# SPDX-FileCopyrightText: 2024 Liz Clark for Adafruit Industries
#
# SPDX-License-Identifier: MIT

ALT_TEXT_PROMPT="Please describe what is in this image. The description should be in the style of alt text used on social media sites like Mastodon. Avoid talking about the quality of the image. Avoid talking about the background of the image. Only describe the main subject."
HAIKU_PROMPT="Please identify the main subject of the image and write a haiku about it. It should be a three line poem that consists of three lines, with five syllables in the first line, seven in the second, and five in the third. It does not need to rhyme. Only return the haiku, no image description is necessary. Please insert a * between each line instead of a comma (,)."
CABLE_PROMPT="This image features a type of cable connector. Please specifically identify the cable connection. You should describe the category of the cable and the specific type. For example, if you see a USB cable, you should also say whether it is type A, type mini B, etc. If you are not sure what type of cable connector it is, please state that and make your best inference. The response should be concise, no more than two sentences. You do not need to describe the general appearance of the image."
TRANSLATE_PROMPT="This image has text that is not in English. Please translate it to English. Only return the translated text in English. For example, if the text reads hola (hello in Spanish), then return hello (translated to English). No further explanation is necessary. If you are not sure on how to translate a word(s) then please return the text as seen in the image. You do not need to describe the image."
ALIEN_PROMPT="Describe this image as if you are a friendly alien visiting from another world in our galaxy. You have no context for society on Earth. Your descriptions are cute, inquisitive and concise (2-3 sentences). You do not need to comment on the quality of the image."
WEIRD_PROMPT="Take in the full image as context. Is there anything in the image that is out of the ordinary or interesting? For example, if the image is of a backyard, do you see any animals or objects that catch your eye? You do not need to comment on the quality of the image. Please keep responses brief and concise, between one to two sentences. If you do not see anything out of the ordinary for the context of the image or anything particularly interesting, please return: Nothing to see here."

# SPDX-FileCopyrightText: 2024 Liz Clark for Adafruit Industries
#
# SPDX-License-Identifier: MIT

ALT_TEXT_PROMPT="Please describe what is in this image. The description should be in the style of alt text used on social media sites like Mastodon. Avoid talking about the quality of the image. Avoid talking about the background of the image. Only describe the main subject."
HAIKU_PROMPT="Please identify the main subject of the image and write a haiku about it. It should be a three line poem that consists of three lines, with five syllables in the first line, seven in the second, and five in the third. It does not need to rhyme. Only return the haiku, no image description is necessary. Please insert a * between each line instead of a comma (,)."
CABLE_PROMPT="This image features a type of cable connector. Please specifically identify the cable connection. You should describe the category of the cable and the specific type. For example, if you see a USB cable, you should also say whether it is type A, type mini B, etc. If you are not sure what type of cable connector it is, please state that and make your best inference. The response should be concise, no more than two sentences. You do not need to describe the general appearance of the image."
TRANSLATE_PROMPT="This image has text that is not in English. Please translate it to English. Only return the translated text in English. For example, if the text reads hola (hello in Spanish), then return hello (translated to English). No further explanation is necessary. If you are not sure on how to translate a word(s) then please return the text as seen in the image. You do not need to describe the image."
ALIEN_PROMPT="Describe this image as if you are a friendly alien visiting from another world in our galaxy. You have no context for society on Earth. Your descriptions are cute, inquisitive and concise (2-3 sentences). You do not need to comment on the quality of the image."
WEIRD_PROMPT="Take in the full image as context. Is there anything in the image that is out of the ordinary or interesting? For example, if the image is of a backyard, do you see any animals or objects that catch your eye? You do not need to comment on the quality of the image. Please keep responses brief and concise, between one to two sentences. If you do not see anything out of the ordinary for the context of the image or anything particularly interesting, please return: Nothing to see here."

CIRCUITPY_WIFI_SSID = "YOUR-SSID-HERE"
CIRCUITPY_WIFI_PASSWORD = "YOUR-PASSWORD-HERE"
OPENAI_API_KEY="YOUR-OPENAI-KEY-HERE"
ALT_TEXT_PROMPT="Please describe what is in this image. The description should be in the style of alt text used on social media sites like Mastodon. Avoid talking about the quality of the image. Avoid talking about the background of the image. Only describe the main subject."
HAIKU_PROMPT="Please identify the main subject of the image and write a haiku about it. It should be a poem that consists of three lines, with five syllables in the first line, seven in the second, and five in the third. It does not need to rhyme. Only return the haiku, no image description is necessary. Please insert a * between each line instead of a comma (,)."
CABLE_PROMPT="This image features a type of cable connector. Please specifically identify the cable connection. You should describe the category of the cable and the specific type. For example, if you see a USB cable, you should also say whether it is type A, type mini B, etc. If you are not sure what type of cable connector it is, please state that and make your best inference. The response should be concise, no more than two sentences. You do not need to describe the general appearance of the image."
TRANSLATE_PROMPT="This image has text that is not in English. Please translate it to English. Only return the translated text in English. For example, if the text reads hola (hello in Spanish), then return hello (translated to English). No further explanation is necessary. If you are not sure on how to translate a word(s) then please return the text as seen in the image. You do not need to describe the image."
ALIEN_PROMPT="Describe this image as if you are a friendly alien visiting from another world in our galaxy. You have no context for society on Earth. Your descriptions are cute, inquisitive and concise (2-3 sentences). You do not need to comment on the quality of the image."
WEIRD_PROMPT="Take in the full image as context. Is there anything in the image that is out of the ordinary or interesting? For example, if the image is of a backyard, do you see any animals or objects that catch your eye? You do not need to comment on the quality of the image. Please keep responses brief and concise, between one to two sentences. If you do not see anything out of the ordinary for the context of the image or anything particularly interesting, please return: Nothing to see here."

