llama agent created

.gitignore

@@ -8,3 +8,5 @@ wheels/
 
 # Virtual environments
 .venv
+app.copy.py
+app.audio.tool.py

app.py

@@ -1,127 +1,44 @@
 import gradio as gr
-from reports.pdf_report import generate_pdf_report
-from utils.youtube_utils import download_youtube_video
-import modal
-
-verify_faces_remote = modal.Function.lookup("deepface-agent", "verify_faces_remote")
-verify_voices_remote = modal.Function.lookup("deepface-agent", "verify_voices_remote")
-verify_faces_in_video_remote = modal.Function.lookup(
-    "deepface-agent", "verify_faces_in_video_remote"
-)
-
-
-# Holds latest results
-last_face_result = None
-last_voice_result = None
-last_video_results = None
-
-
-def compare_faces(img1_path: str, img2_path: str) -> str:
-    """Use this tool to compare to faces for a match
-    Args:
-        img1_path: The path to the first image
-        img2_path: The path to the second image
-    """
-    global last_face_result
-
-    # Read image files as bytes
-    with open(img1_path, "rb") as f1, open(img2_path, "rb") as f2:
-        img1_bytes = f1.read()
-        img2_bytes = f2.read()
-
-    result = verify_faces_remote.remote(img1_bytes, img2_bytes)
-    result_text = ""
-
-    if "error" in result:
-        return f"❌ Error: {result['error']}"
-
-    if result["verified"]:
-        result_text = f"✅ Match! Distance: {result['distance']:.4f} (Threshold: {result['threshold']})"
-        last_face_result = result_text
-        return result_text
-
-    else:
-        result_text = f"❌ No Match. Distance: {result['distance']:.4f} (Threshold: {result['threshold']})"
-        last_face_result = result_text
-        return result_text
-
-
-def compare_voices(audio1: str, audio2: str) -> str:
-    """Use this tool to compare two voices for a match
-    Args:
-        audio1: The path to the first audio file
-        audio2: The path to the second audio file
-    """
-    global last_voice_result
-
-    try:
-        with open(audio1, "rb") as a1, open(audio2, "rb") as a2:
-            audio1_bytes = a1.read()
-            audio2_bytes = a2.read()
-
-        result = verify_voices_remote.remote(audio1_bytes, audio2_bytes)
-        result_text = ""
-
-        if "error" in result:
-            return f"❌ Error: {result['error']}"
-
-        if result["match"]:
-            result_text = f"✅ Same speaker detected. Similarity: {result['similarity']} (Threshold: {result['threshold']})"
-            last_voice_result = result_text
-            return result_text
-        else:
-            result_text = f"❌ Different speakers. Similarity: {result['similarity']} (Threshold: {result['threshold']})"
-            last_voice_result = result_text
-            return result_text
-    except Exception as e:
-        return f"❌ Error reading audio files: {str(e)}"
-
-
-def scan_video(video_file: str, ref_img: str, youtube_url="") -> str:
-    """Use this tool to scan a video for deepfake face swaps
-    Args:
-        video_file: The path to the video file
-        ref_img: The path to the reference image
-        youtube_url: The YouTube URL (optional)
-    """
-    global last_video_results
-
-    if youtube_url:
-        try:
-            video_file = download_youtube_video(youtube_url)
-        except Exception as e:
-            return f"❌ Error downloading YouTube video: {str(e)}"
-
-    with open(video_file, "rb") as vf, open(ref_img, "rb") as rf:
-        video_bytes = vf.read()
-        ref_img_bytes = rf.read()
-    try:
-        results = verify_faces_in_video_remote.remote(video_bytes, ref_img_bytes, interval=30)
-        
-    except Exception as e:
-        return f"❌ Error processing  video: {str(e)}"
-
-    report = ""
-    last_video_results = results
-    for r in results:
-        if "error" in r:
-            report += f"\n⚠️ Frame {r['frame']}: {r['error']}"
-
-        else:
-            status = "✅ Match" if r["verified"] else "❌ Mismatch"
-            report += f"\n🖼 Frame {r['frame']}: {status} (Distance: {r['distance']})"
-
-    return report
-
-
-def generate_report():
-    return generate_pdf_report(last_face_result, last_voice_result, last_video_results)
-
+from tools import compare_faces, compare_voices, scan_video, generate_report
+from llama_agent import chat_with_agent
 
