Bump version

Author: karthikscale3

pyproject.toml

@@ -18,7 +18,7 @@ classifiers=[
     "Operating System :: OS Independent",
 ]
 dependencies = [
-  'trace-attributes>=6.0.0,<7.0.0',
+  'trace-attributes>=6.0.3,<7.0.0',
   'opentelemetry-api>=1.25.0',
   'opentelemetry-sdk>=1.25.0',
   'opentelemetry-instrumentation>=0.46b0',

src/examples/dspy_example/math_problems_cot_parallel.py

@@ -5,7 +5,7 @@
 from concurrent.futures import ThreadPoolExecutor
 
 # flake8: noqa
-from langtrace_python_sdk import langtrace, with_langtrace_root_span
+from langtrace_python_sdk import langtrace, with_langtrace_root_span, inject_additional_attributes
 
 langtrace.init()
 

src/examples/inspect_ai_example/basic_eval.py

@@ -1,24 +1,32 @@
-# langtrace.init(write_spans_to_console=True)
 import fsspec
 from inspect_ai import Task, task
-from inspect_ai.dataset import csv_dataset
+from inspect_ai.dataset import csv_dataset, Sample
 from inspect_ai.scorer import model_graded_qa
-from inspect_ai.solver import chain_of_thought, generate, self_critique
-
+from inspect_ai.solver import chain_of_thought, self_critique
 from langtrace_python_sdk.extensions.langtrace_filesystem import LangTraceFileSystem
 
-# from langtrace_python_sdk import langtrace
-
 
 # Manually register the filesystem with fsspec
 # Note: This is only necessary because the filesystem is not registered.
 fsspec.register_implementation(LangTraceFileSystem.protocol, LangTraceFileSystem)
 
+question = "What is the price?"
+
+
+def hydrate_with_question(record):
+    # add context to input
+    record["input"] = f"Context: {record['input']}\n question: {question}"
+
+    return Sample(
+        input=record["input"],
+        target=record["target"],
+    )
+
 
 @task
-def security_guide():
+def pricing_question():
     return Task(
-        dataset=csv_dataset("langtracefs://clxc2mxu6000lpc7ntsvcjvp9"),
+        dataset=csv_dataset("langtracefs://clyythmcs0001145cuvi426zi", hydrate_with_question),
         plan=[chain_of_thought(), self_critique()],
         scorer=model_graded_qa(),
     )

src/examples/ollama_example/basic_example_2.py

@@ -0,0 +1,34 @@
+from langtrace_python_sdk import langtrace
+from openai import OpenAI
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+
+service_name = "langtrace-python-ollama"
+otlp_endpoint = "http://localhost:4318/v1/traces"
+otlp_exporter = OTLPSpanExporter(
+    endpoint=otlp_endpoint,
+    headers=(("Content-Type", "application/json"),))
+langtrace.init(custom_remote_exporter=otlp_exporter, batch=False)
+
+
+def chat_with_ollama():
+    # Use the OpenAI endpoint, not the Ollama API.
+    base_url = "http://localhost:11434/v1"
+    client = OpenAI(base_url=base_url, api_key="unused")
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, I'm a human.",
+        },
+    ]
+    chat_completion = client.chat.completions.create(
+        model="llama3", messages=messages
+    )
+    print(chat_completion.choices[0].message.content)
+
+
+def main():
+    chat_with_ollama()
+
+
+if __name__ == "__main__":
+    main()

