Merge branch 'main' of github.com:Monadical-SAS/reflector into sara/language-picker

2025-12-21 04:39:06 +00:00 · 2023-10-13 20:23:23 +02:00
parent eca5330f44 1d92d43fe0
commit 3555cc3a3c
24 changed files with 1271 additions and 283 deletions
--- a/server/env.example
+++ b/server/env.example
@@ -48,6 +48,7 @@
 ## Using serverless modal.com (require reflector-gpu-modal deployed)
 #TRANSCRIPT_BACKEND=modal
 #TRANSCRIPT_URL=https://xxxxx--reflector-transcriber-web.modal.run
+#TRANSLATE_URL=https://xxxxx--reflector-translator-web.modal.run
 #TRANSCRIPT_MODAL_API_KEY=xxxxx

 ## Using serverless banana.dev (require reflector-gpu-banana deployed)
--- a/server/gpu/modal/reflector_llm_zephyr.py
+++ b/server/gpu/modal/reflector_llm_zephyr.py
@@ -0,0 +1,208 @@
+"""
+Reflector GPU backend - LLM
+===========================
+
+"""
+import json
+import os
+from typing import Optional
+
+import modal
+from modal import Image, Secret, Stub, asgi_app, method
+
+# LLM
+LLM_MODEL: str = "HuggingFaceH4/zephyr-7b-alpha"
+LLM_LOW_CPU_MEM_USAGE: bool = True
+LLM_TORCH_DTYPE: str = "bfloat16"
+LLM_MAX_NEW_TOKENS: int = 300
+
+IMAGE_MODEL_DIR = "/root/llm_models"
+
+stub = Stub(name="reflector-llm-zephyr")
+
+
+def download_llm():
+    from huggingface_hub import snapshot_download
+
+    print("Downloading LLM model")
+    snapshot_download(LLM_MODEL, cache_dir=IMAGE_MODEL_DIR)
+    print("LLM model downloaded")
+
+
+def migrate_cache_llm():
+    """
+    XXX The cache for model files in Transformers v4.22.0 has been updated.
+    Migrating your old cache. This is a one-time only operation. You can
+    interrupt this and resume the migration later on by calling
+    `transformers.utils.move_cache()`.
+    """
+    from transformers.utils.hub import move_cache
+
+    print("Moving LLM cache")
+    move_cache(cache_dir=IMAGE_MODEL_DIR, new_cache_dir=IMAGE_MODEL_DIR)
+    print("LLM cache moved")
+
+
+llm_image = (
+    Image.debian_slim(python_version="3.10.8")
+    .apt_install("git")
+    .pip_install(
+        "transformers==4.34.0",
+        "torch",
+        "sentencepiece",
+        "protobuf",
+        "jsonformer==0.12.0",
+        "accelerate==0.21.0",
+        "einops==0.6.1",
+        "hf-transfer~=0.1",
+        "huggingface_hub==0.16.4"
+    )
+    .env({"HF_HUB_ENABLE_HF_TRANSFER": "1"})
+    .run_function(download_llm)
+    .run_function(migrate_cache_llm)
+)
+
+
+@stub.cls(
+    gpu="A10G",
+    timeout=60 * 5,
+    container_idle_timeout=60 * 5,
+    concurrency_limit=2,
+    image=llm_image,
+)
+class LLM:
+    def __enter__(self):
+        import torch
+        from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
+
+        print("Instance llm model")
+        model = AutoModelForCausalLM.from_pretrained(
+            LLM_MODEL,
+            torch_dtype=getattr(torch, LLM_TORCH_DTYPE),
+            low_cpu_mem_usage=LLM_LOW_CPU_MEM_USAGE,
+            cache_dir=IMAGE_MODEL_DIR
+        )
+
+        # JSONFormer doesn't yet support generation configs
+        print("Instance llm generation config")
+        model.config.max_new_tokens = LLM_MAX_NEW_TOKENS
+
+        # generation configuration
+        gen_cfg = GenerationConfig.from_model_config(model.config)
+        gen_cfg.max_new_tokens = LLM_MAX_NEW_TOKENS
+
+        # load tokenizer
+        print("Instance llm tokenizer")
+        tokenizer = AutoTokenizer.from_pretrained(
+            LLM_MODEL,
+            cache_dir=IMAGE_MODEL_DIR
+        )
+        gen_cfg.pad_token_id = tokenizer.eos_token_id
+        gen_cfg.eos_token_id = tokenizer.eos_token_id
+        tokenizer.pad_token = tokenizer.eos_token
+        model.config.pad_token_id = tokenizer.eos_token_id
+
+        # move model to gpu
+        print("Move llm model to GPU")
+        model = model.cuda()
+
+        print("Warmup llm done")
+        self.model = model
+        self.tokenizer = tokenizer
+        self.gen_cfg = gen_cfg
+        self.GenerationConfig = GenerationConfig
+
+    def __exit__(self, *args):
+        print("Exit llm")
+
+    @method()
+    def generate(self, prompt: str, gen_schema: str | None, gen_cfg: str | None) -> dict:
+        """
+        Perform a generation action using the LLM
+        """
+        print(f"Generate {prompt=}")
+        if gen_cfg:
+            gen_cfg = self.GenerationConfig.from_dict(json.loads(gen_cfg))
+            gen_cfg.pad_token_id = self.tokenizer.eos_token_id
+            gen_cfg.eos_token_id = self.tokenizer.eos_token_id
+        else:
+            gen_cfg = self.gen_cfg
+
+        # If a gen_schema is given, conform to gen_schema
+        if gen_schema:
+            import jsonformer
+
+            print(f"Schema {gen_schema=}")
+            jsonformer_llm = jsonformer.Jsonformer(
+                model=self.model,
+                tokenizer=self.tokenizer,
+                json_schema=json.loads(gen_schema),
+                prompt=prompt,
+                max_string_token_length=gen_cfg.max_new_tokens
+            )
+            response = jsonformer_llm()
+        else:
+            # If no gen_schema, perform prompt only generation
+
+            # tokenize prompt
+            input_ids = self.tokenizer.encode(prompt, return_tensors="pt").to(
+                self.model.device
+            )
+            output = self.model.generate(input_ids, generation_config=gen_cfg)
+
+            # decode output
+            response = self.tokenizer.decode(output[0].cpu(), skip_special_tokens=True)
+            response = response[len(prompt):]
+            response = {
+                "long_summary": response
+            }
+        print(f"Generated {response=}")
+        return {"text": response}
+
+# -------------------------------------------------------------------
+# Web API
+# -------------------------------------------------------------------
+
+
+@stub.function(
+    container_idle_timeout=60 * 10,
+    timeout=60 * 5,
+    secrets=[
+        Secret.from_name("reflector-gpu"),
+    ],
+)
+@asgi_app()
+def web():
+    from fastapi import Depends, FastAPI, HTTPException, status
+    from fastapi.security import OAuth2PasswordBearer
+    from pydantic import BaseModel
+
+    llmstub = LLM()
+
+    app = FastAPI()
+    oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
+
+    def apikey_auth(apikey: str = Depends(oauth2_scheme)):
+        if apikey != os.environ["REFLECTOR_GPU_APIKEY"]:
+            raise HTTPException(
+                status_code=status.HTTP_401_UNAUTHORIZED,
+                detail="Invalid API key",
+                headers={"WWW-Authenticate": "Bearer"},
+            )
+
+    class LLMRequest(BaseModel):
+        prompt: str
+        gen_schema: Optional[dict] = None
+        gen_cfg: Optional[dict] = None
+
+    @app.post("/llm", dependencies=[Depends(apikey_auth)])
+    async def llm(
+            req: LLMRequest,
+    ):
+        gen_schema = json.dumps(req.gen_schema) if req.gen_schema else None
+        gen_cfg = json.dumps(req.gen_cfg) if req.gen_cfg else None
+        func = llmstub.generate.spawn(prompt=req.prompt, gen_schema=gen_schema, gen_cfg=gen_cfg)
+        result = func.get()
+        return result
+
+    return app
--- a/server/gpu/modal/reflector_transcriber.py
+++ b/server/gpu/modal/reflector_transcriber.py
@@ -14,34 +14,12 @@ WHISPER_MODEL: str = "large-v2"
 WHISPER_COMPUTE_TYPE: str = "float16"
 WHISPER_NUM_WORKERS: int = 1

-# Seamless M4T
-SEAMLESSM4T_MODEL_SIZE: str = "medium"
-SEAMLESSM4T_MODEL_CARD_NAME: str = f"seamlessM4T_{SEAMLESSM4T_MODEL_SIZE}"
-SEAMLESSM4T_VOCODER_CARD_NAME: str = "vocoder_36langs"
-
-HF_SEAMLESS_M4TEPO: str = f"facebook/seamless-m4t-{SEAMLESSM4T_MODEL_SIZE}"
-HF_SEAMLESS_M4T_VOCODEREPO: str = "facebook/seamless-m4t-vocoder"
-
-SEAMLESS_GITEPO: str = "https://github.com/facebookresearch/seamless_communication.git"
-SEAMLESS_MODEL_DIR: str = "m4t"

 WHISPER_MODEL_DIR = "/root/transcription_models"

 stub = Stub(name="reflector-transcriber")


-def install_seamless_communication():
-    import os
-    import subprocess
-    initial_dir = os.getcwd()
-    subprocess.run(["ssh-keyscan", "-t", "rsa", "github.com", ">>", "~/.ssh/known_hosts"])
-    subprocess.run(["rm", "-rf", "seamless_communication"])
-    subprocess.run(["git", "clone", SEAMLESS_GITEPO, "." + "/seamless_communication"])
-    os.chdir("seamless_communication")
-    subprocess.run(["pip", "install", "-e", "."])
-    os.chdir(initial_dir)
-
-
 def download_whisper():
    from faster_whisper.utils import download_model

@@ -50,18 +28,6 @@ def download_whisper():
    print("Whisper model downloaded")


-def download_seamlessm4t_model():
-    from huggingface_hub import snapshot_download
-
-    print("Downloading Transcriber model & tokenizer")
-    snapshot_download(HF_SEAMLESS_M4TEPO, cache_dir=SEAMLESS_MODEL_DIR)
-    print("Transcriber model & tokenizer downloaded")
-
-    print("Downloading vocoder weights")
-    snapshot_download(HF_SEAMLESS_M4T_VOCODEREPO, cache_dir=SEAMLESS_MODEL_DIR)
-    print("Vocoder weights downloaded")
-
-
 def migrate_cache_llm():
    """
    XXX The cache for model files in Transformers v4.22.0 has been updated.
@@ -76,52 +42,6 @@ def migrate_cache_llm():
    print("LLM cache moved")


