feat(pipecat): add auto instrumentor for pipecat

.gitignore

@@ -109,3 +109,6 @@ Thumbs.db
 
 # Scratch files
 .scratch/
+
+# Workspace Definitions
+*.code-workspace

python/instrumentation/openinference-instrumentation-pipecat/CHANGELOG.md

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+# Changelog
+
+## [0.1.0] - TBD
+
+### Features
+
+* Initial release of openinference-instrumentation-pipecat
+* Support for converting Pipecat traces to OpenInference format
+* Compatible with Phoenix and Arize observability platforms
+
+## Changelog

python/instrumentation/openinference-instrumentation-pipecat/LICENSE

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python/instrumentation/openinference-instrumentation-pipecat/README.md

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+# OpenInference Pipecat Instrumentation
+
+Python auto-instrumentation library for Pipecat. This library allows you to convert Pipecat traces to OpenInference, which is OpenTelemetry compatible, and view those traces in [Arize Phoenix](https://github.com/Arize-ai/phoenix).
+
+## Installation
+
+```shell
+pip install openinference-instrumentation-pipecat
+```
+
+## Quickstart
+
+This quickstart shows you how to view your Pipecat traces in Phoenix.
+
+Install required packages.
+
+```shell
+pip install arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp pipecat-ai
+```
+
+Start Phoenix in the background as a collector. By default, it listens on `http://localhost:6006`. You can visit the app via a browser at the same address. (Phoenix does not send data over the internet. It only operates locally on your machine.)
+
+```shell
+phoenix serve
+```
+
+Here's a simple example that demonstrates how to convert Pipecat traces into OpenInference and view those traces in Phoenix:
+
+```python
+import os
+import grpc
+from opentelemetry.sdk.trace.export import BatchSpanProcessor
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
+from phoenix.otel import register
+from openinference.instrumentation.pipecat import OpenInferenceSpanProcessor
+from pipecat.utils.tracing import setup_tracing
+
+# Set your API keys
+os.environ["OPENAI_API_KEY"] = "YOUR_OPENAI_API_KEY"
+
+# Set up the tracer provider
+tracer_provider = register(
+    project_name="default" #Phoenix project name
+)
+
+tracer_provider.add_span_processor(OpenInferenceSpanProcessor())
+
+tracer_provider.add_span_processor(
+    BatchSpanProcessor(
+        OTLPSpanExporter(
+            endpoint="http://localhost:4317", #if using phoenix cloud, change to phoenix cloud endpoint (phoenix cloud space -> settings -> endpoint/hostname)
+            headers={},
+            compression=grpc.Compression.Gzip,  # use enum instead of string
+        )
+    )
+)
+
+# Initialize Pipecat tracing
+setup_tracing(
+    service_name="pipecat-phoenix-demo",
+    exporter=OTLPSpanExporter(
+        endpoint="http://localhost:4317",
+        headers={},
+        compression=grpc.Compression.Gzip,
+    ),
+)
+
+# Build your Pipecat pipeline
+# ... (add your Pipecat pipeline code here)
+
+# Now view your converted Pipecat traces in Phoenix!
+```
+## This example:
+
+1. Uses Pipecat's built-in tracing utilities to instrument the application.
+2. Defines a Pipecat pipeline for voice/conversational AI
+3. Traces are exported to Phoenix using the span processor. 
+
+The traces will be visible in the Phoenix UI at `http://localhost:6006`.
+
+## More Info
+
+-   [More info on OpenInference and Phoenix](https://docs.arize.com/phoenix)
+-   [How to customize spans to track sessions, metadata, etc.](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#customizing-spans)
+-   [How to account for private information and span payload customization](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#tracing-configuration)