diff --git a/2025-05-16-fastapi-demo/.gitignore b/2025-05-16-fastapi-demo/.gitignore
index e757264..e49636c 100644
--- a/2025-05-16-fastapi-demo/.gitignore
+++ b/2025-05-16-fastapi-demo/.gitignore
@@ -1,4 +1,5 @@
 test.db
 .venv
 .logfire
-.env
\ No newline at end of file
+.env
+node_modules
\ No newline at end of file
diff --git a/2025-05-16-fastapi-demo/main.py b/2025-05-16-fastapi-demo/main.py
index 288b8e0..46dccc0 100644
--- a/2025-05-16-fastapi-demo/main.py
+++ b/2025-05-16-fastapi-demo/main.py
@@ -3,13 +3,14 @@
 APP_NAME = "example"
 
 logfire.configure(
-    service_name='cli',
-    service_version='0.1.0',
+    service_name="cli",
+    service_version="0.1.0",
 )
 
+
 def main():
     logfire.info(f"Launching app: {APP_NAME}")
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()
diff --git a/2025-05-16-fastapi-demo/pydantic_ai_evals_schema.json b/2025-05-16-fastapi-demo/pydantic_ai_evals_schema.json
deleted file mode 100644
index 0c1bc1e..0000000
--- a/2025-05-16-fastapi-demo/pydantic_ai_evals_schema.json
+++ /dev/null
@@ -1,992 +0,0 @@
-{
-  "$defs": {
-    "AgentQuery": {
-      "description": "Input model for agent queries.",
-      "properties": {
-        "question": {
-          "description": "Question to ask the PydanticAI docs agent",
-          "title": "Question",
-          "type": "string"
-        }
-      },
-      "required": [
-        "question"
-      ],
-      "title": "AgentQuery",
-      "type": "object"
-    },
-    "BotResponse": {
-      "properties": {
-        "answer": {
-          "title": "Answer",
-          "type": "string"
-        },
-        "reasoning": {
-          "title": "Reasoning",
-          "type": "string"
-        },
-        "reference": {
-          "anyOf": [
-            {
-              "type": "string"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "default": null,
-          "title": "Reference"
-        },
-        "confidence_percentage": {
-          "maximum": 100,
-          "minimum": 0,
-          "title": "Confidence Percentage",
-          "type": "integer"
-        }
-      },
-      "required": [
-        "answer",
-        "reasoning",
-        "confidence_percentage"
-      ],
-      "title": "BotResponse",
-      "type": "object"
-    },
-    "Case": {
-      "additionalProperties": false,
-      "properties": {
-        "name": {
-          "anyOf": [
-            {
-              "type": "string"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "default": null,
-          "title": "Name"
-        },
-        "inputs": {
-          "$ref": "#/$defs/AgentQuery"
-        },
-        "metadata": {
-          "anyOf": [
-            {
-              "additionalProperties": true,
-              "type": "object"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "default": null,
-          "title": "Metadata"
-        },
-        "expected_output": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/BotResponse"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "default": null
-        },
-        "evaluators": {
-          "default": [],
-          "items": {
-            "anyOf": [
-              {
-                "$ref": "#/$defs/short_evaluator_Equals"
-              },
-              {
-                "$ref": "#/$defs/evaluator_Equals"
-              },
-              {
-                "const": "EqualsExpected",
-                "type": "string"
-              },
-              {
-                "$ref": "#/$defs/short_evaluator_EqualsExpected"
-              },
-              {
-                "$ref": "#/$defs/short_evaluator_Contains"
-              },
-              {
-                "$ref": "#/$defs/evaluator_Contains"
-              },
-              {
-                "$ref": "#/$defs/short_evaluator_IsInstance"
-              },
-              {
-                "$ref": "#/$defs/evaluator_IsInstance"
-              },
-              {
-                "$ref": "#/$defs/short_evaluator_MaxDuration"
-              },
-              {
-                "$ref": "#/$defs/short_evaluator_LLMJudge"
-              },
-              {
-                "$ref": "#/$defs/evaluator_LLMJudge"
-              },
-              {
-                "$ref": "#/$defs/short_evaluator_HasMatchingSpan"
-              },
-              {
-                "$ref": "#/$defs/evaluator_HasMatchingSpan"
-              }
-            ]
-          },
-          "title": "Evaluators",
-          "type": "array"
-        }
-      },
-      "required": [
-        "inputs"
-      ],
-      "title": "Case",
-      "type": "object"
-    },
-    "KnownModelName": {
-      "enum": [
-        "anthropic:claude-3-7-sonnet-latest",
-        "anthropic:claude-3-5-haiku-latest",
-        "anthropic:claude-3-5-sonnet-latest",
-        "anthropic:claude-3-opus-latest",
-        "claude-3-7-sonnet-latest",
-        "claude-3-5-haiku-latest",
-        "bedrock:amazon.titan-tg1-large",
-        "bedrock:amazon.titan-text-lite-v1",
-        "bedrock:amazon.titan-text-express-v1",
-        "bedrock:us.amazon.nova-pro-v1:0",
-        "bedrock:us.amazon.nova-lite-v1:0",
-        "bedrock:us.amazon.nova-micro-v1:0",
-        "bedrock:anthropic.claude-3-5-sonnet-20241022-v2:0",
-        "bedrock:us.anthropic.claude-3-5-sonnet-20241022-v2:0",
-        "bedrock:anthropic.claude-3-5-haiku-20241022-v1:0",
-        "bedrock:us.anthropic.claude-3-5-haiku-20241022-v1:0",
-        "bedrock:anthropic.claude-instant-v1",
-        "bedrock:anthropic.claude-v2:1",
-        "bedrock:anthropic.claude-v2",
-        "bedrock:anthropic.claude-3-sonnet-20240229-v1:0",
-        "bedrock:us.anthropic.claude-3-sonnet-20240229-v1:0",
-        "bedrock:anthropic.claude-3-haiku-20240307-v1:0",