-def configure_seamless_m4t():
-    import os
-
-    import yaml
-
-    ASSETS_DIR: str = "./seamless_communication/src/seamless_communication/assets/cards"
-
-    with open(f'{ASSETS_DIR}/seamlessM4T_{SEAMLESSM4T_MODEL_SIZE}.yaml', 'r') as file:
-        model_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
-    with open(f'{ASSETS_DIR}/vocoder_36langs.yaml', 'r') as file:
-        vocoder_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
-    with open(f'{ASSETS_DIR}/unity_nllb-100.yaml', 'r') as file:
-        unity_100_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
-    with open(f'{ASSETS_DIR}/unity_nllb-200.yaml', 'r') as file:
-        unity_200_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
-
-    model_dir = f"{SEAMLESS_MODEL_DIR}/models--facebook--seamless-m4t-{SEAMLESSM4T_MODEL_SIZE}/snapshots"
-    available_model_versions = os.listdir(model_dir)
-    latest_model_version = sorted(available_model_versions)[-1]
-    model_name = f"multitask_unity_{SEAMLESSM4T_MODEL_SIZE}.pt"
-    model_path = os.path.join(os.getcwd(), model_dir, latest_model_version, model_name)
-
-    vocoder_dir = f"{SEAMLESS_MODEL_DIR}/models--facebook--seamless-m4t-vocoder/snapshots"
-    available_vocoder_versions = os.listdir(vocoder_dir)
-    latest_vocoder_version = sorted(available_vocoder_versions)[-1]
-    vocoder_name = "vocoder_36langs.pt"
-    vocoder_path = os.path.join(os.getcwd(), vocoder_dir, latest_vocoder_version, vocoder_name)
-
-    tokenizer_name = "tokenizer.model"
-    tokenizer_path = os.path.join(os.getcwd(), model_dir, latest_model_version, tokenizer_name)
-
-    model_yaml_data['checkpoint'] = f"file:/{model_path}"
-    vocoder_yaml_data['checkpoint'] = f"file:/{vocoder_path}"
-    unity_100_yaml_data['tokenizer'] = f"file:/{tokenizer_path}"
-    unity_200_yaml_data['tokenizer'] = f"file:/{tokenizer_path}"
-
-    with open(f'{ASSETS_DIR}/seamlessM4T_{SEAMLESSM4T_MODEL_SIZE}.yaml', 'w') as file:
-        yaml.dump(model_yaml_data, file)
-    with open(f'{ASSETS_DIR}/vocoder_36langs.yaml', 'w') as file:
-        yaml.dump(vocoder_yaml_data, file)
-    with open(f'{ASSETS_DIR}/unity_nllb-100.yaml', 'w') as file:
-        yaml.dump(unity_100_yaml_data, file)
-    with open(f'{ASSETS_DIR}/unity_nllb-200.yaml', 'w') as file:
-        yaml.dump(unity_200_yaml_data, file)
-
-
 transcriber_image = (
    Image.debian_slim(python_version="3.10.8")
    .apt_install("git")
@@ -131,7 +51,7 @@ transcriber_image = (
        "faster-whisper",
        "requests",
        "torch",
-        "transformers",
+        "transformers==4.34.0",
        "sentencepiece",
        "protobuf",
        "huggingface_hub==0.16.4",
@@ -141,9 +61,6 @@ transcriber_image = (
        "pyyaml",
        "hf-transfer~=0.1"
    )
-    .run_function(install_seamless_communication)
-    .run_function(download_seamlessm4t_model)
-    .run_function(configure_seamless_m4t)
    .run_function(download_whisper)
    .run_function(migrate_cache_llm)
    .env(
@@ -167,7 +84,6 @@ class Transcriber:
    def __enter__(self):
        import faster_whisper
        import torch
-        from seamless_communication.models.inference.translator import Translator

        self.use_gpu = torch.cuda.is_available()
        self.device = "cuda" if self.use_gpu else "cpu"
@@ -178,12 +94,6 @@ class Transcriber:
            num_workers=WHISPER_NUM_WORKERS,
            download_root=WHISPER_MODEL_DIR
        )
-        self.translator = Translator(
-            SEAMLESSM4T_MODEL_CARD_NAME,
-            SEAMLESSM4T_VOCODER_CARD_NAME,
-            torch.device(self.device),
-            dtype=torch.float32
-        )

    @method()
    def transcribe_segment(
@@ -229,38 +139,6 @@ class Transcriber:
                "words": words
            }

-    def get_seamless_lang_code(self, lang_code: str):
-        """
-        The codes for SeamlessM4T is different from regular standards.
-        For ex, French is "fra" and not "fr".
-        """
-        # TODO: Enhance with complete list of lang codes
-        seamless_lang_code = {
-            "en": "eng",
-            "fr": "fra"
-        }
-        return seamless_lang_code.get(lang_code, "eng")
-
-    @method()
-    def translate_text(
-            self,
-            text: str,
-            source_language: str,
-            target_language: str
-    ):
-        translated_text, _, _ = self.translator.predict(
-            text,
-            "t2tt",
-            src_lang=self.get_seamless_lang_code(source_language),
-            tgt_lang=self.get_seamless_lang_code(target_language),
-            ngram_filtering=True
-        )
-        return {
-            "text": {
-                source_language: text,
-                target_language: str(translated_text)
-            }
-        }
 # -------------------------------------------------------------------
 # Web API
 # -------------------------------------------------------------------
@@ -316,18 +194,4 @@ def web():
        result = func.get()
        return result

-    @app.post("/translate", dependencies=[Depends(apikey_auth)])
-    async def translate(
-            text: str,
-            source_language: Annotated[str, Body(...)] = "en",
-            target_language: Annotated[str, Body(...)] = "fr",
-    ) -> TranscriptResponse:
-        func = transcriberstub.translate_text.spawn(
-            text=text,
-            source_language=source_language,
-            target_language=target_language,
-        )
-        result = func.get()
-        return result
-
    return app
--- a/server/gpu/modal/reflector_translator.py
+++ b/server/gpu/modal/reflector_translator.py
@@ -0,0 +1,237 @@
+"""
+Reflector GPU backend - transcriber
+===================================
+"""
+
+import os
+import tempfile
+
+from modal import Image, Secret, Stub, asgi_app, method
+from pydantic import BaseModel
+
+# Seamless M4T
+SEAMLESSM4T_MODEL_SIZE: str = "medium"
+SEAMLESSM4T_MODEL_CARD_NAME: str = f"seamlessM4T_{SEAMLESSM4T_MODEL_SIZE}"
+SEAMLESSM4T_VOCODER_CARD_NAME: str = "vocoder_36langs"
+
+HF_SEAMLESS_M4TEPO: str = f"facebook/seamless-m4t-{SEAMLESSM4T_MODEL_SIZE}"
+HF_SEAMLESS_M4T_VOCODEREPO: str = "facebook/seamless-m4t-vocoder"
+
+SEAMLESS_GITEPO: str = "https://github.com/facebookresearch/seamless_communication.git"
+SEAMLESS_MODEL_DIR: str = "m4t"
+
+stub = Stub(name="reflector-translator")
+
+
+def install_seamless_communication():
+    import os
+    import subprocess
+    initial_dir = os.getcwd()
+    subprocess.run(["ssh-keyscan", "-t", "rsa", "github.com", ">>", "~/.ssh/known_hosts"])
+    subprocess.run(["rm", "-rf", "seamless_communication"])
+    subprocess.run(["git", "clone", SEAMLESS_GITEPO, "." + "/seamless_communication"])
+    os.chdir("seamless_communication")
+    subprocess.run(["pip", "install", "-e", "."])
+    os.chdir(initial_dir)
+
+
+def download_seamlessm4t_model():
+    from huggingface_hub import snapshot_download
+
+    print("Downloading Transcriber model & tokenizer")
+    snapshot_download(HF_SEAMLESS_M4TEPO, cache_dir=SEAMLESS_MODEL_DIR)
+    print("Transcriber model & tokenizer downloaded")
+
+    print("Downloading vocoder weights")
+    snapshot_download(HF_SEAMLESS_M4T_VOCODEREPO, cache_dir=SEAMLESS_MODEL_DIR)
+    print("Vocoder weights downloaded")
+
+
+def configure_seamless_m4t():
+    import os
+
+    import yaml
+
+    ASSETS_DIR: str = "./seamless_communication/src/seamless_communication/assets/cards"
+
+    with open(f'{ASSETS_DIR}/seamlessM4T_{SEAMLESSM4T_MODEL_SIZE}.yaml', 'r') as file:
+        model_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
+    with open(f'{ASSETS_DIR}/vocoder_36langs.yaml', 'r') as file:
+        vocoder_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
+    with open(f'{ASSETS_DIR}/unity_nllb-100.yaml', 'r') as file:
+        unity_100_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
+    with open(f'{ASSETS_DIR}/unity_nllb-200.yaml', 'r') as file:
+        unity_200_yaml_data = yaml.load(file, Loader=yaml.FullLoader)
+
+    model_dir = f"{SEAMLESS_MODEL_DIR}/models--facebook--seamless-m4t-{SEAMLESSM4T_MODEL_SIZE}/snapshots"
+    available_model_versions = os.listdir(model_dir)
+    latest_model_version = sorted(available_model_versions)[-1]
+    model_name = f"multitask_unity_{SEAMLESSM4T_MODEL_SIZE}.pt"
+    model_path = os.path.join(os.getcwd(), model_dir, latest_model_version, model_name)
+
+    vocoder_dir = f"{SEAMLESS_MODEL_DIR}/models--facebook--seamless-m4t-vocoder/snapshots"
+    available_vocoder_versions = os.listdir(vocoder_dir)
+    latest_vocoder_version = sorted(available_vocoder_versions)[-1]
+    vocoder_name = "vocoder_36langs.pt"
+    vocoder_path = os.path.join(os.getcwd(), vocoder_dir, latest_vocoder_version, vocoder_name)
+
+    tokenizer_name = "tokenizer.model"
+    tokenizer_path = os.path.join(os.getcwd(), model_dir, latest_model_version, tokenizer_name)
+
+    model_yaml_data['checkpoint'] = f"file:/{model_path}"
+    vocoder_yaml_data['checkpoint'] = f"file:/{vocoder_path}"
+    unity_100_yaml_data['tokenizer'] = f"file:/{tokenizer_path}"
+    unity_200_yaml_data['tokenizer'] = f"file:/{tokenizer_path}"
+
+    with open(f'{ASSETS_DIR}/seamlessM4T_{SEAMLESSM4T_MODEL_SIZE}.yaml', 'w') as file:
+        yaml.dump(model_yaml_data, file)
+    with open(f'{ASSETS_DIR}/vocoder_36langs.yaml', 'w') as file:
+        yaml.dump(vocoder_yaml_data, file)
+    with open(f'{ASSETS_DIR}/unity_nllb-100.yaml', 'w') as file:
+        yaml.dump(unity_100_yaml_data, file)
+    with open(f'{ASSETS_DIR}/unity_nllb-200.yaml', 'w') as file:
+        yaml.dump(unity_200_yaml_data, file)
+
+
+transcriber_image = (
+    Image.debian_slim(python_version="3.10.8")
+    .apt_install("git")
+    .apt_install("wget")
+    .apt_install("libsndfile-dev")
+    .pip_install(
+        "requests",
+        "torch",
+        "transformers==4.34.0",
+        "sentencepiece",
+        "protobuf",
+        "huggingface_hub==0.16.4",
+        "gitpython",
+        "torchaudio",
+        "fairseq2",
+        "pyyaml",
+        "hf-transfer~=0.1"
+    )
+    .run_function(install_seamless_communication)
+    .run_function(download_seamlessm4t_model)
+    .run_function(configure_seamless_m4t)
+    .env(
+        {
+            "LD_LIBRARY_PATH": (
+                "/usr/local/lib/python3.10/site-packages/nvidia/cudnn/lib/:"
+                "/opt/conda/lib/python3.10/site-packages/nvidia/cublas/lib/"
+            )
+        }
+    )
+)
+
+
+@stub.cls(
+    gpu="A10G",
+    timeout=60 * 5,
+    container_idle_timeout=60 * 5,
+    image=transcriber_image,
+)
+class Translator:
+    def __enter__(self):
+        import torch
+        from seamless_communication.models.inference.translator import Translator
+
+        self.use_gpu = torch.cuda.is_available()
+        self.device = "cuda" if self.use_gpu else "cpu"
+        self.translator = Translator(
+            SEAMLESSM4T_MODEL_CARD_NAME,
+            SEAMLESSM4T_VOCODER_CARD_NAME,
+            torch.device(self.device),
+            dtype=torch.float32
+        )
+
+    @method()
+    def warmup(self):
+        return {"status": "ok"}
+
+    def get_seamless_lang_code(self, lang_code: str):
+        """
+        The codes for SeamlessM4T is different from regular standards.
+        For ex, French is "fra" and not "fr".
+        """
+        # TODO: Enhance with complete list of lang codes
+        seamless_lang_code = {
+            "en": "eng",
+            "fr": "fra"
+        }
+        return seamless_lang_code.get(lang_code, "eng")
+
+    @method()
+    def translate_text(
+            self,
+            text: str,
+            source_language: str,
+            target_language: str
+    ):
+        translated_text, _, _ = self.translator.predict(
+            text,
+            "t2tt",
+            src_lang=self.get_seamless_lang_code(source_language),
+            tgt_lang=self.get_seamless_lang_code(target_language),
+            ngram_filtering=True
+        )
+        return {
+            "text": {
+                source_language: text,
+                target_language: str(translated_text)
+            }
+        }
+# -------------------------------------------------------------------
+# Web API
+# -------------------------------------------------------------------
+
+
+@stub.function(
+    container_idle_timeout=60,
+    timeout=60,
+    secrets=[
+        Secret.from_name("reflector-gpu"),
+    ],
+)
+@asgi_app()
+def web():
+    from fastapi import Body, Depends, FastAPI, HTTPException, status
+    from fastapi.security import OAuth2PasswordBearer
+    from typing_extensions import Annotated
+
+    translatorstub = Translator()
+
+    app = FastAPI()
+
+    oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
+
+    def apikey_auth(apikey: str = Depends(oauth2_scheme)):
+        if apikey != os.environ["REFLECTOR_GPU_APIKEY"]:
+            raise HTTPException(
+                status_code=status.HTTP_401_UNAUTHORIZED,
+                detail="Invalid API key",
+                headers={"WWW-Authenticate": "Bearer"},
+            )
+
+    class TranslateResponse(BaseModel):
+        result: dict
+
+    @app.post("/translate", dependencies=[Depends(apikey_auth)])
+    async def translate(
+            text: str,
+            source_language: Annotated[str, Body(...)] = "en",
+            target_language: Annotated[str, Body(...)] = "fr",
+    ) -> TranslateResponse:
+        func = translatorstub.translate_text.spawn(
+            text=text,
+            source_language=source_language,
+            target_language=target_language,
+        )
+        result = func.get()
+        return result
+
+    @app.post("/warmup", dependencies=[Depends(apikey_auth)])
+    async def warmup():
+        return translatorstub.warmup.spawn().get()
+
+    return app
--- a/server/reflector/llm/base.py
+++ b/server/reflector/llm/base.py
@@ -258,7 +258,7 @@ class LLM:
        """
        Choose the token size to set as the threshold to pack the LLM calls
        """
-        buffer_token_size = 25
+        buffer_token_size = 100
        default_output_tokens = 1000
        context_window = self.tokenizer.model_max_length
        tokens = self.tokenizer.tokenize(
--- a/server/reflector/llm/llm_modal.py
+++ b/server/reflector/llm/llm_modal.py
@@ -23,7 +23,7 @@ class ModalLLM(LLM):
        """
        # TODO: Query the specific GPU platform
        # Replace this with a HTTP call
-        return ["lmsys/vicuna-13b-v1.5"]
+        return ["lmsys/vicuna-13b-v1.5", "HuggingFaceH4/zephyr-7b-alpha"]

