Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+audio.mp3 filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,3 @@
+.env
+__pycache__/
+.venv/

.gradio/flagged/dataset1.csv

@@ -0,0 +1,6 @@
+YouTube URL,Candidate Summary,Detected Accent,Confidence Score,timestamp
+https://huggingface.co/Jzuluaga/accent-id-commonaccent_xlsr-en-english/resolve/main/data/malaysia_1.wav,"Summary: The candidate conveyed that performing a random act of kindness does not require one to be wealthy, physically fit, popular, or possess any special attributes.
+
+Motivation and Key Skills: The candidate demonstrates empathy, inclusiveness, and a positive attitude toward kindness. This reflects emotional intelligence and a value-driven mindset.
+
+Additional Insights: The candidate’s statement suggests they prioritize kindness and accessibility in actions, indicating potential strengths in teamwork, interpersonal relations, and company culture fit focused on compassion and humility.",['malaysia'],tensor([1.0000]),2025-06-07 20:12:45.387168

README.md

@@ -1,12 +1,6 @@
 ---
 title: AccentDetector
-emoji: 📊
-colorFrom: purple
-colorTo: indigo
-sdk: gradio
-sdk_version: 5.33.0
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 5.25.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Summarizer_Agent.py

@@ -0,0 +1,64 @@
+from openai import OpenAI
+# from dotenv import load_dotenv
+import yt_dlp 
+import modal
+import torch
+
+class Summarizer:
+    def __init__(self):
+        self.system='''You are an intelligent assistant working for a company that builds advanced tools to automate real hiring decisions. Your task is to analyze speech-to-text transcripts from candidate interviews. For each candidate’s response, you will:
+
+                        Provide a clear and concise summary of what the candidate said.
+
+                        Identify the candidate’s motivation and key skills expressed in their speech.
+
+                        Highlight any additional insights or relevant observations that could assist recruiters in making informed hiring decisions.
+
+                        Focus on delivering objective, actionable, and relevant information that captures the candidate’s potential skills'''
+        
+        self.transcriber="gpt-4o-transcribe"
+        self.summarizer="gpt-4.1-mini"
+        self.Accentizer= modal.Cls.lookup("ClassifierAudio", "Accentizer")
+        self.client=OpenAI()
+    def download_audio(self,url, output_path='audio'):
+        import yt_dlp 
+        ydl_opts = {
+            'format': 'bestaudio/best',
+            'outtmpl': output_path,
+            'postprocessors': [{
+                'key': 'FFmpegExtractAudio',
+                'preferredcodec': 'mp3',  # or 'wav'
+                'preferredquality': '192',
+            }],
+        }
+
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            ydl.download([url])   
+    def classify(self,url):
+        raw= self.Accentizer.classify.remote(url)
+        accent = raw["label"][0] if isinstance(raw["label"], list) else str(raw["label"])
+        score = raw["score"].item() if isinstance(raw["score"], torch.Tensor) else float(raw["score"])
+        return {
+        "label": accent,
+        "score": round(score, 4)
+    }
+        return result
+    def summarize(self,url):
+        self.download_audio(url=url)
+        audio_file=open("./audio.mp3", "rb")
+        transcription = self.client.audio.transcriptions.create(
+                model=self.transcriber, 
+                file=audio_file
+            )   
+        user_prompt="Here is transcription of the audio \n "
+        user_prompt+=transcription.text
+        prompts = [
+        {"role": "system", "content": self.system},
+        {"role": "user", "content": user_prompt}
+        ]
+        chat=self.client.chat.completions.create(
+        model=self.summarizer,
+        messages=prompts
+        )
+        return chat.choices[0].message.content
+    

app.py

@@ -0,0 +1,50 @@
+from Summarizer_Agent import Summarizer
+import gradio as gr
+
+summarizer=Summarizer()
+flags = {
+    "us": "🇺🇸",
+    "england": "🏴",         
+    "australia": "🇦🇺",
+    "indian": "🇮🇳",          
+    "canada": "🇨🇦",
+    "bermuda": "🇧🇲",
+    "scotland": "🏴",        
+    "african": "🌍",         
+    "ireland": "🇮🇪",
+    "newzealand": "🇳🇿",
+    "wales": "🏴",           
+    "malaysia": "🇲🇾",
+    "philippines": "🇵🇭",
+    "singapore": "🇸🇬",
+    "hongkong": "🇭🇰",
+    "southatlandtic": "🌊"   
+}
+def process_youtube(url):
+    try:
+        summary = summarizer.summarize(url)
+        accent_info = summarizer.classify(url)
+        
+        accent = accent_info["label"]
+        flag = flags.get(accent.lower(), "🏳️")  # fallback to white flag if not found
+        accent_display = f"{flag} {accent.capitalize()}"
+        
+        return summary, accent_display, accent_info["score"]
+    except Exception as e:
+        return f"Error: {e}"
+
+demo = gr.Interface(
+    fn=process_youtube,
+    inputs=gr.Textbox(label="public video  URL", placeholder="Enter public video link here..."),
+    outputs=[
+        gr.Textbox(label="Candidate Summary", lines=10),
+        gr.Textbox(label="Detected Accent"),
+        gr.Slider(label="Confidence Score (%)", minimum=0, maximum=1, step=0.001, interactive=False)
+
+    ],
+    title="Interview Audio Summarizer",
+    description="Paste an interview video link. The app will summarize the candidate's response and detect the speaker's accent."
+)
+
+if __name__=="__main__":
+    demo.launch()

