that is because no API key was provided.
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output = "Please paste your OpenAI key to use this
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"key after pasting it."
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hidden_text = output
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if chain
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# Set OpenAI key
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import openai
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openai.api_key = api_key
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if not monologue:
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else:
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output, hidden_text = inp, None
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text_to_display = hidden_text + "\n\n" + output
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history.append((inp, text_to_display))
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html_audio, temp_file = None, None
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if speak_text:
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except Exception as e:
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raise e
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finally:
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self.lock.release()
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return history, history, html_audio,
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chat = ChatWrapper()
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region_name=os.environ["AWS_DEFAULT_REGION"]
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).client('polly')
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voice_id, language_code, engine = POLLY_VOICE_DATA.get_voice(polly_language, "Female")
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if not voice_id:
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voice_id = "Joanna"
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language_code = "en-US"
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engine = NEURAL_ENGINE
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response = polly_client.synthesize_speech(
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return html_audio, "audios/tempfile.mp3"
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def
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headers = {"Authorization": f"Bearer {os.environ['EXHUMAN_API_KEY']}"}
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body = {
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'bot_name': 'Masahiro',
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'bot_response': words_to_speak,
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'
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}
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api_endpoint = "https://api.exh.ai/animations/v1/generate_lipsync"
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res = requests.post(api_endpoint, json=body, headers=headers)
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html_video = '<pre>no video</pre>'
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if isinstance(res.content, bytes):
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response_stream = io.BytesIO(res.content)
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with open('videos/tempfile.mp4', 'wb') as f:
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f.write(response_stream.read())
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temp_file = gr.File("videos/tempfile.mp4")
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temp_file_url = "/file=" + temp_file.value['name']
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html_video = f'<video width=
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else:
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print('video url unknown')
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return html_video, "videos/tempfile.mp4"
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def update_selected_tools(widget, state, llm):
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if widget:
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state = widget
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chain, express_chain = load_chain(state, llm)
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return state, llm, chain, express_chain
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def update_foo(widget, state):
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if widget:
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state = widget
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return state
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with gr.Blocks(css=".gradio-container {background-color: lightgray}") as block:
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llm_state = gr.State()
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history_state = gr.State()
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tools_list_state = gr.State(TOOLS_DEFAULT_LIST)
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trace_chain_state = gr.State(False)
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speak_text_state = gr.State(False)
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monologue_state = gr.State(False) # Takes the input and repeats it back to the user, optionally transforming it.
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# Pertains to Express-inator functionality
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num_words_state = gr.State(NUM_WORDS_DEFAULT)
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# Pertains to WHISPER functionality
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whisper_lang_state = gr.State(WHISPER_DETECT_LANG)
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with gr.Tab("Chat"):
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with gr.Row():
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with gr.Column():
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gr.HTML(
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"""<b><center>GPT + WolframAlpha + Whisper</center></b>
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<p><center>New feature
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openai_api_key_textbox = gr.Textbox(placeholder="Paste your OpenAI API key (sk-...)",
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show_label=False, lines=1, type='password'
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with gr.Row():
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with gr.Column(scale=1, min_width=
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my_file = gr.File(label="Upload a file", type="file", visible=False)
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tmp_file = gr.File(
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tmp_file_url = "/file=" + tmp_file.value['name']
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htm_video =
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video_html = gr.HTML(htm_video)
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# my_aud_file = gr.File(label="Audio file", type="file", visible=True)
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htm_audio = f'<audio><source src={tmp_aud_file_url} type="audio/mp3"></audio>'
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audio_html = gr.HTML(htm_audio)
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with gr.Column(scale=
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chatbot = gr.Chatbot()
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with gr.Row():
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interactive=True, streaming=False)
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audio_comp.change(transcribe, inputs=[audio_comp, whisper_lang_state], outputs=[message])
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gr.Examples(
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examples=["How many people live in Canada?",
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"What is 2 to the 30th power?",
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trace_chain_cb.change(update_foo, inputs=[trace_chain_cb, trace_chain_state],
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outputs=[trace_chain_state])
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speak_text_cb = gr.Checkbox(label="Speak text from agent", value=False)
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speak_text_cb.change(update_foo, inputs=[speak_text_cb, speak_text_state],
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monologue_cb = gr.Checkbox(label="Babel fish mode (translate/restate what you enter, no conversational agent)",
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value=False)
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monologue_cb.change(update_foo, inputs=[monologue_cb, monologue_state],
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outputs=[monologue_state])
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with gr.Tab("Whisper STT"):
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whisper_lang_radio = gr.Radio(label="Whisper speech-to-text language:", choices=[
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WHISPER_DETECT_LANG, "Arabic", "Arabic (Gulf)", "Catalan", "Chinese (Cantonese)", "Chinese (Mandarin)",
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"Korean", "Norwegian", "Polish",
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"Portuguese (Brazilian)", "Portuguese (European)", "Romanian", "Russian", "Spanish (European)",
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"Spanish (Mexican)", "Spanish (US)", "Swedish", "Turkish", "Ukrainian", "Welsh",
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"emojis", "Gen Z slang", "how the stereotypical Karen would say it", "Klingon",
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"Pirate", "Strange Planet expospeak technical talk", "Yoda"],
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value=TRANSLATE_TO_DEFAULT)
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with gr.Tab("Lit style"):
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literary_style_radio = gr.Radio(label="Literary style:", choices=[
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LITERARY_STYLE_DEFAULT, "Prose", "Summary", "Outline", "Bullets", "Poetry", "Haiku", "Limerick", "
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"Knock-knock"],
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value=LITERARY_STYLE_DEFAULT)
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literary_style_radio.change(update_foo,
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inputs=[num_words_slider, num_words_state],
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outputs=[num_words_state])
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gr.HTML("""
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<p>This application, developed by
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demonstrates a conversational
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When necessary, it leverages tools for complex math, searching the internet, and accessing news and weather.