    async def _generate(
        self, prompt: str, gen_schema: dict | None, gen_cfg: dict | None, **kwargs
@@ -33,6 +33,13 @@ class ModalLLM(LLM):
            json_payload["gen_schema"] = gen_schema
        if gen_cfg:
            json_payload["gen_cfg"] = gen_cfg
+
+        # Handing over generation of the final summary to Zephyr model
+        # but replacing the Vicuna model will happen after more testing
+        # TODO: Create a mapping of model names and cloud deployments
+        if self.model_name == "HuggingFaceH4/zephyr-7b-alpha":
+            self.llm_url = settings.ZEPHYR_LLM_URL + "/llm"
+
        async with httpx.AsyncClient() as client:
            response = await retry(client.post)(
                self.llm_url,
--- a/server/reflector/llm/llm_params.py
+++ b/server/reflector/llm/llm_params.py
@@ -144,7 +144,76 @@ class TopicParams(LLMTaskParams):
        return self._task_params


+class BulletedSummaryParams(LLMTaskParams):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self._gen_cfg = GenerationConfig(
+            max_new_tokens=800,
+            num_beams=1,
+            do_sample=True,
+            temperature=0.2,
+            early_stopping=True,
+        )
+        self._instruct = """
+        Given a meeting transcript, extract the key things discussed in the
+         form of a list.
+
+        While generating the response, follow the constraints mentioned below.
+
+        Summary constraints:
+        i) Do not add new content, except to fix spelling or punctuation.
+        ii) Do not add any prefixes or numbering in the response.
+        iii) The summarization should be as information dense as possible.
+        iv) Do not add any additional sections like Note, Conclusion, etc. in
+        the response.
+
+        Response format:
+        i) The response should be in the form of a bulleted list.
+        ii) Iteratively merge all the relevant paragraphs together to keep the
+         number of paragraphs to a minimum.
+        iii) Remove any unfinished sentences from the final response.
+        iv) Do not include narrative or reporting clauses.
+        v) Use "*" as the bullet icon.
+    """
+        self._task_params = TaskParams(
+            instruct=self._instruct, gen_schema=None, gen_cfg=self._gen_cfg
+        )
+
+    def _get_task_params(self) -> TaskParams:
+        """gen_schema
+        Return the parameters associated with a specific LLM task
+        """
+        return self._task_params
+
+
+class MergedSummaryParams(LLMTaskParams):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self._gen_cfg = GenerationConfig(
+            max_new_tokens=600,
+            num_beams=1,
+            do_sample=True,
+            temperature=0.2,
+            early_stopping=True,
+        )
+        self._instruct = """
+        Given the key points of a meeting, summarize the points to describe the
+         meeting in the form of paragraphs.
+        """
+        self._task_params = TaskParams(
+            instruct=self._instruct, gen_schema=None, gen_cfg=self._gen_cfg
+        )
+
+    def _get_task_params(self) -> TaskParams:
+        """gen_schema
+        Return the parameters associated with a specific LLM task
+        """
+        return self._task_params
+
+
 LLMTaskParams.register("topic", TopicParams)
 LLMTaskParams.register("final_title", FinalTitleParams)
 LLMTaskParams.register("final_short_summary", FinalShortSummaryParams)
 LLMTaskParams.register("final_long_summary", FinalLongSummaryParams)
+LLMTaskParams.register("bullet_summary", BulletedSummaryParams)
+LLMTaskParams.register("merged_summary", MergedSummaryParams)
--- a/server/reflector/processors/transcript_final_long_summary.py
+++ b/server/reflector/processors/transcript_final_long_summary.py
@@ -1,3 +1,4 @@
+import nltk
 from reflector.llm import LLM, LLMTaskParams
 from reflector.processors.base import Processor
 from reflector.processors.types import FinalLongSummary, TitleSummary
@@ -10,36 +11,58 @@ class TranscriptFinalLongSummaryProcessor(Processor):

    INPUT_TYPE = TitleSummary
    OUTPUT_TYPE = FinalLongSummary
-    TASK = "final_long_summary"

    def __init__(self, **kwargs):
        super().__init__(**kwargs)
        self.chunks: list[TitleSummary] = []
-        self.llm = LLM.get_instance()
-        self.params = LLMTaskParams.get_instance(self.TASK).task_params
+        self.llm = LLM.get_instance(model_name="HuggingFaceH4/zephyr-7b-alpha")

    async def _push(self, data: TitleSummary):
        self.chunks.append(data)

+    async def get_bullet_summary(self, text: str) -> str:
+        params = LLMTaskParams.get_instance("bullet_summary").task_params
+        chunks = list(self.llm.split_corpus(corpus=text, task_params=params))
+
+        bullet_summary = ""
+        for chunk in chunks:
+            prompt = self.llm.create_prompt(instruct=params.instruct, text=chunk)
+            summary_result = await self.llm.generate(
+                prompt=prompt,
+                gen_schema=params.gen_schema,
+                gen_cfg=params.gen_cfg,
+                logger=self.logger,
+            )
+            bullet_summary += summary_result["long_summary"]
+        return bullet_summary
+
+    async def get_merged_summary(self, text: str) -> str:
+        params = LLMTaskParams.get_instance("merged_summary").task_params
+        chunks = list(self.llm.split_corpus(corpus=text, task_params=params))
+
+        merged_summary = ""
+        for chunk in chunks:
+            prompt = self.llm.create_prompt(instruct=params.instruct, text=chunk)
+            summary_result = await self.llm.generate(
+                prompt=prompt,
+                gen_schema=params.gen_schema,
+                gen_cfg=params.gen_cfg,
+                logger=self.logger,
+            )
+            merged_summary += summary_result["long_summary"]
+        return merged_summary
+
    async def get_long_summary(self, text: str) -> str:
        """
        Generate a long version of the final summary
        """
-        self.logger.info(f"Smoothing out {len(text)} length summary to a long summary")
-        chunks = list(self.llm.split_corpus(corpus=text, task_params=self.params))
+        bullet_summary = await self.get_bullet_summary(text)
+        merged_summary = await self.get_merged_summary(bullet_summary)

-        accumulated_summaries = ""
-        for chunk in chunks:
-            prompt = self.llm.create_prompt(instruct=self.params.instruct, text=chunk)
-            summary_result = await self.llm.generate(
-                prompt=prompt,
-                gen_schema=self.params.gen_schema,
-                gen_cfg=self.params.gen_cfg,
-                logger=self.logger,
-            )
-            accumulated_summaries += summary_result["long_summary"]
+        return merged_summary

-        return accumulated_summaries
+    def sentence_tokenize(self, text: str) -> [str]:
+        return nltk.sent_tokenize(text)

    async def _flush(self):
        if not self.chunks:
@@ -49,11 +72,25 @@ class TranscriptFinalLongSummaryProcessor(Processor):
        accumulated_summaries = " ".join([chunk.summary for chunk in self.chunks])
        long_summary = await self.get_long_summary(accumulated_summaries)

+        # Format the output as much as possible to be handled
+        # by front-end for displaying
+        summary_sentences = []
+        for sentence in self.sentence_tokenize(long_summary):
+            sentence = str(sentence).strip()
+            if sentence.startswith("- "):
+                sentence.replace("- ", "* ")
+            else:
+                sentence = "* " + sentence
+            sentence += " \n"
+            summary_sentences.append(sentence)
+
+        formatted_long_summary = "".join(summary_sentences)
+
        last_chunk = self.chunks[-1]
        duration = last_chunk.timestamp + last_chunk.duration

        final_long_summary = FinalLongSummary(
-            long_summary=long_summary,
+            long_summary=formatted_long_summary,
            duration=duration,
        )
        await self.emit(final_long_summary)
--- a/server/reflector/processors/transcript_translator.py
+++ b/server/reflector/processors/transcript_translator.py
@@ -16,8 +16,8 @@ class TranscriptTranslatorProcessor(Processor):

    def __init__(self, **kwargs):
        super().__init__(**kwargs)
-        self.transcript_url = settings.TRANSCRIPT_URL
-        self.timeout = settings.TRANSCRIPT_TIMEOUT
+        self.translate_url = settings.TRANSLATE_URL
+        self.timeout = settings.TRANSLATE_TIMEOUT
        self.headers = {"Authorization": f"Bearer {settings.LLM_MODAL_API_KEY}"}

    async def _push(self, data: Transcript):
@@ -46,7 +46,7 @@ class TranscriptTranslatorProcessor(Processor):

        async with httpx.AsyncClient() as client:
            response = await retry(client.post)(
-                settings.TRANSCRIPT_URL + "/translate",
+                self.translate_url + "/translate",
                headers=self.headers,
                params=json_payload,
                timeout=self.timeout,
--- a/server/reflector/settings.py
+++ b/server/reflector/settings.py
@@ -38,6 +38,10 @@ class Settings(BaseSettings):
    TRANSCRIPT_URL: str | None = None
    TRANSCRIPT_TIMEOUT: int = 90

+    # Translate into the target language
+    TRANSLATE_URL: str | None = None
+    TRANSLATE_TIMEOUT: int = 90
+
    # Audio transcription banana.dev configuration
    TRANSCRIPT_BANANA_API_KEY: str | None = None
    TRANSCRIPT_BANANA_MODEL_KEY: str | None = None
@@ -68,6 +72,7 @@ class Settings(BaseSettings):
    LLM_TIMEOUT: int = 60 * 5  # take cold start into account
    LLM_MAX_TOKENS: int = 1024
    LLM_TEMPERATURE: float = 0.7
+    ZEPHYR_LLM_URL: str | None = None

    # LLM Banana configuration
    LLM_BANANA_API_KEY: str | None = None
--- a/server/reflector/utils/audio_waveform.py
+++ b/server/reflector/utils/audio_waveform.py
@@ -9,11 +9,12 @@ def get_audio_waveform(path: Path | str, segments_count: int = 256) -> list[int]
        path = path.as_posix()

    container = av.open(path)
-    stream = container.streams.get(audio=0)[0]
+    stream = container.streams.audio[0]
    duration = container.duration / av.time_base

    chunk_size_secs = duration / segments_count
    chunk_size = int(chunk_size_secs * stream.rate * stream.channels)
+
    if chunk_size == 0:
        # there is not enough data to fill the chunks
        # so basically we use chunk_size of 1.
@@ -22,7 +23,7 @@ def get_audio_waveform(path: Path | str, segments_count: int = 256) -> list[int]
    # 1.1 is a safety margin as it seems that pyav decode
    # does not always return the exact number of chunks
    # that we expect.
-    volumes = np.zeros(int(segments_count * 1.1), dtype=int)
+    volumes = np.zeros(int(segments_count * 1.1), dtype=float)
    current_chunk_idx = 0
    current_chunk_size = 0
    current_chunk_volume = 0
@@ -35,7 +36,6 @@ def get_audio_waveform(path: Path | str, segments_count: int = 256) -> list[int]
        count += len(data)
        frames += 1
        samples += frame.samples
-
        while len(data) > 0:
            datalen = len(data)