CIRCUITPY_WIFI_SSID = "YOUR-SSID-HERE"
CIRCUITPY_WIFI_PASSWORD = "YOUR-PASSWORD-HERE"
OPENAI_API_KEY="YOUR-OPENAI-KEY-HERE"
ALT_TEXT_PROMPT="Please describe what is in this image. The description should be in the style of alt text used on social media sites like Mastodon. Avoid talking about the quality of the image. Avoid talking about the background of the image. Only describe the main subject."
HAIKU_PROMPT="Please identify the main subject of the image and write a haiku about it. It should be a poem that consists of three lines, with five syllables in the first line, seven in the second, and five in the third. It does not need to rhyme. Only return the haiku, no image description is necessary. Please insert a * between each line instead of a comma (,)."
CABLE_PROMPT="This image features a type of cable connector. Please specifically identify the cable connection. You should describe the category of the cable and the specific type. For example, if you see a USB cable, you should also say whether it is type A, type mini B, etc. If you are not sure what type of cable connector it is, please state that and make your best inference. The response should be concise, no more than two sentences. You do not need to describe the general appearance of the image."
TRANSLATE_PROMPT="This image has text that is not in English. Please translate it to English. Only return the translated text in English. For example, if the text reads hola (hello in Spanish), then return hello (translated to English). No further explanation is necessary. If you are not sure on how to translate a word(s) then please return the text as seen in the image. You do not need to describe the image."
ALIEN_PROMPT="Describe this image as if you are a friendly alien visiting from another world in our galaxy. You have no context for society on Earth. Your descriptions are cute, inquisitive and concise (2-3 sentences). You do not need to comment on the quality of the image."
WEIRD_PROMPT="Take in the full image as context. Is there anything in the image that is out of the ordinary or interesting? For example, if the image is of a backyard, do you see any animals or objects that catch your eye? You do not need to comment on the quality of the image. Please keep responses brief and concise, between one to two sentences. If you do not see anything out of the ordinary for the context of the image or anything particularly interesting, please return: Nothing to see here."

# SPDX-FileCopyrightText: 2024 Liz Clark for Adafruit Industries
#
# SPDX-License-Identifier: MIT

import os
import time
import ssl
import binascii
import wifi
import vectorio
import socketpool
import adafruit_requests
import displayio
from jpegio import JpegDecoder
from adafruit_display_text import label, wrap_text_to_lines
import terminalio
import adafruit_pycamera

# scale for displaying returned text from OpenAI
text_scale = 2

# OpenAI key and prompts from settings.toml
openai_api_key = os.getenv("OPENAI_API_KEY")
alt_text_prompt = os.getenv("ALT_TEXT_PROMPT")
haiku_prompt = os.getenv("HAIKU_PROMPT")
cable_prompt = os.getenv("CABLE_PROMPT")
translate_prompt = os.getenv("TRANSLATE_PROMPT")
alien_prompt = os.getenv("ALIEN_PROMPT")
weird_prompt = os.getenv("WEIRD_PROMPT")

prompts = [alt_text_prompt,
           haiku_prompt,
           cable_prompt,
           translate_prompt,
           alien_prompt,
           weird_prompt]
num_prompts = len(prompts)
prompt_index = 0
prompt_labels = ["ALT_TEXT", "HAIKU", "CABLE_IDENTIFIER", "TRANSLATE", "ALIEN", "WEIRD?"]

# encode jpeg to base64 for OpenAI
def encode_image(image_path):
    with open(image_path, 'rb') as image_file:
        image_data = image_file.read()
        base64_encoded_data = binascii.b2a_base64(image_data).decode('utf-8').rstrip()
        return base64_encoded_data

# view returned text on MEMENTO screen
def view_text(the_text):
    rectangle = vectorio.Rectangle(pixel_shader=palette, width=240, height=240, x=0, y=0)
    pycam.splash.append(rectangle)
    the_text = "\n".join(wrap_text_to_lines(the_text, 20))
    if prompt_index == 1:
        the_text = the_text.replace("*", "\n")
    text_area = label.Label(terminalio.FONT, text=the_text,
                            color=0xFFFFFF, x=2, y=10, scale=text_scale)
    pycam.splash.append(text_area)
    pycam.display.refresh()

