[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -7,7 +7,7 @@ ci:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v5.0.0
+    rev: v6.0.0
     hooks:
       - id: end-of-file-fixer
         files: (.*\.(py|md|rst|yaml|yml|json|ts|js|html|svelte|sh))$
@@ -26,7 +26,7 @@ repos:
         args: [--fix=lf]
 
   - repo: https://github.com/Lucas-C/pre-commit-hooks
-    rev: v1.5.5
+    rev: v1.5.6
     hooks:
       - id: insert-license
         files: (Dockerfile)$
@@ -74,12 +74,12 @@ repos:
         name: Unused noqa
 
   - repo: https://github.com/pycqa/isort
-    rev: 6.0.1
+    rev: 9.0.0a3
     hooks:
       - id: isort
 
   - repo: https://github.com/PyCQA/docformatter
-    rev: v1.7.7
+    rev: v1.7.8
     hooks:
       - id: docformatter
         args: [
@@ -99,30 +99,30 @@ repos:
         additional_dependencies:
           - prettier@3.2.5
 
-  - repo: https://github.com/psf/black.git
-    rev: 25.1.0
+  - repo: https://github.com/psf/black-pre-commit-mirror
+    rev: 26.5.1
     hooks:
       - id: black
         files: (.*\.py)$
 
   - repo: https://github.com/asottile/blacken-docs
-    rev: 1.19.1
+    rev: 1.20.0
     hooks:
       - id: blacken-docs
         args: [--line-length=120, --skip-errors]
         additional_dependencies:
           - black==24.10.0
 
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.4.1
+    rev: v2.4.2
     hooks:
       - id: codespell
         args: [-w]
         additional_dependencies:
           - tomli
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.12.2
+    rev: v0.15.20
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix, --no-cache]

AvatarChatbot/ui/gradio/app_gradio_demo_avatarchatbot.py

@@ -51,7 +51,7 @@ def base64_to_int16(base64_string):
 