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For faster inference without waiting in queue, you may duplicate the space.
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</p>""")
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message.submit(chat, inputs=[openai_api_key_textbox, message, history_state, chain_state, trace_chain_state,
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speak_text_state, monologue_state,
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express_chain_state, num_words_state, formality_state,
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anticipation_level_state, joy_level_state, trust_level_state, fear_level_state,
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surprise_level_state, sadness_level_state, disgust_level_state, anger_level_state,
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lang_level_state, translate_to_state, literary_style_state
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outputs=[chatbot, history_state, audio_html, tmp_aud_file, message])
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submit.click(chat, inputs=[openai_api_key_textbox, message, history_state, chain_state, trace_chain_state,
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speak_text_state, monologue_state,
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express_chain_state, num_words_state, formality_state,
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anticipation_level_state, joy_level_state, trust_level_state, fear_level_state,
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surprise_level_state, sadness_level_state, disgust_level_state, anger_level_state,
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lang_level_state, translate_to_state, literary_style_state
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outputs=[chatbot, history_state, audio_html, tmp_aud_file, message])
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inputs=[openai_api_key_textbox],
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outputs=[chain_state, express_chain_state, llm_state
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block.launch(debug=True)
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import io
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import os
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import ssl
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from contextlib import closing
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from typing import Optional, Tuple
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import datetime
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from langchain.prompts import PromptTemplate
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from polly_utils import PollyVoiceData, NEURAL_ENGINE
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34 |
+
from azure_utils import AzureVoiceData
|
35 |
+
|
36 |
+
# Pertains to question answering functionality
|
37 |
+
from langchain.embeddings.openai import OpenAIEmbeddings
|
38 |
+
from langchain.text_splitter import CharacterTextSplitter
|
39 |
+
from langchain.vectorstores.faiss import FAISS
|
40 |
+
from langchain.docstore.document import Document
|
41 |
+
from langchain.chains.question_answering import load_qa_chain
|
42 |
|
43 |
news_api_key = os.environ["NEWS_API_KEY"]
|
44 |
tmdb_bearer_token = os.environ["TMDB_BEARER_TOKEN"]
|
45 |
+
openai_api_key = os.environ["OPENAI_API_KEY"]
|
46 |
|
47 |
TOOLS_LIST = ['serpapi', 'wolfram-alpha', 'pal-math', 'pal-colored-objects', 'news-api', 'tmdb-api',
|
48 |
'open-meteo-api'] # 'google-search'
|
49 |
TOOLS_DEFAULT_LIST = ['serpapi', 'pal-math']
|
50 |
BUG_FOUND_MSG = "Congratulations, you've found a bug in this application!"
|
51 |
+
# AUTH_ERR_MSG = "Please paste your OpenAI key from openai.com to use this application. It is not necessary to hit a button or key after pasting it."
