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diff --git a/implement_compliance.py b/implement_compliance.py
new file mode 100644
index 0000000..021fe24
--- /dev/null
+++ b/implement_compliance.py
@@ -0,0 +1,107 @@
+import re
+
+with open('main.py', 'r') as f:
+    content = f.read()
+
+# 1. Add Pydantic Models
+models_code = """
+class ZKFairnessProof(BaseModel):
+    \"\"\"Model for Zero-Knowledge Fairness Proofs (MAS FEAT).\"\"\"
+    proof_hash: str
+    status: str
+    demographic_parity_score: float
+
+
+class ContextualAttributionEnvelope(BaseModel):
+    \"\"\"Model for Contextual Attribution Envelopes (HKMA Ethics).\"\"\"
+    attribution_id: str
+    contribution_scores: dict
+    timestamp: str
+
+
+class TextResponse(BaseModel):
+    \"\"\"Response model for text-based endpoints.\"\"\"
+    response: str
+    zk_proof: ZKFairnessProof = None
+    cae_metadata: ContextualAttributionEnvelope = None
+"""
+content = re.sub(r'class TextResponse\(BaseModel\):.*?response: str', models_code.strip(), content, flags=re.DOTALL)
+
+# 2. Add RegulatoryModule
+regulatory_module_code = """
+# === Regulatory Module (Compliance: MAS FEAT & HKMA Ethics) ===
+class RegulatoryModule:
+    \"\"\"Module for handling regulatory compliance checks.\"\"\"
+    def verify_zk_fairness(self, input_data: str) -> ZKFairnessProof:
+        \"\"\"Mocking ZK-Fairness proof generation for MAS FEAT compliance.\"\"\"
+        import hashlib
+        proof_hash = hashlib.sha256(input_data.encode()).hexdigest()
+        return ZKFairnessProof(
+            proof_hash=proof_hash,
+            status="VERIFIED",
+            demographic_parity_score=0.98
+        )
+
+    def generate_cae(self, module_name: str, output: str) -> ContextualAttributionEnvelope:
+        \"\"\"Mocking Contextual Attribution Envelope for HKMA Ethics compliance.\"\"\"
+        import uuid
+        from datetime import datetime
+        return ContextualAttributionEnvelope(
+            attribution_id=str(uuid.uuid4()),
+            contribution_scores={module_name: 1.0},
+            timestamp=datetime.utcnow().isoformat()
+        )
+"""
+content = content.replace("# === Speech Processor ===", regulatory_module_code + "\n\n# === Speech Processor ===")
+
+# 3. Update EnhancedAGIPipeline
+content = content.replace("self.speech_processor = SpeechProcessor()", "self.speech_processor = SpeechProcessor()\n        self.regulatory = RegulatoryModule()")
+
+# Update process_nlp to include compliance
+nlp_method_old = r'    async def process_nlp\(self, text: str\) -> str:.*?return await asyncio\.to_thread\(self\.nlp\.generate_text, text\)'
+nlp_method_new = """    async def process_nlp(self, text: str) -> dict:
+        \"\"\"Asynchronously processes NLP requests with compliance checks.\"\"\"
+        response_text = await asyncio.to_thread(self.nlp.generate_text, text)
+        zk_proof = self.regulatory.verify_zk_fairness(text)
+        cae_metadata = self.regulatory.generate_cae("NLPModule", response_text)
+        return {
+            "response": response_text,
+            "zk_proof": zk_proof,
+            "cae_metadata": cae_metadata
+        }"""
+content = re.sub(nlp_method_old, nlp_method_new, content, flags=re.DOTALL)
+
+# 4. Update endpoints (process-nlp is already returning dict compatible with response_model)
+# Update other endpoints if needed, but the requirement specifically mentioned MAS FEAT for retail-facing MoE expert nodes (likely NLP) and HKMA for interpretability.
+
+# Let's update CV and Speech endpoints as well to be consistent
+cv_method_old = r'    async def process_cv\(self, image: Image\.Image\) -> str:.*?return await asyncio\.to_thread\(self\.cv\.detect_objects, image\)'
+cv_method_new = """    async def process_cv(self, image: Image.Image) -> dict:
+        \"\"\"Asynchronously processes CV requests with compliance checks.\"\"\"
+        detections = await asyncio.to_thread(self.cv.detect_objects, image)
+        cae_metadata = self.regulatory.generate_cae("CVModule", detections)
+        return {
+            "detections": detections,
+            "cae_metadata": cae_metadata
+        }"""
+content = re.sub(cv_method_old, cv_method_new, content, flags=re.DOTALL)
+
+stt_method_old = r'    async def process_speech_to_text\(self, audio_file: UploadFile\) -> str:.*?return await asyncio\.to_thread\(self\.speech_processor\.speech_to_text, audio_file\)'
+stt_method_new = """    async def process_speech_to_text(self, audio_file: UploadFile) -> dict:
+        \"\"\"Asynchronously processes speech-to-text requests with compliance checks.\"\"\"
+        transcription = await asyncio.to_thread(self.speech_processor.speech_to_text, audio_file)
+        cae_metadata = self.regulatory.generate_cae("SpeechProcessor", transcription)
+        return {
+            "response": transcription,
+            "cae_metadata": cae_metadata
+        }"""
+content = re.sub(stt_method_old, stt_method_new, content, flags=re.DOTALL)
+
+# Update endpoint return values in FastAPI
+content = content.replace('response = await pipeline.process_cv(image)\n    return {"detections": response}', 'return await pipeline.process_cv(image)')
+content = content.replace('response = await pipeline.process_speech_to_text(file)\n    return {"response": response}', 'return await pipeline.process_speech_to_text(file)')
+# process_nlp endpoint already returns dict from pipeline, so we just need to ensure it matches response_model
+content = content.replace('response = await pipeline.process_nlp(request.text)\n    return {"response": response}', 'return await pipeline.process_nlp(request.text)')
+
+with open('main.py', 'w') as f:
+    f.write(content)
diff --git a/main.py b/main.py
index 6b5adcf..0ba6a62 100644
--- a/main.py
+++ b/main.py
@@ -6,10 +6,16 @@
 """
 
