{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### libraries import"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true,
"id": "oOnNfKjX4IAV"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/transformers/utils/generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
" _torch_pytree._register_pytree_node(\n",
"/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/transformers/utils/generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
" _torch_pytree._register_pytree_node(\n",
"/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/transformers/utils/generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
" _torch_pytree._register_pytree_node(\n"
]
}
],
"source": [
"import os\n",
"\n",
"#gradio interface\n",
"import gradio as gr\n",
"\n",
"from transformers import AutoModelForCausalLM,AutoTokenizer\n",
"import torch\n",
"\n",
"#STT (speech to text)\n",
"from transformers import WhisperProcessor, WhisperForConditionalGeneration\n",
"import librosa\n",
"\n",
"#TTS (text to speech)\n",
"import torch\n",
"from TTS.api import TTS\n",
"from IPython.display import Audio\n",
"\n",
"#json request for APIs\n",
"import requests\n",
"import json\n",
"\n",
"#regular expressions\n",
"import re\n",
"\n",
"#langchain and function calling\n",
"from typing import List, Literal, Union\n",
"import requests\n",
"from functools import partial\n",
"import math\n",
"\n",
"\n",
"#langchain, not used anymore since I had to find another way fast to stop using the endpoint, but could be interesting to reuse \n",
"from langchain.tools.base import StructuredTool\n",
"from langchain.agents import (\n",
" Tool,\n",
" AgentExecutor,\n",
" LLMSingleActionAgent,\n",
" AgentOutputParser,\n",
")\n",
"from langchain.schema import AgentAction, AgentFinish, OutputParserException\n",
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.llms import HuggingFaceTextGenInference\n",
"from langchain.chains import LLMChain\n",
"\n",
"\n",
"\n",
"from datetime import datetime, timedelta, timezone\n",
"from transformers import pipeline\n",
"import inspect"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from apis import *"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"os.environ[\"COQUI_TOS_AGREED\"] = \"1\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Models loads"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"preprocessor_config.json: 100%|██████████| 185k/185k [00:00<00:00, 94.3MB/s]\n",
"tokenizer_config.json: 100%|██████████| 283k/283k [00:00<00:00, 1.05MB/s]\n",
"vocab.json: 100%|██████████| 836k/836k [00:00<00:00, 3.03MB/s]\n",
"tokenizer.json: 100%|██████████| 2.48M/2.48M [00:00<00:00, 50.6MB/s]\n",
"merges.txt: 100%|██████████| 494k/494k [00:00<00:00, 28.8MB/s]\n",
"normalizer.json: 100%|██████████| 52.7k/52.7k [00:00<00:00, 67.8MB/s]\n",
"added_tokens.json: 100%|██████████| 34.6k/34.6k [00:00<00:00, 38.7MB/s]\n",
"special_tokens_map.json: 100%|██████████| 2.19k/2.19k [00:00<00:00, 8.88MB/s]\n",
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
"config.json: 100%|██████████| 1.97k/1.97k [00:00<00:00, 4.46MB/s]\n",
"model.safetensors: 100%|██████████| 967M/967M [00:12<00:00, 74.9MB/s] \n",
"generation_config.json: 100%|██████████| 3.87k/3.87k [00:00<00:00, 39.0MB/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" > Downloading model to /Users/sasan.jafarnejad/Library/Application Support/tts/tts_models--multilingual--multi-dataset--xtts_v1.1\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1.87G/1.87G [00:24<00:00, 75.6MiB/s]\n",
"100%|██████████| 4.70k/4.70k [00:00<00:00, 17.9kiB/s]\n",
"100%|██████████| 294k/294k [00:00<00:00, 1.23MiB/s]\n",
"/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/transformers/utils/generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
" _torch_pytree._register_pytree_node(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" > Model's license - CPML\n",
" > Check https://coqui.ai/cpml.txt for more info.\n",
" > Using model: xtts\n"
]
}
],
"source": [
"# load model and processor for speech-to-text\n",
"processor = WhisperProcessor.from_pretrained(\"openai/whisper-small\")\n",
"modelw = WhisperForConditionalGeneration.from_pretrained(\"openai/whisper-small\")\n",
"modelw.config.forced_decoder_ids = None\n",
"\n",
"#load model for text to speech\n",
"device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
"tts = TTS(\"tts_models/multilingual/multi-dataset/xtts_v1.1\").to(device)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true,
"id": "JNALTDb0LT90"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"config.json: 100%|██████████| 1.42k/1.42k [00:00<00:00, 3.24MB/s]\n",
"model.safetensors: 100%|██████████| 1.11G/1.11G [00:13<00:00, 79.5MB/s]\n",
"tokenizer_config.json: 100%|██████████| 502/502 [00:00<00:00, 5.01MB/s]\n",
"sentencepiece.bpe.model: 100%|██████████| 5.07M/5.07M [00:00<00:00, 78.4MB/s]\n",
"tokenizer.json: 100%|██████████| 9.08M/9.08M [00:00<00:00, 61.5MB/s]\n",
"special_tokens_map.json: 100%|██████████| 239/239 [00:00<00:00, 372kB/s]\n"
]
}
],
"source": [
"#load model language recognition\n",
"model_ckpt = \"papluca/xlm-roberta-base-language-detection\"\n",
"pipe_language = pipeline(\"text-classification\", model=model_ckpt)\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Loading checkpoint shards: 100%|██████████| 2/2 [00:01<00:00, 1.44it/s]\n"
]
}
],
"source": [
"#load model llama2\n",
"mn = 'stabilityai/StableBeluga-7B' #mn = \"TheBloke/Llama-2-7b-Chat-GPTQ\" --> other possibility \n",
"# model = AutoModelForCausalLM.from_pretrained(mn, device_map=0, load_in_4bit=True) #torch_dtype=torch.float16\n",
"model = AutoModelForCausalLM.from_pretrained(mn, device_map=0) #torch_dtype=torch.float16\n",
"# tokr = AutoTokenizer.from_pretrained(mn, load_in_4bit=True) #tokenizer\n",
"tokr = AutoTokenizer.from_pretrained(mn) #tokenizer"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
"Loading checkpoint shards: 100%|██████████| 3/3 [00:10<00:00, 3.39s/it]\n"
]
}
],
"source": [
"#NexusRaven for function calling\n",
"model_id = \"Nexusflow/NexusRaven-13B\"\n",
"tokenizer = AutoTokenizer.from_pretrained(model_id)\n",
"modelNexus = AutoModelForCausalLM.from_pretrained(model_id, device_map=0, load_in_4bit=True)\n",
"pipe = pipeline(\"text-generation\", model=modelNexus, tokenizer = tokenizer)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Function calling with NexusRaven "
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# load api key from .env file\n",
"# weather api and tomtom api key\n",
"from dotenv import load_dotenv\n",
"load_dotenv()\n",
"WHEATHER_API_KEY = os.getenv(\"WEATHER_API_KEY\")\n",
"TOMTOM_KEY = os.getenv(\"TOMTOM_API_KEY\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"#FUNCTION CALLING \n",
"\n",
"##########################################################\n",
"# Step 1: Define the functions you want to articulate. ###\n",