|
52 |
+
AUTH_ERR_MSG = "Please paste your OpenAI key from openai.com to use this application. "
|
53 |
MAX_TOKENS = 512
|
54 |
|
55 |
+
LOOPING_TALKING_HEAD = "videos/Masahiro.mp4"
|
56 |
+
TALKING_HEAD_WIDTH = "192"
|
57 |
+
MAX_TALKING_HEAD_TEXT_LENGTH = 155
|
58 |
+
|
59 |
# Pertains to Express-inator functionality
|
60 |
NUM_WORDS_DEFAULT = 0
|
61 |
MAX_WORDS = 400
|
|
|
66 |
TRANSLATE_TO_DEFAULT = "N/A"
|
67 |
LITERARY_STYLE_DEFAULT = "N/A"
|
68 |
PROMPT_TEMPLATE = PromptTemplate(
|
69 |
+
input_variables=["original_words", "num_words", "formality", "emotions", "lang_level", "translate_to",
|
70 |
+
"literary_style"],
|
71 |
template="Restate {num_words}{formality}{emotions}{lang_level}{translate_to}{literary_style}the following: \n{original_words}\n",
|
72 |
)
|
73 |
|
74 |
POLLY_VOICE_DATA = PollyVoiceData()
|
75 |
+
AZURE_VOICE_DATA = AzureVoiceData()
|
76 |
|
77 |
# Pertains to WHISPER functionality
|
78 |
WHISPER_DETECT_LANG = "Detect language"
|
|
|
104 |
return result_text
|
105 |
|
106 |
|
107 |
+
# Temporarily address Wolfram Alpha SSL certificate issue
|
108 |
+
ssl._create_default_https_context = ssl._create_unverified_context
|
109 |
+
|
110 |
+
|
111 |
+
# TEMPORARY FOR TESTING
|
112 |
+
def transcribe_dummy(aud_inp_tb, whisper_lang):
|
113 |
+
if aud_inp_tb is None:
|
114 |
+
return ""
|
115 |
+
# aud = whisper.load_audio(aud_inp)
|
116 |
+
# aud = whisper.pad_or_trim(aud)
|
117 |
+
# mel = whisper.log_mel_spectrogram(aud).to(WHISPER_MODEL.device)
|
118 |
+
# _, probs = WHISPER_MODEL.detect_language(mel)
|
119 |
+
# options = whisper.DecodingOptions()
|
120 |
+
# options = whisper.DecodingOptions(language="ja")
|
121 |
+
# result = whisper.decode(WHISPER_MODEL, mel, options)
|
122 |
+
result_text = "Whisper will detect language"
|
123 |
+
if whisper_lang != WHISPER_DETECT_LANG:
|
124 |
+
whisper_lang_code = POLLY_VOICE_DATA.get_whisper_lang_code(whisper_lang)
|
125 |
+
result_text = f"Whisper will use lang code: {whisper_lang_code}"
|
126 |
+
print("result_text", result_text)
|
127 |
+
return aud_inp_tb
|
128 |
+
|
129 |
+
|
130 |
# Pertains to Express-inator functionality
|
131 |
def transform_text(desc, express_chain, num_words, formality,
|
132 |
anticipation_level, joy_level, trust_level,
|
|
|
183 |
|
184 |
translate_to_str = ""
|
185 |
if translate_to != TRANSLATE_TO_DEFAULT:
|
186 |
+
translate_to_str = "translated to " + (
|
187 |
+
"" if lang_level == TRANSLATE_TO_DEFAULT else lang_level + " level ") + translate_to + ", "
|
188 |
|
189 |
literary_style_str = ""
|
190 |
if literary_style != LITERARY_STYLE_DEFAULT:
|
191 |
if literary_style == "Prose":
|
192 |
literary_style_str = "as prose, "
|
193 |
+
if literary_style == "Story":
|
194 |
+
literary_style_str = "as a story, "
|
195 |
elif literary_style == "Summary":
|
196 |
literary_style_str = "as a summary, "
|
197 |
elif literary_style == "Outline":
|
|
|
204 |
literary_style_str = "as a haiku, "
|
205 |
elif literary_style == "Limerick":
|
206 |
literary_style_str = "as a limerick, "
|
207 |
+
elif literary_style == "Rap":
|
208 |
+
literary_style_str = "as a rap, "
|
209 |
elif literary_style == "Joke":
|
210 |
literary_style_str = "as a very funny joke with a setup and punchline, "
|
211 |
elif literary_style == "Knock-knock":
|
212 |
literary_style_str = "as a very funny knock-knock joke, "
|
213 |
+
elif literary_style == "FAQ":
|
214 |
+
literary_style_str = "as a FAQ with several questions and answers, "
|
215 |
|
216 |
formatted_prompt = PROMPT_TEMPLATE.format(
|
217 |
original_words=desc,
|
|
|
247 |
def load_chain(tools_list, llm):
|
248 |
chain = None
|
249 |
express_chain = None
|
250 |
+
memory = None
|
251 |
if llm:
|
252 |
print("\ntools_list", tools_list)
|
253 |
tool_names = tools_list
|
|
|
257 |
|
258 |
chain = initialize_agent(tools, llm, agent="conversational-react-description", verbose=True, memory=memory)
|
259 |
express_chain = LLMChain(llm=llm, prompt=PROMPT_TEMPLATE, verbose=True)
|
260 |
+
return chain, express_chain, memory
|
|
|
261 |
|
262 |
|
263 |
def set_openai_api_key(api_key):
|
264 |
"""Set the api key and return chain.