audio.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:09f5ca56abe7aad574432153bac21f6d2ecfba09f5a5f0c1cbe104a02e5ac778
+size 149084

classifier_modal.py

@@ -0,0 +1,55 @@
+import modal
+from modal import App,Image
+
+app=modal.App(name="ClassifierAudio")
+image = Image.debian_slim().pip_install("torch","huggingface","transformers","speechbrain","numpy","torchaudio","yt_dlp").apt_install("ffmpeg")
+model_name = "warisqr7/accent-id-commonaccent_xlsr-en-english"
+secrets = [modal.Secret.from_name("hf-secret")]
+LOCAL_DIR="model"
+@app.cls(image=image, secrets=secrets, timeout=1800)
+
+class Accentizer:
+    @modal.build()
+    def download_model(self):
+        from huggingface_hub import snapshot_download
+        import os
+        import torch
+        BASE_DIR="model"
+        os.makedirs(BASE_DIR, exist_ok=True)
+        snapshot_download(model_name, local_dir=LOCAL_DIR)
+    @modal.enter()
+    def setup(self):
+        import yt_dlp
+        from speechbrain.pretrained.interfaces import foreign_class
+        self.download=self.download_audio
+        self.classifier = foreign_class(source=LOCAL_DIR, pymodule_file="custom_interface.py", classname="CustomEncoderWav2vec2Classifier")
+
+    def download_audio(self,url, output_path='audio'):
+        import yt_dlp 
+        ydl_opts = {
+            'format': 'bestaudio/best',
+            'outtmpl': output_path,
+            'postprocessors': [{
+                'key': 'FFmpegExtractAudio',
+                'preferredcodec': 'mp3',  # or 'wav'
+                'preferredquality': '192',
+            }],
+        }
+
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            ydl.download([url])
+    @modal.method()
+    def classify(self, url):
+        import torch
+        import torchaudio
+        import yt_dlp
+
+        self.download(url)
+        
+        audio_path = "audio.mp3"
+
+        out_prob, score, index, text_lab = self.classifier.classify_file(audio_path)
+        return {"label": text_lab, "score": score, "index": index, "out_prob": out_prob}
+    @modal.method()
+    def wake_up(self) -> str:
+            return "ok"