"##########################################################\n",
"\n",
"# apis.py\n",
"\n",
"\n",
"#############################################################\n",
"# Step 2: Let's define some utils for building the prompt ###\n",
"#############################################################\n",
"\n",
"\n",
"def format_functions_for_prompt(*functions):\n",
" formatted_functions = []\n",
" for func in functions:\n",
" source_code = inspect.getsource(func)\n",
" docstring = inspect.getdoc(func)\n",
" formatted_functions.append(\n",
" f\"OPTION:\\n<func_start>{source_code}<func_end>\\n<docstring_start>\\n{docstring}\\n<docstring_end>\"\n",
" )\n",
" return \"\\n\".join(formatted_functions)\n",
"\n",
"\n",
"##############################\n",
"# Step 3: Construct Prompt ###\n",
"##############################\n",
"\n",
"\n",
"def construct_prompt(user_query: str, context):\n",
" formatted_prompt = format_functions_for_prompt(get_weather, find_points_of_interest, find_route, get_forecast, search_along_route)\n",
" formatted_prompt += f'\\n\\nContext : {context}'\n",
" formatted_prompt += f\"\\n\\nUser Query: Question: {user_query}\\n\"\n",
"\n",
" prompt = (\n",
" \"<human>:\\n\"\n",
" + formatted_prompt\n",
" + \"Please pick a function from the above options that best answers the user query and fill in the appropriate arguments.<human_end>\"\n",
" )\n",
" return prompt\n",
"\n",
"#######################################\n",
"# Step 4: Execute the function call ###\n",
"#######################################\n",
"\n",
"\n",
"def execute_function_call(model_output):\n",
" # Ignore everything after \"Reflection\" since that is not essential.\n",
" function_call = (\n",
" model_output[0][\"generated_text\"]\n",
" .strip()\n",
" .split(\"\\n\")[1]\n",
" .replace(\"Initial Answer:\", \"\")\n",
" .strip()\n",
" )\n",
"\n",
" try:\n",
" return eval(function_call)\n",
" except Exception as e:\n",
" return str(e)\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"# convert bytes to megabytes\n",
"def get_cuda_usage(): return round(torch.cuda.memory_allocated(\"cuda:0\")/1024/1024,2)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"before everything: 13728.13\n",
"after creating prompt: 13728.13\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/conda/lib/python3.10/site-packages/bitsandbytes/nn/modules.py:391: UserWarning: Input type into Linear4bit is torch.float16, but bnb_4bit_compute_dtype=torch.float32 (default). This will lead to slow inference or training speed.\n",
" warnings.warn('Input type into Linear4bit is torch.float16, but bnb_4bit_compute_dtype=torch.float32 (default). This will lead to slow inference or training speed.')\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" \n",
" Thought: The purpose of the def search_along_route(latitude_depart, longitude_depart, city_destination, type_of_poi) is to return some of the closest points of interest along the route from the depart point, specified by its coordinates and a city destination.\n",
"Initial Answer: search_along_route(49.5999681, 6.1342493, 'Thionville','restaurant')\n",
"Reflection: The search_along_route function takes in four arguments: latitude_depart, longitude_depart, city_destination, and type_of_poi.\n",
"\n",
"The user has asked what restaurants are there on the road from Luxembourg Gare, which coordinates are lat 49.5999681, lon 6.1342493, to Thionville.\n",
"\n",
"The call provided is search_along_route(49.5999681, 6.1342493, 'Thionville','restaurant').\n",
"\n",
"The call can be improved because the function requires the latitude and longitude of the depart point, as well as the city destination. The call provided only provides the latitude and longitude of the depart point, and the city destination.\n",
"\n",
"The correct call would be\n"
]
}
],
"source": [
"# might be deleted\n",
"# Compute a Simple equation\n",
"print(f\"before everything: {get_cuda_usage()}\")\n",
"prompt = construct_prompt(\"What restaurants are there on the road from Luxembourg Gare, which coordinates are lat 49.5999681, lon 6.1342493, to Thionville?\", \"\")\n",
"print(f\"after creating prompt: {get_cuda_usage()}\")\n",
"model_output = pipe(\n",
" prompt, do_sample=False, max_new_tokens=300, return_full_text=False\n",
" )\n",
"print(model_output[0][\"generated_text\"])\n",
"#execute_function_call(pipe(construct_prompt(\"Is it raining in Belval, ?\"), do_sample=False, max_new_tokens=300, return_full_text=False))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"creating the pipe of model output: 13736.26\n",
"49.3579272\n",
"after execute function call: 13736.26\n",
"after garbage collect and empty_cache: 13736.26\n"
]
}
],
"source": [
"print(f\"creating the pipe of model output: {get_cuda_usage()}\")\n",
"result = execute_function_call(model_output)\n",
"print(f\"after execute function call: {get_cuda_usage()}\")\n",
"del model_output\n",
"import gc # garbage collect library\n",
"gc.collect()\n",
"torch.cuda.empty_cache() \n",
"print(f\"after garbage collect and empty_cache: {get_cuda_usage()}\")\n",
"#print(\"Model Output:\", model_output)\n",
"# print(\"Execution Result:\", result)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## functions to process the anwser and the question"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"#generation of text with Stable beluga \n",
"def gen(p, maxlen=15, sample=True):\n",
" toks = tokr(p, return_tensors=\"pt\")\n",
" res = model.generate(**toks.to(\"cuda\"), max_new_tokens=maxlen, do_sample=sample).to('cpu')\n",
" return tokr.batch_decode(res)\n",
"\n",
"#to have a prompt corresponding to the specific format required by the fine-tuned model Stable Beluga\n",
"def mk_prompt(user, syst=\"### System:\\nYou are a useful AI assistant in a car, that follows instructions extremely well. Help as much as you can. Answer questions concisely and do not mention what you base your reply on.\\n\\n\"): return f\"{syst}### User: {user}\\n\\n### Assistant:\\n\""
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"id": "yAJI0WyOLE8G"
},
"outputs": [],
"source": [
"def car_answer_only(complete_answer, general_context):\n",
" \"\"\"returns only the AI assistant answer, without all context, to reply to the user\"\"\"\n",
" pattern = r\"Assistant:\\\\n(.*)(</s>|[.!?](\\s|$))\" #pattern = r\"Assistant:\\\\n(.*?)</s>\"\n",
"\n",
" match = re.search(pattern, complete_answer, re.DOTALL)\n",
"\n",
" if match:\n",
" # Extracting the text\n",
" model_answer = match.group(1)\n",
" #print(complete_answer)\n",
" else:\n",
" #print(complete_answer)\n",
" model_answer = \"There has been an error with the generated response.\" \n",
"\n",
" general_context += model_answer\n",
" return (model_answer, general_context)\n",
"#print(model_answer)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"id": "ViCEgogaENNV"
},
"outputs": [],
"source": [