@@ -53,13 +53,13 @@ def get_audio_waveform(path: Path | str, segments_count: int = 256) -> list[int]
                current_chunk_idx += 1
                current_chunk_size = 0
                current_chunk_volume = 0
-
    volumes = volumes[:current_chunk_idx]

-    # normalize the volumes 0-128
-    volumes = volumes * 128 / volumes.max()
+    # number of decimals to use when rounding the peak value
+    digits = 2
+    volumes = np.round(volumes / volumes.max(), digits)

-    return volumes.astype("uint8").tolist()
+    return volumes.tolist()


 if __name__ == "__main__":
--- a/server/reflector/views/transcripts.py
+++ b/server/reflector/views/transcripts.py
@@ -41,7 +41,7 @@ def generate_transcript_name():


 class AudioWaveform(BaseModel):
-    data: list[int]
+    data: list[float]


 class TranscriptText(BaseModel):
--- a/server/tests/conftest.py
+++ b/server/tests/conftest.py
@@ -93,3 +93,12 @@ def ensure_casing():
    with patch("reflector.llm.base.LLM.ensure_casing") as mock_casing:
        mock_casing.return_value = "LLM TITLE"
        yield
+
+
+@pytest.fixture
+def sentence_tokenize():
+    with patch(
+        "reflector.processors.TranscriptFinalLongSummaryProcessor" ".sentence_tokenize"
+    ) as mock_sent_tokenize:
+        mock_sent_tokenize.return_value = ["LLM LONG SUMMARY"]
+        yield
--- a/server/tests/test_processors_pipeline.py
+++ b/server/tests/test_processors_pipeline.py
@@ -9,6 +9,7 @@ async def test_basic_process(
    dummy_llm,
    dummy_processors,
    ensure_casing,
+    sentence_tokenize,
 ):
    # goal is to start the server, and send rtc audio to it
    # validate the events received
--- a/server/tests/test_transcripts_rtc_ws.py
+++ b/server/tests/test_transcripts_rtc_ws.py
@@ -60,6 +60,7 @@ async def test_transcript_rtc_and_websocket(
    dummy_processors,
    ensure_casing,
    appserver,
+    sentence_tokenize,
 ):
    # goal: start the server, exchange RTC, receive websocket events
    # because of that, we need to start the server in a thread
@@ -156,7 +157,7 @@ async def test_transcript_rtc_and_websocket(

    assert "FINAL_LONG_SUMMARY" in eventnames
    ev = events[eventnames.index("FINAL_LONG_SUMMARY")]
-    assert ev["data"]["long_summary"] == "LLM LONG SUMMARY"
+    assert ev["data"]["long_summary"] == "* LLM LONG SUMMARY \n"

    assert "FINAL_SHORT_SUMMARY" in eventnames
    ev = events[eventnames.index("FINAL_SHORT_SUMMARY")]
@@ -193,6 +194,7 @@ async def test_transcript_rtc_and_websocket_and_fr(
    dummy_processors,
    ensure_casing,
    appserver,
+    sentence_tokenize,
 ):
    # goal: start the server, exchange RTC, receive websocket events
    # because of that, we need to start the server in a thread
@@ -292,7 +294,7 @@ async def test_transcript_rtc_and_websocket_and_fr(

    assert "FINAL_LONG_SUMMARY" in eventnames
    ev = events[eventnames.index("FINAL_LONG_SUMMARY")]
-    assert ev["data"]["long_summary"] == "LLM LONG SUMMARY"
+    assert ev["data"]["long_summary"] == "* LLM LONG SUMMARY \n"

    assert "FINAL_SHORT_SUMMARY" in eventnames
    ev = events[eventnames.index("FINAL_SHORT_SUMMARY")]
--- a/www/app/api/apis/DefaultApi.ts
+++ b/www/app/api/apis/DefaultApi.ts
@@ -54,10 +54,6 @@ export interface V1TranscriptGetRequest {
  transcriptId: any;
 }

-export interface V1TranscriptGetAudioRequest {
-  transcriptId: any;
-}
-
 export interface V1TranscriptGetAudioMp3Request {
  transcriptId: any;
 }
@@ -310,69 +306,6 @@ export class DefaultApi extends runtime.BaseAPI {
    return await response.value();
  }

-  /**
-   * Transcript Get Audio
-   */
-  async v1TranscriptGetAudioRaw(
-    requestParameters: V1TranscriptGetAudioRequest,
-    initOverrides?: RequestInit | runtime.InitOverrideFunction,
-  ): Promise<runtime.ApiResponse<any>> {
-    if (
-      requestParameters.transcriptId === null ||
-      requestParameters.transcriptId === undefined
-    ) {
-      throw new runtime.RequiredError(
-        "transcriptId",
-        "Required parameter requestParameters.transcriptId was null or undefined when calling v1TranscriptGetAudio.",
-      );
-    }
-
-    const queryParameters: any = {};
-
-    const headerParameters: runtime.HTTPHeaders = {};
-
-    if (this.configuration && this.configuration.accessToken) {
-      // oauth required
-      headerParameters["Authorization"] = await this.configuration.accessToken(
-        "OAuth2AuthorizationCodeBearer",
-        [],
-      );
-    }
-
-    const response = await this.request(
-      {
-        path: `/v1/transcripts/{transcript_id}/audio`.replace(
-          `{${"transcript_id"}}`,
-          encodeURIComponent(String(requestParameters.transcriptId)),
-        ),
-        method: "GET",
-        headers: headerParameters,
-        query: queryParameters,
-      },
-      initOverrides,
-    );
-
-    if (this.isJsonMime(response.headers.get("content-type"))) {
-      return new runtime.JSONApiResponse<any>(response);
-    } else {
-      return new runtime.TextApiResponse(response) as any;
-    }
-  }
-
-  /**
-   * Transcript Get Audio
-   */
-  async v1TranscriptGetAudio(
-    requestParameters: V1TranscriptGetAudioRequest,
-    initOverrides?: RequestInit | runtime.InitOverrideFunction,
-  ): Promise<any> {
-    const response = await this.v1TranscriptGetAudioRaw(
-      requestParameters,
-      initOverrides,
-    );
-    return await response.value();
-  }
-
  /**
   * Transcript Get Audio Mp3
   */
--- a/www/app/styles/markdown.css
+++ b/www/app/styles/markdown.css
@@ -0,0 +1,91 @@
+/* Headings */
+.markdown h1,
+.markdown h2,
+.markdown h3,
+.markdown h4,
+.markdown h5,
+.markdown h6 {
+  margin-top: 1em;
+  margin-bottom: 0.5em;
+}
+
+/* Paragraphs */
+.markdown p {
+  margin: 1em 0;
+}
+
+/* Lists */
+.markdown ul,
+.markdown ol {
+  margin: 1em;
+  padding-left: 1em;
+}
+
+.markdown li {
+  margin: 0.2em 0;
+}
+
+/* Bold and italic */
+.markdown b,
+.markdown strong {
+  font-weight: bold;
+}
+
+.markdown i,
+.markdown em {
+  font-style: italic;
+}
+
+/* Blockquotes */
+.markdown blockquote {
+  margin: 1em 0;
+  padding-left: 1em;
+  border-left: 2px solid #ccc;
+}
+
+/* Code blocks and inline code */
+.markdown code {
+  font-family: "Courier New", monospace;
+}
+
+.markdown pre {
+  background-color: #f4f4f4;
+  padding: 1em;
+  overflow-x: auto;
+}
+
+/* Links */
+.markdown a {
+  color: blue;
+  text-decoration: underline;
+}
+
+/* Horizontal rule */
+.markdown hr {
+  border: 0;
+  border-bottom: 1px solid #ccc;
+  margin: 1em 0;
+}
+
+/* Images */
+.markdown img {
+  max-width: 100%;
+  height: auto;
+}
+
+/* Lists */
+.markdown ul {
+  margin: 1em;
+  padding-left: 1em;
+  list-style-type: disc;
+}
+
+.markdown ol {
+  margin: 1em;
+  padding-left: 1em;
+  list-style-type: decimal;
+}
+
+.markdown li {
+  margin: 0.2em 0;
+}
--- a/www/app/styles/recorder.js
+++ b/www/app/styles/recorder.js
@@ -0,0 +1,30 @@
+export const waveSurferStyles = {
+  playerSettings: {
+    waveColor: "#777",
+    progressColor: "#222",
+    cursorColor: "OrangeRed",
+  },
+  playerStyle: {
+    cursor: "pointer",
+    backgroundColor: "RGB(240 240 240)",
+    borderRadius: "15px",
+  },
+  marker: `
+    border-left: solid 1px orange;
+    padding: 0 2px 0 5px;
+    font-size: 0.7rem;
+    border-radius: 0 3px 3px 0;
+
+    position: absolute;
+    width: 100px;
+    max-width: fit-content;
+    cursor: pointer;
+    background-color: white;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    transition: width 100ms linear;
+    z-index: 0;
+  `,
+  markerHover: { backgroundColor: "orange" },
+};
--- a/www/app/transcripts/[transcriptId]/page.tsx
+++ b/www/app/transcripts/[transcriptId]/page.tsx
@@ -12,6 +12,7 @@ import "../../styles/button.css";
 import FinalSummary from "../finalSummary";
 import ShareLink from "../shareLink";
 import QRCode from "react-qr-code";
+import TranscriptTitle from "../transcriptTitle";

 type TranscriptDetails = {
  params: {
@@ -50,13 +51,18 @@ export default function TranscriptDetails(details: TranscriptDetails) {
        <Modal title="Loading" text={"Loading transcript..."} />
      ) : (
        <>
-          <Recorder
-            topics={topics?.topics || []}
-            useActiveTopic={useActiveTopic}
-            waveform={waveform?.waveform}
-            isPastMeeting={true}
-            transcriptId={transcript?.response?.id}
-          />
+          <div className="flex flex-col">
+            {transcript?.response?.title && (
+              <TranscriptTitle title={transcript.response.title} />
+            )}
+            <Recorder
+              topics={topics?.topics || []}
+              useActiveTopic={useActiveTopic}
+              waveform={waveform?.waveform}
+              isPastMeeting={true}
+              transcriptId={transcript?.response?.id}
+            />
+          </div>
          <div className="grid grid-cols-1 lg:grid-cols-2 grid-rows-2 lg:grid-rows-1 gap-2 lg:gap-4 h-full">
            <TopicList
              topics={topics?.topics || []}
--- a/www/app/transcripts/finalSummary.tsx
+++ b/www/app/transcripts/finalSummary.tsx
@@ -1,4 +1,8 @@
 import { useRef, useState } from "react";
+import React from "react";
+import ReactDom from "react-dom";
+import Markdown from "react-markdown";
+import "../styles/markdown.css";

 type FinalSummaryProps = {
  summary: string;
@@ -62,7 +66,9 @@ export default function FinalSummary(props: FinalSummaryProps) {
        </div>
      </div>

-      <p ref={finalSummaryRef}>{props.summary}</p>
+      <p ref={finalSummaryRef} className="markdown">
+        <Markdown>{props.summary}</Markdown>
+      </p>
    </div>
  );
 }
--- a/www/app/transcripts/recorder.tsx
+++ b/www/app/transcripts/recorder.tsx
@@ -14,6 +14,7 @@ import { AudioWaveform } from "../api";
 import AudioInputsDropdown from "./audioInputsDropdown";
 import { Option } from "react-dropdown";
 import { useError } from "../(errors)/errorContext";
+import { waveSurferStyles } from "../styles/recorder";

 type RecorderProps = {
  setStream?: React.Dispatch<React.SetStateAction<MediaStream | null>>;
@@ -94,20 +95,29 @@ export default function Recorder(props: RecorderProps) {
    };
  };

+  // Setup Shortcuts
+  useEffect(() => {
+    if (!record) return;
+
+    return setupProjectorKeys();
+  }, [record, deviceId]);
+
+  // Waveform setup
  useEffect(() => {
    if (waveformRef.current) {
      const _wavesurfer = WaveSurfer.create({
        container: waveformRef.current,
-        waveColor: "#777",
-        progressColor: "#222",
-        cursorColor: "OrangeRed",
+        url: props.transcriptId
+          ? `${process.env.NEXT_PUBLIC_API_URL}/v1/transcripts/${props.transcriptId}/audio/mp3`
+          : undefined,
+        peaks: props.waveform?.data,
+
        hideScrollbar: true,
        autoCenter: true,
        barWidth: 2,
        height: "auto",
-        url: props.transcriptId
-          ? `${process.env.NEXT_PUBLIC_API_URL}/v1/transcripts/${props.transcriptId}/audio/mp3`
-          : undefined,
+
+        ...waveSurferStyles.player,
      });

      if (!props.transcriptId) {
@@ -115,10 +125,12 @@ export default function Recorder(props: RecorderProps) {
        _wshack.renderer.renderSingleCanvas = () => {};
      }