# send image to OpenAI, print the returned text and save it as a text file
def send_img(img, prompt):
    base64_image = encode_image(img)
    headers = {
      "Content-Type": "application/json",
      "Authorization": f"Bearer {openai_api_key}"
    }
    payload = {
      "model": "gpt-4-turbo",
      "messages": [
        {
          "role": "user",
          "content": [
            {
              "type": "text",
              "text": f"{prompt}"
            },
            {
              "type": "image_url",
              "image_url": {
                "url": f"data:image/jpeg;base64,{base64_image}"
              }
            }
          ]
        }
      ],
      "max_tokens": 300
    }
    response = requests.post("https://api.openai.com/v1/chat/completions",
                             headers=headers, json=payload)
    json_openai = response.json()
    print(json_openai['choices'][0]['message']['content'])
    alt_text_file = img.replace('jpg', 'txt')
    alt_text_file = alt_text_file[:11] + f"_{prompt_labels[prompt_index]}" + alt_text_file[11:]
    if prompt_index == 5:
        alt_text_file = alt_text_file.replace("?", "")
    with open(alt_text_file, "a") as fp:
        fp.write(json_openai['choices'][0]['message']['content'])
        fp.flush()
        time.sleep(1)
        fp.close()
    view_text(json_openai['choices'][0]['message']['content'])
# view images on sd card to re-send to OpenAI
def load_image(bit, file):
    bit.fill(0b00000_000000_00000)  # fill with a middle grey
    decoder.open(file)
    decoder.decode(bit, scale=0, x=0, y=0)
    pycam.blit(bit, y_offset=32)
    pycam.display.refresh()

print()
print("Connecting to WiFi")
wifi.radio.connect(os.getenv('CIRCUITPY_WIFI_SSID'), os.getenv('CIRCUITPY_WIFI_PASSWORD'))
print("Connected to WiFi")
pool = socketpool.SocketPool(wifi.radio)
requests = adafruit_requests.Session(pool, ssl.create_default_context())

palette = displayio.Palette(1)
palette[0] = 0x000000
decoder = JpegDecoder()
# used for showing images from sd card
bitmap = displayio.Bitmap(240, 176, 65535)

pycam = adafruit_pycamera.PyCamera()
pycam.mode = 0  # only mode 0 (JPEG) will work in this example

# Resolution of 320x240 is plenty for OpenAI
pycam.resolution = 1  # 0-12 preset resolutions:
#                      0: 240x240, 1: 320x240, 2: 640x480, 3: 800x600, 4: 1024x768,
#                      5: 1280x720, 6: 1280x1024, 7: 1600x1200, 8: 1920x1080, 9: 2048x1536,
#                      10: 2560x1440, 11: 2560x1600, 12: 2560x1920
# pycam.led_level = 1  # 0-4 preset brightness levels
# pycam.led_color = 0  # 0-7  preset colors: 0: white, 1: green, 2: yellow, 3: red,
#                                          4: pink, 5: blue, 6: teal, 7: rainbow
pycam.effect = 0  # 0-7 preset FX: 0: normal, 1: invert, 2: b&w, 3: red,
#                                  4: green, 5: blue, 6: sepia, 7: solarize
# sort image files by numeric order
all_images = [
    f"/sd/{filename}"
    for filename in os.listdir("/sd")
    if filename.lower().endswith(".jpg")
    ]
all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
# add label for selected prompt
rect = vectorio.Rectangle(pixel_shader=palette, width=240, height=20, x=0, y=0)
prompt_txt = label.Label(
            terminalio.FONT, text=prompt_labels[prompt_index], color=0xFF0055, x=10, y=15, scale=2
        )
# pylint: disable=protected-access
pycam._botbar.append(rect)
pycam._botbar.append(prompt_txt)
# pylint: enable=protected-access
pycam.display.refresh()

view = False
new_prompt = False
file_index = -1

while True:
    if new_prompt:
        pycam.display_message("SEND?")
    if not view:
        if not new_prompt:
            pycam.blit(pycam.continuous_capture())
    pycam.keys_debounce()
    if pycam.shutter.long_press:
        pycam.autofocus()
    if pycam.shutter.short_count:
        try:
            pycam.display_message("snap", color=0x00DD00)
            pycam.capture_jpeg()
            pycam.live_preview_mode()
        except TypeError as exception:
            pycam.display_message("Failed", color=0xFF0000)
            time.sleep(0.5)
            pycam.live_preview_mode()
        except RuntimeError as exception:
            pycam.display_message("Error\nNo SD Card", color=0xFF0000)
            time.sleep(0.5)
        all_images = [
        f"/sd/{filename}"
        for filename in os.listdir("/sd")
        if filename.lower().endswith(".jpg")
        ]
        all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
        the_image = all_images[-1]
        pycam.display_message("OpenAI..", color=0x00DD00)
        send_img(the_image, prompts[prompt_index])
        view = True

    if pycam.up.fell:
        prompt_index = (prompt_index - 1) % num_prompts
        prompt_txt.text = prompt_labels[prompt_index]
        pycam.display.refresh()

    if pycam.down.fell:
        prompt_index = (prompt_index + 1) % num_prompts
        prompt_txt.text = prompt_labels[prompt_index]
        pycam.display.refresh()