-        "bedrock:us.anthropic.claude-3-haiku-20240307-v1:0",
-        "bedrock:anthropic.claude-3-opus-20240229-v1:0",
-        "bedrock:us.anthropic.claude-3-opus-20240229-v1:0",
-        "bedrock:anthropic.claude-3-5-sonnet-20240620-v1:0",
-        "bedrock:us.anthropic.claude-3-5-sonnet-20240620-v1:0",
-        "bedrock:anthropic.claude-3-7-sonnet-20250219-v1:0",
-        "bedrock:us.anthropic.claude-3-7-sonnet-20250219-v1:0",
-        "bedrock:cohere.command-text-v14",
-        "bedrock:cohere.command-r-v1:0",
-        "bedrock:cohere.command-r-plus-v1:0",
-        "bedrock:cohere.command-light-text-v14",
-        "bedrock:meta.llama3-8b-instruct-v1:0",
-        "bedrock:meta.llama3-70b-instruct-v1:0",
-        "bedrock:meta.llama3-1-8b-instruct-v1:0",
-        "bedrock:us.meta.llama3-1-8b-instruct-v1:0",
-        "bedrock:meta.llama3-1-70b-instruct-v1:0",
-        "bedrock:us.meta.llama3-1-70b-instruct-v1:0",
-        "bedrock:meta.llama3-1-405b-instruct-v1:0",
-        "bedrock:us.meta.llama3-2-11b-instruct-v1:0",
-        "bedrock:us.meta.llama3-2-90b-instruct-v1:0",
-        "bedrock:us.meta.llama3-2-1b-instruct-v1:0",
-        "bedrock:us.meta.llama3-2-3b-instruct-v1:0",
-        "bedrock:us.meta.llama3-3-70b-instruct-v1:0",
-        "bedrock:mistral.mistral-7b-instruct-v0:2",
-        "bedrock:mistral.mixtral-8x7b-instruct-v0:1",
-        "bedrock:mistral.mistral-large-2402-v1:0",
-        "bedrock:mistral.mistral-large-2407-v1:0",
-        "claude-3-5-sonnet-latest",
-        "claude-3-opus-latest",
-        "cohere:c4ai-aya-expanse-32b",
-        "cohere:c4ai-aya-expanse-8b",
-        "cohere:command",
-        "cohere:command-light",
-        "cohere:command-light-nightly",
-        "cohere:command-nightly",
-        "cohere:command-r",
-        "cohere:command-r-03-2024",
-        "cohere:command-r-08-2024",
-        "cohere:command-r-plus",
-        "cohere:command-r-plus-04-2024",
-        "cohere:command-r-plus-08-2024",
-        "cohere:command-r7b-12-2024",
-        "deepseek:deepseek-chat",
-        "deepseek:deepseek-reasoner",
-        "google-gla:gemini-1.0-pro",
-        "google-gla:gemini-1.5-flash",
-        "google-gla:gemini-1.5-flash-8b",
-        "google-gla:gemini-1.5-pro",
-        "google-gla:gemini-2.0-flash-exp",
-        "google-gla:gemini-2.0-flash-thinking-exp-01-21",
-        "google-gla:gemini-exp-1206",
-        "google-gla:gemini-2.0-flash",
-        "google-gla:gemini-2.0-flash-lite-preview-02-05",
-        "google-gla:gemini-2.0-pro-exp-02-05",
-        "google-gla:gemini-2.5-flash-preview-04-17",
-        "google-gla:gemini-2.5-pro-exp-03-25",
-        "google-gla:gemini-2.5-pro-preview-03-25",
-        "google-vertex:gemini-1.0-pro",
-        "google-vertex:gemini-1.5-flash",
-        "google-vertex:gemini-1.5-flash-8b",
-        "google-vertex:gemini-1.5-pro",
-        "google-vertex:gemini-2.0-flash-exp",
-        "google-vertex:gemini-2.0-flash-thinking-exp-01-21",
-        "google-vertex:gemini-exp-1206",
-        "google-vertex:gemini-2.0-flash",
-        "google-vertex:gemini-2.0-flash-lite-preview-02-05",
-        "google-vertex:gemini-2.0-pro-exp-02-05",
-        "google-vertex:gemini-2.5-flash-preview-04-17",
-        "google-vertex:gemini-2.5-pro-exp-03-25",
-        "google-vertex:gemini-2.5-pro-preview-03-25",
-        "gpt-3.5-turbo",
-        "gpt-3.5-turbo-0125",
-        "gpt-3.5-turbo-0301",
-        "gpt-3.5-turbo-0613",
-        "gpt-3.5-turbo-1106",
-        "gpt-3.5-turbo-16k",
-        "gpt-3.5-turbo-16k-0613",
-        "gpt-4",
-        "gpt-4-0125-preview",
-        "gpt-4-0314",
-        "gpt-4-0613",
-        "gpt-4-1106-preview",
-        "gpt-4-32k",
-        "gpt-4-32k-0314",
-        "gpt-4-32k-0613",
-        "gpt-4-turbo",
-        "gpt-4-turbo-2024-04-09",
-        "gpt-4-turbo-preview",
-        "gpt-4-vision-preview",
-        "gpt-4.1",
-        "gpt-4.1-2025-04-14",
-        "gpt-4.1-mini",
-        "gpt-4.1-mini-2025-04-14",
-        "gpt-4.1-nano",
-        "gpt-4.1-nano-2025-04-14",
-        "gpt-4o",
-        "gpt-4o-2024-05-13",
-        "gpt-4o-2024-08-06",
-        "gpt-4o-2024-11-20",
-        "gpt-4o-audio-preview",
-        "gpt-4o-audio-preview-2024-10-01",
-        "gpt-4o-audio-preview-2024-12-17",
-        "gpt-4o-mini",
-        "gpt-4o-mini-2024-07-18",
-        "gpt-4o-mini-audio-preview",
-        "gpt-4o-mini-audio-preview-2024-12-17",
-        "gpt-4o-mini-search-preview",
-        "gpt-4o-mini-search-preview-2025-03-11",
-        "gpt-4o-search-preview",
-        "gpt-4o-search-preview-2025-03-11",
-        "groq:distil-whisper-large-v3-en",
-        "groq:gemma2-9b-it",
-        "groq:llama-3.3-70b-versatile",
-        "groq:llama-3.1-8b-instant",
-        "groq:llama-guard-3-8b",
-        "groq:llama3-70b-8192",
-        "groq:llama3-8b-8192",
-        "groq:whisper-large-v3",
-        "groq:whisper-large-v3-turbo",
-        "groq:playai-tts",
-        "groq:playai-tts-arabic",
-        "groq:qwen-qwq-32b",
-        "groq:mistral-saba-24b",
-        "groq:qwen-2.5-coder-32b",
-        "groq:qwen-2.5-32b",
-        "groq:deepseek-r1-distill-qwen-32b",
-        "groq:deepseek-r1-distill-llama-70b",
-        "groq:llama-3.3-70b-specdec",
-        "groq:llama-3.2-1b-preview",
-        "groq:llama-3.2-3b-preview",
-        "groq:llama-3.2-11b-vision-preview",
-        "groq:llama-3.2-90b-vision-preview",
-        "mistral:codestral-latest",
-        "mistral:mistral-large-latest",
-        "mistral:mistral-moderation-latest",
-        "mistral:mistral-small-latest",
-        "o1",
-        "o1-2024-12-17",
-        "o1-mini",
-        "o1-mini-2024-09-12",
-        "o1-preview",