|
265 |
If no api_key, then None is returned.
|
266 |
"""
|
267 |
+
# if api_key and api_key.startswith("sk-") and len(api_key) > 50:
|
268 |
+
if "OPENAI_API_KEY" not in os.environ:
|
269 |
+
print("OpenAI Key Not found")
|
270 |
+
else:
|
271 |
+
# os.environ["OPENAI_API_KEY"] = api_key
|
272 |
+
# print("\n\n ++++++++++++++ Setting OpenAI API key ++++++++++++++ \n\n")
|
273 |
+
# print(str(datetime.datetime.now()) + ": Before OpenAI, OPENAI_API_KEY length: " + str(
|
274 |
+
# len(os.environ["OPENAI_API_KEY"])))
|
275 |
llm = OpenAI(temperature=0, max_tokens=MAX_TOKENS)
|
276 |
+
# print(str(datetime.datetime.now()) + ": After OpenAI, OPENAI_API_KEY length: " + str(
|
277 |
+
# len(os.environ["OPENAI_API_KEY"])))
|
278 |
+
chain, express_chain, memory = load_chain(TOOLS_DEFAULT_LIST, llm)
|
279 |
+
|
280 |
+
# Pertains to question answering functionality
|
281 |
+
embeddings = OpenAIEmbeddings()
|
282 |
+
qa_chain = load_qa_chain(OpenAI(temperature=0), chain_type="stuff")
|
283 |
+
|
284 |
+
# print(str(datetime.datetime.now()) + ": After load_chain, OPENAI_API_KEY length: " + str(
|
285 |
+
# len(os.environ["OPENAI_API_KEY"])))
|
286 |
+
# os.environ["OPENAI_API_KEY"] = ""
|
287 |
+
return chain, express_chain, llm, embeddings, qa_chain, memory
|
288 |
+
return None, None, None, None, None, None
|
289 |
|
290 |
|
291 |
def run_chain(chain, inp, capture_hidden_text):
|
|
|
300 |
try:
|
301 |
output = chain.run(input=inp)
|
302 |
except AuthenticationError as ae:
|
303 |
+
error_msg = AUTH_ERR_MSG + str(datetime.datetime.now()) + ". " + str(ae)
|
304 |
+
print("error_msg", error_msg)
|
305 |
except RateLimitError as rle:
|
306 |
error_msg = "\n\nRateLimitError: " + str(rle)
|
307 |
except ValueError as ve:
|
|
|
338 |
try:
|
339 |
output = chain.run(input=inp)
|
340 |
except AuthenticationError as ae:
|
341 |
+
output = AUTH_ERR_MSG + str(datetime.datetime.now()) + ". " + str(ae)
|
342 |
+
print("output", output)
|
343 |
except RateLimitError as rle:
|
344 |
output = "\n\nRateLimitError: " + str(rle)
|
345 |
except ValueError as ve:
|
|
|
352 |
return output, hidden_text
|
353 |
|
354 |
|
355 |
+
def reset_memory(history, memory):
|
356 |
+
memory.clear()
|
357 |
+
history = []
|
358 |
+
return history, history, memory
|
359 |
+
|
360 |
+
|
361 |
class ChatWrapper:
|
362 |
|
363 |
def __init__(self):
|
|
|
365 |
|
366 |
def __call__(
|
367 |
self, api_key: str, inp: str, history: Optional[Tuple[str, str]], chain: Optional[ConversationChain],
|
368 |
+
trace_chain: bool, speak_text: bool, talking_head: bool, monologue: bool, express_chain: Optional[LLMChain],
|
369 |
num_words, formality, anticipation_level, joy_level, trust_level,
|
370 |
fear_level, surprise_level, sadness_level, disgust_level, anger_level,
|
371 |
+
lang_level, translate_to, literary_style, qa_chain, docsearch, use_embeddings
|
372 |
):
|
373 |
"""Execute the chat functionality."""
|
374 |
self.lock.acquire()
|
|
|
377 |
print("inp: " + inp)
|
378 |
print("trace_chain: ", trace_chain)
|
379 |
print("speak_text: ", speak_text)
|
380 |
+
print("talking_head: ", talking_head)
|
381 |
print("monologue: ", monologue)
|
382 |
history = history or []