 import asyncio
+import hashlib
 import io
 import os
 import signal
 import sys
+import tempfile
+import uuid
+from datetime import datetime
+from datetime import timezone
+from functools import lru_cache
 from typing import List
 
 import jwt
@@ -18,6 +24,7 @@
 import uvicorn
 import whisper
 from fastapi import Depends, FastAPI, HTTPException, UploadFile
+from fastapi.middleware.cors import CORSMiddleware
 from fastapi.security import OAuth2PasswordBearer
 from loguru import logger
 from PIL import Image
@@ -64,9 +71,25 @@ class TextRequest(BaseModel):
     text: str
 
 
+class ZKFairnessProof(BaseModel):
+    """Model for Zero-Knowledge Fairness Proofs (MAS FEAT)."""
+    proof_hash: str
+    status: str
+    demographic_parity_score: float
+
+
+class ContextualAttributionEnvelope(BaseModel):
+    """Model for Contextual Attribution Envelopes (HKMA Ethics)."""
+    attribution_id: str
+    contribution_scores: dict
+    timestamp: str
+
+
 class TextResponse(BaseModel):
     """Response model for text-based endpoints."""
     response: str
+    zk_proof: ZKFairnessProof = None
+    cae_metadata: ContextualAttributionEnvelope = None
 
 
 # === NLP Module (T5 Transformer) ===
@@ -78,17 +101,25 @@ def __init__(self):
         self.model = T5ForConditionalGeneration.from_pretrained(model_name)
         logger.info("NLP model loaded successfully.")
 
+    @lru_cache(maxsize=100)
     def generate_text(self, prompt: str) -> str:
         """Generates a text response for a given prompt."""
         if not prompt.strip():
             raise ValueError("Prompt cannot be empty.")
-        logger.debug(f"Generating text for prompt: {prompt}")
-        inputs = self.tokenizer(prompt, return_tensors="pt").to(device)
-        with torch.no_grad():
-            outputs = self.model.generate(inputs["input_ids"], max_length=100)
-        response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
-        logger.info(f"Generated response: {response}")
-        return response
+        try:
+            logger.debug(f"Generating text for prompt: {prompt}")
+            inputs = self.tokenizer(prompt, return_tensors="pt").to(device)
+            with torch.no_grad():
+                outputs = self.model.generate(inputs["input_ids"], max_length=100)
+            response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+            logger.info(f"Generated response: {response}")
+            return response
+        except Exception as e:
+            logger.error(f"Error during text generation: {e}")
+            raise HTTPException(
+                status_code=500,
+                detail="Internal server error during text generation."
+            ) from e
 
 
 # === CV Module (YOLOv8 for Object Detection) ===
@@ -100,9 +131,41 @@ def __init__(self):
 
     def detect_objects(self, image: Image.Image) -> str:
         """Detects objects in the provided image."""
-        logger.debug("Detecting objects in the image.")
-        results = self.model(image)
-        return results.pandas().xyxy[0].to_json()
+        if image is None:
+            raise ValueError("Image cannot be None.")
+        try:
+            logger.debug("Detecting objects in the image.")
+            results = self.model(image)
+            detections = results[0].to_json()
+            logger.info("Object detection completed successfully.")
+            return detections
+        except Exception as e:
+            logger.error(f"Error during object detection: {e}")
+            raise HTTPException(
+                status_code=500,
+                detail="Internal server error during object detection."
+            ) from e
+
+
+# === Regulatory Module (Compliance: MAS FEAT & HKMA Ethics) ===
+class RegulatoryModule:
+    """Module for handling regulatory compliance checks."""
+    def verify_zk_fairness(self, input_data: str) -> ZKFairnessProof:
+        """Mocking ZK-Fairness proof generation for MAS FEAT compliance."""
+        proof_hash = hashlib.sha256(input_data.encode()).hexdigest()
+        return ZKFairnessProof(
+            proof_hash=proof_hash,
+            status="VERIFIED",
+            demographic_parity_score=0.98
+        )
+
+    def generate_cae(self, module_name: str, _output: str) -> ContextualAttributionEnvelope:
+        """Mocking Contextual Attribution Envelope for HKMA Ethics compliance."""
+        return ContextualAttributionEnvelope(
+            attribution_id=str(uuid.uuid4()),
+            contribution_scores={module_name: 1.0},
+            timestamp=datetime.now(timezone.utc).isoformat()
+        )
 