+      // styling
      const wsWrapper = _wavesurfer.getWrapper();
-      wsWrapper.style.cursor = "pointer";
-      wsWrapper.style.backgroundColor = "RGB(240 240 240)";
-      wsWrapper.style.borderRadius = "15px";
+      wsWrapper.style.cursor = waveSurferStyles.playerStyle.cursor;
+      wsWrapper.style.backgroundColor =
+        waveSurferStyles.playerStyle.backgroundColor;
+      wsWrapper.style.borderRadius = waveSurferStyles.playerStyle.borderRadius;

      _wavesurfer.on("play", () => {
        setIsPlaying(true);
@@ -131,9 +143,10 @@ export default function Recorder(props: RecorderProps) {
      setRecord(_wavesurfer.registerPlugin(RecordPlugin.create()));
      setWaveRegions(_wavesurfer.registerPlugin(CustomRegionsPlugin.create()));

-      if (props.transcriptId) _wavesurfer.toggleInteraction(true);
+      if (props.isPastMeeting) _wavesurfer.toggleInteraction(true);

      setWavesurfer(_wavesurfer);
+
      return () => {
        _wavesurfer.destroy();
        setIsRecording(false);
@@ -152,35 +165,18 @@ export default function Recorder(props: RecorderProps) {
    if (!waveRegions) return;

    waveRegions.clearRegions();
+
    for (let topic of topicsRef.current) {
      const content = document.createElement("div");
-      content.setAttribute(
-        "style",
-        `
-        position: absolute;
-        border-left: solid 1px orange;
-        padding: 0 2px 0 5px;
-        font-size: 0.7rem;
-        width: 100px;
-        max-width: fit-content;
-        cursor: pointer;
-        background-color: white;
-        border-radius: 0 3px 3px 0;
-        white-space: nowrap;
-        overflow: hidden;
-        text-overflow: ellipsis;
-        transition: width 100ms linear;
-      `,
-      );
+      content.setAttribute("style", waveSurferStyles.marker);
      content.onmouseover = () => {
-        content.style.backgroundColor = "orange";
+        content.style.backgroundColor =
+          waveSurferStyles.markerHover.backgroundColor;
        content.style.zIndex = "999";
        content.style.width = "300px";
      };
      content.onmouseout = () => {
-        content.style.backgroundColor = "white";
-        content.style.zIndex = "0";
-        content.style.width = "100px";
+        content.setAttribute("style", waveSurferStyles.marker);
      };
      content.textContent = topic.title;

@@ -198,12 +194,6 @@ export default function Recorder(props: RecorderProps) {
    }
  };

-  useEffect(() => {
-    if (!record) return;
-
-    return setupProjectorKeys();
-  }, [record, deviceId]);
-
  useEffect(() => {
    if (!record) return;

--- a/www/app/transcripts/transcriptTitle.tsx
+++ b/www/app/transcripts/transcriptTitle.tsx
@@ -0,0 +1,13 @@
+type TranscriptTitle = {
+  title: string;
+};
+
+const TranscriptTitle = (props: TranscriptTitle) => {
+  return (
+    <h2 className="text-2xl lg:text-4xl font-extrabold text-center mb-4">
+      {props.title}
+    </h2>
+  );
+};
+
+export default TranscriptTitle;
--- a/www/package.json
+++ b/www/package.json
@@ -25,6 +25,7 @@
    "react": "^18.2.0",
    "react-dom": "^18.2.0",
    "react-dropdown": "^1.11.0",
+    "react-markdown": "^9.0.0",
    "react-qr-code": "^2.0.12",
    "sass": "^1.63.6",
    "simple-peer": "^9.11.1",
--- a/www/yarn.lock
+++ b/www/yarn.lock
@@ -400,11 +400,25 @@
  dependencies:
    tslib "^2.4.0"

+"@types/debug@^4.0.0":
+  version "4.1.9"
+  resolved "https://registry.yarnpkg.com/@types/debug/-/debug-4.1.9.tgz#906996938bc672aaf2fb8c0d3733ae1dda05b005"
+  integrity sha512-8Hz50m2eoS56ldRlepxSBa6PWEVCtzUo/92HgLc2qTMnotJNIm7xP+UZhyWoYsyOdd5dxZ+NZLb24rsKyFs2ow==
+  dependencies:
+    "@types/ms" "*"
+
 "@types/estree@*", "@types/estree@^1.0.0":
  version "1.0.1"
  resolved "https://registry.yarnpkg.com/@types/estree/-/estree-1.0.1.tgz#aa22750962f3bf0e79d753d3cc067f010c95f194"
  integrity sha512-LG4opVs2ANWZ1TJoKc937iMmNstM/d0ae1vNbnBvBhqCSezgVUOzcLCqbI5elV8Vy6WKwKjaqR+zO9VKirBBCA==

+"@types/hast@^3.0.0":
+  version "3.0.1"
+  resolved "https://registry.yarnpkg.com/@types/hast/-/hast-3.0.1.tgz#e1705ec9258ac4885659c2d50bac06b4fcd16466"
+  integrity sha512-hs/iBJx2aydugBQx5ETV3ZgeSS0oIreQrFJ4bjBl0XvM4wAmDjFEALY7p0rTSLt2eL+ibjRAAs9dTPiCLtmbqQ==
+  dependencies:
+    "@types/unist" "*"
+
 "@types/istanbul-lib-coverage@*", "@types/istanbul-lib-coverage@^2.0.0":
  version "2.0.4"
  resolved "https://registry.yarnpkg.com/@types/istanbul-lib-coverage/-/istanbul-lib-coverage-2.0.4.tgz#8467d4b3c087805d63580480890791277ce35c44"
@@ -424,6 +438,18 @@
  dependencies:
    "@types/istanbul-lib-report" "*"

+"@types/mdast@^4.0.0":
+  version "4.0.1"
+  resolved "https://registry.yarnpkg.com/@types/mdast/-/mdast-4.0.1.tgz#9c45e60a04e79f160dcefe6545d28ae536a6ed22"
+  integrity sha512-IlKct1rUTJ1T81d8OHzyop15kGv9A/ff7Gz7IJgrk6jDb4Udw77pCJ+vq8oxZf4Ghpm+616+i1s/LNg/Vh7d+g==
+  dependencies:
+    "@types/unist" "*"
+
+"@types/ms@*":
+  version "0.7.32"
+  resolved "https://registry.yarnpkg.com/@types/ms/-/ms-0.7.32.tgz#f6cd08939ae3ad886fcc92ef7f0109dacddf61ab"
+  integrity sha512-xPSg0jm4mqgEkNhowKgZFBNtwoEwF6gJ4Dhww+GFpm3IgtNseHQZ5IqdNwnquZEoANxyDAKDRAdVo4Z72VvD/g==
+
 "@types/node@*":
  version "20.4.5"
  resolved "https://registry.yarnpkg.com/@types/node/-/node-20.4.5.tgz#9dc0a5cb1ccce4f7a731660935ab70b9c00a5d69"
@@ -448,6 +474,11 @@
  resolved "https://registry.yarnpkg.com/@types/scheduler/-/scheduler-0.16.3.tgz#cef09e3ec9af1d63d2a6cc5b383a737e24e6dcf5"
  integrity sha512-5cJ8CB4yAx7BH1oMvdU0Jh9lrEXyPkar6F9G/ERswkCuvP4KQZfZkSjcMbAICCpQTN4OuZn8tz0HiKv9TGZgrQ==

+"@types/unist@*", "@types/unist@^3.0.0":
+  version "3.0.0"
+  resolved "https://registry.yarnpkg.com/@types/unist/-/unist-3.0.0.tgz#988ae8af1e5239e89f9fbb1ade4c935f4eeedf9a"
+  integrity sha512-MFETx3tbTjE7Uk6vvnWINA/1iJ7LuMdO4fcq8UfF0pRbj01aGLduVvQcRyswuACJdpnHgg8E3rQLhaRdNEJS0w==
+
 "@types/yargs-parser@*":
  version "21.0.0"
  resolved "https://registry.yarnpkg.com/@types/yargs-parser/-/yargs-parser-21.0.0.tgz#0c60e537fa790f5f9472ed2776c2b71ec117351b"
@@ -460,6 +491,11 @@
  dependencies:
    "@types/yargs-parser" "*"

+"@ungap/structured-clone@^1.0.0":
+  version "1.2.0"
+  resolved "https://registry.yarnpkg.com/@ungap/structured-clone/-/structured-clone-1.2.0.tgz#756641adb587851b5ccb3e095daf27ae581c8406"
+  integrity sha512-zuVdFrMJiuCDQUMCzQaD6KL28MjnqqN8XnAqiEq9PNm/hCPTSGfrXCOfwj1ow4LFb/tNymJPwsNbVePc1xFqrQ==
+
 agent-base@6:
  version "6.0.2"
  resolved "https://registry.yarnpkg.com/agent-base/-/agent-base-6.0.2.tgz#49fff58577cfee3f37176feab4c22e00f86d7f77"
@@ -543,6 +579,11 @@ axios@^1.4.0:
    form-data "^4.0.0"
    proxy-from-env "^1.1.0"

+bail@^2.0.0:
+  version "2.0.2"
+  resolved "https://registry.yarnpkg.com/bail/-/bail-2.0.2.tgz#d26f5cd8fe5d6f832a31517b9f7c356040ba6d5d"
+  integrity sha512-0xO6mYd7JB2YesxDKplafRpsiOzPt9V02ddPCLbY1xYGPOX24NTyN50qnUxgCPcSoYMhKpAuBTjQoRZCAkUDRw==
+
 balanced-match@^1.0.0:
  version "1.0.2"
  resolved "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz"
@@ -656,6 +697,11 @@ chalk@4.1.2, chalk@^4.0.0, chalk@^4.1.0, chalk@^4.1.1:
    ansi-styles "^4.1.0"
    supports-color "^7.1.0"

+character-entities@^2.0.0:
+  version "2.0.2"
+  resolved "https://registry.yarnpkg.com/character-entities/-/character-entities-2.0.2.tgz#2d09c2e72cd9523076ccb21157dff66ad43fcc22"
+  integrity sha512-shx7oQ0Awen/BRIdkjkvz54PnEEI/EjwXDSIZp86/KKdbafHh1Df/RYGBhn4hbe2+uKC9FnT5UCEdyPz3ai9hQ==
+
 chardet@^0.7.0:
  version "0.7.0"
  resolved "https://registry.yarnpkg.com/chardet/-/chardet-0.7.0.tgz#90094849f0937f2eedc2425d0d28a9e5f0cbad9e"
@@ -741,6 +787,11 @@ combined-stream@^1.0.8:
  dependencies:
    delayed-stream "~1.0.0"

+comma-separated-tokens@^2.0.0:
+  version "2.0.3"
+  resolved "https://registry.yarnpkg.com/comma-separated-tokens/-/comma-separated-tokens-2.0.3.tgz#4e89c9458acb61bc8fef19f4529973b2392839ee"
+  integrity sha512-Fu4hJdvzeylCfQPp9SGWidpzrMs7tTrlu6Vb8XGaRGck8QSNZJJp538Wrb60Lax4fPwR64ViY468OIUTbRlGZg==
+
 commander@8.3.0:
  version "8.3.0"
  resolved "https://registry.yarnpkg.com/commander/-/commander-8.3.0.tgz#4837ea1b2da67b9c616a67afbb0fafee567bca66"
@@ -824,13 +875,20 @@ date-fns@^2.16.1:
  dependencies:
    "@babel/runtime" "^7.21.0"

-debug@4, debug@^4.3.2, debug@^4.3.4:
+debug@4, debug@^4.0.0, debug@^4.3.2, debug@^4.3.4:
  version "4.3.4"
  resolved "https://registry.npmjs.org/debug/-/debug-4.3.4.tgz"
  integrity sha512-PRWFHuSU3eDtQJPvnNY7Jcket1j0t5OuOsFzPPzsekD52Zl8qUfFIPEiswXqIvHWGVHOgX+7G/vCNNhehwxfkQ==
  dependencies:
    ms "2.1.2"