 
 async def transcribe(audio_input, face_input, model_choice):
-    """Input: mic audio; Output: ai audio, text, text"""
+    """Input: mic audio; Output: ai audio, text, text."""
     global ai_chatbot_url, chat_history, count
     chat_history = ""
     # Preprocess the audio
@@ -195,12 +195,11 @@ def initial_process(audio_input, face_input, model_choice):
         gr.Markdown("<h1 style='font-size: 36px;'>A PyTorch and OPEA based AI Avatar Audio Chatbot</h1>")
         with gr.Row():
             with gr.Column(scale=8):
-                gr.Markdown(
-                    """
-                <p style='font-size: 24px;'>Welcome to our AI Avatar Audio Chatbot! This application leverages PyTorch and <strong>OPEA (Open Platform for Enterprise AI) v0.8</strong> to provide you with a human-like conversational experience. It's run on Intel® Gaudi® AI Accelerator and Intel® Xeon® Processor, with hardware and software optimizations.<br>
-                Please feel free to interact with the AI avatar by choosing your own avatar and talking into the mic.</p>
-                            """
-                )
+                gr.Markdown("""<p style='font-size: 24px;'>Welcome to our AI Avatar Audio Chatbot!
+
+                    This application leverages PyTorch and <strong>OPEA (Open Platform for Enterprise AI) v0.8</strong> to provide you with a human-like conversational experience. It's run on Intel® Gaudi® AI Accelerator and Intel® Xeon® Processor, with hardware and software optimizations.<br>
+                    Please feel free to interact with the AI avatar by choosing your own avatar and talking into the mic.</p>
+                    """)
             with gr.Column(scale=1):
                 # with gr.Row():
                 #     gr.Markdown(f"""
@@ -285,45 +284,40 @@ def initial_process(audio_input, face_input, model_choice):
         # Technical details
         gr.Markdown("<hr>")  # Divider
         with gr.Row():
-            gr.Markdown(
-                """
-                <p style='font-size: 24px;'>OPEA megaservice deployed: <br>
+            gr.Markdown("""<p style='font-size: 24px;'>OPEA megaservice deployed: <br>
                 <ul style='font-size: 24px;'>
                     <li><strong>AvatarChatbot</strong></li>
                 </ul></p>
                 <p style='font-size: 24px;'>OPEA microservices deployed:
+
                 <ul style='font-size: 24px;'>
                     <li><strong>ASR</strong> (service: opea/whisper-gaudi, model: openai/whisper-small)</li>
                     <li><strong>LLM 'text-generation'</strong> (service: opea/llm-textgen, model: Intel/neural-chat-7b-v3-3)</li>
                     <li><strong>TTS</strong> (service: opea/speecht5-gaudi, model: microsoft/speecht5_tts)</li>
                     <li><strong>Animation</strong> (service: opea/animation, model: wav2lip+gfpgan)</li>
                 </ul></p>
-                        """
-            )
+                """)
         with gr.Row():
             gr.Image("assets/img/flowchart.png", label="Megaservice Flowchart")
         with gr.Row():
             gr.Markdown(
-                """
-            <p style='font-size: 24px;'>The AI Avatar Audio Chatbot is powered by the following Intel® AI software:<br>
+                """<p style='font-size: 24px;'>The AI Avatar Audio Chatbot is powered by the following Intel® AI software:<br>
                         <ul style='font-size: 24px;'>
                         <li><strong>Intel Gaudi Software v1.17.0</strong></li>
                         <li><strong>PyTorch v2.3.1 (Eager mode + torch.compile) </strong></li>
                         <li><strong>HPU Graph</strong></li>
                         <li><strong>Intel Neural Compressor (INC)</strong></li>
-                        </ul></p>
-                        """
+                        </ul></p>"""
             )
-
         # Disclaimer
         gr.Markdown("<hr>")  # Divider
         gr.Markdown("<h2 style='font-size: 24px;'>Notices & Disclaimers</h1>")
         gr.Markdown(
+            """<p style='font-size: 20px;'>Intel is committed to respecting human rights and avoiding complicity in human rights abuses.
+
+            See Intel's Global Human Rights Principles. Intel's products and software are intended only to be used in applications that do not cause or contribute to a violation of an internationally recognized human right.<br></p> <p style='font-size: 20px;'>© Intel Corporation.  Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries.  Other names and brands may be claimed as the property of others.<br></p>
+            <p style='font-size: 20px;'>You may not use or facilitate the use of this document in connection with any infringement or other legal analysis concerning Intel products described herein. You agree to grant Intel a non-exclusive, royalty-free license to any patent claim thereafter drafted which includes subject matter disclosed herein.<br></p>
             """
-                    <p style='font-size: 20px;'>Intel is committed to respecting human rights and avoiding complicity in human rights abuses. See Intel's Global Human Rights Principles. Intel's products and software are intended only to be used in applications that do not cause or contribute to a violation of an internationally recognized human right.<br></p>
-                    <p style='font-size: 20px;'>© Intel Corporation.  Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries.  Other names and brands may be claimed as the property of others.<br></p>
-                    <p style='font-size: 20px;'>You may not use or facilitate the use of this document in connection with any infringement or other legal analysis concerning Intel products described herein. You agree to grant Intel a non-exclusive, royalty-free license to any patent claim thereafter drafted which includes subject matter disclosed herein.<br></p>
-                    """
         )
 
         # State transitions

ChatQnA/docker_compose/amd/cpu/epyc/milvus.yaml

@@ -424,7 +424,7 @@ dataCoord:
     balanceSilentDuration: 300 # The duration after which the channel manager start background channel balancing
     balanceInterval: 360 # The interval with which the channel manager check dml channel balance status
     checkInterval: 1 # The interval in seconds with which the channel manager advances channel states
-    notifyChannelOperationTimeout: 5 # Timeout notifing channel operations (in seconds).
+    notifyChannelOperationTimeout: 5 # Timeout notifying channel operations (in seconds).
   segment:
     maxSize: 1024 # Maximum size of a segment in MB
     diskSegmentMaxSize: 2048 # Maximum size of a segment in MB for collection which has Disk index

ChatQnA/docker_compose/intel/cpu/xeon/milvus.yaml

@@ -423,7 +423,7 @@ dataCoord:
     balanceSilentDuration: 300 # The duration after which the channel manager start background channel balancing
     balanceInterval: 360 # The interval with which the channel manager check dml channel balance status
     checkInterval: 1 # The interval in seconds with which the channel manager advances channel states
-    notifyChannelOperationTimeout: 5 # Timeout notifing channel operations (in seconds).
+    notifyChannelOperationTimeout: 5 # Timeout notifying channel operations (in seconds).
   segment:
     maxSize: 1024 # Maximum size of a segment in MB
     diskSegmentMaxSize: 2048 # Maximum size of a segment in MB for collection which has Disk index