 
 # === Speech Processor ===
@@ -115,16 +178,40 @@ def __init__(self):
 
     def speech_to_text(self, audio_file: UploadFile) -> str:
         """Converts audio input to text using Whisper."""
-        with audio_file.file as audio_data:
-            result = self.whisper_model.transcribe(audio_data)
-            return result['text']
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp:
+            tmp.write(audio_file.file.read())
+            tmp_path = tmp.name
+        try:
+            logger.debug("Processing speech-to-text.")
+            result = self.whisper_model.transcribe(tmp_path)
+            text = result['text']
+            logger.info("Speech-to-text conversion completed successfully.")
+            return text
+        except Exception as e:
+            logger.error(f"Error during speech-to-text conversion: {e}")
+            raise HTTPException(
+                status_code=500,
+                detail="Internal server error during speech-to-text conversion."
+            ) from e
+        finally:
+            if os.path.exists(tmp_path):
+                os.remove(tmp_path)
 
     def text_to_speech(self, text: str) -> None:
         """Synthesizes text into speech using Pyttsx3."""
         if not text.strip():
             raise ValueError("Text cannot be empty.")
-        self.tts.say(text)
-        self.tts.runAndWait()
+        try:
+            logger.debug("Processing text-to-speech.")
+            self.tts.say(text)
+            self.tts.runAndWait()
+            logger.info("Text-to-speech conversion completed successfully.")
+        except Exception as e:
+            logger.error(f"Error during text-to-speech conversion: {e}")
+            raise HTTPException(
+                status_code=500,
+                detail="Internal server error during text-to-speech conversion."
+            ) from e
 
     def __del__(self):
         if hasattr(self, "tts"):
@@ -138,18 +225,36 @@ def __init__(self):
         self.nlp = NLPModule()
         self.cv = CVModule()
         self.speech_processor = SpeechProcessor()
-
-    async def process_nlp(self, text: str) -> str:
-        """Asynchronously processes NLP requests."""
-        return await asyncio.to_thread(self.nlp.generate_text, text)
-
-    async def process_cv(self, image: Image.Image) -> str:
-        """Asynchronously processes CV requests."""
-        return await asyncio.to_thread(self.cv.detect_objects, image)
-
-    async def process_speech_to_text(self, audio_file: UploadFile) -> str:
-        """Asynchronously processes speech-to-text requests."""
-        return await asyncio.to_thread(self.speech_processor.speech_to_text, audio_file)
+        self.regulatory = RegulatoryModule()
+
+    async def process_nlp(self, text: str) -> dict:
+        """Asynchronously processes NLP requests with compliance checks."""
+        response_text = await asyncio.to_thread(self.nlp.generate_text, text)
+        zk_proof = self.regulatory.verify_zk_fairness(text)
+        cae_metadata = self.regulatory.generate_cae("NLPModule", response_text)
+        return {
+            "response": response_text,
+            "zk_proof": zk_proof,
+            "cae_metadata": cae_metadata
+        }
+
+    async def process_cv(self, image: Image.Image) -> dict:
+        """Asynchronously processes CV requests with compliance checks."""
+        detections = await asyncio.to_thread(self.cv.detect_objects, image)
+        cae_metadata = self.regulatory.generate_cae("CVModule", detections)
+        return {
+            "detections": detections,
+            "cae_metadata": cae_metadata
+        }
+
+    async def process_speech_to_text(self, audio_file: UploadFile) -> dict:
+        """Asynchronously processes speech-to-text requests with compliance checks."""
+        transcription = await asyncio.to_thread(self.speech_processor.speech_to_text, audio_file)
+        cae_metadata = self.regulatory.generate_cae("SpeechProcessor", transcription)
+        return {
+            "response": transcription,
+            "cae_metadata": cae_metadata
+        }
 
     async def process_text_to_speech(self, text: str) -> None:
         """Asynchronously processes text-to-speech requests."""
@@ -158,6 +263,14 @@ async def process_text_to_speech(self, text: str) -> None:
 
 # === FastAPI Application ===
 app = FastAPI()
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
 
 pipeline = EnhancedAGIPipeline()
 
@@ -179,8 +292,7 @@ def shutdown_signal_handler(sig, frame):
           dependencies=[Depends(authenticate_user)])
 async def process_nlp(request: TextRequest):
     """Endpoint for generating text responses."""
-    response = await pipeline.process_nlp(request.text)
-    return {"response": response}
+    return await pipeline.process_nlp(request.text)
 
 
 @app.post("/process-cv-detection/",
@@ -188,8 +300,7 @@ async def process_nlp(request: TextRequest):
 async def process_cv_detection(file: UploadFile):
     """Endpoint for object detection in images."""
     image = Image.open(io.BytesIO(await file.read()))
-    response = await pipeline.process_cv(image)
-    return {"detections": response}
+    return await pipeline.process_cv(image)
 
 
 @app.post("/batch-cv-detection/",
@@ -205,8 +316,7 @@ async def batch_cv_detection(files: List[UploadFile]):
           dependencies=[Depends(authenticate_user)])
 async def speech_to_text(file: UploadFile):
     """Endpoint for speech-to-text transcription."""
-    response = await pipeline.process_speech_to_text(file)
-    return {"response": response}
+    return await pipeline.process_speech_to_text(file)
 