 with gr.Blocks(title="Deepfake Watchdog") as demo:
     gr.Markdown("# 🛡️Deepfake Watchdog 🤗")
     gr.Markdown("## Upload your image and/or voice to scan for deepfake misuse online.")
 
+    # Chat
+    with gr.Tab("🤖 Chat with Agent"):
+        gr.Markdown(
+            "Chat with the AI agent. Ask it to compare faces, voices, or scan videos naturally."
+        )
+        user_prompt = gr.Textbox(label="Prompt", lines=3)
+        gr.Markdown("### Example Prompts:")
+        gr.Markdown("##### Compare the two uploaded faces and tell me if they match")
+        gr.Markdown("##### Check if the two voices are from the same speaker")
+        gr.Markdown(
+            "##### Scan a video for a provided reference image to check for deepfakes"
+        )
+
+        with gr.Row():
+            img1 = gr.Image(type="filepath", label="Image 1")
+            img2 = gr.Image(type="filepath", label="Image 2")
+
+        with gr.Row():
+            audio1 = gr.Audio(type="filepath", label="Audio 1")
+            audio2 = gr.Audio(type="filepath", label="Audio 2")
+
+        ref_img = gr.Image(type="filepath", label="Reference Image")
+        video = gr.Video(label="Video file")
+
+        chat_btn = gr.Button("Chat")
+        chat_output = gr.Textbox(label="Chat Output", lines=10)
+
+        chat_btn.click(
+            chat_with_agent,
+            inputs=[user_prompt, img1, img2, audio1, audio2, video, ref_img],
+            outputs=[chat_output],
+        )
+
     # Face Verification
     with gr.Tab("Face Verification"):
         image1 = gr.Image(label="Upload your face", type="filepath")

pyproject.toml

@@ -5,9 +5,12 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.12"
 dependencies = [
+    "anthropic>=0.53.0",
     "deepface>=0.0.93",
     "fpdf>=1.7.2",
     "gradio[mcp]>=5.32.1",
+    "llama-index>=0.12.41",
+    "llama-index-llms-anthropic>=0.7.2",
     "modal>=1.0.3",
     "opencv-python-headless>=4.11.0.86",
     "pydub>=0.25.1",