+decode-named-character-reference@^1.0.0:
+  version "1.0.2"
+  resolved "https://registry.yarnpkg.com/decode-named-character-reference/-/decode-named-character-reference-1.0.2.tgz#daabac9690874c394c81e4162a0304b35d824f0e"
+  integrity sha512-O8x12RzrUF8xyVcY0KJowWsmaJxQbmy0/EtnNtHRpsOcT7dFk5W598coHqBVpmWo1oQQfsCqfCmkZN5DJrZVdg==
+  dependencies:
+    character-entities "^2.0.0"
+
 defaults@^1.0.3:
  version "1.0.4"
  resolved "https://registry.yarnpkg.com/defaults/-/defaults-1.0.4.tgz#b0b02062c1e2aa62ff5d9528f0f98baa90978d7a"
@@ -843,6 +901,18 @@ delayed-stream@~1.0.0:
  resolved "https://registry.yarnpkg.com/delayed-stream/-/delayed-stream-1.0.0.tgz#df3ae199acadfb7d440aaae0b29e2272b24ec619"
  integrity sha512-ZySD7Nf91aLB0RxL4KGrKHBXl7Eds1DAmEdcoVawXnLD7SDhpNgtuII2aAkg7a7QS41jxPSZ17p4VdGnMHk3MQ==

+dequal@^2.0.0:
+  version "2.0.3"
+  resolved "https://registry.yarnpkg.com/dequal/-/dequal-2.0.3.tgz#2644214f1997d39ed0ee0ece72335490a7ac67be"
+  integrity sha512-0je+qPKHEMohvfRTCEo3CrPG6cAzAYgmzKyxRiYSSDkS6eGJdyVJm7WaYA5ECaAD9wLB2T4EEeymA5aFVcYXCA==
+
+devlop@^1.0.0:
+  version "1.1.0"
+  resolved "https://registry.yarnpkg.com/devlop/-/devlop-1.1.0.tgz#4db7c2ca4dc6e0e834c30be70c94bbc976dc7018"
+  integrity sha512-RWmIqhcFf1lRYBvNmr7qTNuyCt/7/ns2jbpp1+PalgE/rDQcBT0fioSMUpJ93irlUhC5hrg4cYqe6U+0ImW0rA==
+  dependencies:
+    dequal "^2.0.0"
+
 dezalgo@^1.0.4:
  version "1.0.4"
  resolved "https://registry.yarnpkg.com/dezalgo/-/dezalgo-1.0.4.tgz#751235260469084c132157dfa857f386d4c33d81"
@@ -905,6 +975,11 @@ estree-walker@^2.0.2:
  resolved "https://registry.yarnpkg.com/estree-walker/-/estree-walker-2.0.2.tgz#52f010178c2a4c117a7757cfe942adb7d2da4cac"
  integrity sha512-Rfkk/Mp/DL7JVje3u18FxFujQlTNR2q6QfMSMB7AvCBx91NGj/ba3kCfza0f6dVDbw7YlRf/nDrn7pQrCCyQ/w==

+extend@^3.0.0:
+  version "3.0.2"
+  resolved "https://registry.yarnpkg.com/extend/-/extend-3.0.2.tgz#f8b1136b4071fbd8eb140aff858b1019ec2915fa"
+  integrity sha512-fjquC59cD7CyW6urNXK0FBufkZcoiGG80wTuPujX590cB5Ttln20E2UB4S/WARVqhXffZl2LNgS+gQdPIIim/g==
+
 external-editor@^3.0.3:
  version "3.1.0"
  resolved "https://registry.yarnpkg.com/external-editor/-/external-editor-3.1.0.tgz#cb03f740befae03ea4d283caed2741a83f335495"
@@ -1098,6 +1173,28 @@ has@^1.0.3:
  dependencies:
    function-bind "^1.1.1"

+hast-util-to-jsx-runtime@^2.0.0:
+  version "2.2.0"
+  resolved "https://registry.yarnpkg.com/hast-util-to-jsx-runtime/-/hast-util-to-jsx-runtime-2.2.0.tgz#ffd59bfcf0eb8321c6ed511bfc4b399ac3404bc2"
+  integrity sha512-wSlp23N45CMjDg/BPW8zvhEi3R+8eRE1qFbjEyAUzMCzu2l1Wzwakq+Tlia9nkCtEl5mDxa7nKHsvYJ6Gfn21A==
+  dependencies:
+    "@types/hast" "^3.0.0"
+    "@types/unist" "^3.0.0"
+    comma-separated-tokens "^2.0.0"
+    hast-util-whitespace "^3.0.0"
+    property-information "^6.0.0"
+    space-separated-tokens "^2.0.0"
+    style-to-object "^0.4.0"
+    unist-util-position "^5.0.0"
+    vfile-message "^4.0.0"
+
+hast-util-whitespace@^3.0.0:
+  version "3.0.0"
+  resolved "https://registry.yarnpkg.com/hast-util-whitespace/-/hast-util-whitespace-3.0.0.tgz#7778ed9d3c92dd9e8c5c8f648a49c21fc51cb621"
+  integrity sha512-88JUN06ipLwsnv+dVn+OIYOvAuvBMy/Qoi6O7mQHxdPXpjy+Cd6xRkWwux7DKO+4sYILtLBRIKgsdpS2gQc7qw==
+  dependencies:
+    "@types/hast" "^3.0.0"
+
 hexoid@^1.0.0:
  version "1.0.0"
  resolved "https://registry.yarnpkg.com/hexoid/-/hexoid-1.0.0.tgz#ad10c6573fb907de23d9ec63a711267d9dc9bc18"
@@ -1110,6 +1207,11 @@ hoist-non-react-statics@^3.3.2:
  dependencies:
    react-is "^16.7.0"

+html-url-attributes@^3.0.0:
+  version "3.0.0"
+  resolved "https://registry.yarnpkg.com/html-url-attributes/-/html-url-attributes-3.0.0.tgz#fc4abf0c3fb437e2329c678b80abb3c62cff6f08"
+  integrity sha512-/sXbVCWayk6GDVg3ctOX6nxaVj7So40FcFAnWlWGNAB1LpYKcV5Cd10APjPjW80O7zYW2MsjBV4zZ7IZO5fVow==
+
 https-proxy-agent@^5.0.0:
  version "5.0.1"
  resolved "https://registry.yarnpkg.com/https-proxy-agent/-/https-proxy-agent-5.0.1.tgz#c59ef224a04fe8b754f3db0063a25ea30d0005d6"
@@ -1160,6 +1262,11 @@ inherits@2, inherits@^2.0.3, inherits@^2.0.4:
  resolved "https://registry.npmjs.org/inherits/-/inherits-2.0.4.tgz"
  integrity sha512-k/vGaX4/Yla3WzyMCvTQOXYeIHvqOKtnqBduzTHpzpQZzAskKMhZ2K+EnBiSM9zGSoIFeMpXKxa4dYeZIQqewQ==

+inline-style-parser@0.1.1:
+  version "0.1.1"
+  resolved "https://registry.yarnpkg.com/inline-style-parser/-/inline-style-parser-0.1.1.tgz#ec8a3b429274e9c0a1f1c4ffa9453a7fef72cea1"
+  integrity sha512-7NXolsK4CAS5+xvdj5OMMbI962hU/wvwoxk+LWR9Ek9bVtyuuYScDN6eS0rUm6TxApFpw7CX1o4uJzcd4AyD3Q==
+
 inquirer@8.2.5:
  version "8.2.5"
  resolved "https://registry.yarnpkg.com/inquirer/-/inquirer-8.2.5.tgz#d8654a7542c35a9b9e069d27e2df4858784d54f8"
@@ -1222,6 +1329,11 @@ is-number@^7.0.0:
  resolved "https://registry.npmjs.org/is-number/-/is-number-7.0.0.tgz"
  integrity sha512-41Cifkg6e8TylSpdtTpeLVMqvSBEVzTttHvERD741+pnZ8ANv0004MRL43QKPDlK9cGvNp6NZWZUBlbGXYxxng==

+is-plain-obj@^4.0.0:
+  version "4.1.0"
+  resolved "https://registry.yarnpkg.com/is-plain-obj/-/is-plain-obj-4.1.0.tgz#d65025edec3657ce032fd7db63c97883eaed71f0"
+  integrity sha512-+Pgi+vMuUNkJyExiMBt5IlFoMyKnr5zhJ4Uspz58WOhBF5QoIZkFyNHIbBAtHwzVAgk5RtndVNsDRN61/mmDqg==
+
 is-reference@1.2.1:
  version "1.2.1"
  resolved "https://registry.yarnpkg.com/is-reference/-/is-reference-1.2.1.tgz#8b2dac0b371f4bc994fdeaba9eb542d03002d0b7"
@@ -1353,6 +1465,45 @@ magic-string@^0.27.0:
  dependencies:
    "@jridgewell/sourcemap-codec" "^1.4.13"

+mdast-util-from-markdown@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/mdast-util-from-markdown/-/mdast-util-from-markdown-2.0.0.tgz#52f14815ec291ed061f2922fd14d6689c810cb88"
+  integrity sha512-n7MTOr/z+8NAX/wmhhDji8O3bRvPTV/U0oTCaZJkjhPSKTPhS3xufVhKGF8s1pJ7Ox4QgoIU7KHseh09S+9rTA==
+  dependencies:
+    "@types/mdast" "^4.0.0"
+    "@types/unist" "^3.0.0"
+    decode-named-character-reference "^1.0.0"
+    devlop "^1.0.0"
+    mdast-util-to-string "^4.0.0"
+    micromark "^4.0.0"
+    micromark-util-decode-numeric-character-reference "^2.0.0"
+    micromark-util-decode-string "^2.0.0"
+    micromark-util-normalize-identifier "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+    unist-util-stringify-position "^4.0.0"
+
+mdast-util-to-hast@^13.0.0:
+  version "13.0.2"
+  resolved "https://registry.yarnpkg.com/mdast-util-to-hast/-/mdast-util-to-hast-13.0.2.tgz#74c0a9f014bb2340cae6118f6fccd75467792be7"
+  integrity sha512-U5I+500EOOw9e3ZrclN3Is3fRpw8c19SMyNZlZ2IS+7vLsNzb2Om11VpIVOR+/0137GhZsFEF6YiKD5+0Hr2Og==
+  dependencies:
+    "@types/hast" "^3.0.0"
+    "@types/mdast" "^4.0.0"
+    "@ungap/structured-clone" "^1.0.0"
+    devlop "^1.0.0"
+    micromark-util-sanitize-uri "^2.0.0"
+    trim-lines "^3.0.0"
+    unist-util-position "^5.0.0"
+    unist-util-visit "^5.0.0"
+
+mdast-util-to-string@^4.0.0:
+  version "4.0.0"
+  resolved "https://registry.yarnpkg.com/mdast-util-to-string/-/mdast-util-to-string-4.0.0.tgz#7a5121475556a04e7eddeb67b264aae79d312814"
+  integrity sha512-0H44vDimn51F0YwvxSJSm0eCDOJTRlmN0R1yBh4HLj9wiV1Dn0QoXGbvFAWj2hSItVTlCmBF1hqKlIyUBVFLPg==
+  dependencies:
+    "@types/mdast" "^4.0.0"
+
 merge-stream@^2.0.0:
  version "2.0.0"
  resolved "https://registry.yarnpkg.com/merge-stream/-/merge-stream-2.0.0.tgz#52823629a14dd00c9770fb6ad47dc6310f2c1f60"
@@ -1368,6 +1519,200 @@ methods@^1.1.2:
  resolved "https://registry.yarnpkg.com/methods/-/methods-1.1.2.tgz#5529a4d67654134edcc5266656835b0f851afcee"
  integrity sha512-iclAHeNqNm68zFtnZ0e+1L2yUIdvzNoauKU4WBA3VvH/vPFieF7qfRlwUZU+DA9P9bPXIS90ulxoUoCH23sV2w==