-        "o1-preview-2024-09-12",
-        "o3",
-        "o3-2025-04-16",
-        "o3-mini",
-        "o3-mini-2025-01-31",
-        "openai:chatgpt-4o-latest",
-        "openai:gpt-3.5-turbo",
-        "openai:gpt-3.5-turbo-0125",
-        "openai:gpt-3.5-turbo-0301",
-        "openai:gpt-3.5-turbo-0613",
-        "openai:gpt-3.5-turbo-1106",
-        "openai:gpt-3.5-turbo-16k",
-        "openai:gpt-3.5-turbo-16k-0613",
-        "openai:gpt-4",
-        "openai:gpt-4-0125-preview",
-        "openai:gpt-4-0314",
-        "openai:gpt-4-0613",
-        "openai:gpt-4-1106-preview",
-        "openai:gpt-4-32k",
-        "openai:gpt-4-32k-0314",
-        "openai:gpt-4-32k-0613",
-        "openai:gpt-4-turbo",
-        "openai:gpt-4-turbo-2024-04-09",
-        "openai:gpt-4-turbo-preview",
-        "openai:gpt-4-vision-preview",
-        "openai:gpt-4.1",
-        "openai:gpt-4.1-2025-04-14",
-        "openai:gpt-4.1-mini",
-        "openai:gpt-4.1-mini-2025-04-14",
-        "openai:gpt-4.1-nano",
-        "openai:gpt-4.1-nano-2025-04-14",
-        "openai:gpt-4o",
-        "openai:gpt-4o-2024-05-13",
-        "openai:gpt-4o-2024-08-06",
-        "openai:gpt-4o-2024-11-20",
-        "openai:gpt-4o-audio-preview",
-        "openai:gpt-4o-audio-preview-2024-10-01",
-        "openai:gpt-4o-audio-preview-2024-12-17",
-        "openai:gpt-4o-mini",
-        "openai:gpt-4o-mini-2024-07-18",
-        "openai:gpt-4o-mini-audio-preview",
-        "openai:gpt-4o-mini-audio-preview-2024-12-17",
-        "openai:gpt-4o-mini-search-preview",
-        "openai:gpt-4o-mini-search-preview-2025-03-11",
-        "openai:gpt-4o-search-preview",
-        "openai:gpt-4o-search-preview-2025-03-11",
-        "openai:o1",
-        "openai:o1-2024-12-17",
-        "openai:o1-mini",
-        "openai:o1-mini-2024-09-12",
-        "openai:o1-preview",
-        "openai:o1-preview-2024-09-12",
-        "openai:o3",
-        "openai:o3-2025-04-16",
-        "openai:o3-mini",
-        "openai:o3-mini-2025-01-31",
-        "openai:o4-mini",
-        "openai:o4-mini-2025-04-16",
-        "test"
-      ],
-      "type": "string"
-    },
-    "ModelSettings": {
-      "description": "Settings to configure an LLM.\n\nHere we include only settings which apply to multiple models / model providers,\nthough not all of these settings are supported by all models.",
-      "properties": {
-        "max_tokens": {
-          "title": "Max Tokens",
-          "type": "integer"
-        },
-        "temperature": {
-          "title": "Temperature",
-          "type": "number"
-        },
-        "top_p": {
-          "title": "Top P",
-          "type": "number"
-        },
-        "timeout": {
-          "title": "Timeout",
-          "type": "number"
-        },
-        "parallel_tool_calls": {
-          "title": "Parallel Tool Calls",
-          "type": "boolean"
-        },
-        "seed": {
-          "title": "Seed",
-          "type": "integer"
-        },
-        "presence_penalty": {
-          "title": "Presence Penalty",
-          "type": "number"
-        },
-        "frequency_penalty": {
-          "title": "Frequency Penalty",
-          "type": "number"
-        },
-        "logit_bias": {
-          "additionalProperties": {
-            "type": "integer"
-          },
-          "title": "Logit Bias",
-          "type": "object"
-        },
-        "stop_sequences": {
-          "items": {
-            "type": "string"
-          },
-          "title": "Stop Sequences",
-          "type": "array"
-        },
-        "extra_headers": {
-          "additionalProperties": {
-            "type": "string"
-          },
-          "title": "Extra Headers",
-          "type": "object"
-        },
-        "extra_body": {
-          "title": "Extra Body"
-        }
-      },
-      "title": "ModelSettings",
-      "type": "object"
-    },
-    "OutputConfig": {
-      "description": "Configuration for the score and assertion outputs of the LLMJudge evaluator.",
-      "properties": {
-        "evaluation_name": {
-          "title": "Evaluation Name",
-          "type": "string"
-        },
-        "include_reason": {
-          "title": "Include Reason",
-          "type": "boolean"
-        }
-      },
-      "title": "OutputConfig",
-      "type": "object"
-    },
-    "SpanQuery": {
-      "description": "A serializable query for filtering SpanNodes based on various conditions.\n\nAll fields are optional and combined with AND logic by default.",
-      "properties": {
-        "name_equals": {
-          "title": "Name Equals",
-          "type": "string"
-        },
-        "name_contains": {
-          "title": "Name Contains",
-          "type": "string"
-        },
-        "name_matches_regex": {
-          "title": "Name Matches Regex",
-          "type": "string"
-        },
-        "has_attributes": {
-          "additionalProperties": true,
-          "title": "Has Attributes",
-          "type": "object"
-        },
-        "has_attribute_keys": {
-          "items": {
-            "type": "string"
-          },
-          "title": "Has Attribute Keys",
-          "type": "array"
-        },
-        "min_duration": {
-          "anyOf": [
-            {
-              "format": "duration",
-              "type": "string"
-            },
-            {
-              "type": "number"
-            }
-          ],
-          "title": "Min Duration"
-        },
-        "max_duration": {
-          "anyOf": [
-            {
-              "format": "duration",
-              "type": "string"
-            },
-            {
-              "type": "number"
-            }
-          ],
-          "title": "Max Duration"