reports/pdf_report.py

@@ -0,0 +1,83 @@
+from fpdf import FPDF
+import os
+import datetime
+
+
+class ReportGenerator(FPDF):
+    def header(self):
+        self.set_font("Arial", "B", 16)
+        self.cell(0, 10, "Deepfake Watchdog Report", ln=1, align="C")
+        self.ln(5)
+
+    def add_section_title(self, title):
+        self.set_font("Arial", "B", 12)
+        self.cell(0, 10, title, ln=1, align="L")
+        self.ln(2)
+
+    def add_text(self, text):
+        self.set_font("Arial", "", 12)
+        safe_text = str(text) if text is not None else ""
+        self.multi_cell(0, 8, safe_text)
+        self.ln(2)
+
+    def add_image(self, image_path, w=60):
+        if os.path.exists(image_path):
+            self.image(image_path, w=w)
+            self.ln(5)
+        else:
+            print(f"Image not found: {image_path}")
+
+
+# Replace emojis with text equivalents
+def clean_text(text):
+    return (
+        text.replace("✅", "[MATCH]")
+        .replace("❌", "[NO MATCH]")
+        .replace("⚠️", "[WARNING]")
+    )
+
+
+# Generate PDF Report
+def generate_pdf_report(
+    face_result,
+    voice_result,
+    video_results,
+    output_path=f"report{datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}.pdf",
+):
+    pdf = ReportGenerator()
+    pdf.add_page()
+
+    print("Generating PDF report...")
+    print(face_result)
+    print(voice_result)
+    print(video_results)
+    
+    # Section 1: Face Verification
+    if face_result:
+        pdf.add_section_title("Face Verification Results")
+        pdf.add_text(clean_text(face_result))
+
+    # Section 2: Voice Verification
+    if voice_result:
+        pdf.add_section_title("Voice Verification Results")
+        pdf.add_text(clean_text(voice_result))
+
+    # Section 3: Video Verification
+    if video_results:
+        pdf.add_section_title("Video Verification Results")
+
+        for frame in video_results:
+            if "error" in frame:
+                pdf.add_text(clean_text(f"{frame['frame']}: ERROR - {frame['error']}"))
+            else:
+                status = "✅ Match" if frame["verified"] else "❌ Mismatch"
+                pdf.add_text(
+                    clean_text(f"{frame['frame']} - {status} (Distance: {frame['distance']})")
+                )
+
+                if not frame["verified"]:
+                    pdf.add_image(frame["frame"], w=80)
+
+    pdf.output(output_path)
+    print(f"PDF report generated at: {output_path}")
+    return output_path

tools.py

@@ -0,0 +1,116 @@
+import modal
+from utils.youtube_utils import download_youtube_video
+from reports.pdf_report import generate_pdf_report
+
+last_face_result = ""
+last_voice_result = ""
+last_video_results = []
+
+verify_faces_remote = modal.Function.lookup("deepface-agent", "verify_faces_remote")
+verify_voices_remote = modal.Function.lookup("deepface-agent", "verify_voices_remote")
+verify_faces_in_video_remote = modal.Function.lookup(
+    "deepface-agent", "verify_faces_in_video_remote"
+)
+
+
+def compare_faces(img1_path: str, img2_path: str) -> str:
+    """Use this tool to compare to faces for a match
+    Args:
+        img1_path: The path to the first image
+        img2_path: The path to the second image
+    """
+    global last_face_result
+
+    # Read image files as bytes
+    with open(img1_path, "rb") as f1, open(img2_path, "rb") as f2:
+        img1_bytes = f1.read()
+        img2_bytes = f2.read()
+
+    result = verify_faces_remote.remote(img1_bytes, img2_bytes)
+    result_text = ""
+
+    if "error" in result:
+        return f"❌ Error: {result['error']}"
+
+    if result["verified"]:
+        result_text = f"✅ Match! Distance: {result['distance']:.4f} (Threshold: {result['threshold']})"
+        last_face_result = result_text
+        return result_text
+
+    else:
+        result_text = f"❌ No Match. Distance: {result['distance']:.4f} (Threshold: {result['threshold']})"
+        last_face_result = result_text
+        return result_text
+
+
+def compare_voices(audio1: str, audio2: str) -> str:
+    """Use this tool to compare two voices for a match
+    Args:
+        audio1: The path to the first audio file
+        audio2: The path to the second audio file
+    """
+    global last_voice_result
+
+    try:
+        with open(audio1, "rb") as a1, open(audio2, "rb") as a2:
+            audio1_bytes = a1.read()
+            audio2_bytes = a2.read()
+
+        result = verify_voices_remote.remote(audio1_bytes, audio2_bytes)
+        result_text = ""
+
+        if "error" in result:
+            return f"❌ Error: {result['error']}"
+
+        if result["match"]:
+            result_text = f"✅ Same speaker detected. Similarity: {result['similarity']} (Threshold: {result['threshold']})"
+            last_voice_result = result_text
+            return result_text
+        else:
+            result_text = f"❌ Different speakers. Similarity: {result['similarity']} (Threshold: {result['threshold']})"
+            last_voice_result = result_text
+            return result_text
+    except Exception as e:
+        return f"❌ Error reading audio files: {str(e)}"
+
+
+def scan_video(video_file: str, ref_img: str, youtube_url="") -> str:
+    """Use this tool to scan a video for deepfake face swaps
+    Args:
+        video_file: The path to the video file
+        ref_img: The path to the reference image
+        youtube_url: The YouTube URL (optional)
+    """
+    global last_video_results
+
+    if youtube_url:
+        try:
+            video_file = download_youtube_video(youtube_url)
+        except Exception as e:
+            return f"❌ Error downloading YouTube video: {str(e)}"
+
+    with open(video_file, "rb") as vf, open(ref_img, "rb") as rf:
+        video_bytes = vf.read()
+        ref_img_bytes = rf.read()
+    try:
+        results = verify_faces_in_video_remote.remote(video_bytes, ref_img_bytes, interval=30)
+        
+    except Exception as e:
+        return f"❌ Error processing  video: {str(e)}"
+
+    report = ""
+    last_video_results = results
+    for r in results:
+        if "error" in r:
+            report += f"\n⚠️ Frame {r['frame']}: {r['error']}"
+
+        else:
+            status = "✅ Match" if r["verified"] else "❌ Mismatch"
+            report += f"\n🖼 Frame {r['frame']}: {status} (Distance: {r['distance']})"
+
+    return report
+    
+    
+
+def generate_report():
+    return generate_pdf_report(last_face_result, last_voice_result, last_video_results)