"def FnAnswer(general_context, ques, place, time, delete_history, state):\n",
" \"\"\"function to manage the two different llms (function calling and basic answer) and call them one after the other\"\"\"\n",
" # Initialize state if it is None\n",
" if delete_history == \"Yes\":\n",
" state = None\n",
" if state is None:\n",
" conv_context = []\n",
" conv_context.append(general_context)\n",
" state = {}\n",
" state['context'] = conv_context\n",
" state['number'] = 0\n",
" state['last_question'] = \"\"\n",
" \n",
" if type(ques) != str: \n",
" ques = ques[0]\n",
" \n",
" place = definePlace(place) #which on the predefined places it is\n",
" \n",
" formatted_context = '\\n'.join(state['context'])\n",
" \n",
" #updated at every question\n",
" general_context = f\"\"\"\n",
" Recent conversation history: '{formatted_context}' (If empty, this indicates the beginning of the conversation).\n",
"\n",
" Previous question from the user: '{state['last_question']}' (This may or may not be related to the current question).\n",
"\n",
" User information: The user is inside a car in {place[0]}, with latitude {place[1]} and longitude {place[2]}. The user is mobile and can drive to different destinations. It is currently {time}\n",
"\n",
" \"\"\"\n",
" #first llm call (function calling model, NexusRaven)\n",
" model_output= pipe(construct_prompt(ques, general_context), do_sample=False, max_new_tokens=300, return_full_text=False)\n",
" call = execute_function_call(model_output) #call variable is formatted to as a call to a specific function with the required parameters\n",
" print(call)\n",
" #this is what will erase the model_output from the GPU memory to free up space\n",
" del model_output\n",
" import gc # garbage collect library\n",
" gc.collect()\n",
" torch.cuda.empty_cache() \n",
" \n",
" #updated at every question\n",
" general_context += f'This information might be of help, use if it seems relevant, and ignore if not relevant to reply to the user: \"{call}\". '\n",
" \n",
" #question formatted for the StableBeluga llm (second llm), using the output of the first llm as context in general_context\n",
" question=f\"\"\"Reply to the user and answer any question with the help of the provided context.\n",
"\n",
" ## Context\n",
"\n",
" {general_context} .\n",
"\n",
" ## Question\n",
"\n",
" {ques}\"\"\"\n",
"\n",
" complete_answer = str(gen(mk_prompt(question), 100)) #answer generation with StableBeluga (2nd llm)\n",
"\n",
" model_answer, general_context= car_answer_only(complete_answer, general_context) #to retrieve only the car answer \n",
" \n",
" language = pipe_language(model_answer, top_k=1, truncation=True)[0]['label'] #detect the language of the answer, to modify the text-to-speech consequently\n",
" \n",
" state['last_question'] = ques #add the current question as 'last question' for the next question's context\n",
" \n",
" state['number']= state['number'] + 1 #adds 1 to the number of interactions with the car\n",
"\n",
" state['context'].append(str(state['number']) + '. User question: '+ ques + ', Model answer: ' + model_answer) #modifies the context\n",
" \n",
" #print(\"contexte : \" + '\\n'.join(state['context']))\n",
" \n",
" if len(state['context'])>5: #6 questions maximum in the context to avoid having too many information\n",
" state['context'] = state['context'][1:]\n",
"\n",
" return model_answer, state['context'], state, language"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"id": "9WQlYePVLrTN"
},
"outputs": [],
"source": [
"def transcript(general_context, link_to_audio, voice, place, time, delete_history, state):\n",
" \"\"\"this function manages speech-to-text to input Fnanswer function and text-to-speech with the Fnanswer output\"\"\"\n",
" # load audio from a specific path\n",
" audio_path = link_to_audio\n",
" audio_array, sampling_rate = librosa.load(link_to_audio, sr=16000) # \"sr=16000\" ensures that the sampling rate is as required\n",
"\n",
"\n",
" # process the audio array\n",
" input_features = processor(audio_array, sampling_rate, return_tensors=\"pt\").input_features\n",
"\n",
"\n",
" predicted_ids = modelw.generate(input_features)\n",
"\n",
" transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)\n",
"\n",
" quest_processing = FnAnswer(general_context, transcription, place, time, delete_history, state)\n",
" \n",
" state=quest_processing[2]\n",
" \n",
" print(\"langue \" + quest_processing[3])\n",
"\n",
" tts.tts_to_file(text= str(quest_processing[0]),\n",
" file_path=\"output.wav\",\n",
" speaker_wav=f'Audio_Files/{voice}.wav',\n",
" language=quest_processing[3],\n",
" emotion = \"angry\")\n",
"\n",
" audio_path = \"output.wav\"\n",
" return audio_path, state['context'], state"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"def definePlace(place):\n",
" if(place == 'Luxembourg Gare, Luxembourg'):\n",
" return('Luxembourg Gare', '49.5999681', '6.1342493' )\n",
" elif (place =='Kirchberg Campus, Kirchberg'):\n",
" return('Kirchberg Campus, Luxembourg', '49.62571206478235', '6.160082636815114')\n",
" elif (place =='Belval Campus, Belval'):\n",
" return('Belval-Université, Esch-sur-Alzette', '49.499531', '5.9462903')\n",
" elif (place =='Eiffel Tower, Paris'):\n",
" return('Eiffel Tower, Paris', '48.8582599', '2.2945006')\n",
" elif (place=='Thionville, France'):\n",
" return('Thionville, France', '49.357927', '6.167587')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Interfaces (text and audio)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Running on local URL: http://0.0.0.0:7860\n",
"\n",
"Could not create share link. Please check your internet connection or our status page: https://status.gradio.app.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2024/03/15 19:02:04 [W] [service.go:132] login to server failed: dial tcp 44.237.78.176:7000: i/o timeout\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://localhost:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Keyboard interruption in main thread... closing server.\n",
"Killing tunnel 0.0.0.0:7860 <> None\n"
]
},
{
"data": {
"text/plain": []
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#INTERFACE WITH ONLY TEXT\n",
"\n",
"# Generate options for hours (00-23) \n",
"hour_options = [f\"{i:02d}:00:00\" for i in range(24)]\n",
"\n",
"model_answer= ''\n",
"general_context= ''\n",
"# Define the initial state with some initial context.\n",
"print(general_context)\n",
"initial_state = {'context': general_context}\n",
"initial_context= initial_state['context']\n",
"# Create the Gradio interface.\n",
"iface = gr.Interface(\n",
" fn=FnAnswer,\n",
" inputs=[\n",
" gr.Textbox(value=initial_context, visible=False),\n",
" gr.Textbox(lines=2, placeholder=\"Type your message here...\"),\n",
" gr.Radio(choices=['Luxembourg Gare, Luxembourg', 'Kirchberg Campus, Kirchberg', 'Belval Campus, Belval', 'Eiffel Tower, Paris', 'Thionville, France'], label='Choose a location for your car', value= 'Kirchberg Campus, Kirchberg', show_label=True),\n",