-        },
-        "not_": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "and_": {
-          "items": {
-            "$ref": "#/$defs/SpanQuery"
-          },
-          "title": "And",
-          "type": "array"
-        },
-        "or_": {
-          "items": {
-            "$ref": "#/$defs/SpanQuery"
-          },
-          "title": "Or",
-          "type": "array"
-        },
-        "min_child_count": {
-          "title": "Min Child Count",
-          "type": "integer"
-        },
-        "max_child_count": {
-          "title": "Max Child Count",
-          "type": "integer"
-        },
-        "some_child_has": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "all_children_have": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "no_child_has": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "stop_recursing_when": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "min_descendant_count": {
-          "title": "Min Descendant Count",
-          "type": "integer"
-        },
-        "max_descendant_count": {
-          "title": "Max Descendant Count",
-          "type": "integer"
-        },
-        "some_descendant_has": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "all_descendants_have": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "no_descendant_has": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "min_depth": {
-          "title": "Min Depth",
-          "type": "integer"
-        },
-        "max_depth": {
-          "title": "Max Depth",
-          "type": "integer"
-        },
-        "some_ancestor_has": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "all_ancestors_have": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "no_ancestor_has": {
-          "$ref": "#/$defs/SpanQuery"
-        }
-      },
-      "title": "SpanQuery",
-      "type": "object"
-    },
-    "evaluator_Contains": {
-      "additionalProperties": false,
-      "properties": {
-        "Contains": {
-          "$ref": "#/$defs/evaluator_params_Contains"
-        }
-      },
-      "required": [
-        "Contains"
-      ],
-      "title": "evaluator_Contains",
-      "type": "object"
-    },
-    "evaluator_Equals": {
-      "additionalProperties": false,
-      "properties": {
-        "Equals": {
-          "$ref": "#/$defs/evaluator_params_Equals"
-        }
-      },
-      "required": [
-        "Equals"
-      ],
-      "title": "evaluator_Equals",
-      "type": "object"
-    },
-    "evaluator_HasMatchingSpan": {
-      "additionalProperties": false,
-      "properties": {
-        "HasMatchingSpan": {
-          "$ref": "#/$defs/evaluator_params_HasMatchingSpan"
-        }
-      },
-      "required": [
-        "HasMatchingSpan"
-      ],
-      "title": "evaluator_HasMatchingSpan",
-      "type": "object"
-    },
-    "evaluator_IsInstance": {
-      "additionalProperties": false,
-      "properties": {
-        "IsInstance": {
-          "$ref": "#/$defs/evaluator_params_IsInstance"
-        }
-      },
-      "required": [
-        "IsInstance"
-      ],
-      "title": "evaluator_IsInstance",
-      "type": "object"
-    },
-    "evaluator_LLMJudge": {
-      "additionalProperties": false,
-      "properties": {
-        "LLMJudge": {
-          "$ref": "#/$defs/evaluator_params_LLMJudge"
-        }
-      },
-      "required": [
-        "LLMJudge"
-      ],
-      "title": "evaluator_LLMJudge",
-      "type": "object"
-    },
-    "evaluator_params_Contains": {
-      "additionalProperties": false,
-      "properties": {
-        "value": {
-          "title": "Value"
-        },
-        "case_sensitive": {
-          "title": "Case Sensitive",
-          "type": "boolean"
-        },
-        "as_strings": {
-          "title": "As Strings",
-          "type": "boolean"
-        },
-        "evaluation_name": {
-          "anyOf": [
-            {
-              "type": "string"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "title": "Evaluation Name"
-        }
-      },
-      "required": [
-        "value"
-      ],
-      "title": "evaluator_params_Contains",
-      "type": "object"
-    },
-    "evaluator_params_Equals": {
-      "additionalProperties": false,
-      "properties": {
-        "value": {
-          "title": "Value"
-        },
-        "evaluation_name": {
-          "anyOf": [
-            {
-              "type": "string"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "title": "Evaluation Name"
-        }
-      },
-      "required": [
-        "value"
-      ],
-      "title": "evaluator_params_Equals",
-      "type": "object"
-    },
-    "evaluator_params_HasMatchingSpan": {
-      "additionalProperties": false,
-      "properties": {
-        "query": {
-          "$ref": "#/$defs/SpanQuery"
-        },
-        "evaluation_name": {
-          "anyOf": [
-            {
-              "type": "string"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "title": "Evaluation Name"
-        }
-      },
-      "required": [
-        "query"
-      ],
-      "title": "evaluator_params_HasMatchingSpan",
-      "type": "object"
-    },
-    "evaluator_params_IsInstance": {
-      "additionalProperties": false,
-      "properties": {
-        "type_name": {
-          "title": "Type Name",
-          "type": "string"
-        },
-        "evaluation_name": {
-          "anyOf": [
-            {
-              "type": "string"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "title": "Evaluation Name"
-        }
-      },
-      "required": [
-        "type_name"
-      ],
-      "title": "evaluator_params_IsInstance",
-      "type": "object"
-    },
-    "evaluator_params_LLMJudge": {
-      "additionalProperties": false,