modal.deploy.ipynb

@@ -0,0 +1,149 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "┌─ Modal Deprecation Warning (2025-02-06) ────────────────────────────────────┐\n",
+      "│ Using Python module paths will require using the -m flag in a future        │\n",
+      "│ version of Modal.                                                           │\n",
+      "│ Use `modal deploy -m classifier_modal` instead.                             │\n",
+      "└─────────────────────────────────────────────────────────────────────────────┘\n",
+      "┌─ Modal Deprecation Warning (2025-01-15) ────────────────────────────────────┐\n",
+      "│ The `@modal.build` decorator is deprecated and will be removed in a future  │\n",
+      "│ release.                                                                    │\n",
+      "│                                                                             │\n",
+      "│ We now recommend storing large assets (such as model weights) using a       │\n",
+      "│ `modal.Volume` instead of writing them directly into the `modal.Image`      │\n",
+      "│ filesystem. For other use cases we recommend using `Image.run_function`     │\n",
+      "│ instead.                                                                    │\n",
+      "│                                                                             │\n",
+      "│ See https://modal.com/docs/guide/modal-1-0-migration for more information.  │\n",
+      "│                                                                             │\n",
+      "│ Source: c:\\LLM\\AccentDetector\\classifier_modal.py:12                        │\n",
+      "│   @modal.build()                                                            │\n",
+      "└─────────────────────────────────────────────────────────────────────────────┘\n",
+      "- Creating objects...\n",
+      "\\ Creating objects...\n",
+      "└── - Creating mount c:\\LLM\\AccentDetector\\classifier_modal.py: Uploaded 0/1 \n",
+      "    files\n",
+      "/ Creating objects...\n",
+      "└── | Creating mount c:\\LLM\\AccentDetector\\classifier_modal.py: Uploaded 0/1 \n",
+      "    files\n",
+      "\\ Creating objects...\n",
+      "└── / Creating mount c:\\LLM\\AccentDetector\\classifier_modal.py: Uploaded 0/1 \n",
+      "    files\n",
+      "/ Creating objects...\n",
+      "└── \\ Creating mount c:\\LLM\\AccentDetector\\classifier_modal.py: Finalizing \n",
+      "    index of 1 files\n",
+      "\\ Creating objects...\n",
+      "├── 🔨 Created mount c:\\LLM\\AccentDetector\\classifier_modal.py\n",
+      "└── 🔨 Created function Accentizer.download_model.\n",
+      "/ Creating objects...\n",
+      "├── 🔨 Created mount c:\\LLM\\AccentDetector\\classifier_modal.py\n",
+      "├── 🔨 Created function Accentizer.download_model.\n",
+      "└── - Creating function Accentizer.*...\n",
+      "\\ Creating objects...\n",
+      "├── 🔨 Created mount c:\\LLM\\AccentDetector\\classifier_modal.py\n",
+      "├── 🔨 Created function Accentizer.download_model.\n",
+      "└── 🔨 Created function Accentizer.*.\n",
+      "\\ Creating objects...\n",
+      "├── 🔨 Created mount c:\\LLM\\AccentDetector\\classifier_modal.py\n",
+      "├── 🔨 Created function Accentizer.download_model.\n",
+      "└── 🔨 Created function Accentizer.*.\n",
+      "\n",
+      "✓ Created objects.\n",
+      "├── 🔨 Created mount c:\\LLM\\AccentDetector\\classifier_modal.py\n",
+      "├── 🔨 Created function Accentizer.download_model.\n",
+      "└── 🔨 Created function Accentizer.*.\n",
+      "✓ App deployed in 2.520s! 🎉\n",
+      "\n",
+      "View Deployment: \n",
+      "https://modal.com/apps/djallelbrahmia/main/deployed/ClassifierAudio\n"
+     ]
+    }
+   ],
+   "source": [
+    "!modal deploy classifier_modal"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Python312\\Lib\\asyncio\\events.py:88: DeprecationError: 2025-01-27: `modal.Cls.lookup` is deprecated and will be removed in a future release. It can be replaced with `modal.Cls.from_name`.\n",
+      "\n",
+      "See https://modal.com/docs/guide/modal-1-0-migration for more information.\n",
+      "  self._context.run(self._callback, *self._args)\n",
+      "C:\\Users\\dbrah\\AppData\\Local\\Temp\\ipykernel_62300\\1972719297.py:5: DeprecationError: 2025-01-13: Calling a method on an uninstantiated class will soon be deprecated; update your code to instantiate the class first, i.e.:\n",
+      "Accentizer().classify instead of Accentizer.classify\n",
+      "  result=Accentizer.classify.remote(link)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import modal\n",
+    "import torch\n",
+    "link=\"https://huggingface.co/Jzuluaga/accent-id-commonaccent_xlsr-en-english/resolve/main/data/malaysia_1.wav\"\n",
+    "Accentizer = modal.Cls.lookup(\"ClassifierAudio\", \"Accentizer\")\n",
+    "result=Accentizer.classify.remote(link)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'label': ['malaysia'],\n",
+       " 'score': tensor([1.0000]),\n",
+       " 'index': tensor([11]),\n",
+       " 'out_prob': tensor([[1.1861e-06, 1.2054e-10, 5.3472e-11, 5.4380e-13, 2.0032e-15, 4.4907e-07,\n",
+       "          6.3840e-15, 4.1447e-15, 6.7380e-18, 1.5645e-16, 2.8600e-14, 1.0000e+00,\n",
+       "          9.1363e-11, 1.0672e-14, 2.5263e-11, 2.2510e-09]])}"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

pyproject.toml

@@ -0,0 +1,48 @@
+[project]
+name = "agents"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "anthropic>=0.49.0",
+    "autogen-agentchat>=0.4.9.2",
+    "autogen-ext[grpc,mcp,ollama,openai]>=0.4.9.2",
+    "bs4>=0.0.2",
+    "google-genai>=1.14.0",
+    "gradio>=5.22.0",
+    "httpx>=0.28.1",
+    "ipywidgets>=8.1.5",
+    "langchain-anthropic>=0.3.10",
+    "langchain-community>=0.3.20",
+    "langchain-experimental>=0.3.4",
+    "langchain-openai>=0.3.9",
+    "langgraph>=0.3.18",
+    "langgraph-checkpoint-sqlite>=2.0.6",
+    "langsmith>=0.3.18",
+    "lxml>=5.3.1",
+    "mcp-server-fetch>=2025.1.17",
+    "mcp[cli]>=1.5.0",
+    "openai>=1.68.2",
+    "openai-agents>=0.0.6",
+    "playwright>=1.51.0",
+    "plotly>=6.0.1",
+    "polygon-api-client>=1.14.5",
+    "psutil>=7.0.0",
+    "pypdf>=5.4.0",
+    "pypdf2>=3.0.1",
+    "python-dotenv>=1.0.1",
+    "python-hue-v2>=2.2.1",
+    "requests>=2.32.3",
+    "semantic-kernel>=1.25.0",
+    "sendgrid>=6.11.0",
+    "setuptools>=78.1.0",
+    "smithery>=0.1.0",
+    "speedtest-cli>=2.1.3",
+    "wikipedia>=1.4.0",
+]
+
+[dependency-groups]
+dev = [
+    "ipykernel>=6.29.5",
+]

