Lint & format

Author: freddiev4

examples/log-and-detect/example_fast_api/main.py

@@ -5,8 +5,8 @@
 # Configure logging
 logging.basicConfig(
     level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-    handlers=[logging.StreamHandler()]
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+    handlers=[logging.StreamHandler()],
 )
 
 app = FastAPI()

examples/tracing/quotient_trace_agno_agent.py

@@ -15,19 +15,21 @@
     instruments=[AgnoInstrumentor()],
 )
 
-@quotient.trace('agno-agent-ddgs-search')
+
+@quotient.trace("agno-agent-ddgs-search")
 def run_agno():
     # add additional span attributes
     span = get_current_span()
     span.set_attribute("mycustom.attr", "customvalue")
 
     agent = Agent(
-        model=OpenAIChat(id="gpt-4o-mini"), 
+        model=OpenAIChat(id="gpt-4o-mini"),
         tools=[DuckDuckGoTools()],
-        markdown=True, 
+        markdown=True,
     )
 
     agent.print_response("What is currently trending on Twitter?")
 
+
 if __name__ == "__main__":
     run_agno()

examples/tracing/quotient_trace_chroma.py

@@ -4,6 +4,7 @@
 This example shows how to use the ChromaInstrumentor to automatically
 trace ChromaDB operations with OpenTelemetry semantic conventions.
 """
+
 import chromadb
 
 from quotientai import QuotientAI
@@ -24,67 +25,71 @@
 # Alternative: Manual instrumentation after initialization
 # quotient.tracer.instrument_vector_dbs("chroma")
 
+
 @quotient.trace()
 def run_chroma():
     """Demonstrate ChromaDB operations with tracing."""
     with start_span("chroma_demo"):
-        try:            
+        try:
             # Create client
             client = chromadb.Client()
-            
+
             # Create collection
             collection = client.create_collection(name="test_collection")
-            
+
             # Add documents
             collection.add(
                 documents=["This is a test document", "Another test document"],
                 metadatas=[{"source": "test"}, {"source": "test"}],
-                ids=["id1", "id2"]
+                ids=["id1", "id2"],
             )
-            
+
             # Query documents
             results = collection.query(
                 query_texts=["test document"],
                 n_results=2,
-                include=["metadatas", "documents", "distances"]
+                include=["metadatas", "documents", "distances"],
             )
-            
+
             print(f"ChromaDB query results: {results}")
-            
+
             # Update documents
             collection.update(
                 ids=["id1"],
                 documents=["Updated test document"],
-                metadatas=[{"source": "updated"}]
+                metadatas=[{"source": "updated"}],
             )
-            
+
             # Delete documents
             collection.delete(ids=["id2"])
-            
+
             # Get collection info
             collection_info = collection.get()
             print(f"Collection info: {collection_info}")
-            
+
         except ImportError:
             print("ChromaDB not installed. Install with: pip install chromadb")
         except Exception as e:
             print(f"Error in ChromaDB demo: {e}")
 
+
 if __name__ == "__main__":
     print("Starting ChromaDB Tracing Demo...")
     print("=" * 50)
-    
+
     # Run demonstrations
     run_chroma()
-    
+
     # Force flush to ensure spans are sent immediately
     quotient.tracer.force_flush()
-    
+
     print("=" * 50)
     print("ChromaDB demo completed! Check your tracing dashboard for spans.")
     print("\nChromaDB spans will include these semantic conventions:")
     print("- db.system.name: 'chroma'")
-    print("- db.operation: 'create_collection', 'add', 'query', 'update', 'delete', 'get'")
+    print(
+        "- db.operation: 'create_collection', 'add', 'query', 'update', 'delete', 'get'"
+    )
     print("- db.collection.name: collection name")
     print("- db.ids_count: number of IDs processed")
     print("- db.vector_count: number of vectors processed")

examples/tracing/quotient_trace_openai.py

@@ -11,6 +11,7 @@
     instruments=[OpenAIInstrumentor()],
 )
 