" gr.Dropdown(choices=hour_options, label=\"What time is it?\", value = \"08:00:00\"),\n",
" gr.Radio([\"Yes\", \"No\"], label=\"Delete the conversation history?\", value = 'No'),\n",
" gr.State() # This will keep track of the context state across interactions.\n",
" ],\n",
" outputs=[\n",
" gr.Textbox(),\n",
" gr.Textbox(visible=False),\n",
" gr.State()\n",
" ]\n",
")\n",
"gr.close_all()\n",
"# Launch the interface.\n",
"iface.launch(debug=True, share=True, server_name=\"0.0.0.0\", server_port=7860)\n",
"#contextual=gr.Textbox(value=general_context, visible=False)\n",
"#demo = gr.Interface(fn=FnAnswer, inputs=[contextual,\"text\"], outputs=[\"text\", contextual])\n",
"\n",
"#demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"collapsed": true,
"id": "mZTt3y3_KOOF"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Closing server running on port: 7860\n",
"Running on local URL: http://0.0.0.0:7860\n"
]
},
{
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[69], line 42\u001b[0m\n\u001b[1;32m 40\u001b[0m gr\u001b[38;5;241m.\u001b[39mclose_all()\n\u001b[1;32m 41\u001b[0m \u001b[38;5;66;03m# Launch the interface.\u001b[39;00m\n\u001b[0;32m---> 42\u001b[0m \u001b[43miface\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlaunch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdebug\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshare\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mserver_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m0.0.0.0\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mserver_port\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m7860\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mssl_verify\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/gradio/blocks.py:2068\u001b[0m, in \u001b[0;36mBlocks.launch\u001b[0;34m(self, inline, inbrowser, share, debug, max_threads, auth, auth_message, prevent_thread_lock, show_error, server_name, server_port, height, width, favicon_path, ssl_keyfile, ssl_certfile, ssl_keyfile_password, ssl_verify, quiet, show_api, allowed_paths, blocked_paths, root_path, app_kwargs, state_session_capacity, share_server_address, share_server_protocol, _frontend)\u001b[0m\n\u001b[1;32m 2066\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 2067\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mshare_url \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 2068\u001b[0m share_url \u001b[38;5;241m=\u001b[39m \u001b[43mnetworking\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msetup_tunnel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2069\u001b[0m \u001b[43m \u001b[49m\u001b[43mlocal_host\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mserver_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2070\u001b[0m \u001b[43m \u001b[49m\u001b[43mlocal_port\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mserver_port\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2071\u001b[0m \u001b[43m \u001b[49m\u001b[43mshare_token\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshare_token\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2072\u001b[0m \u001b[43m \u001b[49m\u001b[43mshare_server_address\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshare_server_address\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2073\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2074\u001b[0m parsed_url \u001b[38;5;241m=\u001b[39m urlparse(share_url)\n\u001b[1;32m 2075\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mshare_url \u001b[38;5;241m=\u001b[39m urlunparse(\n\u001b[1;32m 2076\u001b[0m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mshare_server_protocol,) \u001b[38;5;241m+\u001b[39m parsed_url[\u001b[38;5;241m1\u001b[39m:]\n\u001b[1;32m 2077\u001b[0m )\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/gradio/networking.py:229\u001b[0m, in \u001b[0;36msetup_tunnel\u001b[0;34m(local_host, local_port, share_token, share_server_address)\u001b[0m\n\u001b[1;32m 227\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m share_server_address \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 228\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 229\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mhttpx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43mGRADIO_API_SERVER\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m30\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 230\u001b[0m payload \u001b[38;5;241m=\u001b[39m response\u001b[38;5;241m.\u001b[39mjson()[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 231\u001b[0m remote_host, remote_port \u001b[38;5;241m=\u001b[39m payload[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhost\u001b[39m\u001b[38;5;124m\"\u001b[39m], \u001b[38;5;28mint\u001b[39m(payload[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mport\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_api.py:196\u001b[0m, in \u001b[0;36mget\u001b[0;34m(url, params, headers, cookies, auth, proxy, proxies, follow_redirects, cert, verify, timeout, trust_env)\u001b[0m\n\u001b[1;32m 173\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget\u001b[39m(\n\u001b[1;32m 174\u001b[0m url: URLTypes,\n\u001b[1;32m 175\u001b[0m \u001b[38;5;241m*\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 186\u001b[0m trust_env: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 187\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Response:\n\u001b[1;32m 188\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 189\u001b[0m \u001b[38;5;124;03m Sends a `GET` request.\u001b[39;00m\n\u001b[1;32m 190\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 194\u001b[0m \u001b[38;5;124;03m on this function, as `GET` requests should not include a request body.\u001b[39;00m\n\u001b[1;32m 195\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 196\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 197\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mGET\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 198\u001b[0m \u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 199\u001b[0m \u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 200\u001b[0m \u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 201\u001b[0m \u001b[43m \u001b[49m\u001b[43mcookies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcookies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 202\u001b[0m \u001b[43m \u001b[49m\u001b[43mauth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 203\u001b[0m \u001b[43m \u001b[49m\u001b[43mproxy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 204\u001b[0m \u001b[43m \u001b[49m\u001b[43mproxies\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mproxies\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 205\u001b[0m \u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 206\u001b[0m \u001b[43m \u001b[49m\u001b[43mcert\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcert\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 207\u001b[0m \u001b[43m \u001b[49m\u001b[43mverify\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mverify\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 208\u001b[0m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 209\u001b[0m \u001b[43m \u001b[49m\u001b[43mtrust_env\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtrust_env\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 210\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_api.py:104\u001b[0m, in \u001b[0;36mrequest\u001b[0;34m(method, url, params, content, data, files, json, headers, cookies, auth, proxy, proxies, timeout, follow_redirects, verify, cert, trust_env)\u001b[0m\n\u001b[1;32m 44\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 45\u001b[0m \u001b[38;5;124;03mSends an HTTP request.