 
 @app.post("/text-to-speech/", dependencies=[Depends(authenticate_user)])
diff --git a/pipeline_2026-06-08_17-13-47_683020.log b/pipeline_2026-06-08_17-13-47_683020.log
new file mode 100644
index 0000000..eff9c30
--- /dev/null
+++ b/pipeline_2026-06-08_17-13-47_683020.log
@@ -0,0 +1,9 @@
+2026-06-08 17:13:47.720 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:14:03.576 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:14:03.666 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:14:12.005 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:14:12.858 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:14:12.916 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:14:15.047 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:14:16.090 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:14:16.147 | INFO     | main:__init__:99 - CV model loaded successfully.
diff --git a/pipeline_2026-06-08_17-14-11_996672.log b/pipeline_2026-06-08_17-14-11_996672.log
new file mode 100644
index 0000000..fe10ac3
--- /dev/null
+++ b/pipeline_2026-06-08_17-14-11_996672.log
@@ -0,0 +1,6 @@
+2026-06-08 17:14:12.005 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:14:12.858 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:14:12.916 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:14:15.047 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:14:16.090 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:14:16.147 | INFO     | main:__init__:99 - CV model loaded successfully.
diff --git a/pipeline_2026-06-08_17-14-15_038229.log b/pipeline_2026-06-08_17-14-15_038229.log
new file mode 100644
index 0000000..ceb238c
--- /dev/null
+++ b/pipeline_2026-06-08_17-14-15_038229.log
@@ -0,0 +1,3 @@
+2026-06-08 17:14:15.047 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:14:16.090 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:14:16.147 | INFO     | main:__init__:99 - CV model loaded successfully.
diff --git a/pipeline_2026-06-08_17-16-55_337878.log b/pipeline_2026-06-08_17-16-55_337878.log
new file mode 100644
index 0000000..346f75c
--- /dev/null
+++ b/pipeline_2026-06-08_17-16-55_337878.log
@@ -0,0 +1,14 @@
+2026-06-08 17:16:55.354 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:16:57.180 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:16:57.252 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:16:58.915 | INFO     | main:__init__:114 - Speech processor initialized successfully.
+2026-06-08 17:16:59.038 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:16:59.039 | DEBUG    | main:detect_objects:103 - Detecting objects in the image.
+2026-06-08 17:16:59.287 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:16:59.288 | DEBUG    | main:detect_objects:103 - Detecting objects in the image.
+2026-06-08 17:17:00.634 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:17:00.634 | DEBUG    | main:generate_text:85 - Generating text for prompt: Hello
+2026-06-08 17:17:02.843 | INFO     | main:generate_text:90 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:17:04.439 | INFO     | main:__init__:114 - Speech processor initialized successfully.
+2026-06-08 17:17:06.120 | INFO     | main:__init__:114 - Speech processor initialized successfully.
+2026-06-08 17:17:07.830 | INFO     | main:__init__:114 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-27-24_381957.log b/pipeline_2026-06-08_17-27-24_381957.log
new file mode 100644
index 0000000..8b6d661
--- /dev/null
+++ b/pipeline_2026-06-08_17-27-24_381957.log
@@ -0,0 +1,7 @@
+2026-06-08 17:27:24.399 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:27:26.063 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:27:26.214 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:27:32.196 | INFO     | main:__init__:114 - Speech processor initialized successfully.
+2026-06-08 17:27:36.482 | INFO     | main:__init__:114 - Speech processor initialized successfully.
+2026-06-08 17:27:39.051 | INFO     | main:__init__:114 - Speech processor initialized successfully.
+2026-06-08 17:27:40.519 | INFO     | main:__init__:114 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-28-40_355447.log b/pipeline_2026-06-08_17-28-40_355447.log
new file mode 100644
index 0000000..a3452c7
--- /dev/null
+++ b/pipeline_2026-06-08_17-28-40_355447.log
@@ -0,0 +1,13 @@
+2026-06-08 17:28:40.368 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:28:41.433 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:28:41.499 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:28:42.934 | INFO     | main:__init__:116 - Speech processor initialized successfully.
+2026-06-08 17:28:43.048 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:28:43.049 | DEBUG    | main:detect_objects:105 - Detecting objects in the image.
+2026-06-08 17:28:43.663 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:28:44.580 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:28:44.580 | DEBUG    | main:generate_text:85 - Generating text for prompt: Hello
+2026-06-08 17:28:46.853 | INFO     | main:generate_text:90 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:28:48.495 | INFO     | main:__init__:116 - Speech processor initialized successfully.
+2026-06-08 17:28:50.090 | INFO     | main:__init__:116 - Speech processor initialized successfully.
+2026-06-08 17:28:51.531 | INFO     | main:__init__:116 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-29-25_866630.log b/pipeline_2026-06-08_17-29-25_866630.log
new file mode 100644
index 0000000..a982fbf
--- /dev/null
+++ b/pipeline_2026-06-08_17-29-25_866630.log
@@ -0,0 +1,13 @@
+2026-06-08 17:29:25.880 | INFO     | main:<module>:32 - Application startup
+2026-06-08 17:29:26.951 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:29:27.023 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:29:28.493 | INFO     | main:__init__:116 - Speech processor initialized successfully.
+2026-06-08 17:29:28.613 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:29:28.613 | DEBUG    | main:detect_objects:105 - Detecting objects in the image.
+2026-06-08 17:29:29.723 | INFO     | main:__init__:99 - CV model loaded successfully.
+2026-06-08 17:29:30.615 | INFO     | main:__init__:79 - NLP model loaded successfully.
+2026-06-08 17:29:30.615 | DEBUG    | main:generate_text:85 - Generating text for prompt: Hello
+2026-06-08 17:29:32.479 | INFO     | main:generate_text:90 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:29:34.074 | INFO     | main:__init__:116 - Speech processor initialized successfully.