+
 @quotient.trace()
 def test_openai():
     client = openai.OpenAI()
@@ -23,8 +24,9 @@ def test_openai():
     )
 
     for chunk in response:
-            if chunk.choices and (content := chunk.choices[0].delta.content):
-                print(content, end="")
+        if chunk.choices and (content := chunk.choices[0].delta.content):
+            print(content, end="")
+
 
 if __name__ == "__main__":
-    test_openai()
+    test_openai()

examples/tracing/quotient_trace_pinecone.py

@@ -4,6 +4,7 @@
 This example shows how to use the PineconeInstrumentor to automatically
 trace Pinecone operations with OpenTelemetry semantic conventions.
 """
+
 import os
 
 from pinecone import Pinecone, ServerlessSpec
@@ -26,77 +27,70 @@
 # Alternative: Manual instrumentation after initialization
 # quotient.tracer.instrument_vector_dbs("pinecone")
 
+
 @quotient.trace()
 def demonstrate_pinecone_operations():
     """Demonstrate Pinecone operations with tracing."""
     with start_span("pinecone_demo"):
-        try:            
+        try:
             # Check for API key
             api_key = os.environ.get("PINECONE_API_KEY")
-            
+
             if not api_key:
                 print("Pinecone API key not set.")
                 print("Set PINECONE_API_KEY environment variable.")
                 print("You can get this from https://app.pinecone.io/")
                 return
-            
+
             pc = Pinecone(api_key=api_key)
-            
+
             # List existing indexes
             indexes = pc.list_indexes()
             print(f"Existing indexes: {indexes}")
-            
+
             # Create index (if it doesn't exist)
             index_name = "test-index"
             if index_name not in indexes:
-                spec = ServerlessSpec(
-                    cloud="aws",
-                    region="us-east-1"
-                )
+                spec = ServerlessSpec(cloud="aws", region="us-east-1")
                 pc.create_index(
                     name=index_name,
                     spec=spec,
                     dimension=128,
                     metric="cosine",
                 )
                 print(f"Created index: {index_name}")
-            
+
             # Get index
             index = pc.Index(index_name)
-            
+
             # Upsert vectors
             vectors = [
                 ("id1", [0.1] * 128, {"source": "test", "category": "demo"}),
                 ("id2", [0.2] * 128, {"source": "test", "category": "demo"}),
-                ("id3", [0.3] * 128, {"source": "test", "category": "demo"})
+                ("id3", [0.3] * 128, {"source": "test", "category": "demo"}),
             ]
             index.upsert(vectors=vectors)
             print("Upserted vectors")
-            
+
             # Query vectors
             query_vector = [0.1] * 128
-            results = index.query(
-                vector=query_vector,
-                top_k=3,
-                include_metadata=True
-            )
+            results = index.query(vector=query_vector, top_k=3, include_metadata=True)
             print(f"Query results: {results}")
-            
+
             # Fetch specific vectors
             fetch_results = index.fetch(ids=["id1", "id2"])
             print(f"Fetch results: {fetch_results}")
-            
+
             # Update metadata
             index.update(
-                id="id1",
-                set_metadata={"source": "updated", "category": "modified"}
+                id="id1", set_metadata={"source": "updated", "category": "modified"}
             )
             print("Updated metadata")
-            
+
             # Delete vectors
             index.delete(ids=["id3"])
             print("Deleted vector id3")
-            
+
         except ImportError:
             print("Pinecone not installed. Install with: pip install pinecone")
         except Exception as e:
@@ -107,15 +101,17 @@ def demonstrate_pinecone_operations():
 if __name__ == "__main__":
     print("Starting Pinecone Tracing Demo...")
     print("=" * 50)
-    
+
     # Run demonstrations
     demonstrate_pinecone_operations()
-    
+
     print("=" * 50)
     print("Pinecone demo completed! Check your tracing dashboard for spans.")
     print("\nPinecone spans will include these semantic conventions:")
     print("- db.system.name: 'pinecone'")
-    print("- db.operation: 'create_index', 'upsert', 'query', 'fetch', 'update', 'delete', 'describe_index_stats'")
+    print(
+        "- db.operation: 'create_index', 'upsert', 'query', 'fetch', 'update', 'delete', 'describe_index_stats'"
+    )
     print("- db.collection.name: index name")
     print("- db.ids_count: number of IDs processed")
     print("- db.vector_count: number of vectors processed")