|
383 |
# If chain is None, that is because no API key was provided.
|
384 |
+
output = "Please paste your OpenAI key from openai.com to use this app. " + str(datetime.datetime.now())
|
|
|
385 |
hidden_text = output
|
386 |
|
387 |
+
if chain:
|
388 |
# Set OpenAI key
|
389 |
import openai
|
390 |
openai.api_key = api_key
|
391 |
if not monologue:
|
392 |
+
if use_embeddings:
|
393 |
+
if inp and inp.strip() != "":
|
394 |
+
if docsearch:
|
395 |
+
docs = docsearch.similarity_search(inp)
|
396 |
+
output = str(qa_chain.run(input_documents=docs, question=inp))
|
397 |
+
else:
|
398 |
+
output, hidden_text = "Please supply some text in the the Embeddings tab.", None
|
399 |
+
else:
|
400 |
+
output, hidden_text = "What's on your mind?", None
|
401 |
+
else:
|
402 |
+
output, hidden_text = run_chain(chain, inp, capture_hidden_text=trace_chain)
|
403 |
else:
|
404 |
output, hidden_text = inp, None
|
405 |
|
|
|
413 |
text_to_display = hidden_text + "\n\n" + output
|
414 |
history.append((inp, text_to_display))
|
415 |
|
416 |
+
html_video, temp_file, html_audio, temp_aud_file = None, None, None, None
|
|
|
417 |
if speak_text:
|
418 |
+
if talking_head:
|
419 |
+
if len(output) <= MAX_TALKING_HEAD_TEXT_LENGTH:
|
420 |
+
html_video, temp_file = do_html_video_speak(output, translate_to)
|
421 |
+
else:
|
422 |
+
temp_file = LOOPING_TALKING_HEAD
|
423 |
+
html_video = create_html_video(temp_file, TALKING_HEAD_WIDTH)
|
424 |
+
html_audio, temp_aud_file = do_html_audio_speak(output, translate_to)
|
425 |
+
else:
|
426 |
+
html_audio, temp_aud_file = do_html_audio_speak(output, translate_to)
|
427 |
+
else:
|
428 |
+
if talking_head:
|
429 |
+
temp_file = LOOPING_TALKING_HEAD
|
430 |
+
html_video = create_html_video(temp_file, TALKING_HEAD_WIDTH)
|
431 |
+
else:
|
432 |
+
# html_audio, temp_aud_file = do_html_audio_speak(output, translate_to)
|
433 |
+
# html_video = create_html_video(temp_file, "128")
|
434 |
+
pass
|
435 |
+
|
436 |
except Exception as e:
|
437 |
raise e
|
438 |
finally:
|
439 |
self.lock.release()
|
440 |
+
return history, history, html_video, temp_file, html_audio, temp_aud_file, ""
|
441 |
+
# return history, history, html_audio, temp_aud_file, ""
|
442 |
|
443 |
|
444 |
chat = ChatWrapper()
|
|
|
451 |
region_name=os.environ["AWS_DEFAULT_REGION"]
|
452 |
).client('polly')
|
453 |
|
454 |
+
# voice_id, language_code, engine = POLLY_VOICE_DATA.get_voice(polly_language, "Female")
|
455 |
+
voice_id, language_code, engine = POLLY_VOICE_DATA.get_voice(polly_language, "Male")
|
456 |
if not voice_id:
|
457 |
+
# voice_id = "Joanna"
|
458 |
+
voice_id = "Matthew"
|
459 |
language_code = "en-US"
|
460 |
engine = NEURAL_ENGINE
|
461 |
response = polly_client.synthesize_speech(
|
|
|
491 |
return html_audio, "audios/tempfile.mp3"
|
492 |
|
493 |
|
494 |
+
def create_html_video(file_name, width):
|
495 |
+
temp_file_url = "/file=" + tmp_file.value['name']
|
496 |
+
html_video = f'<video width={width} height={width} autoplay muted loop><source src={temp_file_url} type="video/mp4" poster="Masahiro.png"></video>'
|
497 |
+
return html_video
|
498 |
+
|
499 |
+
|
500 |
+
def do_html_video_speak(words_to_speak, azure_language):
|
501 |
+
azure_voice = AZURE_VOICE_DATA.get_voice(azure_language, "Male")
|
502 |
+
if not azure_voice:
|
503 |
+
azure_voice = "en-US-ChristopherNeural"
|
504 |
+
|
505 |
headers = {"Authorization": f"Bearer {os.environ['EXHUMAN_API_KEY']}"}
|
506 |
body = {
|
507 |
'bot_name': 'Masahiro',
|
508 |
'bot_response': words_to_speak,
|
509 |
+
'azure_voice': azure_voice,
|
510 |
+
'azure_style': 'friendly',
|
511 |
+
'animation_pipeline': 'high_speed',
|
512 |
}
|
513 |
api_endpoint = "https://api.exh.ai/animations/v1/generate_lipsync"
|
514 |
res = requests.post(api_endpoint, json=body, headers=headers)
|
515 |
+
print("res.status_code: ", res.status_code)
|
516 |
|
517 |
html_video = '<pre>no video</pre>'
|
518 |
if isinstance(res.content, bytes):
|
519 |
response_stream = io.BytesIO(res.content)
|
520 |
+