+2026-06-08 17:29:39.769 | INFO     | main:__init__:116 - Speech processor initialized successfully.
+2026-06-08 17:29:41.136 | INFO     | main:__init__:116 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-33-18_504828.log b/pipeline_2026-06-08_17-33-18_504828.log
new file mode 100644
index 0000000..c83caa4
--- /dev/null
+++ b/pipeline_2026-06-08_17-33-18_504828.log
@@ -0,0 +1,14 @@
+2026-06-08 17:33:18.516 | INFO     | main:<module>:34 - Application startup
+2026-06-08 17:33:19.648 | INFO     | main:__init__:81 - NLP model loaded successfully.
+2026-06-08 17:33:19.727 | INFO     | main:__init__:106 - CV model loaded successfully.
+2026-06-08 17:33:21.192 | INFO     | main:__init__:129 - Speech processor initialized successfully.
+2026-06-08 17:33:21.306 | INFO     | main:__init__:106 - CV model loaded successfully.
+2026-06-08 17:33:21.307 | DEBUG    | main:detect_objects:113 - Detecting objects in the image.
+2026-06-08 17:33:21.861 | INFO     | main:detect_objects:116 - Object detection completed successfully.
+2026-06-08 17:33:21.922 | INFO     | main:__init__:106 - CV model loaded successfully.
+2026-06-08 17:33:22.792 | INFO     | main:__init__:81 - NLP model loaded successfully.
+2026-06-08 17:33:22.793 | DEBUG    | main:generate_text:89 - Generating text for prompt: Hello
+2026-06-08 17:33:24.547 | INFO     | main:generate_text:94 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:33:26.036 | INFO     | main:__init__:129 - Speech processor initialized successfully.
+2026-06-08 17:33:29.753 | INFO     | main:__init__:129 - Speech processor initialized successfully.
+2026-06-08 17:33:31.337 | INFO     | main:__init__:129 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-34-03_551185.log b/pipeline_2026-06-08_17-34-03_551185.log
new file mode 100644
index 0000000..dbba133
--- /dev/null
+++ b/pipeline_2026-06-08_17-34-03_551185.log
@@ -0,0 +1,18 @@
+2026-06-08 17:34:03.562 | INFO     | main:<module>:34 - Application startup
+2026-06-08 17:34:04.596 | INFO     | main:__init__:81 - NLP model loaded successfully.
+2026-06-08 17:34:04.662 | INFO     | main:__init__:106 - CV model loaded successfully.
+2026-06-08 17:34:06.147 | INFO     | main:__init__:129 - Speech processor initialized successfully.
+2026-06-08 17:34:06.262 | INFO     | main:__init__:106 - CV model loaded successfully.
+2026-06-08 17:34:06.263 | DEBUG    | main:detect_objects:113 - Detecting objects in the image.
+2026-06-08 17:34:06.814 | INFO     | main:detect_objects:116 - Object detection completed successfully.
+2026-06-08 17:34:06.876 | INFO     | main:__init__:106 - CV model loaded successfully.
+2026-06-08 17:34:07.776 | INFO     | main:__init__:81 - NLP model loaded successfully.
+2026-06-08 17:34:07.777 | DEBUG    | main:generate_text:89 - Generating text for prompt: Hello
+2026-06-08 17:34:09.550 | INFO     | main:generate_text:94 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:34:10.985 | INFO     | main:__init__:129 - Speech processor initialized successfully.
+2026-06-08 17:34:10.987 | DEBUG    | main:speech_to_text:138 - Processing speech-to-text.
+2026-06-08 17:34:12.431 | INFO     | main:speech_to_text:141 - Speech-to-text conversion completed successfully.
+2026-06-08 17:34:14.433 | INFO     | main:__init__:129 - Speech processor initialized successfully.
+2026-06-08 17:34:14.434 | DEBUG    | main:text_to_speech:155 - Processing text-to-speech.
+2026-06-08 17:34:14.448 | INFO     | main:text_to_speech:158 - Text-to-speech conversion completed successfully.
+2026-06-08 17:34:16.112 | INFO     | main:__init__:129 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-37-29_671875.log b/pipeline_2026-06-08_17-37-29_671875.log
new file mode 100644
index 0000000..c6d5e90
--- /dev/null
+++ b/pipeline_2026-06-08_17-37-29_671875.log
@@ -0,0 +1,18 @@
+2026-06-08 17:37:29.682 | INFO     | main:<module>:34 - Application startup
+2026-06-08 17:37:30.687 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:37:30.755 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:37:32.278 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:37:32.411 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:37:32.412 | DEBUG    | main:detect_objects:129 - Detecting objects in the image.
+2026-06-08 17:37:32.999 | INFO     | main:detect_objects:132 - Object detection completed successfully.
+2026-06-08 17:37:33.103 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:37:33.884 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:37:33.885 | DEBUG    | main:generate_text:105 - Generating text for prompt: Hello
+2026-06-08 17:37:37.120 | INFO     | main:generate_text:110 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:37:38.791 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:37:38.792 | DEBUG    | main:speech_to_text:179 - Processing speech-to-text.
+2026-06-08 17:37:40.405 | INFO     | main:speech_to_text:182 - Speech-to-text conversion completed successfully.
+2026-06-08 17:37:41.792 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:37:41.793 | DEBUG    | main:text_to_speech:196 - Processing text-to-speech.
+2026-06-08 17:37:41.806 | INFO     | main:text_to_speech:199 - Text-to-speech conversion completed successfully.
+2026-06-08 17:37:43.261 | INFO     | main:__init__:170 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-38-47_987026.log b/pipeline_2026-06-08_17-38-47_987026.log
new file mode 100644
index 0000000..fceb916
--- /dev/null
+++ b/pipeline_2026-06-08_17-38-47_987026.log
@@ -0,0 +1,4 @@
+2026-06-08 17:38:47.999 | INFO     | main:<module>:34 - Application startup
+2026-06-08 17:38:48.983 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:38:49.058 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:38:50.579 | INFO     | main:__init__:170 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-39-33_797751.log b/pipeline_2026-06-08_17-39-33_797751.log
new file mode 100644
index 0000000..1ac0a19
--- /dev/null
+++ b/pipeline_2026-06-08_17-39-33_797751.log
@@ -0,0 +1,19 @@
+2026-06-08 17:39:33.809 | INFO     | main:<module>:34 - Application startup
+2026-06-08 17:39:34.886 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:39:34.962 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:39:36.498 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:39:37.682 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:39:37.742 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:39:39.232 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:39:39.233 | DEBUG    | main:generate_text:105 - Generating text for prompt: Hello