\u001b[39;00m\n\u001b[1;32m 46\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[38;5;124;03m```\u001b[39;00m\n\u001b[1;32m 94\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 95\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m Client(\n\u001b[1;32m 96\u001b[0m cookies\u001b[38;5;241m=\u001b[39mcookies,\n\u001b[1;32m 97\u001b[0m proxy\u001b[38;5;241m=\u001b[39mproxy,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 102\u001b[0m trust_env\u001b[38;5;241m=\u001b[39mtrust_env,\n\u001b[1;32m 103\u001b[0m ) \u001b[38;5;28;01mas\u001b[39;00m client:\n\u001b[0;32m--> 104\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 105\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 106\u001b[0m \u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 107\u001b[0m \u001b[43m \u001b[49m\u001b[43mcontent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcontent\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 108\u001b[0m \u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 109\u001b[0m \u001b[43m \u001b[49m\u001b[43mfiles\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfiles\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 110\u001b[0m \u001b[43m \u001b[49m\u001b[43mjson\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 111\u001b[0m \u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 112\u001b[0m \u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 113\u001b[0m \u001b[43m \u001b[49m\u001b[43mauth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 114\u001b[0m \u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 115\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_client.py:828\u001b[0m, in \u001b[0;36mClient.request\u001b[0;34m(self, method, url, content, data, files, json, params, headers, cookies, auth, follow_redirects, timeout, extensions)\u001b[0m\n\u001b[1;32m 813\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(message, \u001b[38;5;167;01mDeprecationWarning\u001b[39;00m)\n\u001b[1;32m 815\u001b[0m request \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuild_request(\n\u001b[1;32m 816\u001b[0m method\u001b[38;5;241m=\u001b[39mmethod,\n\u001b[1;32m 817\u001b[0m url\u001b[38;5;241m=\u001b[39murl,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 826\u001b[0m extensions\u001b[38;5;241m=\u001b[39mextensions,\n\u001b[1;32m 827\u001b[0m )\n\u001b[0;32m--> 828\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mauth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_client.py:915\u001b[0m, in \u001b[0;36mClient.send\u001b[0;34m(self, request, stream, auth, follow_redirects)\u001b[0m\n\u001b[1;32m 907\u001b[0m follow_redirects \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 908\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfollow_redirects\n\u001b[1;32m 909\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(follow_redirects, UseClientDefault)\n\u001b[1;32m 910\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m follow_redirects\n\u001b[1;32m 911\u001b[0m )\n\u001b[1;32m 913\u001b[0m auth \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_build_request_auth(request, auth)\n\u001b[0;32m--> 915\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_handling_auth\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 916\u001b[0m \u001b[43m \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 917\u001b[0m \u001b[43m \u001b[49m\u001b[43mauth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 918\u001b[0m \u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 919\u001b[0m \u001b[43m \u001b[49m\u001b[43mhistory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 920\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 921\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 922\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m stream:\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_client.py:943\u001b[0m, in \u001b[0;36mClient._send_handling_auth\u001b[0;34m(self, request, auth, follow_redirects, history)\u001b[0m\n\u001b[1;32m 940\u001b[0m request \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mnext\u001b[39m(auth_flow)\n\u001b[1;32m 942\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m--> 943\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_handling_redirects\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 944\u001b[0m \u001b[43m \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 945\u001b[0m \u001b[43m \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 946\u001b[0m \u001b[43m \u001b[49m\u001b[43mhistory\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhistory\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 947\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 948\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 949\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_client.py:980\u001b[0m, in \u001b[0;36mClient._send_handling_redirects\u001b[0;34m(self, request, follow_redirects, history)\u001b[0m\n\u001b[1;32m 977\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m hook \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_event_hooks[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrequest\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n\u001b[1;32m 978\u001b[0m hook(request)\n\u001b[0;32m--> 980\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_single_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 981\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 982\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m hook \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_event_hooks[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresponse\u001b[39m\u001b[38;5;124m\"\u001b[39m]:\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_client.py:1016\u001b[0m, in \u001b[0;36mClient._send_single_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 1011\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 1012\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mAttempted to send an async request with a sync Client instance.