Add OTLP example

src/examples/otlp_example/otlp_with_langtrace.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()