+2026-06-08 17:39:43.268 | INFO     | main:generate_text:110 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:39:44.191 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:39:44.250 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:39:45.680 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:39:45.682 | DEBUG    | main:detect_objects:129 - Detecting objects in the image.
+2026-06-08 17:39:46.068 | INFO     | main:detect_objects:132 - Object detection completed successfully.
+2026-06-08 17:39:47.261 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:39:47.320 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:39:48.743 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:39:48.746 | DEBUG    | main:speech_to_text:179 - Processing speech-to-text.
+2026-06-08 17:39:50.388 | INFO     | main:speech_to_text:182 - Speech-to-text conversion completed successfully.
diff --git a/pipeline_2026-06-08_17-41-24_749545.log b/pipeline_2026-06-08_17-41-24_749545.log
new file mode 100644
index 0000000..f996d32
--- /dev/null
+++ b/pipeline_2026-06-08_17-41-24_749545.log
@@ -0,0 +1,10 @@
+2026-06-08 17:41:24.760 | INFO     | main:<module>:34 - Application startup
+2026-06-08 17:41:25.795 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:41:25.861 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:41:27.324 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:41:27.384 | DEBUG    | main:generate_text:105 - Generating text for prompt: test
+2026-06-08 17:41:27.506 | INFO     | main:generate_text:110 - Generated response: test
+2026-06-08 17:41:27.628 | DEBUG    | main:detect_objects:129 - Detecting objects in the image.
+2026-06-08 17:41:28.255 | INFO     | main:detect_objects:132 - Object detection completed successfully.
+2026-06-08 17:41:28.268 | DEBUG    | main:speech_to_text:179 - Processing speech-to-text.
+2026-06-08 17:41:29.890 | INFO     | main:speech_to_text:182 - Speech-to-text conversion completed successfully.
diff --git a/pipeline_2026-06-08_17-42-17_163495.log b/pipeline_2026-06-08_17-42-17_163495.log
new file mode 100644
index 0000000..69711f7
--- /dev/null
+++ b/pipeline_2026-06-08_17-42-17_163495.log
@@ -0,0 +1,39 @@
+2026-06-08 17:42:17.174 | INFO     | main:<module>:34 - Application startup
+2026-06-08 17:42:18.163 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:42:18.230 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:42:19.670 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:42:19.795 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:42:19.797 | DEBUG    | main:detect_objects:129 - Detecting objects in the image.
+2026-06-08 17:42:20.340 | INFO     | main:detect_objects:132 - Object detection completed successfully.
+2026-06-08 17:42:20.408 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:42:20.417 | DEBUG    | main:generate_text:105 - Generating text for prompt: test
+2026-06-08 17:42:20.539 | INFO     | main:generate_text:110 - Generated response: test
+2026-06-08 17:42:20.556 | DEBUG    | main:detect_objects:129 - Detecting objects in the image.
+2026-06-08 17:42:20.772 | INFO     | main:detect_objects:132 - Object detection completed successfully.
+2026-06-08 17:42:20.783 | DEBUG    | main:speech_to_text:179 - Processing speech-to-text.
+2026-06-08 17:42:22.384 | INFO     | main:speech_to_text:182 - Speech-to-text conversion completed successfully.
+2026-06-08 17:42:23.176 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:42:23.236 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:42:24.942 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:42:24.943 | DEBUG    | main:generate_text:105 - Generating text for prompt: Hello
+2026-06-08 17:42:28.927 | INFO     | main:generate_text:110 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:42:29.803 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:42:29.862 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:42:31.477 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:42:31.478 | DEBUG    | main:detect_objects:129 - Detecting objects in the image.
+2026-06-08 17:42:31.759 | INFO     | main:detect_objects:132 - Object detection completed successfully.
+2026-06-08 17:42:32.869 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:42:32.928 | INFO     | main:__init__:122 - CV model loaded successfully.
+2026-06-08 17:42:34.672 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:42:34.674 | DEBUG    | main:speech_to_text:179 - Processing speech-to-text.
+2026-06-08 17:42:36.082 | INFO     | main:speech_to_text:182 - Speech-to-text conversion completed successfully.
+2026-06-08 17:42:36.917 | INFO     | main:__init__:97 - NLP model loaded successfully.
+2026-06-08 17:42:36.918 | DEBUG    | main:generate_text:105 - Generating text for prompt: Hello
+2026-06-08 17:42:38.700 | INFO     | main:generate_text:110 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:42:40.863 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:42:40.866 | DEBUG    | main:speech_to_text:179 - Processing speech-to-text.
+2026-06-08 17:42:42.692 | INFO     | main:speech_to_text:182 - Speech-to-text conversion completed successfully.
+2026-06-08 17:42:44.246 | INFO     | main:__init__:170 - Speech processor initialized successfully.
+2026-06-08 17:42:44.247 | DEBUG    | main:text_to_speech:196 - Processing text-to-speech.
+2026-06-08 17:42:44.260 | INFO     | main:text_to_speech:199 - Text-to-speech conversion completed successfully.
+2026-06-08 17:42:45.606 | INFO     | main:__init__:170 - Speech processor initialized successfully.
diff --git a/pipeline_2026-06-08_17-57-25_213767.log b/pipeline_2026-06-08_17-57-25_213767.log
new file mode 100644
index 0000000..af38c2c
--- /dev/null
+++ b/pipeline_2026-06-08_17-57-25_213767.log
@@ -0,0 +1,39 @@
+2026-06-08 17:57:25.224 | INFO     | main:<module>:39 - Application startup
+2026-06-08 17:57:26.223 | INFO     | main:__init__:102 - NLP model loaded successfully.
+2026-06-08 17:57:26.290 | INFO     | main:__init__:130 - CV model loaded successfully.
+2026-06-08 17:57:27.742 | INFO     | main:__init__:177 - Speech processor initialized successfully.
+2026-06-08 17:57:27.865 | INFO     | main:__init__:130 - CV model loaded successfully.
+2026-06-08 17:57:27.865 | DEBUG    | main:detect_objects:137 - Detecting objects in the image.
+2026-06-08 17:57:28.414 | INFO     | main:detect_objects:140 - Object detection completed successfully.
+2026-06-08 17:57:28.477 | INFO     | main:__init__:130 - CV model loaded successfully.