print("len(res.content)): ", len(res.content))
|
521 |
+
|
522 |
with open('videos/tempfile.mp4', 'wb') as f:
|
523 |
f.write(response_stream.read())
|
524 |
temp_file = gr.File("videos/tempfile.mp4")
|
525 |
temp_file_url = "/file=" + temp_file.value['name']
|
526 |
+
html_video = f'<video width={TALKING_HEAD_WIDTH} height={TALKING_HEAD_WIDTH} autoplay><source src={temp_file_url} type="video/mp4" poster="Masahiro.png"></video>'
|
527 |
else:
|
528 |
print('video url unknown')
|
529 |
return html_video, "videos/tempfile.mp4"
|
|
|
532 |
def update_selected_tools(widget, state, llm):
|
533 |
if widget:
|
534 |
state = widget
|
535 |
+
chain, express_chain, memory = load_chain(state, llm)
|
536 |
return state, llm, chain, express_chain
|
537 |
|
538 |
|
539 |
+
def update_talking_head(widget, state):
|
540 |
+
if widget:
|
541 |
+
state = widget
|
542 |
+
|
543 |
+
video_html_talking_head = create_html_video(LOOPING_TALKING_HEAD, TALKING_HEAD_WIDTH)
|
544 |
+
return state, video_html_talking_head
|
545 |
+
else:
|
546 |
+
# return state, create_html_video(LOOPING_TALKING_HEAD, "32")
|
547 |
+
return None, "<pre></pre>"
|
548 |
+
|
549 |
+
|
550 |
def update_foo(widget, state):
|
551 |
if widget:
|
552 |
state = widget
|
553 |
return state
|
554 |
|
555 |
|
556 |
+
# Pertains to question answering functionality
|
557 |
+
def update_embeddings(embeddings_text, embeddings, qa_chain):
|
558 |
+
if embeddings_text:
|
559 |
+
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
|
560 |
+
texts = text_splitter.split_text(embeddings_text)
|
561 |
+
|
562 |
+
docsearch = FAISS.from_texts(texts, embeddings)
|
563 |
+
print("Embeddings updated")
|
564 |
+
return docsearch
|
565 |
+
|
566 |
+
|
567 |
+
# Pertains to question answering functionality
|
568 |
+
def update_use_embeddings(widget, state):
|
569 |
+
if widget:
|
570 |
+
state = widget
|
571 |
+
return state
|
572 |
+
|
573 |
+
|
574 |
with gr.Blocks(css=".gradio-container {background-color: lightgray}") as block:
|
575 |
llm_state = gr.State()
|
576 |
history_state = gr.State()
|
|
|
579 |
tools_list_state = gr.State(TOOLS_DEFAULT_LIST)
|
580 |
trace_chain_state = gr.State(False)
|
581 |
speak_text_state = gr.State(False)
|
582 |
+
talking_head_state = gr.State(True)
|
583 |
monologue_state = gr.State(False) # Takes the input and repeats it back to the user, optionally transforming it.
|
584 |
+
memory_state = gr.State()
|
585 |
|
586 |
# Pertains to Express-inator functionality
|
587 |
num_words_state = gr.State(NUM_WORDS_DEFAULT)
|
|
|
601 |
# Pertains to WHISPER functionality
|
602 |
whisper_lang_state = gr.State(WHISPER_DETECT_LANG)
|
603 |
|
604 |
+
# Pertains to question answering functionality
|
605 |
+
embeddings_state = gr.State()
|
606 |
+
qa_chain_state = gr.State()
|
607 |
+
docsearch_state = gr.State()
|
608 |
+
use_embeddings_state = gr.State(False)
|
609 |
+
|
610 |
with gr.Tab("Chat"):
|
611 |
with gr.Row():
|
612 |
with gr.Column():
|
613 |
gr.HTML(
|
614 |
"""<b><center>GPT + WolframAlpha + Whisper</center></b>
|
615 |
+
<p><center>New feature: <b>Embeddings</b></center></p>""")
|
616 |
|
617 |
openai_api_key_textbox = gr.Textbox(placeholder="Paste your OpenAI API key (sk-...)",
|
618 |
+
show_label=False, lines=1, type='password',
|
619 |
+
value=openai_api_key,
|
620 |
+
visible=False,)
|
621 |
|
622 |
with gr.Row():
|
623 |
+
with gr.Column(scale=1, min_width=TALKING_HEAD_WIDTH, visible=True):
|
624 |
+
speak_text_cb = gr.Checkbox(label="Enable speech", value=False)
|
625 |
+
speak_text_cb.change(update_foo, inputs=[speak_text_cb, speak_text_state],
|
626 |
+
outputs=[speak_text_state])
|
627 |
+
|
628 |
my_file = gr.File(label="Upload a file", type="file", visible=False)
|
629 |
+
tmp_file = gr.File(LOOPING_TALKING_HEAD, visible=False)
|
630 |
+
# tmp_file_url = "/file=" + tmp_file.value['name']
|
631 |
+
htm_video = create_html_video(LOOPING_TALKING_HEAD, TALKING_HEAD_WIDTH)
|
632 |
video_html = gr.HTML(htm_video)
|
633 |
|
634 |