requirements.txt

@@ -0,0 +1,4 @@
+openai
+yt_dlp
+modal
+torch

summarize_agent.ipynb

@@ -0,0 +1,352 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mKeyboardInterrupt\u001b[39m                         Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 7\u001b[39m\n\u001b[32m      4\u001b[39m client = OpenAI()\n\u001b[32m      5\u001b[39m audio_file= \u001b[38;5;28mopen\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33m./audio.wav\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mrb\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m----> \u001b[39m\u001b[32m7\u001b[39m transcription = \u001b[43mclient\u001b[49m\u001b[43m.\u001b[49m\u001b[43maudio\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtranscriptions\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m      8\u001b[39m \u001b[43m    \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mgpt-4o-transcribe\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[32m      9\u001b[39m \u001b[43m    \u001b[49m\u001b[43mfile\u001b[49m\u001b[43m=\u001b[49m\u001b[43maudio_file\u001b[49m\n\u001b[32m     10\u001b[39m \u001b[43m)\u001b[49m\n\u001b[32m     12\u001b[39m \u001b[38;5;28mprint\u001b[39m(transcription.text)\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\openai\\_utils\\_utils.py:287\u001b[39m, in \u001b[36mrequired_args.<locals>.inner.<locals>.wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m    285\u001b[39m             msg = \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mMissing required argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquote(missing[\u001b[32m0\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m    286\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[32m--> \u001b[39m\u001b[32m287\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\openai\\resources\\audio\\transcriptions.py:333\u001b[39m, in \u001b[36mTranscriptions.create\u001b[39m\u001b[34m(self, file, model, chunking_strategy, include, language, prompt, response_format, stream, temperature, timestamp_granularities, extra_headers, extra_query, extra_body, timeout)\u001b[39m\n\u001b[32m    329\u001b[39m \u001b[38;5;66;03m# It should be noted that the actual Content-Type header that will be\u001b[39;00m\n\u001b[32m    330\u001b[39m \u001b[38;5;66;03m# sent to the server will contain a `boundary` parameter, e.g.\u001b[39;00m\n\u001b[32m    331\u001b[39m \u001b[38;5;66;03m# multipart/form-data; boundary=---abc--\u001b[39;00m\n\u001b[32m    332\u001b[39m extra_headers = {\u001b[33m\"\u001b[39m\u001b[33mContent-Type\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mmultipart/form-data\u001b[39m\u001b[33m\"\u001b[39m, **(extra_headers \u001b[38;5;129;01mor\u001b[39;00m {})}\n\u001b[32m--> \u001b[39m\u001b[32m333\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_post\u001b[49m\u001b[43m(\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# type: ignore[return-value]\u001b[39;49;00m\n\u001b[32m    334\u001b[39m \u001b[43m    \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m/audio/transcriptions\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m    335\u001b[39m \u001b[43m    \u001b[49m\u001b[43mbody\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    336\u001b[39m \u001b[43m        \u001b[49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    337\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtranscription_create_params\u001b[49m\u001b[43m.\u001b[49m\u001b[43mTranscriptionCreateParamsStreaming\u001b[49m\n\u001b[32m    338\u001b[39m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\n\u001b[32m    339\u001b[39m \u001b[43m        \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mtranscription_create_params\u001b[49m\u001b[43m.\u001b[49m\u001b[43mTranscriptionCreateParamsNonStreaming\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    340\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    341\u001b[39m \u001b[43m    \u001b[49m\u001b[43mfiles\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfiles\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    342\u001b[39m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmake_request_options\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    343\u001b[39m \u001b[43m        \u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_query\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_query\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_body\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\n\u001b[32m    344\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    345\u001b[39m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m=\u001b[49m\u001b[43m_get_response_format_type\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresponse_format\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    346\u001b[39m \u001b[43m    \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m    347\u001b[39m \u001b[43m    \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m=\u001b[49m\u001b[43mStream\u001b[49m\u001b[43m[\u001b[49m\u001b[43mTranscriptionStreamEvent\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    348\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\openai\\_base_client.py:1242\u001b[39m, in \u001b[36mSyncAPIClient.post\u001b[39m\u001b[34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[39m\n\u001b[32m   1228\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mpost\u001b[39m(\n\u001b[32m   1229\u001b[39m     \u001b[38;5;28mself\u001b[39m,\n\u001b[32m   1230\u001b[39m     path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[32m   (...)