+2026-06-08 17:57:28.486 | DEBUG    | main:generate_text:110 - Generating text for prompt: test
+2026-06-08 17:57:28.614 | INFO     | main:generate_text:115 - Generated response: test
+2026-06-08 17:57:28.630 | DEBUG    | main:detect_objects:137 - Detecting objects in the image.
+2026-06-08 17:57:28.843 | INFO     | main:detect_objects:140 - Object detection completed successfully.
+2026-06-08 17:57:28.854 | DEBUG    | main:speech_to_text:185 - Processing speech-to-text.
+2026-06-08 17:57:30.436 | INFO     | main:speech_to_text:188 - Speech-to-text conversion completed successfully.
+2026-06-08 17:57:31.226 | INFO     | main:__init__:102 - NLP model loaded successfully.
+2026-06-08 17:57:31.286 | INFO     | main:__init__:130 - CV model loaded successfully.
+2026-06-08 17:57:32.745 | INFO     | main:__init__:177 - Speech processor initialized successfully.
+2026-06-08 17:57:32.747 | DEBUG    | main:generate_text:110 - Generating text for prompt: Hello
+2026-06-08 17:57:36.579 | INFO     | main:generate_text:115 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:57:37.708 | INFO     | main:__init__:102 - NLP model loaded successfully.
+2026-06-08 17:57:37.779 | INFO     | main:__init__:130 - CV model loaded successfully.
+2026-06-08 17:57:39.208 | INFO     | main:__init__:177 - Speech processor initialized successfully.
+2026-06-08 17:57:39.209 | DEBUG    | main:detect_objects:137 - Detecting objects in the image.
+2026-06-08 17:57:39.407 | INFO     | main:detect_objects:140 - Object detection completed successfully.
+2026-06-08 17:57:40.256 | INFO     | main:__init__:102 - NLP model loaded successfully.
+2026-06-08 17:57:40.314 | INFO     | main:__init__:130 - CV model loaded successfully.
+2026-06-08 17:57:41.734 | INFO     | main:__init__:177 - Speech processor initialized successfully.
+2026-06-08 17:57:41.737 | DEBUG    | main:speech_to_text:185 - Processing speech-to-text.
+2026-06-08 17:57:42.995 | INFO     | main:speech_to_text:188 - Speech-to-text conversion completed successfully.
+2026-06-08 17:57:44.140 | INFO     | main:__init__:102 - NLP model loaded successfully.
+2026-06-08 17:57:44.140 | DEBUG    | main:generate_text:110 - Generating text for prompt: Hello
+2026-06-08 17:57:45.897 | INFO     | main:generate_text:115 - Generated response: Hello, Hello. Hello, Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello. Hello
+2026-06-08 17:57:47.319 | INFO     | main:__init__:177 - Speech processor initialized successfully.
+2026-06-08 17:57:47.320 | DEBUG    | main:speech_to_text:185 - Processing speech-to-text.
+2026-06-08 17:57:48.447 | INFO     | main:speech_to_text:188 - Speech-to-text conversion completed successfully.
+2026-06-08 17:57:49.793 | INFO     | main:__init__:177 - Speech processor initialized successfully.
+2026-06-08 17:57:49.794 | DEBUG    | main:text_to_speech:205 - Processing text-to-speech.
+2026-06-08 17:57:49.806 | INFO     | main:text_to_speech:208 - Text-to-speech conversion completed successfully.
+2026-06-08 17:57:51.149 | INFO     | main:__init__:177 - Speech processor initialized successfully.
diff --git a/requirements.txt b/requirements.txt
index 5177bb8..c4a281f 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -8,3 +8,7 @@ ultralytics
 pyttsx3
 loguru
 nest_asyncio
+PyJWT
+python-multipart
+pytest
+lxml
diff --git a/test_main_endpoints.py b/test_main_endpoints.py
new file mode 100644
index 0000000..671b74c
--- /dev/null
+++ b/test_main_endpoints.py
@@ -0,0 +1,42 @@
+import pytest
+from fastapi.testclient import TestClient
+from main import app, create_access_token
+import io
+from PIL import Image
+
+client = TestClient(app)
+
+@pytest.fixture
+def auth_header():
+    token = create_access_token({"sub": "testuser"})
+    return {"Authorization": f"Bearer {token}"}
+
+def test_nlp_endpoint(auth_header):
+    response = client.post("/process-nlp/", json={"text": "test"}, headers=auth_header)
+    assert response.status_code == 200
+    data = response.json()
+    assert "response" in data
+    assert "zk_proof" in data
+    assert "cae_metadata" in data
+
+def test_cv_endpoint(auth_header):
+    image = Image.new('RGB', (100, 100), color = 'white')
+    img_byte_arr = io.BytesIO()
+    image.save(img_byte_arr, format='PNG')
+    img_byte_arr.seek(0)
+
+    files = {'file': ('test.png', img_byte_arr, 'image/png')}
+    response = client.post("/process-cv-detection/", files=files, headers=auth_header)
+    assert response.status_code == 200
+    data = response.json()
+    assert "detections" in data
+    assert "cae_metadata" in data
+
+def test_stt_endpoint(auth_header):
+    with open("test.wav", "rb") as f:
+        files = {'file': ('test.wav', f, 'audio/wav')}
+        response = client.post("/speech-to-text/", files=files, headers=auth_header)
+    assert response.status_code == 200
+    data = response.json()
+    assert "response" in data
+    assert "cae_metadata" in data
diff --git a/test_main_pipeline.py b/test_main_pipeline.py
new file mode 100644
index 0000000..79cce42
--- /dev/null
+++ b/test_main_pipeline.py
@@ -0,0 +1,32 @@
+import pytest
+from main import EnhancedAGIPipeline, TextResponse
+from PIL import Image
+import io
+
+@pytest.mark.asyncio
+async def test_pipeline_nlp():
+    pipeline = EnhancedAGIPipeline()
+    result = await pipeline.process_nlp("Hello")
+    assert "response" in result
+    assert "zk_proof" in result
+    assert "cae_metadata" in result
+    assert result["zk_proof"].status == "VERIFIED"
+
+@pytest.mark.asyncio
+async def test_pipeline_cv():
+    pipeline = EnhancedAGIPipeline()
+    image = Image.new('RGB', (100, 100), color = 'white')
+    result = await pipeline.process_cv(image)
+    assert "detections" in result
+    assert "cae_metadata" in result
+
+@pytest.mark.asyncio
+async def test_pipeline_stt():
+    # This requires test.wav to exist from previous steps
+    pipeline = EnhancedAGIPipeline()
+    from fastapi import UploadFile
+    with open("test.wav", "rb") as f:
+        audio_file = UploadFile(filename="test.wav", file=io.BytesIO(f.read()))
+    result = await pipeline.process_speech_to_text(audio_file)
+    assert "response" in result
+    assert "cae_metadata" in result
diff --git a/test_nlp_module.py b/test_nlp_module.py
index 12e2e69..dde059b 100644
--- a/test_nlp_module.py
+++ b/test_nlp_module.py
@@ -1,5 +1,5 @@
 import unittest
-from main import NLPModule
+from main import NLPModule, ZKFairnessProof, ContextualAttributionEnvelope
 