    if pycam.right.fell:
        if new_prompt:
            file_index = (file_index - -1) % -len(all_images)
            filename = all_images[file_index]
            load_image(bitmap, filename)
        else:
            prompt_index = (prompt_index + 1) % num_prompts
            prompt_txt.text = prompt_labels[prompt_index]
            pycam.display.refresh()

    if pycam.left.fell:
        if new_prompt:
            file_index = (file_index + -1) % -len(all_images)
            filename = all_images[file_index]
            load_image(bitmap, filename)
        else:
            prompt_index = (prompt_index - 1) % num_prompts
            prompt_txt.text = prompt_labels[prompt_index]
            pycam.display.refresh()

    if pycam.select.fell:
        if not new_prompt:
            file_index = -1
            new_prompt = True
            filename = all_images[file_index]
            load_image(bitmap, filename)
        else:
            new_prompt = False
            pycam.display.refresh()

    if pycam.ok.fell:
        if view:
            pycam.splash.pop()
            pycam.splash.pop()
            pycam.display.refresh()
            view = False
        if new_prompt:
            pycam.display_message("OpenAI..", color=0x00DD00)
            send_img(filename, prompts[prompt_index])
            new_prompt = False
            view = True

# SPDX-FileCopyrightText: 2024 Liz Clark for Adafruit Industries
#
# SPDX-License-Identifier: MIT

import os
import time
import ssl
import binascii
import wifi
import vectorio
import socketpool
import adafruit_requests
import displayio
from jpegio import JpegDecoder
from adafruit_display_text import label, wrap_text_to_lines
import terminalio
import adafruit_pycamera

# scale for displaying returned text from OpenAI
text_scale = 2

# OpenAI key and prompts from settings.toml
openai_api_key = os.getenv("OPENAI_API_KEY")
alt_text_prompt = os.getenv("ALT_TEXT_PROMPT")
haiku_prompt = os.getenv("HAIKU_PROMPT")
cable_prompt = os.getenv("CABLE_PROMPT")
translate_prompt = os.getenv("TRANSLATE_PROMPT")
alien_prompt = os.getenv("ALIEN_PROMPT")
weird_prompt = os.getenv("WEIRD_PROMPT")

prompts = [alt_text_prompt,
           haiku_prompt,
           cable_prompt,
           translate_prompt,
           alien_prompt,
           weird_prompt]
num_prompts = len(prompts)
prompt_index = 0
prompt_labels = ["ALT_TEXT", "HAIKU", "CABLE_IDENTIFIER", "TRANSLATE", "ALIEN", "WEIRD?"]

# encode jpeg to base64 for OpenAI
def encode_image(image_path):
    with open(image_path, 'rb') as image_file:
        image_data = image_file.read()
        base64_encoded_data = binascii.b2a_base64(image_data).decode('utf-8').rstrip()
        return base64_encoded_data

# view returned text on MEMENTO screen
def view_text(the_text):
    rectangle = vectorio.Rectangle(pixel_shader=palette, width=240, height=240, x=0, y=0)
    pycam.splash.append(rectangle)
    the_text = "\n".join(wrap_text_to_lines(the_text, 20))
    if prompt_index == 1:
        the_text = the_text.replace("*", "\n")
    text_area = label.Label(terminalio.FONT, text=the_text,
                            color=0xFFFFFF, x=2, y=10, scale=text_scale)
    pycam.splash.append(text_area)
    pycam.display.refresh()

# send image to OpenAI, print the returned text and save it as a text file
def send_img(img, prompt):
    base64_image = encode_image(img)
    headers = {
      "Content-Type": "application/json",
      "Authorization": f"Bearer {openai_api_key}"
    }
    payload = {
      "model": "gpt-4-turbo",
      "messages": [
        {
          "role": "user",
          "content": [
            {
              "type": "text",
              "text": f"{prompt}"
            },
            {
              "type": "image_url",
              "image_url": {
                "url": f"data:image/jpeg;base64,{base64_image}"
              }
            }
          ]
        }
      ],
      "max_tokens": 300
    }
    response = requests.post("https://api.openai.com/v1/chat/completions",
                             headers=headers, json=payload)
    json_openai = response.json()
    print(json_openai['choices'][0]['message']['content'])
    alt_text_file = img.replace('jpg', 'txt')
    alt_text_file = alt_text_file[:11] + f"_{prompt_labels[prompt_index]}" + alt_text_file[11:]
    if prompt_index == 5:
        alt_text_file = alt_text_file.replace("?", "")
    with open(alt_text_file, "a") as fp:
        fp.write(json_openai['choices'][0]['message']['content'])
        fp.flush()
        time.sleep(1)
        fp.close()
    view_text(json_openai['choices'][0]['message']['content'])
# view images on sd card to re-send to OpenAI
def load_image(bit, file):
    bit.fill(0b00000_000000_00000)  # fill with a middle grey
    decoder.open(file)
    decoder.decode(bit, scale=0, x=0, y=0)
    pycam.blit(bit, y_offset=32)
    pycam.display.refresh()

print()
print("Connecting to WiFi")
wifi.radio.connect(os.getenv('CIRCUITPY_WIFI_SSID'), os.getenv('CIRCUITPY_WIFI_PASSWORD'))
print("Connected to WiFi")
pool = socketpool.SocketPool(wifi.radio)
requests = adafruit_requests.Session(pool, ssl.create_default_context())

palette = displayio.Palette(1)
palette[0] = 0x000000
decoder = JpegDecoder()
# used for showing images from sd card
bitmap = displayio.Bitmap(240, 176, 65535)

pycam = adafruit_pycamera.PyCamera()
pycam.mode = 0  # only mode 0 (JPEG) will work in this example