\u001b[39m\u001b[32m   1237\u001b[39m     stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] | \u001b[38;5;28;01mNone\u001b[39;00m = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m   1238\u001b[39m ) -> ResponseT | _StreamT:\n\u001b[32m   1239\u001b[39m     opts = FinalRequestOptions.construct(\n\u001b[32m   1240\u001b[39m         method=\u001b[33m\"\u001b[39m\u001b[33mpost\u001b[39m\u001b[33m\"\u001b[39m, url=path, json_data=body, files=to_httpx_files(files), **options\n\u001b[32m   1241\u001b[39m     )\n\u001b[32m-> \u001b[39m\u001b[32m1242\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\openai\\_base_client.py:972\u001b[39m, in \u001b[36mSyncAPIClient.request\u001b[39m\u001b[34m(self, cast_to, options, stream, stream_cls)\u001b[39m\n\u001b[32m    970\u001b[39m response = \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m    971\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m972\u001b[39m     response = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_client\u001b[49m\u001b[43m.\u001b[49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    973\u001b[39m \u001b[43m        \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    974\u001b[39m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_should_stream_response_body\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    975\u001b[39m \u001b[43m        \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    976\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    977\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m httpx.TimeoutException \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[32m    978\u001b[39m     log.debug(\u001b[33m\"\u001b[39m\u001b[33mEncountered httpx.TimeoutException\u001b[39m\u001b[33m\"\u001b[39m, exc_info=\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpx\\_client.py:914\u001b[39m, in \u001b[36mClient.send\u001b[39m\u001b[34m(self, request, stream, auth, follow_redirects)\u001b[39m\n\u001b[32m    910\u001b[39m \u001b[38;5;28mself\u001b[39m._set_timeout(request)\n\u001b[32m    912\u001b[39m auth = \u001b[38;5;28mself\u001b[39m._build_request_auth(request, auth)\n\u001b[32m--> \u001b[39m\u001b[32m914\u001b[39m response = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_send_handling_auth\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    915\u001b[39m \u001b[43m    \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    916\u001b[39m \u001b[43m    \u001b[49m\u001b[43mauth\u001b[49m\u001b[43m=\u001b[49m\u001b[43mauth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    917\u001b[39m \u001b[43m    \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    918\u001b[39m \u001b[43m    \u001b[49m\u001b[43mhistory\u001b[49m\u001b[43m=\u001b[49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    919\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    920\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    921\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m stream:\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpx\\_client.py:942\u001b[39m, in \u001b[36mClient._send_handling_auth\u001b[39m\u001b[34m(self, request, auth, follow_redirects, history)\u001b[39m\n\u001b[32m    939\u001b[39m request = \u001b[38;5;28mnext\u001b[39m(auth_flow)\n\u001b[32m    941\u001b[39m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m942\u001b[39m     response = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_send_handling_redirects\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    943\u001b[39m \u001b[43m        \u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    944\u001b[39m \u001b[43m        \u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfollow_redirects\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    945\u001b[39m \u001b[43m        \u001b[49m\u001b[43mhistory\u001b[49m\u001b[43m=\u001b[49m\u001b[43mhistory\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    946\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    947\u001b[39m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    948\u001b[39m         \u001b[38;5;28;01mtry\u001b[39;00m:\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpx\\_client.py:979\u001b[39m, in \u001b[36mClient._send_handling_redirects\u001b[39m\u001b[34m(self, request, follow_redirects, history)\u001b[39m\n\u001b[32m    976\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m hook \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._event_hooks[\u001b[33m\"\u001b[39m\u001b[33mrequest\u001b[39m\u001b[33m\"\u001b[39m]:\n\u001b[32m    977\u001b[39m     hook(request)\n\u001b[32m--> \u001b[39m\u001b[32m979\u001b[39m response = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_send_single_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    980\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    981\u001b[39m     \u001b[38;5;28;01mfor\u001b[39;00m hook \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._event_hooks[\u001b[33m\"\u001b[39m\u001b[33mresponse\u001b[39m\u001b[33m\"\u001b[39m]:\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpx\\_client.py:1014\u001b[39m, in \u001b[36mClient._send_single_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m   1009\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[32m   1010\u001b[39m         \u001b[33m\"\u001b[39m\u001b[33mAttempted to send an async request with a sync Client instance.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m   1011\u001b[39m     )\n\u001b[32m   1013\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m request_context(request=request):\n\u001b[32m-> \u001b[39m\u001b[32m1014\u001b[39m     response = \u001b[43mtransport\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   1016\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(response.stream, SyncByteStream)\n\u001b[32m   1018\u001b[39m response.request = request\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpx\\_transports\\default.py:250\u001b[39m, in \u001b[36mHTTPTransport.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    237\u001b[39m req = httpcore.Request(\n\u001b[32m    238\u001b[39m     method=request.method,\n\u001b[32m    239\u001b[39m     url=httpcore.URL(\n\u001b[32m   (...)\u001b[39m\u001b[32m    247\u001b[39m     extensions=request.extensions,\n\u001b[32m    248\u001b[39m )\n\u001b[32m    249\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m map_httpcore_exceptions():\n\u001b[32m--> \u001b[39m\u001b[32m250\u001b[39m     resp = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_pool\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mreq\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    252\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(resp.stream, typing.Iterable)\n\u001b[32m    254\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m Response(\n\u001b[32m    255\u001b[39m     status_code=resp.status,\n\u001b[32m    256\u001b[39m     headers=resp.headers,\n\u001b[32m    257\u001b[39m     stream=ResponseStream(resp.stream),\n\u001b[32m    258\u001b[39m     extensions=resp.extensions,\n\u001b[32m    259\u001b[39m )\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_sync\\connection_pool.py:256\u001b[39m, in \u001b[36mConnectionPool.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    253\u001b[39m         closing = \u001b[38;5;28mself\u001b[39m._assign_requests_to_connections()\n\u001b[32m    255\u001b[39m     \u001b[38;5;28mself\u001b[39m._close_connections(closing)\n\u001b[32m--> \u001b[39m\u001b[32m256\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m exc \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m    258\u001b[39m \u001b[38;5;66;03m# Return the response. Note that in this case we still have to manage\u001b[39;00m\n\u001b[32m    259\u001b[39m \u001b[38;5;66;03m# the point at which the response is closed.\u001b[39;00m\n\u001b[32m    260\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(response.stream, typing.Iterable)\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_sync\\connection_pool.py:236\u001b[39m, in \u001b[36mConnectionPool.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    232\u001b[39m connection = pool_request.wait_for_connection(timeout=timeout)\n\u001b[32m    234\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    235\u001b[39m     \u001b[38;5;66;03m# Send the request on the assigned connection.\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m236\u001b[39m     response = \u001b[43mconnection\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    237\u001b[39m \u001b[43m        \u001b[49m\u001b[43mpool_request\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\n\u001b[32m    238\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    239\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m ConnectionNotAvailable:\n\u001b[32m    240\u001b[39m     \u001b[38;5;66;03m# In some cases a connection may initially be available to\u001b[39;00m\n\u001b[32m    241\u001b[39m     \u001b[38;5;66;03m# handle a request, but then become unavailable.\u001b[39;00m\n\u001b[32m    242\u001b[39m     \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[32m    243\u001b[39m     \u001b[38;5;66;03m# In this case we clear the connection and try again.\u001b[39;00m\n\u001b[32m    244\u001b[39m     pool_request.clear_connection()\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_sync\\connection.py:103\u001b[39m, in \u001b[36mHTTPConnection.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    100\u001b[39m     \u001b[38;5;28mself\u001b[39m._connect_failed = \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[32m    101\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m exc\n\u001b[32m--> \u001b[39m\u001b[32m103\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_connection\u001b[49m\u001b[43m.\u001b[49m\u001b[43mhandle_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_sync\\http11.py:136\u001b[39m, in \u001b[36mHTTP11Connection.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    134\u001b[39m     \u001b[38;5;28;01mwith\u001b[39;00m Trace(\u001b[33m\"\u001b[39m\u001b[33mresponse_closed\u001b[39m\u001b[33m\"\u001b[39m, logger, request) \u001b[38;5;28;01mas\u001b[39;00m trace:\n\u001b[32m    135\u001b[39m         \u001b[38;5;28mself\u001b[39m._response_closed()\n\u001b[32m--> \u001b[39m\u001b[32m136\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m exc\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_sync\\http11.py:106\u001b[39m, in \u001b[36mHTTP11Connection.handle_request\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m     95\u001b[39m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[32m     97\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m Trace(\n\u001b[32m     98\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mreceive_response_headers\u001b[39m\u001b[33m\"\u001b[39m, logger, request, kwargs\n\u001b[32m     99\u001b[39m ) \u001b[38;5;28;01mas\u001b[39;00m trace:\n\u001b[32m    100\u001b[39m     (\n\u001b[32m    101\u001b[39m         http_version,\n\u001b[32m    102\u001b[39m         status,\n\u001b[32m    103\u001b[39m         reason_phrase,\n\u001b[32m    104\u001b[39m         headers,\n\u001b[32m    105\u001b[39m         trailing_data,\n\u001b[32m--> \u001b[39m\u001b[32m106\u001b[39m     ) = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_receive_response_headers\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    107\u001b[39m     trace.return_value = (\n\u001b[32m    108\u001b[39m         http_version,\n\u001b[32m    109\u001b[39m         status,\n\u001b[32m    110\u001b[39m         reason_phrase,\n\u001b[32m    111\u001b[39m         headers,\n\u001b[32m    112\u001b[39m     )\n\u001b[32m    114\u001b[39m network_stream = \u001b[38;5;28mself\u001b[39m._network_stream\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_sync\\http11.py:177\u001b[39m, in \u001b[36mHTTP11Connection._receive_response_headers\u001b[39m\u001b[34m(self, request)\u001b[39m\n\u001b[32m    174\u001b[39m timeout = timeouts.get(\u001b[33m\"\u001b[39m\u001b[33mread\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m    176\u001b[39m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m177\u001b[39m     event = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_receive_event\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    178\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(event, h11.Response):\n\u001b[32m    179\u001b[39m         \u001b[38;5;28;01mbreak\u001b[39;00m\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_sync\\http11.py:217\u001b[39m, in \u001b[36mHTTP11Connection._receive_event\u001b[39m\u001b[34m(self, timeout)\u001b[39m\n\u001b[32m    214\u001b[39m     event = \u001b[38;5;28mself\u001b[39m._h11_state.next_event()\n\u001b[32m    216\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m event \u001b[38;5;129;01mis\u001b[39;00m h11.NEED_DATA:\n\u001b[32m--> \u001b[39m\u001b[32m217\u001b[39m     data = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_network_stream\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    218\u001b[39m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mREAD_NUM_BYTES\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\n\u001b[32m    219\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    221\u001b[39m     \u001b[38;5;66;03m# If we feed this case through h11 we'll raise an exception like:\u001b[39;00m\n\u001b[32m    222\u001b[39m     \u001b[38;5;66;03m#\u001b[39;00m\n\u001b[32m    223\u001b[39m     \u001b[38;5;66;03m#     httpcore.RemoteProtocolError: can't handle event type\u001b[39;00m\n\u001b[32m   (...)\u001b[39m\u001b[32m    227\u001b[39m     \u001b[38;5;66;03m# perspective. Instead we handle this case distinctly and treat\u001b[39;00m\n\u001b[32m    228\u001b[39m     \u001b[38;5;66;03m# it as a ConnectError.\u001b[39;00m\n\u001b[32m    229\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m data == \u001b[33mb\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m._h11_state.their_state == h11.SEND_RESPONSE:\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mc:\\LLM\\AccentDetector\\.venv\\Lib\\site-packages\\httpcore\\_backends\\sync.py:128\u001b[39m, in \u001b[36mSyncStream.read\u001b[39m\u001b[34m(self, max_bytes, timeout)\u001b[39m\n\u001b[32m    126\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m map_exceptions(exc_map):\n\u001b[32m    127\u001b[39m     \u001b[38;5;28mself\u001b[39m._sock.settimeout(timeout)\n\u001b[32m--> \u001b[39m\u001b[32m128\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_sock\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrecv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmax_bytes\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mC:\\Python312\\Lib\\ssl.py:1232\u001b[39m, in \u001b[36mSSLSocket.recv\u001b[39m\u001b[34m(self, buflen, flags)\u001b[39m\n\u001b[32m   1228\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m flags != \u001b[32m0\u001b[39m:\n\u001b[32m   1229\u001b[39m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m   1230\u001b[39m             \u001b[33m\"\u001b[39m\u001b[33mnon-zero flags not allowed in calls to recv() on \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m\"\u001b[39m %\n\u001b[32m   1231\u001b[39m             \u001b[38;5;28mself\u001b[39m.\u001b[34m__class__\u001b[39m)\n\u001b[32m-> \u001b[39m\u001b[32m1232\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbuflen\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   1233\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m   1234\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m().recv(buflen, flags)\n",
+      "\u001b[36mFile \u001b[39m\u001b[32mC:\\Python312\\Lib\\ssl.py:1105\u001b[39m, in \u001b[36mSSLSocket.read\u001b[39m\u001b[34m(self, len, buffer)\u001b[39m\n\u001b[32m   1103\u001b[39m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._sslobj.read(\u001b[38;5;28mlen\u001b[39m, buffer)\n\u001b[32m   1104\u001b[39m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1105\u001b[39m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_sslobj\u001b[49m\u001b[43m.\u001b[49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m   1106\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m SSLError \u001b[38;5;28;01mas\u001b[39;00m x:\n\u001b[32m   1107\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m x.args[\u001b[32m0\u001b[39m] == SSL_ERROR_EOF \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m.suppress_ragged_eofs:\n",
+      "\u001b[31mKeyboardInterrupt\u001b[39m: "
+     ]
+    }
+   ],
+   "source": [
+    "from openai import OpenAI\n",
+    "from dotenv import load_dotenv\n",
+    "load_dotenv(override=True)\n",
+    "client = OpenAI()\n",
+    "audio_file= open(\"./audio.wav\", \"rb\")\n",
+    "\n",
+    "transcription = client.audio.transcriptions.create(\n",
+    "    model=\"gpt-4o-transcribe\", \n",
+    "    file=audio_file\n",
+    ")\n",
+    "\n",
+    "print(transcription.text)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system='''You are an intelligent assistant working for a company that builds advanced tools to automate real hiring decisions. Your task is to analyze speech-to-text transcripts from candidate interviews. For each candidate’s response, you will:\n",
+    "\n",
+    "Provide a clear and concise summary of what the candidate said.\n",
+    "\n",
+    "Identify the candidate’s motivation and key skills expressed in their speech.\n",
+    "\n",
+    "Highlight any additional insights or relevant observations that could assist recruiters in making informed hiring decisions.\n",
+    "\n",
+    "Focus on delivering objective, actionable, and relevant information that captures the candidate’s potential skills'''"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def summarize_audio(file_path):\n",
+    "    audio_file=open(\"./audio.wav\", \"rb\")\n",
+    "    transcription = client.audio.transcriptions.create(\n",
+    "    model=\"gpt-4o-transcribe\", \n",
+    "    file=audio_file\n",
+    ")   \n",
+    "    user_prompt=\"Here is transcription of the audio \\n \"\n",
+    "    user_prompt+=transcription.text\n",
+    "    prompts = [\n",
+    "    {\"role\": \"system\", \"content\": system},\n",
+    "    {\"role\": \"user\", \"content\": user_prompt}\n",
+    "  ]\n",
+    "    chat=client.chat.completions.create(\n",
+    "        model='gpt-4.1-mini',\n",
+    "        messages=prompts\n",
+    "\n",
+    "    )\n",