# my_aud_file = gr.File(label="Audio file", type="file", visible=True)
|
|
|
637 |
htm_audio = f'<audio><source src={tmp_aud_file_url} type="audio/mp3"></audio>'
|
638 |
audio_html = gr.HTML(htm_audio)
|
639 |
|
640 |
+
with gr.Column(scale=7):
|
641 |
chatbot = gr.Chatbot()
|
642 |
|
643 |
with gr.Row():
|
|
|
652 |
interactive=True, streaming=False)
|
653 |
audio_comp.change(transcribe, inputs=[audio_comp, whisper_lang_state], outputs=[message])
|
654 |
|
655 |
+
# TEMPORARY FOR TESTING
|
656 |
+
# with gr.Row():
|
657 |
+
# audio_comp_tb = gr.Textbox(label="Just say it!", lines=1)
|
658 |
+
# audio_comp_tb.submit(transcribe_dummy, inputs=[audio_comp_tb, whisper_lang_state], outputs=[message])
|
659 |
+
|
660 |
gr.Examples(
|
661 |
examples=["How many people live in Canada?",
|
662 |
"What is 2 to the 30th power?",
|
|
|
680 |
trace_chain_cb.change(update_foo, inputs=[trace_chain_cb, trace_chain_state],
|
681 |
outputs=[trace_chain_state])
|
682 |
|
683 |
+
# speak_text_cb = gr.Checkbox(label="Speak text from agent", value=False)
|
684 |
+
# speak_text_cb.change(update_foo, inputs=[speak_text_cb, speak_text_state],
|
685 |
+
# outputs=[speak_text_state])
|
686 |
+
|
687 |
+
talking_head_cb = gr.Checkbox(label="Show talking head", value=True)
|
688 |
+
talking_head_cb.change(update_talking_head, inputs=[talking_head_cb, talking_head_state],
|
689 |
+
outputs=[talking_head_state, video_html])
|
690 |
|
691 |
monologue_cb = gr.Checkbox(label="Babel fish mode (translate/restate what you enter, no conversational agent)",
|
692 |
value=False)
|
693 |
monologue_cb.change(update_foo, inputs=[monologue_cb, monologue_state],
|
694 |
outputs=[monologue_state])
|
695 |
|
696 |
+
reset_btn = gr.Button(value="Reset chat", variant="secondary").style(full_width=False)
|
697 |
+
reset_btn.click(reset_memory, inputs=[history_state, memory_state], outputs=[chatbot, history_state, memory_state])
|
698 |
+
|
699 |
with gr.Tab("Whisper STT"):
|
700 |
whisper_lang_radio = gr.Radio(label="Whisper speech-to-text language:", choices=[
|
701 |
WHISPER_DETECT_LANG, "Arabic", "Arabic (Gulf)", "Catalan", "Chinese (Cantonese)", "Chinese (Mandarin)",
|
|
|
727 |
"Korean", "Norwegian", "Polish",
|
728 |
"Portuguese (Brazilian)", "Portuguese (European)", "Romanian", "Russian", "Spanish (European)",
|
729 |
"Spanish (Mexican)", "Spanish (US)", "Swedish", "Turkish", "Ukrainian", "Welsh",
|
730 |
+
"emojis", "Gen Z slang", "how the stereotypical Karen would say it", "Klingon", "Neanderthal",
|
731 |
"Pirate", "Strange Planet expospeak technical talk", "Yoda"],
|
732 |
value=TRANSLATE_TO_DEFAULT)
|
733 |
|
|
|
745 |
|
746 |
with gr.Tab("Lit style"):
|
747 |
literary_style_radio = gr.Radio(label="Literary style:", choices=[
|
748 |
+
LITERARY_STYLE_DEFAULT, "Prose", "Story", "Summary", "Outline", "Bullets", "Poetry", "Haiku", "Limerick", "Rap",
|
749 |
+
"Joke", "Knock-knock", "FAQ"],
|
750 |
value=LITERARY_STYLE_DEFAULT)
|
751 |
|
752 |
literary_style_radio.change(update_foo,
|
|
|
817 |
inputs=[num_words_slider, num_words_state],
|
818 |
outputs=[num_words_state])
|
819 |
|
820 |
+
with gr.Tab("Embeddings"):
|
821 |
+
embeddings_text_box = gr.Textbox(label="Enter text for embeddings and hit Create:",
|
822 |
+
lines=20)
|
823 |
+
|
824 |
+
with gr.Row():
|
825 |
+
use_embeddings_cb = gr.Checkbox(label="Use embeddings", value=False)
|
826 |
+
use_embeddings_cb.change(update_use_embeddings, inputs=[use_embeddings_cb, use_embeddings_state],
|
827 |
+
outputs=[use_embeddings_state])
|
828 |
+
|
829 |
+
embeddings_text_submit = gr.Button(value="Create", variant="secondary").style(full_width=False)
|
830 |
+
embeddings_text_submit.click(update_embeddings,
|
831 |
+
inputs=[embeddings_text_box, embeddings_state, qa_chain_state],
|
832 |
+
outputs=[docsearch_state])
|
833 |
+
|
834 |
gr.HTML("""
|
835 |
+
<p>This application, developed by <a href='https://www.linkedin.com/in/javafxpert/'>James L. Weaver</a>,
|
836 |
+
demonstrates a conversational agent implemented with OpenAI GPT-3.5 and LangChain.