# Resolution of 320x240 is plenty for OpenAI
pycam.resolution = 1  # 0-12 preset resolutions:
#                      0: 240x240, 1: 320x240, 2: 640x480, 3: 800x600, 4: 1024x768,
#                      5: 1280x720, 6: 1280x1024, 7: 1600x1200, 8: 1920x1080, 9: 2048x1536,
#                      10: 2560x1440, 11: 2560x1600, 12: 2560x1920
# pycam.led_level = 1  # 0-4 preset brightness levels
# pycam.led_color = 0  # 0-7  preset colors: 0: white, 1: green, 2: yellow, 3: red,
#                                          4: pink, 5: blue, 6: teal, 7: rainbow
pycam.effect = 0  # 0-7 preset FX: 0: normal, 1: invert, 2: b&w, 3: red,
#                                  4: green, 5: blue, 6: sepia, 7: solarize
# sort image files by numeric order
all_images = [
    f"/sd/{filename}"
    for filename in os.listdir("/sd")
    if filename.lower().endswith(".jpg")
    ]
all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
# add label for selected prompt
rect = vectorio.Rectangle(pixel_shader=palette, width=240, height=20, x=0, y=0)
prompt_txt = label.Label(
            terminalio.FONT, text=prompt_labels[prompt_index], color=0xFF0055, x=10, y=15, scale=2
        )
# pylint: disable=protected-access
pycam._botbar.append(rect)
pycam._botbar.append(prompt_txt)
# pylint: enable=protected-access
pycam.display.refresh()

view = False
new_prompt = False
file_index = -1

while True:
    if new_prompt:
        pycam.display_message("SEND?")
    if not view:
        if not new_prompt:
            pycam.blit(pycam.continuous_capture())
    pycam.keys_debounce()
    if pycam.shutter.long_press:
        pycam.autofocus()
    if pycam.shutter.short_count:
        try:
            pycam.display_message("snap", color=0x00DD00)
            pycam.capture_jpeg()
            pycam.live_preview_mode()
        except TypeError as exception:
            pycam.display_message("Failed", color=0xFF0000)
            time.sleep(0.5)
            pycam.live_preview_mode()
        except RuntimeError as exception:
            pycam.display_message("Error\nNo SD Card", color=0xFF0000)
            time.sleep(0.5)
        all_images = [
        f"/sd/{filename}"
        for filename in os.listdir("/sd")
        if filename.lower().endswith(".jpg")
        ]
        all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
        the_image = all_images[-1]
        pycam.display_message("OpenAI..", color=0x00DD00)
        send_img(the_image, prompts[prompt_index])
        view = True

    if pycam.up.fell:
        prompt_index = (prompt_index - 1) % num_prompts
        prompt_txt.text = prompt_labels[prompt_index]
        pycam.display.refresh()

    if pycam.down.fell:
        prompt_index = (prompt_index + 1) % num_prompts
        prompt_txt.text = prompt_labels[prompt_index]
        pycam.display.refresh()

    if pycam.right.fell:
        if new_prompt:
            file_index = (file_index - -1) % -len(all_images)
            filename = all_images[file_index]
            load_image(bitmap, filename)
        else:
            prompt_index = (prompt_index + 1) % num_prompts
            prompt_txt.text = prompt_labels[prompt_index]
            pycam.display.refresh()

    if pycam.left.fell:
        if new_prompt:
            file_index = (file_index + -1) % -len(all_images)
            filename = all_images[file_index]
            load_image(bitmap, filename)
        else:
            prompt_index = (prompt_index - 1) % num_prompts
            prompt_txt.text = prompt_labels[prompt_index]
            pycam.display.refresh()

    if pycam.select.fell:
        if not new_prompt:
            file_index = -1
            new_prompt = True
            filename = all_images[file_index]
            load_image(bitmap, filename)
        else:
            new_prompt = False
            pycam.display.refresh()

    if pycam.ok.fell:
        if view:
            pycam.splash.pop()
            pycam.splash.pop()
            pycam.display.refresh()
            view = False
        if new_prompt:
            pycam.display_message("OpenAI..", color=0x00DD00)
            send_img(filename, prompts[prompt_index])
            new_prompt = False
            view = True

# scale for displaying returned text from OpenAI
text_scale = 2

# OpenAI key and prompts from settings.toml
openai_api_key = os.getenv("OPENAI_API_KEY")
alt_text_prompt = os.getenv("ALT_TEXT_PROMPT")
haiku_prompt = os.getenv("HAIKU_PROMPT")
cable_prompt = os.getenv("CABLE_PROMPT")
translate_prompt = os.getenv("TRANSLATE_PROMPT")
alien_prompt = os.getenv("ALIEN_PROMPT")
weird_prompt = os.getenv("WEIRD_PROMPT")

prompts = [alt_text_prompt,
           haiku_prompt,
           cable_prompt,
           translate_prompt,
           alien_prompt,
           weird_prompt]
num_prompts = len(prompts)
prompt_index = 0
prompt_labels = ["ALT_TEXT", "HAIKU", "CABLE_IDENTIFIER", "TRANSLATE", "ALIEN", "WEIRD?"]