+    "    return chat.choices[0].message.content"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result=summarize_audio(\"./audio.wav\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Summary:\\nThe candidate emphasized that anyone can perform a random act of kindness regardless of their wealth, appearance, popularity, or status.\\n\\nMotivation and Key Skills:\\n- Motivation: The candidate appears motivated by kindness and inclusivity, valuing acts of goodwill accessible to all people.\\n- Key Skills: Empathy, social awareness, and a positive attitude towards helping others.\\n\\nAdditional Insights:\\nThis response reflects an individual who values compassion and believes in simple, meaningful actions. Such a mindset can contribute to a positive workplace culture and teamwork. The candidate may bring interpersonal skills and an inclusive approach to collaboration.'"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Python312\\Lib\\asyncio\\events.py:88: DeprecationError: 2025-01-27: `modal.Cls.lookup` is deprecated and will be removed in a future release. It can be replaced with `modal.Cls.from_name`.\n",
+      "\n",
+      "See https://modal.com/docs/guide/modal-1-0-migration for more information.\n",
+      "  self._context.run(self._callback, *self._args)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from Summarizer_Agent import Summarizer\n",
+    "summarizer=Summarizer()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\LLM\\AccentDetector\\Summarizer_Agent.py:38: DeprecationError: 2025-01-13: Calling a method on an uninstantiated class will soon be deprecated; update your code to instantiate the class first, i.e.:\n",
+      "Accentizer().classify instead of Accentizer.classify\n",
+      "  result= self.Accentizer.classify.remote(url)\n"
+     ]
+    }
+   ],
+   "source": [
+    "classification_result=summarizer.classify(\"https://huggingface.co/Jzuluaga/accent-id-commonaccent_xlsr-en-english/resolve/main/data/malaysia_1.wav\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'label': ['malaysia'],\n",
+       " 'score': tensor([1.0000]),\n",
+       " 'index': tensor([11]),\n",
+       " 'out_prob': tensor([[1.1861e-06, 1.2055e-10, 5.3473e-11, 5.4380e-13, 2.0032e-15, 4.4907e-07,\n",
+       "          6.3841e-15, 4.1446e-15, 6.7382e-18, 1.5646e-16, 2.8600e-14, 1.0000e+00,\n",
+       "          9.1365e-11, 1.0672e-14, 2.5264e-11, 2.2511e-09]])}"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "classification_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "flags = {\n",
+    "    \"us\": \"🇺🇸\",\n",
+    "    \"england\": \"🏴\",         # Flag of England (subdivision of UK)\n",
+    "    \"australia\": \"🇦🇺\",\n",
+    "    \"indian\": \"🇮🇳\",          # Assuming you meant India\n",
+    "    \"canada\": \"🇨🇦\",\n",
+    "    \"bermuda\": \"🇧🇲\",\n",
+    "    \"scotland\": \"🏴\",        # Flag of Scotland (subdivision of UK)\n",
+    "    \"african\": \"🌍\",         # No single African flag – using globe showing Africa\n",
+    "    \"ireland\": \"🇮🇪\",\n",
+    "    \"newzealand\": \"🇳🇿\",\n",
+    "    \"wales\": \"🏴\",           # Flag of Wales (subdivision of UK)\n",
+    "    \"malaysia\": \"🇲🇾\",\n",
+    "    \"philippines\": \"🇵🇭\",\n",
+    "    \"singapore\": \"🇸🇬\",\n",
+    "    \"hongkong\": \"🇭🇰\",\n",
+    "    \"southatlandtic\": \"🌊\"   # Not a country – using water wave\n",
+    "}\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "import gradio as gr\n",
+    "\n",
+    "def process_youtube(url):\n",
+    "    try:\n",
+    "        summary = summarizer.summarize(url)\n",
+    "        accent_info = summarizer.classify(url)\n",
+    "        \n",
+    "        accent = accent_info[\"label\"]\n",
+    "        flag = flags.get(accent.lower(), \"🏳️\")  # fallback to white flag if not found\n",
+    "        accent_display = f\"{flag} {accent.capitalize()}\"\n",
+    "        \n",
+    "        return summary, accent_display, accent_info[\"score\"]\n",
+    "    except Exception as e:\n",
+    "        return f\"Error: {e}\", \"N/A\", \"N/A\"\n",
+    "\n",
+    "demo = gr.Interface(\n",
+    "    fn=process_youtube,\n",
+    "    inputs=gr.Textbox(label=\"public video  URL\", placeholder=\"Enter public video link here...\"),\n",
+    "    outputs=[\n",
+    "        gr.Textbox(label=\"Candidate Summary\", lines=10),\n",
+    "        gr.Textbox(label=\"Detected Accent\"),\n",
+    "        gr.Slider(label=\"Confidence Score (%)\", minimum=0, maximum=1, step=0.001, interactive=False)\n",
+    "\n",
+    "    ],\n",
+    "    title=\"Interview Audio Summarizer\",\n",
+    "    description=\"Paste an interview video link. The app will summarize the candidate's response and detect the speaker's accent.\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "* Running on local URL:  http://127.0.0.1:7864\n",
+      "* To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7864/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[generic] Extracting URL: https://huggingface.co/Jzuluaga/accent-id-commonaccent_xlsr-en-english/resolve/main/data/malaysia_1.wav\n",
+      "[generic] malaysia_1: Downloading webpage\n",
+      "[info] malaysia_1: Downloading 1 format(s): wave\n",
+      "[download] Destination: audio\n",
+      "[download] 100% of  228.79KiB in 00:00:00 at 639.15KiB/s   \n",
+      "[ExtractAudio] Destination: audio.mp3\n",
+      "Deleting original file audio (pass -k to keep)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\LLM\\AccentDetector\\Summarizer_Agent.py:38: DeprecationError: 2025-01-13: Calling a method on an uninstantiated class will soon be deprecated; update your code to instantiate the class first, i.e.:\n",
+      "Accentizer().classify instead of Accentizer.classify\n",
+      "  raw= self.Accentizer.classify.remote(url)\n"
+     ]
+    }
+   ],
+   "source": [
+    "demo.launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "^C\n"
+     ]
+    }
+   ],
+   "source": [
+    "!gradio deploy"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}