 class TestNLPModule(unittest.TestCase):
     def setUp(self):
diff --git a/test_regulatory.py b/test_regulatory.py
new file mode 100644
index 0000000..34f53df
--- /dev/null
+++ b/test_regulatory.py
@@ -0,0 +1,21 @@
+import unittest
+from main import RegulatoryModule, ZKFairnessProof, ContextualAttributionEnvelope
+
+class TestRegulatoryModule(unittest.TestCase):
+    def setUp(self):
+        self.regulatory = RegulatoryModule()
+
+    def test_verify_zk_fairness(self):
+        result = self.regulatory.verify_zk_fairness("test input")
+        self.assertIsInstance(result, ZKFairnessProof)
+        self.assertEqual(result.status, "VERIFIED")
+        self.assertEqual(result.demographic_parity_score, 0.98)
+
+    def test_generate_cae(self):
+        result = self.regulatory.generate_cae("TestModule", "test output")
+        self.assertIsInstance(result, ContextualAttributionEnvelope)
+        self.assertIn("TestModule", result.contribution_scores)
+        self.assertEqual(result.contribution_scores["TestModule"], 1.0)
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/test_speech_processor.py b/test_speech_processor.py
index de97623..3d513a8 100644
--- a/test_speech_processor.py
+++ b/test_speech_processor.py
@@ -2,14 +2,16 @@
 from io import BytesIO
 from fastapi import UploadFile
 from main import SpeechProcessor
+import os
 
 class TestSpeechProcessor(unittest.TestCase):
     def setUp(self):
         self.speech_processor = SpeechProcessor()
 
     def test_speech_to_text(self):
-        # Create a dummy audio file for testing
-        audio_content = BytesIO(b'Test audio content')
+        # Use a real (valid) dummy wav file
+        with open("test.wav", "rb") as f:
+            audio_content = BytesIO(f.read())
         audio_file = UploadFile(filename="test.wav", file=audio_content)
         result = self.speech_processor.speech_to_text(audio_file)
         self.assertIsNotNone(result)