uv.lock

@@ -100,6 +100,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/ec/6a/bc7e17a3e87a2985d3e8f4da4cd0f481060eb78fb08596c42be62c90a4d9/aiosignal-1.3.2-py2.py3-none-any.whl", hash = "sha256:45cde58e409a301715980c2b01d0c28bdde3770d8290b5eb2173759d9acb31a5", size = 7597, upload-time = "2024-12-13T17:10:38.469Z" },
 ]
 
+[[package]]
+name = "aiosqlite"
+version = "0.21.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/13/7d/8bca2bf9a247c2c5dfeec1d7a5f40db6518f88d314b8bca9da29670d2671/aiosqlite-0.21.0.tar.gz", hash = "sha256:131bb8056daa3bc875608c631c678cda73922a2d4ba8aec373b19f18c17e7aa3", size = 13454, upload-time = "2025-02-03T07:30:16.235Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/f5/10/6c25ed6de94c49f88a91fa5018cb4c0f3625f31d5be9f771ebe5cc7cd506/aiosqlite-0.21.0-py3-none-any.whl", hash = "sha256:2549cf4057f95f53dcba16f2b64e8e2791d7e1adedb13197dd8ed77bb226d7d0", size = 15792, upload-time = "2025-02-03T07:30:13.6Z" },
+]
+
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -109,6 +121,33 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
+[[package]]
+name = "anthropic"
+version = "0.53.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "httpx" },
+    { name = "jiter" },
+    { name = "pydantic" },
+    { name = "sniffio" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c1/f6/a78ff9e23981fde136c3ae5427a39b27df92ebe5e5997c6203796449f1e5/anthropic-0.53.0.tar.gz", hash = "sha256:f5d1499fc45b2e05801fcbbeae25679f72f7479763e3c706126a7a7c8de06eff", size = 307716, upload-time = "2025-06-09T16:20:31.689Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a9/3f/82c21f74afa3541d69d20b8265c7fdfd078a687e9eea48fda30f1838d0b7/anthropic-0.53.0-py3-none-any.whl", hash = "sha256:b3a84751885a81d96bbddef180c3ce559c9140f7f230cdd825385405bd6d312e", size = 287248, upload-time = "2025-06-09T16:20:29.98Z" },
+]
+
+[package.optional-dependencies]
+bedrock = [
+    { name = "boto3" },
+    { name = "botocore" },
+]
+vertex = [
+    { name = "google-auth", extra = ["requests"] },
+]
+
 [[package]]
 name = "anyio"
 version = "4.9.0"
@@ -194,6 +233,22 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/57/8d/30aa32745af16af0a9a650115fbe81bde7c610ed5c21b381fca0196f3a7f/audioread-3.0.1-py3-none-any.whl", hash = "sha256:4cdce70b8adc0da0a3c9e0d85fb10b3ace30fbdf8d1670fd443929b61d117c33", size = 23492, upload-time = "2023-09-27T19:27:51.334Z" },
 ]
 