src/examples/otlp_example/otlp_basic.py

@@ -0,0 +1,43 @@
+# Instructions
+# 1. Run the OpenTelemetry Collector with the OTLP receiver enabled
+# Create otel-config.yaml with the following content:
+# receivers:
+#   otlp:
+#     protocols:
+#       grpc:
+#         endpoint: "0.0.0.0:4317"
+#       http:
+#         endpoint: "0.0.0.0:4318"
+
+# exporters:
+#   logging:
+#     loglevel: debug
+
+# service:
+#   pipelines:
+#     traces:
+#       receivers: [otlp]
+#       exporters: [logging]
+# docker pull otel/opentelemetry-collector:latest
+# docker run --rm -p 4317:4317 -p 4318:4318 -v $(pwd)/otel-config.yaml:/otel-config.yaml otel/opentelemetry-collector --config otel-config.yaml
+# 2. Run the following code
+
+from opentelemetry import trace
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.sdk.trace.export import BatchSpanProcessor
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
+
+# Set up the tracer provider
+trace.set_tracer_provider(TracerProvider())
+tracer = trace.get_tracer(__name__)
+
+# Set up the OTLP exporter
+otlp_exporter = OTLPSpanExporter(endpoint="http://localhost:4317")
+
+# Set up a span processor and add it to the tracer provider
+span_processor = BatchSpanProcessor(otlp_exporter)
+trace.get_tracer_provider().add_span_processor(span_processor)
+
+# Create a span
+with tracer.start_as_current_span("example-span"):
+    print("Hello, World!")

src/langtrace_python_sdk/instrumentation/groq/patch.py

@@ -104,10 +104,10 @@ def traced_method(wrapped, instance, args, kwargs):
 
         # TODO(Karthik): Gotta figure out how to handle streaming with context
         # with tracer.start_as_current_span(APIS["CHAT_COMPLETION"]["METHOD"],
-        #                                   kind=SpanKind.CLIENT.value) as span:
+        #                                   kind=SpanKind.CLIENT) as span:
         span = tracer.start_span(
             APIS["CHAT_COMPLETION"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         )
         for field, value in attributes.model_dump(by_alias=True).items():
@@ -333,9 +333,9 @@ async def traced_method(wrapped, instance, args, kwargs):
 
         # TODO(Karthik): Gotta figure out how to handle streaming with context
         # with tracer.start_as_current_span(APIS["CHAT_COMPLETION"]["METHOD"],
-        #                                   kind=SpanKind.CLIENT.value) as span:
+        #                                   kind=SpanKind.CLIENT) as span:
         span = tracer.start_span(
-            APIS["CHAT_COMPLETION"]["METHOD"], kind=SpanKind.CLIENT.value
+            APIS["CHAT_COMPLETION"]["METHOD"], kind=SpanKind.CLIENT
         )
         for field, value in attributes.model_dump(by_alias=True).items():
             set_span_attribute(span, field, value)

src/langtrace_python_sdk/instrumentation/openai/patch.py

@@ -65,7 +65,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         with tracer.start_as_current_span(
             APIS["IMAGES_GENERATION"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
             set_span_attributes(span, attributes)
@@ -128,7 +128,7 @@ async def traced_method(wrapped, instance, args, kwargs):
 
         with tracer.start_as_current_span(
             APIS["IMAGES_GENERATION"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
             set_span_attributes(span, attributes)
@@ -193,7 +193,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         with tracer.start_as_current_span(
             APIS["IMAGES_EDIT"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
             set_span_attributes(span, attributes)
@@ -283,7 +283,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         span = tracer.start_span(
             APIS["CHAT_COMPLETION"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         )
         _set_input_attributes(span, kwargs, attributes)
@@ -377,7 +377,7 @@ async def traced_method(wrapped, instance, args, kwargs):
 
         span = tracer.start_span(
             APIS["CHAT_COMPLETION"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         )
         _set_input_attributes(span, kwargs, attributes)
@@ -456,7 +456,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         with tracer.start_as_current_span(
             APIS["EMBEDDINGS_CREATE"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
 
@@ -513,7 +513,7 @@ async def traced_method(wrapped, instance, args, kwargs):
 
         with tracer.start_as_current_span(
             APIS["EMBEDDINGS_CREATE"]["METHOD"],
-            kind=SpanKind.CLIENT.value,
+            kind=SpanKind.CLIENT,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
 

src/langtrace_python_sdk/version.py

@@ -1 +1 @@
-__version__ = "2.2.4"
+__version__ = "2.2.5"