+micromark-core-commonmark@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-core-commonmark/-/micromark-core-commonmark-2.0.0.tgz#50740201f0ee78c12a675bf3e68ffebc0bf931a3"
+  integrity sha512-jThOz/pVmAYUtkroV3D5c1osFXAMv9e0ypGDOIZuCeAe91/sD6BoE2Sjzt30yuXtwOYUmySOhMas/PVyh02itA==
+  dependencies:
+    decode-named-character-reference "^1.0.0"
+    devlop "^1.0.0"
+    micromark-factory-destination "^2.0.0"
+    micromark-factory-label "^2.0.0"
+    micromark-factory-space "^2.0.0"
+    micromark-factory-title "^2.0.0"
+    micromark-factory-whitespace "^2.0.0"
+    micromark-util-character "^2.0.0"
+    micromark-util-chunked "^2.0.0"
+    micromark-util-classify-character "^2.0.0"
+    micromark-util-html-tag-name "^2.0.0"
+    micromark-util-normalize-identifier "^2.0.0"
+    micromark-util-resolve-all "^2.0.0"
+    micromark-util-subtokenize "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-factory-destination@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-factory-destination/-/micromark-factory-destination-2.0.0.tgz#857c94debd2c873cba34e0445ab26b74f6a6ec07"
+  integrity sha512-j9DGrQLm/Uhl2tCzcbLhy5kXsgkHUrjJHg4fFAeoMRwJmJerT9aw4FEhIbZStWN8A3qMwOp1uzHr4UL8AInxtA==
+  dependencies:
+    micromark-util-character "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-factory-label@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-factory-label/-/micromark-factory-label-2.0.0.tgz#17c5c2e66ce39ad6f4fc4cbf40d972f9096f726a"
+  integrity sha512-RR3i96ohZGde//4WSe/dJsxOX6vxIg9TimLAS3i4EhBAFx8Sm5SmqVfR8E87DPSR31nEAjZfbt91OMZWcNgdZw==
+  dependencies:
+    devlop "^1.0.0"
+    micromark-util-character "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-factory-space@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-factory-space/-/micromark-factory-space-2.0.0.tgz#5e7afd5929c23b96566d0e1ae018ae4fcf81d030"
+  integrity sha512-TKr+LIDX2pkBJXFLzpyPyljzYK3MtmllMUMODTQJIUfDGncESaqB90db9IAUcz4AZAJFdd8U9zOp9ty1458rxg==
+  dependencies:
+    micromark-util-character "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-factory-title@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-factory-title/-/micromark-factory-title-2.0.0.tgz#726140fc77892af524705d689e1cf06c8a83ea95"
+  integrity sha512-jY8CSxmpWLOxS+t8W+FG3Xigc0RDQA9bKMY/EwILvsesiRniiVMejYTE4wumNc2f4UbAa4WsHqe3J1QS1sli+A==
+  dependencies:
+    micromark-factory-space "^2.0.0"
+    micromark-util-character "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-factory-whitespace@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-factory-whitespace/-/micromark-factory-whitespace-2.0.0.tgz#9e92eb0f5468083381f923d9653632b3cfb5f763"
+  integrity sha512-28kbwaBjc5yAI1XadbdPYHX/eDnqaUFVikLwrO7FDnKG7lpgxnvk/XGRhX/PN0mOZ+dBSZ+LgunHS+6tYQAzhA==
+  dependencies:
+    micromark-factory-space "^2.0.0"
+    micromark-util-character "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-util-character@^2.0.0:
+  version "2.0.1"
+  resolved "https://registry.yarnpkg.com/micromark-util-character/-/micromark-util-character-2.0.1.tgz#52b824c2e2633b6fb33399d2ec78ee2a90d6b298"
+  integrity sha512-3wgnrmEAJ4T+mGXAUfMvMAbxU9RDG43XmGce4j6CwPtVxB3vfwXSZ6KhFwDzZ3mZHhmPimMAXg71veiBGzeAZw==
+  dependencies:
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-util-chunked@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-chunked/-/micromark-util-chunked-2.0.0.tgz#e51f4db85fb203a79dbfef23fd41b2f03dc2ef89"
+  integrity sha512-anK8SWmNphkXdaKgz5hJvGa7l00qmcaUQoMYsBwDlSKFKjc6gjGXPDw3FNL3Nbwq5L8gE+RCbGqTw49FK5Qyvg==
+  dependencies:
+    micromark-util-symbol "^2.0.0"
+
+micromark-util-classify-character@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-classify-character/-/micromark-util-classify-character-2.0.0.tgz#8c7537c20d0750b12df31f86e976d1d951165f34"
+  integrity sha512-S0ze2R9GH+fu41FA7pbSqNWObo/kzwf8rN/+IGlW/4tC6oACOs8B++bh+i9bVyNnwCcuksbFwsBme5OCKXCwIw==
+  dependencies:
+    micromark-util-character "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-util-combine-extensions@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-combine-extensions/-/micromark-util-combine-extensions-2.0.0.tgz#75d6ab65c58b7403616db8d6b31315013bfb7ee5"
+  integrity sha512-vZZio48k7ON0fVS3CUgFatWHoKbbLTK/rT7pzpJ4Bjp5JjkZeasRfrS9wsBdDJK2cJLHMckXZdzPSSr1B8a4oQ==
+  dependencies:
+    micromark-util-chunked "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-util-decode-numeric-character-reference@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-decode-numeric-character-reference/-/micromark-util-decode-numeric-character-reference-2.0.0.tgz#a798808d02cc74113e2c939fc95363096ade7f1d"
+  integrity sha512-pIgcsGxpHEtTG/rPJRz/HOLSqp5VTuIIjXlPI+6JSDlK2oljApusG6KzpS8AF0ENUMCHlC/IBb5B9xdFiVlm5Q==
+  dependencies:
+    micromark-util-symbol "^2.0.0"
+
+micromark-util-decode-string@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-decode-string/-/micromark-util-decode-string-2.0.0.tgz#7dfa3a63c45aecaa17824e656bcdb01f9737154a"
+  integrity sha512-r4Sc6leeUTn3P6gk20aFMj2ntPwn6qpDZqWvYmAG6NgvFTIlj4WtrAudLi65qYoaGdXYViXYw2pkmn7QnIFasA==
+  dependencies:
+    decode-named-character-reference "^1.0.0"
+    micromark-util-character "^2.0.0"
+    micromark-util-decode-numeric-character-reference "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+
+micromark-util-encode@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-encode/-/micromark-util-encode-2.0.0.tgz#0921ac7953dc3f1fd281e3d1932decfdb9382ab1"
+  integrity sha512-pS+ROfCXAGLWCOc8egcBvT0kf27GoWMqtdarNfDcjb6YLuV5cM3ioG45Ys2qOVqeqSbjaKg72vU+Wby3eddPsA==
+
+micromark-util-html-tag-name@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-html-tag-name/-/micromark-util-html-tag-name-2.0.0.tgz#ae34b01cbe063363847670284c6255bb12138ec4"
+  integrity sha512-xNn4Pqkj2puRhKdKTm8t1YHC/BAjx6CEwRFXntTaRf/x16aqka6ouVoutm+QdkISTlT7e2zU7U4ZdlDLJd2Mcw==
+
+micromark-util-normalize-identifier@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-normalize-identifier/-/micromark-util-normalize-identifier-2.0.0.tgz#91f9a4e65fe66cc80c53b35b0254ad67aa431d8b"
+  integrity sha512-2xhYT0sfo85FMrUPtHcPo2rrp1lwbDEEzpx7jiH2xXJLqBuy4H0GgXk5ToU8IEwoROtXuL8ND0ttVa4rNqYK3w==
+  dependencies:
+    micromark-util-symbol "^2.0.0"
+
+micromark-util-resolve-all@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-resolve-all/-/micromark-util-resolve-all-2.0.0.tgz#189656e7e1a53d0c86a38a652b284a252389f364"
+  integrity sha512-6KU6qO7DZ7GJkaCgwBNtplXCvGkJToU86ybBAUdavvgsCiG8lSSvYxr9MhwmQ+udpzywHsl4RpGJsYWG1pDOcA==
+  dependencies:
+    micromark-util-types "^2.0.0"
+
+micromark-util-sanitize-uri@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-sanitize-uri/-/micromark-util-sanitize-uri-2.0.0.tgz#ec8fbf0258e9e6d8f13d9e4770f9be64342673de"
+  integrity sha512-WhYv5UEcZrbAtlsnPuChHUAsu/iBPOVaEVsntLBIdpibO0ddy8OzavZz3iL2xVvBZOpolujSliP65Kq0/7KIYw==
+  dependencies:
+    micromark-util-character "^2.0.0"
+    micromark-util-encode "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+
+micromark-util-subtokenize@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-subtokenize/-/micromark-util-subtokenize-2.0.0.tgz#9f412442d77e0c5789ffdf42377fa8a2bcbdf581"
+  integrity sha512-vc93L1t+gpR3p8jxeVdaYlbV2jTYteDje19rNSS/H5dlhxUYll5Fy6vJ2cDwP8RnsXi818yGty1ayP55y3W6fg==
+  dependencies:
+    devlop "^1.0.0"
+    micromark-util-chunked "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
+micromark-util-symbol@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-symbol/-/micromark-util-symbol-2.0.0.tgz#12225c8f95edf8b17254e47080ce0862d5db8044"
+  integrity sha512-8JZt9ElZ5kyTnO94muPxIGS8oyElRJaiJO8EzV6ZSyGQ1Is8xwl4Q45qU5UOg+bGH4AikWziz0iN4sFLWs8PGw==
+
+micromark-util-types@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/micromark-util-types/-/micromark-util-types-2.0.0.tgz#63b4b7ffeb35d3ecf50d1ca20e68fc7caa36d95e"
+  integrity sha512-oNh6S2WMHWRZrmutsRmDDfkzKtxF+bc2VxLC9dvtrDIRFln627VsFP6fLMgTryGDljgLPjkrzQSDcPrjPyDJ5w==
+
+micromark@^4.0.0:
+  version "4.0.0"
+  resolved "https://registry.yarnpkg.com/micromark/-/micromark-4.0.0.tgz#84746a249ebd904d9658cfabc1e8e5f32cbc6249"
+  integrity sha512-o/sd0nMof8kYff+TqcDx3VSrgBTcZpSvYcAHIfHhv5VAuNmisCxjhx6YmxS8PFEpb9z5WKWKPdzf0jM23ro3RQ==
+  dependencies:
+    "@types/debug" "^4.0.0"
+    debug "^4.0.0"
+    decode-named-character-reference "^1.0.0"
+    devlop "^1.0.0"
+    micromark-core-commonmark "^2.0.0"
+    micromark-factory-space "^2.0.0"
+    micromark-util-character "^2.0.0"
+    micromark-util-chunked "^2.0.0"
+    micromark-util-combine-extensions "^2.0.0"
+    micromark-util-decode-numeric-character-reference "^2.0.0"
+    micromark-util-encode "^2.0.0"
+    micromark-util-normalize-identifier "^2.0.0"
+    micromark-util-resolve-all "^2.0.0"
+    micromark-util-sanitize-uri "^2.0.0"
+    micromark-util-subtokenize "^2.0.0"
+    micromark-util-symbol "^2.0.0"
+    micromark-util-types "^2.0.0"
+
 micromatch@^4.0.4, micromatch@^4.0.5:
  version "4.0.5"
  resolved "https://registry.npmjs.org/micromatch/-/micromatch-4.0.5.tgz"
@@ -1664,6 +2009,11 @@ prop-types@^15.8.1:
    object-assign "^4.1.1"
    react-is "^16.13.1"

+property-information@^6.0.0:
+  version "6.3.0"
+  resolved "https://registry.yarnpkg.com/property-information/-/property-information-6.3.0.tgz#ba4a06ec6b4e1e90577df9931286953cdf4282c3"
+  integrity sha512-gVNZ74nqhRMiIUYWGQdosYetaKc83x8oT41a0LlV3AAFCAZwCpg4vmGkq8t34+cUhp3cnM4XDiU/7xlgK7HGrg==
+
 proxy-from-env@^1.1.0:
  version "1.1.0"
  resolved "https://registry.yarnpkg.com/proxy-from-env/-/proxy-from-env-1.1.0.tgz#e102f16ca355424865755d2c9e8ea4f24d58c3e2"
@@ -1713,6 +2063,23 @@ react-is@^16.13.1, react-is@^16.7.0:
  resolved "https://registry.npmjs.org/react-is/-/react-is-16.13.1.tgz"
  integrity sha512-24e6ynE2H+OKt4kqsOvNd8kBpV65zoxbA4BVsEOB3ARVWQki/DHzaUoC5KuON/BiccDaCCTZBuOcfZs70kR8bQ==