+[[package]]
+name = "banks"
+version = "2.1.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "deprecated" },
+    { name = "griffe" },
+    { name = "jinja2" },
+    { name = "platformdirs" },
+    { name = "pydantic" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/77/34/2b6697f02ffb68bee50e5fd37d6c64432244d3245603fd62950169dfed7e/banks-2.1.2.tar.gz", hash = "sha256:a0651db9d14b57fa2e115e78f68dbb1b36fe226ad6eef96192542908b1d20c1f", size = 173332, upload-time = "2025-04-20T07:09:21.674Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/04/4a/7fdca29d1db62f5f5c3446bf8f668beacdb0b5a8aff4247574ddfddc6bcd/banks-2.1.2-py3-none-any.whl", hash = "sha256:7fba451069f6bea376483b8136a0f29cb1e6883133626d00e077e20a3d102c0e", size = 28064, upload-time = "2025-04-20T07:09:20.201Z" },
+]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.13.4"
@@ -216,6 +271,43 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl", hash = "sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc", size = 8458, upload-time = "2024-11-08T17:25:46.184Z" },
 ]
 
+[[package]]
+name = "boto3"
+version = "1.38.33"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "botocore" },
+    { name = "jmespath" },
+    { name = "s3transfer" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ad/95/99046c55799732d97b0f9a0bb99b64760f07dd55ac793393a6c4e847d8d6/boto3-1.38.33.tar.gz", hash = "sha256:6467909c1ae01ff67981f021bb2568592211765ec8a9a1d2c4529191e46c3541", size = 111825, upload-time = "2025-06-09T19:24:16.167Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/96/7e/b3eb354e82f5a2a8ae1977f983f0cb6005b2e5fae79b7d06bd5a14b4e9c6/boto3-1.38.33-py3-none-any.whl", hash = "sha256:25d0717489c658f7ae6c3c7f0f7e1b4d611b30b2f08f0fcef6455ac6864a8768", size = 139937, upload-time = "2025-06-09T19:24:12.774Z" },
+]
+
+[[package]]
+name = "botocore"
+version = "1.38.33"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jmespath" },
+    { name = "python-dateutil" },
+    { name = "urllib3" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/9d/aa/1521d7e1dcb76af8dca81539eec141ee3581a32e0dc1f31d092b59feb06a/botocore-1.38.33.tar.gz", hash = "sha256:dbe8fea9d0426c644c89ef2018ead886ccbcc22901a02b377b4e65ce1cb69a2b", size = 13953431, upload-time = "2025-06-09T19:24:03.916Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c1/5a/253b707c29283a5d8516448da4febe017bcec0b7ed109981250d1b5f5347/botocore-1.38.33-py3-none-any.whl", hash = "sha256:ad25233e93dcebe95809b1f9393c1f11a639696327793d166295fb78dd7bc597", size = 13614262, upload-time = "2025-06-09T19:24:00.393Z" },
+]
+
+[[package]]
+name = "cachetools"
+version = "5.5.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/6c/81/3747dad6b14fa2cf53fcf10548cf5aea6913e96fab41a3c198676f8948a5/cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4", size = 28380, upload-time = "2025-02-20T21:01:19.524Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/72/76/20fa66124dbe6be5cafeb312ece67de6b61dd91a0247d1ea13db4ebb33c2/cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a", size = 10080, upload-time = "2025-02-20T21:01:16.647Z" },
+]
+
 [[package]]
 name = "certifi"
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