# scale for displaying returned text from OpenAI
text_scale = 2

# OpenAI key and prompts from settings.toml
openai_api_key = os.getenv("OPENAI_API_KEY")
alt_text_prompt = os.getenv("ALT_TEXT_PROMPT")
haiku_prompt = os.getenv("HAIKU_PROMPT")
cable_prompt = os.getenv("CABLE_PROMPT")
translate_prompt = os.getenv("TRANSLATE_PROMPT")
alien_prompt = os.getenv("ALIEN_PROMPT")
weird_prompt = os.getenv("WEIRD_PROMPT")

prompts = [alt_text_prompt,
           haiku_prompt,
           cable_prompt,
           translate_prompt,
           alien_prompt,
           weird_prompt]
num_prompts = len(prompts)
prompt_index = 0
prompt_labels = ["ALT_TEXT", "HAIKU", "CABLE_IDENTIFIER", "TRANSLATE", "ALIEN", "WEIRD?"]

# encode jpeg to base64 for OpenAI
def encode_image(image_path):
    with open(image_path, 'rb') as image_file:
        image_data = image_file.read()
        base64_encoded_data = binascii.b2a_base64(image_data).decode('utf-8').rstrip()
        return base64_encoded_data

# encode jpeg to base64 for OpenAI
def encode_image(image_path):
    with open(image_path, 'rb') as image_file:
        image_data = image_file.read()
        base64_encoded_data = binascii.b2a_base64(image_data).decode('utf-8').rstrip()
        return base64_encoded_data

# view returned text on MEMENTO screen
def view_text(the_text):
    rectangle = vectorio.Rectangle(pixel_shader=palette, width=240, height=240, x=0, y=0)
    pycam.splash.append(rectangle)
    the_text = "\n".join(wrap_text_to_lines(the_text, 20))
    if prompt_index == 1:
        the_text = the_text.replace("*", "\n")
    text_area = label.Label(terminalio.FONT, text=the_text,
                            color=0xFFFFFF, x=2, y=10, scale=text_scale)
    pycam.splash.append(text_area)
    pycam.display.refresh()

# view returned text on MEMENTO screen
def view_text(the_text):
    rectangle = vectorio.Rectangle(pixel_shader=palette, width=240, height=240, x=0, y=0)
    pycam.splash.append(rectangle)
    the_text = "\n".join(wrap_text_to_lines(the_text, 20))
    if prompt_index == 1:
        the_text = the_text.replace("*", "\n")
    text_area = label.Label(terminalio.FONT, text=the_text,
                            color=0xFFFFFF, x=2, y=10, scale=text_scale)
    pycam.splash.append(text_area)
    pycam.display.refresh()

# send image to OpenAI, print the returned text and save it as a text file
def send_img(img, prompt):
    base64_image = encode_image(img)
    headers = {
      "Content-Type": "application/json",
      "Authorization": f"Bearer {openai_api_key}"
    }
    payload = {
      "model": "gpt-4-vision-preview",
      "messages": [
        {
          "role": "user",
          "content": [
            {
              "type": "text",
              "text": f"{prompt}"
            },
            {
              "type": "image_url",
              "image_url": {
                "url": f"data:image/jpeg;base64,{base64_image}"
              }
            }
          ]
        }
      ],
      "max_tokens": 300
    }
    response = requests.post("https://api.openai.com/v1/chat/completions",
                             headers=headers, json=payload)
    json_openai = response.json()
    print(json_openai['choices'][0]['message']['content'])
    alt_text_file = img.replace('jpg', 'txt')
    alt_text_file = alt_text_file[:11] + f"_{prompt_labels[prompt_index]}" + alt_text_file[11:]
    if prompt_index == 5:
        alt_text_file = alt_text_file.replace("?", "")
    with open(alt_text_file, "a") as fp:
        fp.write(json_openai['choices'][0]['message']['content'])
        fp.flush()
        time.sleep(1)
        fp.close()
    view_text(json_openai['choices'][0]['message']['content'])

