Release 2.2.7 (#260)

* Add OTLP example (#259)

* Adhere to otel span attributes (#257)

* adhere to otel's semconv

* lock attributes version

* lock to 7.0.0 trace attributes

* bump version

---------

Co-authored-by: Karthik Kalyanaraman <[email protected]>

---------

Co-authored-by: Ali Waleed <[email protected]>

Author: karthikscale3

pyproject.toml

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

src/examples/ollama_example/basic_example_2.py

@@ -0,0 +1,59 @@
+# 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 langtrace_python_sdk import langtrace
+from openai import OpenAI
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+
+
+# Configure the OTLP exporter to use the correct endpoint and API key
+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_openai():
+    client = OpenAI()
+    messages = [
+        {
+            "role": "user",
+            "content": "Hello, I'm a human.",
+        },
+    ]
+    chat_completion = client.chat.completions.create(
+        messages=messages,
+        stream=False,
+        model="gpt-3.5-turbo",
+    )
+    print(chat_completion.choices[0].message.content)
+
+
+def main():
+    chat_with_openai()
+
+
+if __name__ == "__main__":
+    main()

src/examples/otlp_example/otlp_with_langtrace.py

@@ -44,7 +44,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         span_attributes = {
             **get_langtrace_attributes(version, service_provider),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, operation_name="rerank"),
             **get_llm_url(instance),
             SpanAttributes.LLM_REQUEST_MODEL: kwargs.get("model") or "command-r-plus",
             SpanAttributes.LLM_URL: APIS["RERANK"]["URL"],
@@ -121,7 +121,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         span_attributes = {
             **get_langtrace_attributes(version, service_provider),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, operation_name="embed"),
             **get_llm_url(instance),
             SpanAttributes.LLM_URL: APIS["EMBED"]["URL"],
             SpanAttributes.LLM_PATH: APIS["EMBED"]["ENDPOINT"],

src/langtrace_python_sdk/instrumentation/cohere/patch.py

@@ -55,7 +55,7 @@ def traced_method(wrapped, instance, args, kwargs):
         service_provider = SERVICE_PROVIDERS["OPENAI"]
         span_attributes = {
             **get_langtrace_attributes(version, service_provider, vendor_type="llm"),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, operation_name="images_generate"),
             **get_llm_url(instance),
             SpanAttributes.LLM_PATH: APIS["IMAGES_GENERATION"]["ENDPOINT"],
             **get_extra_attributes(),
@@ -118,7 +118,7 @@ async def traced_method(wrapped, instance, args, kwargs):
 
         span_attributes = {
             **get_langtrace_attributes(version, service_provider, vendor_type="llm"),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, operation_name="images_generate"),
             **get_llm_url(instance),
             SpanAttributes.LLM_PATH: APIS["IMAGES_GENERATION"]["ENDPOINT"],
             **get_extra_attributes(),
@@ -181,7 +181,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         span_attributes = {
             **get_langtrace_attributes(version, service_provider, vendor_type="llm"),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, operation_name="images_edit"),
             **get_llm_url(instance),
             SpanAttributes.LLM_PATH: APIS["IMAGES_EDIT"]["ENDPOINT"],
             SpanAttributes.LLM_RESPONSE_FORMAT: kwargs.get("response_format"),
@@ -432,7 +432,7 @@ def traced_method(wrapped, instance, args, kwargs):
 
         span_attributes = {
             **get_langtrace_attributes(version, service_provider, vendor_type="llm"),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, operation_name="embed"),
             **get_llm_url(instance),
             SpanAttributes.LLM_PATH: APIS["EMBEDDINGS_CREATE"]["ENDPOINT"],
             SpanAttributes.LLM_REQUEST_DIMENSIONS: kwargs.get("dimensions"),
@@ -490,7 +490,7 @@ async def traced_method(wrapped, instance, args, kwargs):
 
         span_attributes = {
             **get_langtrace_attributes(version, service_provider, vendor_type="llm"),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, operation_name="embed"),
             SpanAttributes.LLM_PATH: APIS["EMBEDDINGS_CREATE"]["ENDPOINT"],
             SpanAttributes.LLM_REQUEST_DIMENSIONS: kwargs.get("dimensions"),
             **get_extra_attributes(),

src/langtrace_python_sdk/instrumentation/openai/patch.py

@@ -92,7 +92,7 @@ def get_langtrace_attributes(version, service_provider, vendor_type="llm"):
     }
 
 
-def get_llm_request_attributes(kwargs, prompts=None, model=None):
+def get_llm_request_attributes(kwargs, prompts=None, model=None, operation_name="chat"):
 
     user = kwargs.get("user", None)
     if prompts is None:
@@ -111,6 +111,7 @@ def get_llm_request_attributes(kwargs, prompts=None, model=None):
     top_p = kwargs.get("p", None) or kwargs.get("top_p", None)
     tools = kwargs.get("tools", None)
     return {
+        SpanAttributes.LLM_OPERATION_NAME: operation_name,
         SpanAttributes.LLM_REQUEST_MODEL: model or kwargs.get("model"),
         SpanAttributes.LLM_IS_STREAMING: kwargs.get("stream"),
         SpanAttributes.LLM_REQUEST_TEMPERATURE: kwargs.get("temperature"),

src/langtrace_python_sdk/utils/llm.py

@@ -1 +1 @@
-__version__ = "2.2.6"
+__version__ = "2.2.7"