|
837 |
When necessary, it leverages tools for complex math, searching the internet, and accessing news and weather.
|
838 |
+
Uses talking heads from <a href='https://exh.ai/'>Ex-Human</a>.
|
839 |
For faster inference without waiting in queue, you may duplicate the space.
|
840 |
</p>""")
|
841 |
|
842 |
+
gr.HTML("""
|
843 |
+
<form action="https://www.paypal.com/donate" method="post" target="_blank">
|
844 |
+
<input type="hidden" name="business" value="AK8BVNALBXSPQ" />
|
845 |
+
<input type="hidden" name="no_recurring" value="0" />
|
846 |
+
<input type="hidden" name="item_name" value="Please consider helping to defray the cost of APIs such as SerpAPI and WolframAlpha that this app uses." />
|
847 |
+
<input type="hidden" name="currency_code" value="USD" />
|
848 |
+
<input type="image" src="https://www.paypalobjects.com/en_US/i/btn/btn_donate_LG.gif" border="0" name="submit" title="PayPal - The safer, easier way to pay online!" alt="Donate with PayPal button" />
|
849 |
+
<img alt="" border="0" src="https://www.paypal.com/en_US/i/scr/pixel.gif" width="1" height="1" />
|
850 |
+
</form>
|
851 |
+
""")
|
852 |
+
|
853 |
+
gr.HTML("""<center>
|
854 |
+
<a href="https://huggingface.co/spaces/JavaFXpert/Chat-GPT-LangChain?duplicate=true">
|
855 |
+
<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
|
856 |
+
Powered by <a href='https://github.com/hwchase17/langchain'>LangChain 🦜️🔗</a>
|
857 |
+
</center>""")
|
858 |
|
859 |
message.submit(chat, inputs=[openai_api_key_textbox, message, history_state, chain_state, trace_chain_state,
|
860 |
+
speak_text_state, talking_head_state, monologue_state,
|
861 |
express_chain_state, num_words_state, formality_state,
|
862 |
anticipation_level_state, joy_level_state, trust_level_state, fear_level_state,
|
863 |
surprise_level_state, sadness_level_state, disgust_level_state, anger_level_state,
|
864 |
+
lang_level_state, translate_to_state, literary_style_state,
|
865 |
+
qa_chain_state, docsearch_state, use_embeddings_state],
|
866 |
+
outputs=[chatbot, history_state, video_html, my_file, audio_html, tmp_aud_file, message])
|
867 |
+
# outputs=[chatbot, history_state, audio_html, tmp_aud_file, message])
|
868 |
|
869 |
submit.click(chat, inputs=[openai_api_key_textbox, message, history_state, chain_state, trace_chain_state,
|
870 |
+
speak_text_state, talking_head_state, monologue_state,
|
871 |
express_chain_state, num_words_state, formality_state,
|
872 |
anticipation_level_state, joy_level_state, trust_level_state, fear_level_state,
|
873 |
surprise_level_state, sadness_level_state, disgust_level_state, anger_level_state,
|
874 |
+
lang_level_state, translate_to_state, literary_style_state,
|
875 |
+
qa_chain_state, docsearch_state, use_embeddings_state],
|
876 |
+
outputs=[chatbot, history_state, video_html, my_file, audio_html, tmp_aud_file, message])
|
877 |
+
# outputs=[chatbot, history_state, audio_html, tmp_aud_file, message])
|
878 |
|
879 |
+
block.load(set_openai_api_key,
|
880 |
inputs=[openai_api_key_textbox],
|
881 |
+
outputs=[chain_state, express_chain_state, llm_state, embeddings_state,
|
882 |
+
qa_chain_state, memory_state])
|
883 |
|
884 |
+
block.launch(debug=True)
|