# send image to OpenAI, print the returned text and save it as a text file
def send_img(img, prompt):
    base64_image = encode_image(img)
    headers = {
      "Content-Type": "application/json",
      "Authorization": f"Bearer {openai_api_key}"
    }
    payload = {
      "model": "gpt-4-vision-preview",
      "messages": [
        {
          "role": "user",
          "content": [
            {
              "type": "text",
              "text": f"{prompt}"
            },
            {
              "type": "image_url",
              "image_url": {
                "url": f"data:image/jpeg;base64,{base64_image}"
              }
            }
          ]
        }
      ],
      "max_tokens": 300
    }
    response = requests.post("https://api.openai.com/v1/chat/completions",
                             headers=headers, json=payload)
    json_openai = response.json()
    print(json_openai['choices'][0]['message']['content'])
    alt_text_file = img.replace('jpg', 'txt')
    alt_text_file = alt_text_file[:11] + f"_{prompt_labels[prompt_index]}" + alt_text_file[11:]
    if prompt_index == 5:
        alt_text_file = alt_text_file.replace("?", "")
    with open(alt_text_file, "a") as fp:
        fp.write(json_openai['choices'][0]['message']['content'])
        fp.flush()
        time.sleep(1)
        fp.close()
    view_text(json_openai['choices'][0]['message']['content'])

# view images on sd card to re-send to OpenAI
def load_image(bit, file):
    bit.fill(0b00000_000000_00000)
    decoder.open(file)
    decoder.decode(bit, scale=0, x=0, y=0)
    pycam.blit(bit, y_offset=32)
    pycam.display.refresh()

# view images on sd card to re-send to OpenAI
def load_image(bit, file):
    bit.fill(0b00000_000000_00000)
    decoder.open(file)
    decoder.decode(bit, scale=0, x=0, y=0)
    pycam.blit(bit, y_offset=32)
    pycam.display.refresh()

print()
print("Connecting to WiFi")
wifi.radio.connect(os.getenv('CIRCUITPY_WIFI_SSID'), os.getenv('CIRCUITPY_WIFI_PASSWORD'))
print("Connected to WiFi")
pool = socketpool.SocketPool(wifi.radio)
requests = adafruit_requests.Session(pool, ssl.create_default_context())

pycam = adafruit_pycamera.PyCamera()
pycam.mode = 0  # only mode 0 (JPEG) will work in this example

# Resolution of 320x240 is plenty for OpenAI
pycam.resolution = 1  # 0-12 preset resolutions:
#                      0: 240x240, 1: 320x240, 2: 640x480, 3: 800x600, 4: 1024x768,
#                      5: 1280x720, 6: 1280x1024, 7: 1600x1200, 8: 1920x1080, 9: 2048x1536,
#                      10: 2560x1440, 11: 2560x1600, 12: 2560x1920
# pycam.led_level = 1  # 0-4 preset brightness levels
# pycam.led_color = 0  # 0-7  preset colors: 0: white, 1: green, 2: yellow, 3: red,
#                                          4: pink, 5: blue, 6: teal, 7: rainbow
pycam.effect = 0  # 0-7 preset FX: 0: normal, 1: invert, 2: b&w, 3: red,
#                                  4: green, 5: blue, 6: sepia, 7: solarize

print()
print("Connecting to WiFi")
wifi.radio.connect(os.getenv('CIRCUITPY_WIFI_SSID'), os.getenv('CIRCUITPY_WIFI_PASSWORD'))
print("Connected to WiFi")
pool = socketpool.SocketPool(wifi.radio)
requests = adafruit_requests.Session(pool, ssl.create_default_context())

pycam = adafruit_pycamera.PyCamera()
pycam.mode = 0  # only mode 0 (JPEG) will work in this example

# Resolution of 320x240 is plenty for OpenAI
pycam.resolution = 1  # 0-12 preset resolutions:
#                      0: 240x240, 1: 320x240, 2: 640x480, 3: 800x600, 4: 1024x768,
#                      5: 1280x720, 6: 1280x1024, 7: 1600x1200, 8: 1920x1080, 9: 2048x1536,
#                      10: 2560x1440, 11: 2560x1600, 12: 2560x1920
# pycam.led_level = 1  # 0-4 preset brightness levels
# pycam.led_color = 0  # 0-7  preset colors: 0: white, 1: green, 2: yellow, 3: red,
#                                          4: pink, 5: blue, 6: teal, 7: rainbow
pycam.effect = 0  # 0-7 preset FX: 0: normal, 1: invert, 2: b&w, 3: red,
#                                  4: green, 5: blue, 6: sepia, 7: solarize

# sort image files by numeric order
all_images = [
    f"/sd/{filename}"
    for filename in os.listdir("/sd")
    if filename.lower().endswith(".jpg")
    ]
all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))

# sort image files by numeric order
all_images = [
    f"/sd/{filename}"
    for filename in os.listdir("/sd")
    if filename.lower().endswith(".jpg")
    ]
all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))

# add label for selected prompt
rect = vectorio.Rectangle(pixel_shader=palette, width=240, height=20, x=0, y=0)
prompt_txt = label.Label(
            terminalio.FONT, text=prompt_labels[prompt_index], color=0xFF0055, x=10, y=15, scale=2
        )
# pylint: disable=protected-access
pycam._botbar.append(rect)
pycam._botbar.append(prompt_txt)
# pylint: enable=protected-access
pycam.display.refresh()

