feat: add local langfuse tracing option (#106)

packages/exchange/pyproject.toml

@@ -13,6 +13,8 @@ dependencies = [
     "tiktoken>=0.7.0",
     "httpx>=0.27.0",
     "tenacity>=9.0.0",
+    "python-dotenv>=1.0.1",
+    "langfuse-wrapper"   
 ]
 
 [tool.hatch.build.targets.wheel]
@@ -47,3 +49,10 @@ ai-exchange = "exchange:module_name"
 markers = [
     "integration: marks tests that need to authenticate (deselect with '-m \"not integration\"')",
 ]
+
+[tool.uv.sources]
+langfuse-wrapper = { workspace = true}
+
+[tool.uv.workspace]
+members = ["../langfuse-wrapper"]
+

packages/exchange/src/exchange/exchange.py

@@ -14,6 +14,7 @@ from exchange.moderators.truncate import ContextTruncate
 from exchange.providers import Provider, Usage
 from exchange.tool import Tool
 from exchange.token_usage_collector import _token_usage_collector
+from langfuse_wrapper.langfuse_wrapper import observe_wrapper
 
 
 def validate_tool_output(output: str) -> None:
@@ -127,6 +128,7 @@ class Exchange:
 
         return response
 
+    @observe_wrapper()
     def call_function(self, tool_use: ToolUse) -> ToolResult:
         """Call the function indicated by the tool use"""
         tool = self._toolmap.get(tool_use.name)

packages/exchange/src/exchange/providers/anthropic.py

@@ -8,6 +8,7 @@ from exchange.content import Text, ToolResult, ToolUse
 from exchange.providers.base import Provider, Usage
 from tenacity import retry, wait_fixed, stop_after_attempt
 from exchange.providers.utils import retry_if_status, raise_for_status
+from langfuse_wrapper.langfuse_wrapper import observe_wrapper
 
 ANTHROPIC_HOST = "https://api.anthropic.com/v1/messages"
 
@@ -123,6 +124,7 @@ class AnthropicProvider(Provider):
             messages_spec.append(converted)
         return messages_spec
 
+    @observe_wrapper(as_type="generation")
     def complete(
         self,
         model: str,

packages/exchange/src/exchange/providers/bedrock.py

@@ -15,6 +15,7 @@ from exchange.providers import Provider, Usage
 from tenacity import retry, wait_fixed, stop_after_attempt
 from exchange.providers.utils import raise_for_status, retry_if_status
 from exchange.tool import Tool
+from langfuse_wrapper.langfuse_wrapper import observe_wrapper
 
 SERVICE = "bedrock-runtime"
 UTC = timezone.utc
@@ -175,6 +176,7 @@ class BedrockProvider(Provider):
         )
         return cls(client=client)
 
+    @observe_wrapper(as_type="generation")
     def complete(
         self,
         model: str,

packages/exchange/src/exchange/providers/databricks.py

@@ -13,7 +13,7 @@ from exchange.providers.utils import (
     tools_to_openai_spec,
 )
 from exchange.tool import Tool
-
+from langfuse_wrapper.langfuse_wrapper import observe_wrapper
 
 retry_procedure = retry(
     wait=wait_fixed(2),
@@ -69,6 +69,7 @@ class DatabricksProvider(Provider):
             total_tokens=total_tokens,
         )
 
+    @observe_wrapper(as_type="generation")
     def complete(
         self,
         model: str,

packages/exchange/src/exchange/providers/google.py

@@ -8,6 +8,7 @@ from exchange.content import Text, ToolResult, ToolUse
 from exchange.providers.base import Provider, Usage
 from tenacity import retry, wait_fixed, stop_after_attempt
 from exchange.providers.utils import raise_for_status, retry_if_status
+from langfuse_wrapper.langfuse_wrapper import observe_wrapper
 
 GOOGLE_HOST = "https://generativelanguage.googleapis.com/v1beta"
 
@@ -121,6 +122,7 @@ class GoogleProvider(Provider):
 
         return messages_spec
 
+    @observe_wrapper(as_type="generation")
     def complete(
         self,
         model: str,

packages/exchange/src/exchange/providers/openai.py

@@ -15,6 +15,7 @@ from exchange.providers.utils import (
 from exchange.tool import Tool
 from tenacity import retry, wait_fixed, stop_after_attempt
 from exchange.providers.utils import retry_if_status
+from langfuse_wrapper.langfuse_wrapper import observe_wrapper
 
 OPENAI_HOST = "https://api.openai.com/"
 
@@ -65,6 +66,7 @@ class OpenAiProvider(Provider):
             total_tokens=total_tokens,
         )
 
+    @observe_wrapper(as_type="generation")
     def complete(
         self,
         model: str,