CodeGen/codegen.py

@@ -59,7 +59,6 @@ def align_inputs(self, inputs, cur_node, runtime_graph, llm_parameters_dict, **k
     Returns:
     - inputs: The aligned inputs for the current node.
     """
-
     # Check if the current service type is EMBEDDING
     if self.services[cur_node].service_type == ServiceType.EMBEDDING:
         # Store the input query for later use
@@ -100,7 +99,6 @@ def __init__(self, host="0.0.0.0", port=8000):
 
     def add_remote_service(self):
         """Adds remote microservices to the service orchestrators and defines the flow between them."""
-
         # Define the embedding microservice
         embedding = MicroService(
             name="embedding",

CogniwareIms/backend/app/main.py

@@ -152,7 +152,6 @@ async def root():
 @app.get("/api/health")
 async def health_check():
     """Comprehensive health check including all OPEA services."""
-
     embedding_health = await embedding_service.health_check()
     retrieval_health = await retrieval_service.health_check()
     llm_health = await llm_service.health_check()

CogniwareIms/backend/app/services/dbqna_service.py

@@ -45,25 +45,21 @@ async def get_schema(self) -> Dict[str, Any]:
             # Get table information
             with engine.connect() as conn:
                 # Get all tables
-                tables_query = text(
-                    """
+                tables_query = text("""
                     SELECT table_name
                     FROM information_schema.tables
                     WHERE table_schema = 'public'
-                """
-                )
+                """)
                 tables = conn.execute(tables_query).fetchall()
 
                 for (table_name,) in tables:
                     # Get columns for each table
-                    columns_query = text(
-                        """
+                    columns_query = text("""
                         SELECT column_name, data_type
                         FROM information_schema.columns
                         WHERE table_name = :table_name
                         ORDER BY ordinal_position
-                    """
-                    )
+                    """)
                     columns = conn.execute(columns_query, {"table_name": table_name}).fetchall()
 
                     schema["tables"][table_name] = {"columns": [{"name": col, "type": dtype} for col, dtype in columns]}
@@ -146,8 +142,7 @@ async def _get_product_inventory(self, sku: str, warehouse: str) -> Dict[str, An
         try:
             engine = self.get_engine()
             with engine.connect() as conn:
-                query = text(
-                    """
+                query = text("""
                     SELECT
                         p.name as product,
                         p.sku,
@@ -159,8 +154,7 @@ async def _get_product_inventory(self, sku: str, warehouse: str) -> Dict[str, An
                     JOIN products p ON i.product_id = p.id
                     JOIN warehouses w ON i.warehouse_id = w.id
                     WHERE p.sku = :sku AND w.name = :warehouse
-                """
-                )
+                """)
 
                 result = conn.execute(query, {"sku": sku, "warehouse": warehouse})
                 row = result.fetchone()

CogniwareIms/backend/app/services/interactive_agent.py

@@ -183,7 +183,6 @@ def _build_chat_messages(
         user_role: str,
     ) -> List[Dict[str, str]]:
         """Build message list for LLM including context and history."""
-
         # System prompt based on user role
         role_prompts = {
             "Consumer": "You are a helpful AI assistant for product research and PC building. Help users find products and make informed decisions.",

CogniwareIms/cogniwareims.py

@@ -32,7 +32,6 @@ def __init__(self, host: str = "0.0.0.0", port: int = 8888):
 
     def add_remote_service(self):
         """Configure and add microservices to the megaservice."""
-
         # LLM Microservice - Text Generation (Intel neural-chat)
         llm_service = MicroService(
             name="llm",

DeepResearchAgent/benchmark/accuracy/eval.py

@@ -253,7 +253,6 @@ def run_benchmark(
     Returns:
         Tuple of (accuracy score, detailed results)
     """
-
     results = []
     total_questions = len(questions)
     details = []
@@ -275,7 +274,6 @@ def run_benchmark(
 
 def main():
     """Main function to run the benchmark."""
-
     # Set up argument parser
     parser = argparse.ArgumentParser(description="Run scoring with benchmarking options")
     parser.add_argument(