-      "properties": {
-        "rubric": {
-          "title": "Rubric",
-          "type": "string"
-        },
-        "model": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/KnownModelName"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "title": "Model"
-        },
-        "include_input": {
-          "title": "Include Input",
-          "type": "boolean"
-        },
-        "model_settings": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/ModelSettings"
-            },
-            {
-              "type": "null"
-            }
-          ]
-        },
-        "score": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/OutputConfig"
-            },
-            {
-              "const": false,
-              "type": "boolean"
-            }
-          ],
-          "title": "Score"
-        },
-        "assertion": {
-          "anyOf": [
-            {
-              "$ref": "#/$defs/OutputConfig"
-            },
-            {
-              "const": false,
-              "type": "boolean"
-            }
-          ],
-          "title": "Assertion"
-        }
-      },
-      "required": [
-        "rubric"
-      ],
-      "title": "evaluator_params_LLMJudge",
-      "type": "object"
-    },
-    "short_evaluator_Contains": {
-      "additionalProperties": false,
-      "properties": {
-        "Contains": {
-          "title": "Contains"
-        }
-      },
-      "required": [
-        "Contains"
-      ],
-      "title": "short_evaluator_Contains",
-      "type": "object"
-    },
-    "short_evaluator_Equals": {
-      "additionalProperties": false,
-      "properties": {
-        "Equals": {
-          "title": "Equals"
-        }
-      },
-      "required": [
-        "Equals"
-      ],
-      "title": "short_evaluator_Equals",
-      "type": "object"
-    },
-    "short_evaluator_EqualsExpected": {
-      "additionalProperties": false,
-      "properties": {
-        "EqualsExpected": {
-          "anyOf": [
-            {
-              "type": "string"
-            },
-            {
-              "type": "null"
-            }
-          ],
-          "title": "Equalsexpected"
-        }
-      },
-      "title": "short_evaluator_EqualsExpected",
-      "type": "object"
-    },
-    "short_evaluator_HasMatchingSpan": {
-      "additionalProperties": false,
-      "properties": {
-        "HasMatchingSpan": {
-          "$ref": "#/$defs/SpanQuery"
-        }
-      },
-      "required": [
-        "HasMatchingSpan"
-      ],
-      "title": "short_evaluator_HasMatchingSpan",
-      "type": "object"
-    },
-    "short_evaluator_IsInstance": {
-      "additionalProperties": false,
-      "properties": {
-        "IsInstance": {
-          "title": "Isinstance",
-          "type": "string"
-        }
-      },
-      "required": [
-        "IsInstance"
-      ],
-      "title": "short_evaluator_IsInstance",
-      "type": "object"
-    },
-    "short_evaluator_LLMJudge": {
-      "additionalProperties": false,
-      "properties": {
-        "LLMJudge": {
-          "title": "Llmjudge",
-          "type": "string"
-        }
-      },
-      "required": [
-        "LLMJudge"
-      ],
-      "title": "short_evaluator_LLMJudge",
-      "type": "object"
-    },
-    "short_evaluator_MaxDuration": {
-      "additionalProperties": false,
-      "properties": {
-        "MaxDuration": {
-          "anyOf": [
-            {
-              "type": "number"
-            },
-            {
-              "format": "duration",
-              "type": "string"
-            }
-          ],
-          "title": "Maxduration"
-        }
-      },
-      "required": [
-        "MaxDuration"
-      ],
-      "title": "short_evaluator_MaxDuration",
-      "type": "object"
-    }
-  },
-  "additionalProperties": false,
-  "properties": {
-    "cases": {
-      "items": {
-        "$ref": "#/$defs/Case"
-      },
-      "title": "Cases",
-      "type": "array"
-    },
-    "evaluators": {
-      "default": [],
-      "items": {
-        "anyOf": [
-          {
-            "$ref": "#/$defs/short_evaluator_Equals"
-          },
-          {
-            "$ref": "#/$defs/evaluator_Equals"
-          },
-          {
-            "const": "EqualsExpected",
-            "type": "string"
-          },
-          {
-            "$ref": "#/$defs/short_evaluator_EqualsExpected"
-          },
-          {
-            "$ref": "#/$defs/short_evaluator_Contains"
-          },
-          {
-            "$ref": "#/$defs/evaluator_Contains"
-          },
-          {
-            "$ref": "#/$defs/short_evaluator_IsInstance"
-          },
-          {
-            "$ref": "#/$defs/evaluator_IsInstance"
-          },
-          {
-            "$ref": "#/$defs/short_evaluator_MaxDuration"
-          },
-          {
-            "$ref": "#/$defs/short_evaluator_LLMJudge"
-          },
-          {
-            "$ref": "#/$defs/evaluator_LLMJudge"
-          },
-          {
-            "$ref": "#/$defs/short_evaluator_HasMatchingSpan"
-          },
-          {
-            "$ref": "#/$defs/evaluator_HasMatchingSpan"
-          }
-        ]
-      },
-      "title": "Evaluators",
-      "type": "array"
-    },
-    "$schema": {
-      "type": "string"
-    }
-  },
-  "required": [
-    "cases"
-  ],
-  "title": "Dataset",
-  "type": "object"
-}
diff --git a/2025-05-16-fastapi-demo/pyproject.toml b/2025-05-16-fastapi-demo/pyproject.toml
index 977e1d6..a32f6f5 100644
--- a/2025-05-16-fastapi-demo/pyproject.toml
+++ b/2025-05-16-fastapi-demo/pyproject.toml
@@ -14,6 +14,7 @@ dependencies = [
     "mcp>=1.9.2",
     "python-dotenv>=1.1.0",
     "pydantic-evals>=0.2.9",
+    "logfire-mcp>=0.0.11",
 ]
 
 [tool.ruff]
diff --git a/2025-05-16-fastapi-demo/src/agent.py b/2025-05-16-fastapi-demo/src/agent.py
index 38acad7..2a6cfac 100644
--- a/2025-05-16-fastapi-demo/src/agent.py
+++ b/2025-05-16-fastapi-demo/src/agent.py
@@ -12,12 +12,14 @@
 ROOT_DIR = Path(__file__).parent.parent
 load_dotenv(dotenv_path=ROOT_DIR / ".env")
 
+
 class BotResponse(BaseModel):
     answer: str
     reasoning: str
     reference: str | None = None
     confidence_percentage: Annotated[int, Field(ge=0, le=100)]
 
+
 SYSTEM_PROMPT = dedent(
     """
     You're an all-knowing expert in the PydanticAI agent framework.
@@ -31,7 +33,8 @@ class BotResponse(BaseModel):
     """
 )
 
-def build_agent() -> Agent[None, BotResponse]:
+
+def build_docs_agent() -> Agent[None, BotResponse]:
     api_key = os.getenv("TAVILY_API_KEY")
     assert api_key is not None
 
@@ -40,9 +43,26 @@ def build_agent() -> Agent[None, BotResponse]:
         tools=[tavily_search_tool(api_key)],
         output_type=BotResponse,
         system_prompt=SYSTEM_PROMPT,
-        instrument=True,
     )
 
-async def answer_question(agent: Agent[None, BotResponse], question: str) -> BotResponse:
+
+def build_grammar_agent() -> Agent[None, BotResponse]:
+    return Agent(
+        "openai:gpt-4o-mini",
+        output_type=BotResponse,
+        system_prompt="Fix the punctuation in the BotResponse object fields.",
+    )
+
+
+async def answer_question(
+    agent: Agent[None, BotResponse], question: str
+) -> BotResponse:
     result = await agent.run(user_prompt=question)
     return result.output
+
+
+async def improve_answer(
+    agent: Agent[None, BotResponse], initial_answer: str
+) -> BotResponse:
+    result = await agent.run(user_prompt=initial_answer)
+    return result.output
diff --git a/2025-05-16-fastapi-demo/src/app.py b/2025-05-16-fastapi-demo/src/app.py
index 05eb959..e2443ff 100644
--- a/2025-05-16-fastapi-demo/src/app.py
+++ b/2025-05-16-fastapi-demo/src/app.py
@@ -8,13 +8,10 @@
 from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.orm import sessionmaker, Session
 
-from src.agent import build_agent, answer_question, BotResponse
+from src.agent import answer_question, BotResponse, improve_answer, build_docs_agent, build_grammar_agent
 from src.mcp_agent import answer_mcp_question, MCPBotResponse
 
-logfire.configure(
-    service_name='api',
-    environment='staging'
-)
+logfire.configure(service_name="api", environment="staging", scrubbing=False)
 
 # FastAPI application setup
 app = FastAPI(title="Math, Database and PydanticAI API")
@@ -27,6 +24,7 @@
 SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
 Base = declarative_base()
 logfire.instrument_sqlalchemy(engine)
+logfire.instrument_pydantic_ai()
 logfire.instrument_mcp()
 
 
@@ -74,8 +72,12 @@ def get_db():
 
 
 # Dependency to get agent instance
-def get_agent() -> Agent[None, BotResponse]:
-    return build_agent()
+def get_docs_agent() -> Agent[None, BotResponse]:
+    return build_docs_agent()
+
+# Dependency to get agent instance
+def get_grammar_agent() -> Agent[None, BotResponse]:
+    return build_grammar_agent()
 
 
 # Endpoint 1: Division
@@ -96,7 +98,9 @@ async def fibonacci(n: int):
     Raises an HTTPException if n is negative.
     """
     if n < 0:
-        raise HTTPException(status_code=400, detail="Input must be a non-negative integer")
+        raise HTTPException(
+            status_code=400, detail="Input must be a non-negative integer"
+        )
 
     if n <= 1:
         return {"result": n}
@@ -143,13 +147,19 @@ async def read_item(item_id: int, db: Session = Depends(get_db)):
 
 
 @app.post("/agent/query", response_model=BotResponse)
-async def query_agent(query: AgentQuery, agent: Agent[None, BotResponse] = Depends(get_agent)):
+async def query_agent(
+    query: AgentQuery,
+    docs_agent: Agent[None, BotResponse] = Depends(get_docs_agent),
+    grammar_agent: Agent[None, BotResponse] = Depends(get_grammar_agent)
+):
     """
     Queries the PydanticAI agent with a user question and returns the response.
     """
     logfire.info(f"Querying agent with question: {query.question}")
-    response = await answer_question(agent, query.question)
-    return response
+    initial_response = await answer_question(docs_agent, query.question)
+    improved_response = await improve_answer(grammar_agent, initial_response.answer)
+
+    return improved_response
 
 
 @app.post("/mcp/query", response_model=MCPBotResponse)
@@ -165,4 +175,7 @@ async def query_mcp_agent(query: MCPQuery):
 
 if __name__ == '__main__':  # Fixed double asterisks
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)  # Added this line to complete the if block
\ No newline at end of file
+
+    uvicorn.run(
+        app, host="0.0.0.0", port=8000
+    )  # Added this line to complete the if block
diff --git a/2025-05-16-fastapi-demo/src/mcp_agent.py b/2025-05-16-fastapi-demo/src/mcp_agent.py
index 923cc3f..76d389b 100644
--- a/2025-05-16-fastapi-demo/src/mcp_agent.py
+++ b/2025-05-16-fastapi-demo/src/mcp_agent.py
@@ -1,4 +1,5 @@
 import asyncio
+import os
 from pathlib import Path
 from textwrap import dedent
 from typing import Annotated
@@ -13,6 +14,7 @@
 load_dotenv(dotenv_path=ROOT_DIR / ".env")
 
 # Configure logfire instrumentation
+logfire.instrument_mcp()
 logfire.configure(scrubbing=False, service_name='playwright-browser')
 logfire.instrument_mcp()
 logfire.instrument_pydantic_ai()
@@ -20,6 +22,57 @@
 class MCPBotResponse(BaseModel):
     answer: str
     reasoning: str
+    services_used: list[str] = []
+    confidence_percentage: Annotated[int, Field(ge=0, le=100)]
+
+
+SYSTEM_PROMPT = dedent(
+    """
+    You're a helpful AI assistant with access to browser automation and Logfire telemetry analysis capabilities.
+    
+    File system capabilities:
+    - Read and write files in the demo workspace
+    
+    Logfire capabilities:
+    - Find and analyze exceptions in OpenTelemetry traces grouped by file
+    - Get detailed trace information about exceptions in specific files
+    - Run custom SQL queries on traces and metrics data
+    - Access OpenTelemetry schema information for query building
+    - Analyze application performance and error patterns
+    
+    When working with these services:
+    - Explain what you're doing clearly
+    - Be mindful of website terms of service and respectful browsing practices
+    - Use appropriate time ranges for telemetry queries (max 7 days)
+    - Help identify patterns in application behavior and errors
+    
+    Give a confidence percentage for your answer, from 0 to 100.
+    List any services you used (e.g., "playwright", "logfire") in the services_used field.
+    """
+)
+
+
+logfire_read_token = os.environ['LOGFIRE_READ_TOKEN']
+logfire_mcp = MCPServerStdio(
+    "uvx",
+    args=[
+        "logfire-mcp",
+        f"--read-token={logfire_read_token}",
+    ],
+    tool_prefix="logfire",
+)
+
+# Create the agent with both MCP servers
+agent = Agent(
+    "openai:gpt-4o",
+    output_type=MCPBotResponse,
+    system_prompt=SYSTEM_PROMPT,
+    mcp_servers=[logfire_mcp],
+)
+
+
+async def answer_mcp_question(question: str) -> MCPBotResponse:
+    """Run a question through the MCP-enabled agent."""
     websites_accessed: list[str] = []
     confidence_percentage: Annotated[int, Field(ge=0, le=100)]
 
@@ -58,14 +111,18 @@ async def answer_mcp_question(question: str) -> MCPBotResponse:
         result = await agent.run(user_prompt=question)
         return result.output
 
+
 async def main():
-    """Example usage of the browser agent."""
-    async with agent.run_mcp_servers():
-        result = await agent.run(
-            'Navigate to pydantic.dev and get information about their latest blog post or announcement. '
-            'Summarize what you find.'
-        )
-    print(result.output)
-
-if __name__ == '__main__':
-    asyncio.run(main()) 
\ No newline at end of file
+    """Example usage of the browser and Logfire telemetry agent."""
+    question = (
+        "Help me analyze my application: First, check for any exceptions in traces from the last hour using Logfire. "
+        "Then navigate to the Logfire documentation to get information about best practices for error monitoring. "
+        "Finally, provide recommendations based on what you find."
+    )
+
+    result = await answer_mcp_question(question)
+    print(result)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/2025-05-16-fastapi-demo/tests/evals.py b/2025-05-16-fastapi-demo/tests/evals.py
index 99d9f16..6ac6960 100644
--- a/2025-05-16-fastapi-demo/tests/evals.py
+++ b/2025-05-16-fastapi-demo/tests/evals.py
@@ -13,25 +13,30 @@
 
 from src.agent import build_agent, answer_question, BotResponse
 
+logfire.instrument_pydantic_ai()
 
 class AgentQuery(BaseModel):
     """Input model for agent queries."""
+
     question: str = Field(description="Question to ask the PydanticAI docs agent")
 
 
 class EvalMetadata(BaseModel):
     """Metadata for evaluation cases."""
+
     difficulty: str = Field(description="Difficulty level: easy, medium, hard")
     topic: str = Field(description="Topic area being tested")
-    expected_keywords: list[str] = Field(description="Keywords that should appear in response")
+    expected_keywords: list[str] = Field(
+        description="Keywords that should appear in response"
+    )
 
 
 class ConfidenceEvaluator(Evaluator[AgentQuery, BotResponse]):
     """Evaluator that checks if the agent's confidence meets minimum threshold."""
-    
+
     def __init__(self, min_confidence: int = 70):
         self.min_confidence = min_confidence
-    
+
     def evaluate(self, ctx: EvaluatorContext[AgentQuery, BotResponse]) -> float:
         if ctx.output.confidence_percentage >= self.min_confidence:
             return 1.0
@@ -40,21 +45,20 @@ def evaluate(self, ctx: EvaluatorContext[AgentQuery, BotResponse]) -> float:
 
 class KeywordPresenceEvaluator(Evaluator[AgentQuery, BotResponse]):
     """Evaluator that checks if expected keywords appear in the response."""
-    
+
     def evaluate(self, ctx: EvaluatorContext[AgentQuery, BotResponse]) -> float:
-        if not hasattr(ctx, 'metadata') or not ctx.metadata:
+        if not hasattr(ctx, "metadata") or not ctx.metadata:
             return 0.0
-            
-        expected_keywords = ctx.metadata.get('expected_keywords', [])
+
+        expected_keywords = ctx.metadata.get("expected_keywords", [])
         if not expected_keywords:
             return 1.0
-            
+
         answer_lower = ctx.output.answer.lower()
         found_keywords = [
-            keyword for keyword in expected_keywords 
-            if keyword.lower() in answer_lower
+            keyword for keyword in expected_keywords if keyword.lower() in answer_lower
         ]
-        
+
         return len(found_keywords) / len(expected_keywords)
 
 
@@ -69,97 +73,97 @@ async def query_pydantic_ai_agent(query: AgentQuery) -> BotResponse:
 pydantic_ai_dataset = Dataset[AgentQuery, BotResponse, dict[str, Any]](
     cases=[
         Case(
-            name='basic_agent_creation',
+            name="basic_agent_creation",
             inputs=AgentQuery(question="How do I create a basic PydanticAI agent?"),
             metadata={
-                'difficulty': 'easy',
-                'topic': 'agent_creation',
-                'expected_keywords': ['Agent', 'model', 'system_prompt', 'pydantic_ai']
+                "difficulty": "easy",
+                "topic": "agent_creation",
+                "expected_keywords": ["Agent", "model", "system_prompt", "pydantic_ai"],
             },
-                         evaluators=(
-                 ConfidenceEvaluator(min_confidence=80),
-                 KeywordPresenceEvaluator(),
-                 LLMJudge(
-                     rubric="Response should clearly explain how to create a PydanticAI agent with code examples",
-                     include_input=True
-                 ),
-             )
+            evaluators=(
+                ConfidenceEvaluator(min_confidence=80),
+                KeywordPresenceEvaluator(),
+                LLMJudge(
+                    rubric="Response should clearly explain how to create a PydanticAI agent with code examples",
+                    include_input=True,
+                ),
+            ),
         ),
-        
         Case(
-            name='user_prompt_modification',
-            inputs=AgentQuery(question="How do I change the user prompt in PydanticAI?"),
+            name="user_prompt_modification",
+            inputs=AgentQuery(
+                question="How do I change the user prompt in PydanticAI?"
+            ),
             metadata={
-                'difficulty': 'medium',
-                'topic': 'prompt_handling',
-                'expected_keywords': ['run', 'run_sync', 'user_prompt', 'agent']
+                "difficulty": "medium",
+                "topic": "prompt_handling",
+                "expected_keywords": ["run", "run_sync", "user_prompt", "agent"],
             },
-                         evaluators=(
-                 ConfidenceEvaluator(min_confidence=75),
-                 KeywordPresenceEvaluator(),
-                 LLMJudge(
-                     rubric="Response should explain how to modify user prompts with practical examples",
-                     include_input=True
-                 ),
-             )
+            evaluators=(
+                ConfidenceEvaluator(min_confidence=75),
+                KeywordPresenceEvaluator(),
+                LLMJudge(
+                    rubric="Response should explain how to modify user prompts with practical examples",
+                    include_input=True,
+                ),
+            ),
         ),
-        
         Case(
-            name='tools_integration',
+            name="tools_integration",
             inputs=AgentQuery(question="How do I add tools to a PydanticAI agent?"),
             metadata={
-                'difficulty': 'medium',
-                'topic': 'tools',
-                'expected_keywords': ['tools', 'function', 'decorator', '@tool']
+                "difficulty": "medium",
+                "topic": "tools",
+                "expected_keywords": ["tools", "function", "decorator", "@tool"],
             },
-                         evaluators=(
-                 ConfidenceEvaluator(min_confidence=70),
-                 KeywordPresenceEvaluator(),
-                 LLMJudge(
-                     rubric="Response should explain tools integration with clear examples and best practices",
-                     include_input=True
-                 ),
-             )
+            evaluators=(
+                ConfidenceEvaluator(min_confidence=70),
+                KeywordPresenceEvaluator(),
+                LLMJudge(
+                    rubric="Response should explain tools integration with clear examples and best practices",
+                    include_input=True,
+                ),
+            ),
         ),
     ],
     evaluators=[
         # Global evaluators that apply to all cases
         LLMJudge(
             rubric="Response should be helpful, accurate, and well-structured for PydanticAI documentation questions",
-            model='openai:gpt-4o-mini'  # Use a cost-effective model for evaluation
+            model="openai:gpt-4o-mini",  # Use a cost-effective model for evaluation
         ),
-    ]
+    ],
 )
 
 
 async def run_evaluation(send_to_logfire: bool = True):
     """Run the PydanticAI docs agent evaluation."""
-    
+
     if send_to_logfire:
         logfire.configure(
             send_to_logfire=True,
-            service_name='pydantic-ai-docs-evals',
-            environment='development'
+            service_name="pydantic-ai-docs-evals",
+            environment="development",
         )
-    
+
     print("🚀 Running PydanticAI Docs Agent Evaluation")
     print("=" * 60)
-    
+
     # Run the evaluation
     report = await pydantic_ai_dataset.evaluate(query_pydantic_ai_agent)
-    
+
     # Print detailed results
     report.print(
         include_input=True,
         include_output=True,
         include_durations=True,
-        include_averages=True
+        include_averages=True,
     )
-    
+
     # Save results to file
-    pydantic_ai_dataset.to_file('pydantic_ai_evals.yaml')
+    pydantic_ai_dataset.to_file("pydantic_ai_evals.yaml")
     print(f"\n📁 Dataset saved to: pydantic_ai_evals.yaml")
-    
+
     return report
 
 
diff --git a/2025-05-16-fastapi-demo/uv.lock b/2025-05-16-fastapi-demo/uv.lock
index 088be10..c6246a4 100644
--- a/2025-05-16-fastapi-demo/uv.lock
+++ b/2025-05-16-fastapi-demo/uv.lock
@@ -1,4 +1,5 @@
 version = 1
+revision = 2
 requires-python = ">=3.13"
 
 [[package]]
@@ -8,6 +9,7 @@ source = { virtual = "." }
 dependencies = [
     { name = "fastapi" },
     { name = "logfire", extra = ["fastapi", "sqlalchemy"] },
+    { name = "logfire-mcp" },
     { name = "mcp" },
     { name = "opentelemetry-api" },
     { name = "pydantic-ai" },
@@ -27,6 +29,7 @@ dev = [
 requires-dist = [
     { name = "fastapi", specifier = ">=0.115.12" },
     { name = "logfire", extras = ["fastapi", "sqlalchemy"], specifier = ">=3.14.0" },
+    { name = "logfire-mcp", specifier = ">=0.0.11" },
     { name = "mcp", specifier = ">=1.9.2" },
     { name = "opentelemetry-api", specifier = ">=1.20.0" },
     { name = "pydantic-ai", specifier = ">=0.2.9" },
@@ -44,14 +47,14 @@ dev = [{ name = "ruff", specifier = ">=0.11.6" }]
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 version = "0.7.0"
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+sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
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 [[package]]
 name = "anthropic"
-version = "0.52.0"
+version = "0.52.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "anyio" },
@@ -62,9 +65,9 @@ dependencies = [
     { name = "sniffio" },
     { name = "typing-extensions" },
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 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/77/3b/6f67f4e061d73cfaffc44dd41cbbe8b09efe1ec37b8135a2bcc043736d62/anthropic-0.52.2-py3-none-any.whl", hash = "sha256:00d52555f503e81e21aff0103db04cd93979cdf87ce8dd43c660ca6deae83ac6", size = 286262, upload-time = "2025-06-02T11:27:57.536Z" },
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