+react-markdown@^9.0.0:
+  version "9.0.0"
+  resolved "https://registry.yarnpkg.com/react-markdown/-/react-markdown-9.0.0.tgz#7a41bde9e1b0b1d6911f6f9f8c3cdb4a3e9f9328"
+  integrity sha512-v6yNf3AB8GfJ8lCpUvzxAXKxgsHpdmWPlcVRQ6Nocsezp255E/IDrF31kLQsPJeB/cKto/geUwjU36wH784FCA==
+  dependencies:
+    "@types/hast" "^3.0.0"
+    devlop "^1.0.0"
+    hast-util-to-jsx-runtime "^2.0.0"
+    html-url-attributes "^3.0.0"
+    mdast-util-to-hast "^13.0.0"
+    micromark-util-sanitize-uri "^2.0.0"
+    remark-parse "^11.0.0"
+    remark-rehype "^11.0.0"
+    unified "^11.0.0"
+    unist-util-visit "^5.0.0"
+    vfile "^6.0.0"
+
 react-qr-code@^2.0.12:
  version "2.0.12"
  resolved "https://registry.yarnpkg.com/react-qr-code/-/react-qr-code-2.0.12.tgz#98f99e9ad5ede46d73ab819e2dd9925c5f5d7a2d"
@@ -1761,6 +2128,27 @@ regenerator-runtime@^0.14.0:
  resolved "https://registry.yarnpkg.com/regenerator-runtime/-/regenerator-runtime-0.14.0.tgz#5e19d68eb12d486f797e15a3c6a918f7cec5eb45"
  integrity sha512-srw17NI0TUWHuGa5CFGGmhfNIeja30WMBfbslPNhf6JrqQlLN5gcrvig1oqPxiVaXb0oW0XRKtH6Nngs5lKCIA==

+remark-parse@^11.0.0:
+  version "11.0.0"
+  resolved "https://registry.yarnpkg.com/remark-parse/-/remark-parse-11.0.0.tgz#aa60743fcb37ebf6b069204eb4da304e40db45a1"
+  integrity sha512-FCxlKLNGknS5ba/1lmpYijMUzX2esxW5xQqjWxw2eHFfS2MSdaHVINFmhjo+qN1WhZhNimq0dZATN9pH0IDrpA==
+  dependencies:
+    "@types/mdast" "^4.0.0"
+    mdast-util-from-markdown "^2.0.0"
+    micromark-util-types "^2.0.0"
+    unified "^11.0.0"
+
+remark-rehype@^11.0.0:
+  version "11.0.0"
+  resolved "https://registry.yarnpkg.com/remark-rehype/-/remark-rehype-11.0.0.tgz#7f21c08738bde024be5f16e4a8b13e5d7a04cf6b"
+  integrity sha512-vx8x2MDMcxuE4lBmQ46zYUDfcFMmvg80WYX+UNLeG6ixjdCCLcw1lrgAukwBTuOFsS78eoAedHGn9sNM0w7TPw==
+  dependencies:
+    "@types/hast" "^3.0.0"
+    "@types/mdast" "^4.0.0"
+    mdast-util-to-hast "^13.0.0"
+    unified "^11.0.0"
+    vfile "^6.0.0"
+
 require-directory@^2.1.1:
  version "2.1.1"
  resolved "https://registry.yarnpkg.com/require-directory/-/require-directory-2.1.1.tgz#8c64ad5fd30dab1c976e2344ffe7f792a6a6df42"
@@ -1893,6 +2281,11 @@ simple-peer@^9.11.1:
  resolved "https://registry.npmjs.org/source-map-js/-/source-map-js-1.0.2.tgz"
  integrity sha512-R0XvVJ9WusLiqTCEiGCmICCMplcCkIwwR11mOSD9CR5u+IXYdiseeEuXCVAjS54zqwkLcPNnmU4OeJ6tUrWhDw==

+space-separated-tokens@^2.0.0:
+  version "2.0.2"
+  resolved "https://registry.yarnpkg.com/space-separated-tokens/-/space-separated-tokens-2.0.2.tgz#1ecd9d2350a3844572c3f4a312bceb018348859f"
+  integrity sha512-PEGlAwrG8yXGXRjW32fGbg66JAlOAwbObuqVoJpv/mRgoWDQfgH1wDPvtzWyUSNAXBGSk8h755YDbbcEy3SH2Q==
+
 spawn-command@^0.0.2-1:
  version "0.0.2-1"
  resolved "https://registry.yarnpkg.com/spawn-command/-/spawn-command-0.0.2-1.tgz#62f5e9466981c1b796dc5929937e11c9c6921bd0"
@@ -1933,6 +2326,13 @@ strip-ansi@^6.0.0, strip-ansi@^6.0.1:
  dependencies:
    ansi-regex "^5.0.1"

+style-to-object@^0.4.0:
+  version "0.4.2"
+  resolved "https://registry.yarnpkg.com/style-to-object/-/style-to-object-0.4.2.tgz#a8247057111dea8bd3b8a1a66d2d0c9cf9218a54"
+  integrity sha512-1JGpfPB3lo42ZX8cuPrheZbfQ6kqPPnPHlKMyeRYtfKD+0jG+QsXgXN57O/dvJlzlB2elI6dGmrPnl5VPQFPaA==
+  dependencies:
+    inline-style-parser "0.1.1"
+
 styled-jsx@5.1.1:
  version "5.1.1"
  resolved "https://registry.npmjs.org/styled-jsx/-/styled-jsx-5.1.1.tgz"
@@ -2065,6 +2465,16 @@ tree-kill@^1.2.2:
  resolved "https://registry.yarnpkg.com/tree-kill/-/tree-kill-1.2.2.tgz#4ca09a9092c88b73a7cdc5e8a01b507b0790a0cc"
  integrity sha512-L0Orpi8qGpRG//Nd+H90vFB+3iHnue1zSSGmNOOCh1GLJ7rUKVwV2HvijphGQS2UmhUZewS9VgvxYIdgr+fG1A==

+trim-lines@^3.0.0:
+  version "3.0.1"
+  resolved "https://registry.yarnpkg.com/trim-lines/-/trim-lines-3.0.1.tgz#d802e332a07df861c48802c04321017b1bd87338"
+  integrity sha512-kRj8B+YHZCc9kQYdWfJB2/oUl9rA99qbowYYBtr4ui4mZyAQ2JpvVBd/6U2YloATfqBhBTSMhTpgBHtU0Mf3Rg==
+
+trough@^2.0.0:
+  version "2.1.0"
+  resolved "https://registry.yarnpkg.com/trough/-/trough-2.1.0.tgz#0f7b511a4fde65a46f18477ab38849b22c554876"
+  integrity sha512-AqTiAOLcj85xS7vQ8QkAV41hPDIJ71XJB4RCUrzo/1GM2CQwhkJGaf9Hgr7BOugMRpgGUrqRg/DrBDl4H40+8g==
+
 ts-interface-checker@^0.1.9:
  version "0.1.13"
  resolved "https://registry.npmjs.org/ts-interface-checker/-/ts-interface-checker-0.1.13.tgz"
@@ -2117,6 +2527,57 @@ uid@2.0.1:
  dependencies:
    "@lukeed/csprng" "^1.0.0"

+unified@^11.0.0:
+  version "11.0.3"
+  resolved "https://registry.yarnpkg.com/unified/-/unified-11.0.3.tgz#e141be0fe466a2d28b2160f62712bc9cbc08fdd4"
+  integrity sha512-jlCV402P+YDcFcB2VcN/n8JasOddqIiaxv118wNBoZXEhOn+lYG7BR4Bfg2BwxvlK58dwbuH2w7GX2esAjL6Mg==
+  dependencies:
+    "@types/unist" "^3.0.0"
+    bail "^2.0.0"
+    devlop "^1.0.0"
+    extend "^3.0.0"
+    is-plain-obj "^4.0.0"
+    trough "^2.0.0"
+    vfile "^6.0.0"
+
+unist-util-is@^6.0.0:
+  version "6.0.0"
+  resolved "https://registry.yarnpkg.com/unist-util-is/-/unist-util-is-6.0.0.tgz#b775956486aff107a9ded971d996c173374be424"
+  integrity sha512-2qCTHimwdxLfz+YzdGfkqNlH0tLi9xjTnHddPmJwtIG9MGsdbutfTc4P+haPD7l7Cjxf/WZj+we5qfVPvvxfYw==
+  dependencies:
+    "@types/unist" "^3.0.0"
+
+unist-util-position@^5.0.0:
+  version "5.0.0"
+  resolved "https://registry.yarnpkg.com/unist-util-position/-/unist-util-position-5.0.0.tgz#678f20ab5ca1207a97d7ea8a388373c9cf896be4"
+  integrity sha512-fucsC7HjXvkB5R3kTCO7kUjRdrS0BJt3M/FPxmHMBOm8JQi2BsHAHFsy27E0EolP8rp0NzXsJ+jNPyDWvOJZPA==
+  dependencies:
+    "@types/unist" "^3.0.0"
+
+unist-util-stringify-position@^4.0.0:
+  version "4.0.0"
+  resolved "https://registry.yarnpkg.com/unist-util-stringify-position/-/unist-util-stringify-position-4.0.0.tgz#449c6e21a880e0855bf5aabadeb3a740314abac2"
+  integrity sha512-0ASV06AAoKCDkS2+xw5RXJywruurpbC4JZSm7nr7MOt1ojAzvyyaO+UxZf18j8FCF6kmzCZKcAgN/yu2gm2XgQ==
+  dependencies:
+    "@types/unist" "^3.0.0"
+
+unist-util-visit-parents@^6.0.0:
+  version "6.0.1"
+  resolved "https://registry.yarnpkg.com/unist-util-visit-parents/-/unist-util-visit-parents-6.0.1.tgz#4d5f85755c3b8f0dc69e21eca5d6d82d22162815"
+  integrity sha512-L/PqWzfTP9lzzEa6CKs0k2nARxTdZduw3zyh8d2NVBnsyvHjSX4TWse388YrrQKbvI8w20fGjGlhgT96WwKykw==
+  dependencies:
+    "@types/unist" "^3.0.0"
+    unist-util-is "^6.0.0"
+
+unist-util-visit@^5.0.0:
+  version "5.0.0"
+  resolved "https://registry.yarnpkg.com/unist-util-visit/-/unist-util-visit-5.0.0.tgz#a7de1f31f72ffd3519ea71814cccf5fd6a9217d6"
+  integrity sha512-MR04uvD+07cwl/yhVuVWAtw+3GOR/knlL55Nd/wAdblk27GCVt3lqpTivy/tkJcZoNPzTwS1Y+KMojlLDhoTzg==
+  dependencies:
+    "@types/unist" "^3.0.0"
+    unist-util-is "^6.0.0"
+    unist-util-visit-parents "^6.0.0"
+
 universalify@^2.0.0:
  version "2.0.0"
  resolved "https://registry.yarnpkg.com/universalify/-/universalify-2.0.0.tgz#75a4984efedc4b08975c5aeb73f530d02df25717"
@@ -2135,6 +2596,23 @@ util-deprecate@^1.0.1, util-deprecate@^1.0.2:
  resolved "https://registry.npmjs.org/util-deprecate/-/util-deprecate-1.0.2.tgz"
  integrity sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw==

+vfile-message@^4.0.0:
+  version "4.0.2"
+  resolved "https://registry.yarnpkg.com/vfile-message/-/vfile-message-4.0.2.tgz#c883c9f677c72c166362fd635f21fc165a7d1181"
+  integrity sha512-jRDZ1IMLttGj41KcZvlrYAaI3CfqpLpfpf+Mfig13viT6NKvRzWZ+lXz0Y5D60w6uJIBAOGq9mSHf0gktF0duw==
+  dependencies:
+    "@types/unist" "^3.0.0"
+    unist-util-stringify-position "^4.0.0"
+
+vfile@^6.0.0:
+  version "6.0.1"
+  resolved "https://registry.yarnpkg.com/vfile/-/vfile-6.0.1.tgz#1e8327f41eac91947d4fe9d237a2dd9209762536"
+  integrity sha512-1bYqc7pt6NIADBJ98UiG0Bn/CHIVOoZ/IyEkqIruLg0mE1BKzkOXY2D6CSqQIcKqgadppE5lrxgWXJmXd7zZJw==
+  dependencies:
+    "@types/unist" "^3.0.0"
+    unist-util-stringify-position "^4.0.0"
+    vfile-message "^4.0.0"
+
 watchpack@2.4.0:
  version "2.4.0"
  resolved "https://registry.npmjs.org/watchpack/-/watchpack-2.4.0.tgz"