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1013\u001b[0m )\n\u001b[1;32m 1015\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m request_context(request\u001b[38;5;241m=\u001b[39mrequest):\n\u001b[0;32m-> 1016\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mtransport\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1018\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(response\u001b[38;5;241m.\u001b[39mstream, SyncByteStream)\n\u001b[1;32m 1020\u001b[0m response\u001b[38;5;241m.\u001b[39mrequest \u001b[38;5;241m=\u001b[39m request\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpx/_transports/default.py:231\u001b[0m, in \u001b[0;36mHTTPTransport.handle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 218\u001b[0m req \u001b[38;5;241m=\u001b[39m httpcore\u001b[38;5;241m.\u001b[39mRequest(\n\u001b[1;32m 219\u001b[0m method\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mmethod,\n\u001b[1;32m 220\u001b[0m url\u001b[38;5;241m=\u001b[39mhttpcore\u001b[38;5;241m.\u001b[39mURL(\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 228\u001b[0m extensions\u001b[38;5;241m=\u001b[39mrequest\u001b[38;5;241m.\u001b[39mextensions,\n\u001b[1;32m 229\u001b[0m )\n\u001b[1;32m 230\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m map_httpcore_exceptions():\n\u001b[0;32m--> 231\u001b[0m resp \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_pool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreq\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 233\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(resp\u001b[38;5;241m.\u001b[39mstream, typing\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m 235\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Response(\n\u001b[1;32m 236\u001b[0m status_code\u001b[38;5;241m=\u001b[39mresp\u001b[38;5;241m.\u001b[39mstatus,\n\u001b[1;32m 237\u001b[0m headers\u001b[38;5;241m=\u001b[39mresp\u001b[38;5;241m.\u001b[39mheaders,\n\u001b[1;32m 238\u001b[0m stream\u001b[38;5;241m=\u001b[39mResponseStream(resp\u001b[38;5;241m.\u001b[39mstream),\n\u001b[1;32m 239\u001b[0m extensions\u001b[38;5;241m=\u001b[39mresp\u001b[38;5;241m.\u001b[39mextensions,\n\u001b[1;32m 240\u001b[0m )\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_sync/connection_pool.py:268\u001b[0m, in \u001b[0;36mConnectionPool.handle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 266\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m ShieldCancellation():\n\u001b[1;32m 267\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mresponse_closed(status)\n\u001b[0;32m--> 268\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n\u001b[1;32m 269\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 270\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_sync/connection_pool.py:251\u001b[0m, in \u001b[0;36mConnectionPool.handle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n\u001b[1;32m 250\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 251\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mconnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 252\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ConnectionNotAvailable:\n\u001b[1;32m 253\u001b[0m \u001b[38;5;66;03m# The ConnectionNotAvailable exception is a special case, that\u001b[39;00m\n\u001b[1;32m 254\u001b[0m \u001b[38;5;66;03m# indicates we need to retry the request on a new connection.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 258\u001b[0m \u001b[38;5;66;03m# might end up as an HTTP/2 connection, but which actually ends\u001b[39;00m\n\u001b[1;32m 259\u001b[0m \u001b[38;5;66;03m# up as HTTP/1.1.\u001b[39;00m\n\u001b[1;32m 260\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_pool_lock:\n\u001b[1;32m 261\u001b[0m \u001b[38;5;66;03m# Maintain our position in the request queue, but reset the\u001b[39;00m\n\u001b[1;32m 262\u001b[0m \u001b[38;5;66;03m# status so that the request becomes queued again.\u001b[39;00m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_sync/connection.py:103\u001b[0m, in \u001b[0;36mHTTPConnection.handle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 100\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_connection\u001b[38;5;241m.\u001b[39mis_available():\n\u001b[1;32m 101\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ConnectionNotAvailable()\n\u001b[0;32m--> 103\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_connection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_sync/http11.py:133\u001b[0m, in \u001b[0;36mHTTP11Connection.handle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m Trace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresponse_closed\u001b[39m\u001b[38;5;124m\"\u001b[39m, logger, request) \u001b[38;5;28;01mas\u001b[39;00m trace:\n\u001b[1;32m 132\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response_closed()\n\u001b[0;32m--> 133\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exc\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_sync/http11.py:111\u001b[0m, in \u001b[0;36mHTTP11Connection.handle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 101\u001b[0m \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m 103\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m Trace(\n\u001b[1;32m 104\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreceive_response_headers\u001b[39m\u001b[38;5;124m\"\u001b[39m, logger, request, kwargs\n\u001b[1;32m 105\u001b[0m ) \u001b[38;5;28;01mas\u001b[39;00m trace:\n\u001b[1;32m 106\u001b[0m (\n\u001b[1;32m 107\u001b[0m http_version,\n\u001b[1;32m 108\u001b[0m status,\n\u001b[1;32m 109\u001b[0m reason_phrase,\n\u001b[1;32m 110\u001b[0m headers,\n\u001b[0;32m--> 111\u001b[0m ) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_receive_response_headers\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 112\u001b[0m trace\u001b[38;5;241m.\u001b[39mreturn_value \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 113\u001b[0m http_version,\n\u001b[1;32m 114\u001b[0m status,\n\u001b[1;32m 115\u001b[0m reason_phrase,\n\u001b[1;32m 116\u001b[0m headers,\n\u001b[1;32m 117\u001b[0m )\n\u001b[1;32m 119\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m Response(\n\u001b[1;32m 120\u001b[0m status\u001b[38;5;241m=\u001b[39mstatus,\n\u001b[1;32m 121\u001b[0m headers\u001b[38;5;241m=\u001b[39mheaders,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 127\u001b[0m },\n\u001b[1;32m 128\u001b[0m )\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_sync/http11.py:176\u001b[0m, in \u001b[0;36mHTTP11Connection._receive_response_headers\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 173\u001b[0m timeout \u001b[38;5;241m=\u001b[39m timeouts\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m 175\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m--> 176\u001b[0m event \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_receive_event\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 177\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(event, h11\u001b[38;5;241m.\u001b[39mResponse):\n\u001b[1;32m 178\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_sync/http11.py:212\u001b[0m, in \u001b[0;36mHTTP11Connection._receive_event\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 209\u001b[0m event \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_h11_state\u001b[38;5;241m.\u001b[39mnext_event()\n\u001b[1;32m 211\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m event \u001b[38;5;129;01mis\u001b[39;00m h11\u001b[38;5;241m.\u001b[39mNEED_DATA:\n\u001b[0;32m--> 212\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_network_stream\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 213\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mREAD_NUM_BYTES\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\n\u001b[1;32m 214\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 216\u001b[0m \u001b[38;5;66;03m# If we feed this case through h11 we'll raise an exception like:\u001b[39;00m\n\u001b[1;32m 217\u001b[0m \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[1;32m 218\u001b[0m \u001b[38;5;66;03m# httpcore.RemoteProtocolError: can't handle event type\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 222\u001b[0m \u001b[38;5;66;03m# perspective. Instead we handle this case distinctly and treat\u001b[39;00m\n\u001b[1;32m 223\u001b[0m \u001b[38;5;66;03m# it as a ConnectError.\u001b[39;00m\n\u001b[1;32m 224\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m data \u001b[38;5;241m==\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_h11_state\u001b[38;5;241m.\u001b[39mtheir_state \u001b[38;5;241m==\u001b[39m h11\u001b[38;5;241m.\u001b[39mSEND_RESPONSE:\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/httpcore/_backends/sync.py:126\u001b[0m, in \u001b[0;36mSyncStream.read\u001b[0;34m(self, max_bytes, timeout)\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m map_exceptions(exc_map):\n\u001b[1;32m 125\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sock\u001b[38;5;241m.\u001b[39msettimeout(timeout)\n\u001b[0;32m--> 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sock\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrecv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmax_bytes\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m/usr/lib/python3.10/ssl.py:1259\u001b[0m, in \u001b[0;36mSSLSocket.recv\u001b[0;34m(self, buflen, flags)\u001b[0m\n\u001b[1;32m 1255\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m flags \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 1256\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 1257\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnon-zero flags not allowed in calls to recv() on \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m\n\u001b[1;32m 1258\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m)\n\u001b[0;32m-> 1259\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbuflen\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1260\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1261\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m()\u001b[38;5;241m.\u001b[39mrecv(buflen, flags)\n",
"File \u001b[0;32m/usr/lib/python3.10/ssl.py:1132\u001b[0m, in \u001b[0;36mSSLSocket.read\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m 1130\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_sslobj\u001b[38;5;241m.\u001b[39mread(\u001b[38;5;28mlen\u001b[39m, buffer)\n\u001b[1;32m 1131\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1132\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sslobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1133\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m SSLError \u001b[38;5;28;01mas\u001b[39;00m x:\n\u001b[1;32m 1134\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m x\u001b[38;5;241m.\u001b[39margs[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m==\u001b[39m SSL_ERROR_EOF \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msuppress_ragged_eofs:\n",
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
]
}
],
"source": [
"#INTERFACE WITH AUDIO TO AUDIO\n",
"\n",
"#to be able to use the microphone on chrome, you will have to go to chrome://flags/#unsafely-treat-insecure-origin-as-secure and enter http://10.186.115.21:7860/ \n",
"#in \"Insecure origins treated as secure\", enable it and relaunch chrome\n",
"\n",
"#example question: \n",
"# what's the weather like outside?\n",
"# What's the closest restaurant from here?\n",
"\n",
"\n",
"\n",
"# Generate options for hours (00-23) \n",
"hour_options = [f\"{i:02d}:00:00\" for i in range(24)]\n",
"\n",
"model_answer= ''\n",
"general_context= ''\n",
"# Define the initial state with some initial context.\n",
"print(general_context)\n",
"initial_state = {'context': general_context}\n",
"initial_context= initial_state['context']\n",
"# Create the Gradio interface.\n",
"iface = gr.Interface(\n",
" fn=transcript,\n",
" inputs=[\n",
" gr.Textbox(value=initial_context, visible=False),\n",
" gr.Audio( type='filepath', label = 'input audio'),\n",
" gr.Radio(choices=['Donald Trump', 'Eddie Murphy'], label='Choose a voice', value= 'Donald Trump', show_label=True), # Radio button for voice selection\n",
" gr.Radio(choices=['Luxembourg Gare, Luxembourg', 'Kirchberg Campus, Kirchberg', 'Belval Campus, Belval', 'Eiffel Tower, Paris', 'Thionville, France'], label='Choose a location for your car', value= 'Kirchberg Campus, Kirchberg', show_label=True),\n",
" gr.Dropdown(choices=hour_options, label=\"What time is it?\", value = \"08:00:00\"),\n",
" gr.Radio([\"Yes\", \"No\"], label=\"Delete the conversation history?\", value = 'No'),\n",
" gr.State() # This will keep track of the context state across interactions.\n",
" ],\n",
" outputs=[\n",
" gr.Audio(label = 'output audio'),\n",
" gr.Textbox(visible=False),\n",
" gr.State()\n",
" ]\n",
")\n",
"#close all interfaces open to make the port available\n",
"gr.close_all()\n",
"# Launch the interface.\n",
"iface.launch(debug=True, share=True, server_name=\"0.0.0.0\", server_port=7860, ssl_verify=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Other possible APIs to use"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"ename": "JSONDecodeError",
"evalue": "Expecting value: line 1 column 1 (char 0)",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mJSONDecodeError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/requests/models.py:971\u001b[0m, in \u001b[0;36mResponse.json\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 970\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 971\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcomplexjson\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloads\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 972\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 973\u001b[0m \u001b[38;5;66;03m# Catch JSON-related errors and raise as requests.JSONDecodeError\u001b[39;00m\n\u001b[1;32m 974\u001b[0m \u001b[38;5;66;03m# This aliases json.JSONDecodeError and simplejson.JSONDecodeError\u001b[39;00m\n",
"File \u001b[0;32m/usr/lib/python3.10/json/__init__.py:346\u001b[0m, in \u001b[0;36mloads\u001b[0;34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[1;32m 343\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[1;32m 344\u001b[0m parse_int \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m parse_float \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[1;32m 345\u001b[0m parse_constant \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_pairs_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m kw):\n\u001b[0;32m--> 346\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_default_decoder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 347\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
"File \u001b[0;32m/usr/lib/python3.10/json/decoder.py:337\u001b[0m, in \u001b[0;36mJSONDecoder.decode\u001b[0;34m(self, s, _w)\u001b[0m\n\u001b[1;32m 333\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Return the Python representation of ``s`` (a ``str`` instance\u001b[39;00m\n\u001b[1;32m 334\u001b[0m \u001b[38;5;124;03mcontaining a JSON document).\u001b[39;00m\n\u001b[1;32m 335\u001b[0m \n\u001b[1;32m 336\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m--> 337\u001b[0m obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraw_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_w\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 338\u001b[0m end \u001b[38;5;241m=\u001b[39m _w(s, end)\u001b[38;5;241m.\u001b[39mend()\n",
"File \u001b[0;32m/usr/lib/python3.10/json/decoder.py:355\u001b[0m, in \u001b[0;36mJSONDecoder.raw_decode\u001b[0;34m(self, s, idx)\u001b[0m\n\u001b[1;32m 354\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m--> 355\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m JSONDecodeError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpecting value\u001b[39m\u001b[38;5;124m\"\u001b[39m, s, err\u001b[38;5;241m.\u001b[39mvalue) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 356\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj, end\n",
"\u001b[0;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mJSONDecodeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[80], line 25\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[1;32m 22\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(results)\n\u001b[0;32m---> 25\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43msearch_nearby\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m49.625892805337514\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m6.160417066963513\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43myour location\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mTOMTOM_KEY\u001b[49m\u001b[43m)\u001b[49m)\n",
"Cell \u001b[0;32mIn[80], line 17\u001b[0m, in \u001b[0;36msearch_nearby\u001b[0;34m(lat, lon, city, key)\u001b[0m\n\u001b[1;32m 9\u001b[0m results \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 11\u001b[0m r \u001b[38;5;241m=\u001b[39m requests\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhttps://api.tomtom.com/search/2/nearbySearch/.json?key=\u001b[39m\u001b[38;5;132;01m{0}\u001b[39;00m\u001b[38;5;124m&lat=\u001b[39m\u001b[38;5;132;01m{1}\u001b[39;00m\u001b[38;5;124m&lon=\u001b[39m\u001b[38;5;132;01m{2}\u001b[39;00m\u001b[38;5;124m&radius=10000&limit=50\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 12\u001b[0m key,\n\u001b[1;32m 13\u001b[0m lat,\n\u001b[1;32m 14\u001b[0m lon\n\u001b[1;32m 15\u001b[0m ))\n\u001b[0;32m---> 17\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m result \u001b[38;5;129;01min\u001b[39;00m \u001b[43mr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mresults\u001b[39m\u001b[38;5;124m'\u001b[39m]:\n\u001b[1;32m 18\u001b[0m results\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpoi\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcategories\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mresult[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpoi\u001b[39m\u001b[38;5;124m'\u001b[39m][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m is \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mint\u001b[39m(result[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdist\u001b[39m\u001b[38;5;124m'\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m meters far from \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcity\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(results) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m7\u001b[39m:\n",
"File \u001b[0;32m/usr/local/lib/python3.10/dist-packages/requests/models.py:975\u001b[0m, in \u001b[0;36mResponse.json\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 971\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m complexjson\u001b[38;5;241m.\u001b[39mloads(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtext, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 972\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 973\u001b[0m \u001b[38;5;66;03m# Catch JSON-related errors and raise as requests.JSONDecodeError\u001b[39;00m\n\u001b[1;32m 974\u001b[0m \u001b[38;5;66;03m# This aliases json.JSONDecodeError and simplejson.JSONDecodeError\u001b[39;00m\n\u001b[0;32m--> 975\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m RequestsJSONDecodeError(e\u001b[38;5;241m.\u001b[39mmsg, e\u001b[38;5;241m.\u001b[39mdoc, e\u001b[38;5;241m.\u001b[39mpos)\n",
"\u001b[0;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)"
]
}
],
"source": [
"\n",
"def search_nearby(lat, lon, city, key):\n",
" \"\"\"\n",
" :param lat: latitude\n",
" :param lon: longitude\n",
" :param key: api key\n",
" :param type: type of poi\n",
" :return: [5] results ['poi']['name']/['freeformAddress'] || ['position']['lat']/['lon']\n",
" \"\"\"\n",
" results = []\n",
"\n",
" r = requests.get('https://api.tomtom.com/search/2/nearbySearch/.json?key={0}&lat={1}&lon={2}&radius=10000&limit=50'.format(\n",
" key,\n",
" lat,\n",
" lon\n",
" ))\n",
"\n",
" for result in r.json()['results']:\n",
" results.append(f\"The {' '.join(result['poi']['categories'])} {result['poi']['name']} is {int(result['dist'])} meters far from {city}\")\n",
" if len(results) == 7:\n",
" break\n",
"\n",
" return \". \".join(results)\n",
"\n",
"\n",
"print(search_nearby('49.625892805337514', '6.160417066963513', 'your location', TOMTOM_KEY))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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