# add label for selected prompt
rect = vectorio.Rectangle(pixel_shader=palette, width=240, height=20, x=0, y=0)
prompt_txt = label.Label(
            terminalio.FONT, text=prompt_labels[prompt_index], color=0xFF0055, x=10, y=15, scale=2
        )
# pylint: disable=protected-access
pycam._botbar.append(rect)
pycam._botbar.append(prompt_txt)
# pylint: enable=protected-access
pycam.display.refresh()

if pycam.shutter.long_press:
      pycam.autofocus()
if pycam.shutter.short_count:
      try:
        pycam.display_message("snap", color=0x00DD00)
        pycam.capture_jpeg()
        pycam.live_preview_mode()
      except TypeError as exception:
        pycam.display_message("Failed", color=0xFF0000)
        time.sleep(0.5)
        pycam.live_preview_mode()
      except RuntimeError as exception:
        pycam.display_message("Error\nNo SD Card", color=0xFF0000)
        time.sleep(0.5)
      all_images = [
              f"/sd/{filename}"
              for filename in os.listdir("/sd")
              if filename.lower().endswith(".jpg")
            ]
      all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
      the_image = all_images[-1]
      pycam.display_message("OpenAI..", color=0x00DD00)
      send_img(the_image, prompts[prompt_index])
      view = True

if pycam.shutter.long_press:
      pycam.autofocus()
if pycam.shutter.short_count:
      try:
        pycam.display_message("snap", color=0x00DD00)
        pycam.capture_jpeg()
        pycam.live_preview_mode()
      except TypeError as exception:
        pycam.display_message("Failed", color=0xFF0000)
        time.sleep(0.5)
        pycam.live_preview_mode()
      except RuntimeError as exception:
        pycam.display_message("Error\nNo SD Card", color=0xFF0000)
        time.sleep(0.5)
      all_images = [
              f"/sd/{filename}"
              for filename in os.listdir("/sd")
              if filename.lower().endswith(".jpg")
            ]
      all_images.sort(key=lambda f: int(''.join(filter(str.isdigit, f))))
      the_image = all_images[-1]
      pycam.display_message("OpenAI..", color=0x00DD00)
      send_img(the_image, prompts[prompt_index])
      view = True

if pycam.select.fell:
     if not new_prompt:
     	file_index = -1
      	new_prompt = True
      	filename = all_images[file_index]
      	load_image(bitmap, filename)
    else:
      	new_prompt = False
      	pycam.display.refresh()

if pycam.ok.fell:
  	if view:
    	pycam.splash.pop()
    	pycam.splash.pop()
    	pycam.display.refresh()
    	view = False
    if new_prompt:
      	pycam.display_message("OpenAI..", color=0x00DD00)
      	send_img(filename, prompts[prompt_index])
      	new_prompt = False
      	view = True

if pycam.select.fell:
     if not new_prompt:
     	file_index = -1
      	new_prompt = True
      	filename = all_images[file_index]
      	load_image(bitmap, filename)
    else:
      	new_prompt = False
      	pycam.display.refresh()

if pycam.ok.fell:
  	if view:
    	pycam.splash.pop()
    	pycam.splash.pop()
    	pycam.display.refresh()
    	view = False
    if new_prompt:
      	pycam.display_message("OpenAI..", color=0x00DD00)
      	send_img(filename, prompts[prompt_index])
      	new_prompt = False
      	view = True

if pycam.up.fell:
    prompt_index = (prompt_index - 1) % num_prompts
    prompt_txt.text = prompt_labels[prompt_index]
    pycam.display.refresh()

if pycam.down.fell:
	prompt_index = (prompt_index + 1) % num_prompts
    prompt_txt.text = prompt_labels[prompt_index]
    pycam.display.refresh()

if pycam.right.fell:
	if new_prompt:
        file_index = (file_index - -1) % -len(all_images)
        filename = all_images[file_index]
        load_image(bitmap, filename)
	else:
		prompt_index = (prompt_index + 1) % num_prompts
		prompt_txt.text = prompt_labels[prompt_index]
		pycam.display.refresh()

if pycam.left.fell:
	if new_prompt:
		file_index = (file_index + -1) % -len(all_images)
		filename = all_images[file_index]
		load_image(bitmap, filename)
	else:
		prompt_index = (prompt_index - 1) % num_prompts
		prompt_txt.text = prompt_labels[prompt_index]
		pycam.display.refresh()

if pycam.up.fell:
    prompt_index = (prompt_index - 1) % num_prompts
    prompt_txt.text = prompt_labels[prompt_index]
    pycam.display.refresh()

if pycam.down.fell:
	prompt_index = (prompt_index + 1) % num_prompts
    prompt_txt.text = prompt_labels[prompt_index]
    pycam.display.refresh()

if pycam.right.fell:
	if new_prompt:
        file_index = (file_index - -1) % -len(all_images)
        filename = all_images[file_index]
        load_image(bitmap, filename)
	else:
		prompt_index = (prompt_index + 1) % num_prompts
		prompt_txt.text = prompt_labels[prompt_index]
		pycam.display.refresh()

if pycam.left.fell:
	if new_prompt:
		file_index = (file_index + -1) % -len(all_images)
		filename = all_images[file_index]
		load_image(bitmap, filename)
	else:
		prompt_index = (prompt_index - 1) % num_prompts
		prompt_txt.text = prompt_labels[prompt_index]
		pycam.display.refresh()