DocIndexRetriever/docker_compose/intel/cpu/xeon/config/milvus.yaml

@@ -423,7 +423,7 @@ dataCoord:
     balanceSilentDuration: 300 # The duration after which the channel manager start background channel balancing
     balanceInterval: 360 # The interval with which the channel manager check dml channel balance status
     checkInterval: 1 # The interval in seconds with which the channel manager advances channel states
-    notifyChannelOperationTimeout: 5 # Timeout notifing channel operations (in seconds).
+    notifyChannelOperationTimeout: 5 # Timeout notifying channel operations (in seconds).
   segment:
     maxSize: 1024 # Maximum size of a segment in MB
     diskSegmentMaxSize: 2048 # Maximum size of a segment in MB for collection which has Disk index

DocIndexRetriever/docker_compose/intel/hpu/gaudi/config/milvus.yaml

@@ -423,7 +423,7 @@ dataCoord:
     balanceSilentDuration: 300 # The duration after which the channel manager start background channel balancing
     balanceInterval: 360 # The interval with which the channel manager check dml channel balance status
     checkInterval: 1 # The interval in seconds with which the channel manager advances channel states
-    notifyChannelOperationTimeout: 5 # Timeout notifing channel operations (in seconds).
+    notifyChannelOperationTimeout: 5 # Timeout notifying channel operations (in seconds).
   segment:
     maxSize: 1024 # Maximum size of a segment in MB
     diskSegmentMaxSize: 2048 # Maximum size of a segment in MB for collection which has Disk index

DocSum/ui/gradio/docsum_ui_gradio.py

@@ -44,7 +44,6 @@ def read_url(self, url):
         Returns:
             str: The content of the website or an error message if the url is unsupported.
         """
-
         self.page_content = ""
 
         logger.info(">>> Reading url: %s", url)
@@ -91,7 +90,7 @@ def process_response(self, response):
                         ("\n\ndata: b", ""),
                         ("'\n\n", ""),
                         ("'\n", ""),
-                        ('''\'"''', ""),
+                        ("""\'".""", ""),
                     ]
                     for old, new in replacements:
                         cleaned_text = cleaned_text.replace(old, new)

EdgeCraftRAG/cli/README.md

@@ -329,12 +329,14 @@ The CLI will display error messages from the API in JSON format. Network errors
 ## Tips
 
 - Use `--help` with any command to see detailed help:
+
   ```bash
   ecrag pipeline --help
   ecrag pipeline create --help
   ```
 
 - Pipe JSON output to other tools:
+
   ```bash
   ecrag kb list | jq '.[]' | head -n 20
   ```

EdgeCraftRAG/cli/client.py

@@ -2,17 +2,18 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import json
-import requests
-from typing import Optional, Dict, Any
+from typing import Any, Dict, Optional
 from urllib.parse import urljoin
 
+import requests
+
 
 class EcragApiClient:
     """API client for Edge Craft RAG."""
 
     def __init__(self, host: str = "http://localhost", server_port: int = 16010, mega_port: int = 16011):
         """Initialize the API client.
-        
+
         Args:
             host: The host URL (default: http://localhost)
             server_port: The server port (default: 16010)
@@ -21,10 +22,10 @@ def __init__(self, host: str = "http://localhost", server_port: int = 16010, meg
         # Normalize host URL
         if not host.startswith(("http://", "https://")):
             host = f"http://{host}"
-        
+
         # Remove trailing slash if present
         host = host.rstrip("/")
-        
+
         self.server_url = f"{host}:{server_port}"
         self.mega_url = f"{host}:{mega_port}"
 
@@ -170,12 +171,16 @@ def delete_knowledge_base(self, kb_name: str) -> Dict[str, Any]:
     def add_files_to_kb(self, kb_name: str, local_paths: list) -> Dict[str, Any]:
         """Add files to a knowledge base."""
         url = urljoin(self.server_url, f"/v1/knowledge/{kb_name}/files")
-        return self._request("POST", url, json={"local_paths": local_paths}, headers={"Content-Type": "application/json"})
+        return self._request(
+            "POST", url, json={"local_paths": local_paths}, headers={"Content-Type": "application/json"}
+        )
 
     def delete_files_from_kb(self, kb_name: str, local_paths: list) -> Dict[str, Any]:
         """Delete files from a knowledge base."""
         url = urljoin(self.server_url, f"/v1/knowledge/{kb_name}/files")
-        return self._request("DELETE", url, json={"local_paths": local_paths}, headers={"Content-Type": "application/json"})
+        return self._request(
+            "DELETE", url, json={"local_paths": local_paths}, headers={"Content-Type": "application/json"}
+        )
 
     # Experience Management
     def get_experiences(self) -> Dict[str, Any]: