uprev to v0.0.19 (#696)

README.md

@@ -58,6 +58,9 @@ This is useful for testing and eval-driven iterative development.
 * __Streamed Responses__
 Provides the ability to [stream](https://ai.pydantic.dev/results/#streamed-results) LLM outputs continuously, with immediate validation, ensuring rapid and accurate results.
 
+* __Graph Support__
+[Pydantic Graph](https://ai.pydantic.dev/graph) provides a powerful way to define graphs using typing hints, this is useful in complex applications where standard control flow can degrade to spaghetti code.
+
 ## In Beta!
 
 PydanticAI is in early beta, the API is still subject to change and there's a lot more to do.

docs/graph.md

@@ -194,7 +194,7 @@ stateDiagram-v2
 
 The "state" concept in `pydantic-graph` provides an optional way to access and mutate an object (often a `dataclass` or Pydantic model) as nodes run in a graph. If you think of Graphs as a production line, then you state is the engine being passed along the line and built up by each node as the graph is run.
 
-In future, we intend to extend `pydantic-graph` to provide state persistence with the state recorded after each node is run, see [#695](https://github.com/pydantic/pydantic-ai/issues/695).
+In the future, we intend to extend `pydantic-graph` to provide state persistence with the state recorded after each node is run, see [#695](https://github.com/pydantic/pydantic-ai/issues/695).
 
 Here's an example of a graph which represents a vending machine where the user may insert coins and select a product to purchase.
 

docs/index.md

@@ -38,6 +38,9 @@ This is useful for testing and eval-driven iterative development.
 :material-sine-wave:{ .md .middle }&nbsp;<strong class="vertical-middle">Streamed Responses</strong><br>
 Provides the ability to [stream](results.md#streamed-results) LLM outputs continuously, with immediate validation, ensuring rapid and accurate results.
 
+:material-graph:{ .md .middle .graph-green }&nbsp;<strong class="vertical-middle">Graph Support</strong><br>
+[Pydantic Graph](graph.md) provides a powerful way to define graphs using typing hints, this is useful in complex applications where standard control flow can degrade to spaghetti code.
+
 !!! example "In Beta"
     PydanticAI is in early beta, the API is still subject to change and there's a lot more to do.
     [Feedback](https://github.com/pydantic/pydantic-ai/issues) is very welcome!

examples/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "pydantic-ai-examples"
-version = "0.0.18"
+version = "0.0.19"
 description = "Examples of how to use PydanticAI and what it can do."
 authors = [
     { name = "Samuel Colvin", email = "[email protected]" },
@@ -34,7 +34,7 @@ classifiers = [
 ]
 requires-python = ">=3.9"
 dependencies = [
-    "pydantic-ai-slim[openai,vertexai,groq,anthropic]==0.0.18",
+    "pydantic-ai-slim[openai,vertexai,groq,anthropic]==0.0.19",
     "asyncpg>=0.30.0",
     "fastapi>=0.115.4",
     "logfire[asyncpg,fastapi,sqlite3]>=2.6",

pydantic_ai_slim/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "pydantic-ai-slim"
-version = "0.0.18"
+version = "0.0.19"
 description = "Agent Framework / shim to use Pydantic with LLMs, slim package"
 authors = [
     { name = "Samuel Colvin", email = "[email protected]" },
@@ -44,7 +44,7 @@ dependencies = [
 [project.optional-dependencies]
 # WARNING if you add optional groups, please update docs/install.md
 logfire = ["logfire>=2.3"]
-graph = ["pydantic-graph==0.0.18"]
+graph = ["pydantic-graph==0.0.19"]
 openai = ["openai>=1.54.3"]
 vertexai = ["google-auth>=2.36.0", "requests>=2.32.3"]
 anthropic = ["anthropic>=0.40.0"]

pydantic_graph/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "pydantic-graph"
-version = "0.0.18"
+version = "0.0.19"
 description = "Graph and state machine library"
 authors = [
     { name = "Samuel Colvin", email = "[email protected]" },

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "pydantic-ai"
-version = "0.0.18"
+version = "0.0.19"
 description = "Agent Framework / shim to use Pydantic with LLMs"
 authors = [
     { name = "Samuel Colvin", email = "[email protected]" },
@@ -37,7 +37,7 @@ classifiers = [
 ]
 requires-python = ">=3.9"
 
-dependencies = ["pydantic-ai-slim[graph,openai,vertexai,groq,anthropic,mistral]==0.0.18"]
+dependencies = ["pydantic-ai-slim[graph,openai,vertexai,groq,anthropic,mistral]==0.0.19"]
 
 [project.urls]
 Homepage = "https://ai.pydantic.dev"
@@ -46,7 +46,7 @@ Documentation = "https://ai.pydantic.dev"
 Changelog = "https://github.com/pydantic/pydantic-ai/releases"
 
 [project.optional-dependencies]
-examples = ["pydantic-ai-examples==0.0.18"]
+examples = ["pydantic-ai-examples==0.0.19"]
 logfire = ["logfire>=2.3"]
 
 [tool.uv.sources]

uprev.py

@@ -51,11 +51,11 @@ def sub_version(m: re.Match[str]) -> str:
 
 def replace_deps_version(text: str) -> tuple[str, int]:
     ovr = re.escape(old_version)
-    text, c = re.subn(f'(pydantic-ai-.+?==){ovr}', fr'\g<1>{version}', text, count=5)
+    text, c1 = re.subn(f'(pydantic-(?:ai-.+?|graph)==){ovr}', fr'\g<1>{version}', text, count=5)
     text, c2 = re.subn(
         fr'^(version ?= ?)(["\']){ovr}\2$', fr'\g<1>\g<2>{version}\g<2>', text, count=5, flags=re.M
     )
-    return text, c + c2
+    return text, c1 + c2
 
 
 root_pp_text, count_root = replace_deps_version(root_pp_text)
@@ -72,7 +72,7 @@ def replace_deps_version(text: str) -> tuple[str, int]:
 graph_pp_text = graph_pp.read_text()
 graph_pp_text, count_graph = replace_deps_version(graph_pp_text)
 
-if count_root == 2 and count_ex == 2 and count_slim == 1 and count_graph == 1:
+if count_root == 2 and count_ex == 2 and count_slim == 2 and count_graph == 1:
     root_pp.write_text(root_pp_text)
     examples_pp.write_text(examples_pp_text)
     slim_pp.write_text(slim_pp_text)