Merge branch 'strands-agents:main' into pruning

Author: roeetal

.codecov.yml

@@ -0,0 +1,11 @@
+coverage:
+  status:
+    project:
+      default:
+        target: 90%    # overall coverage threshold
+    patch:
+      default:
+        target: 90%    # patch coverage threshold
+        base: auto
+        # Only post patch coverage on decreases
+        only_pulls: true

.github/workflows/auto-close.yml

@@ -11,6 +11,11 @@ on:
         default: 'false'
         type: boolean
 
+permissions:
+  contents: read
+  issues: write
+  pull-requests: write
+
 jobs:
   auto-close:
     runs-on: ubuntu-latest

.github/workflows/pr-size-labeler.yml

@@ -0,0 +1,58 @@
+name: PR Size Labeler
+
+on:
+  pull_request_target:
+    branches: main
+
+jobs:
+  label-size:
+    runs-on: ubuntu-latest
+    permissions:
+      pull-requests: write
+      issues: write
+    steps:
+      - name: Calculate PR size and apply label
+        uses: actions/github-script@v8
+        with:
+          script: |
+            const pr = context.payload.pull_request;
+            const totalChanges = pr.additions + pr.deletions;
+            
+            // Remove existing size labels
+            const labels = await github.rest.issues.listLabelsOnIssue({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.payload.pull_request.number
+            });
+            
+            for (const label of labels.data) {
+              if (label.name.startsWith('size/')) {
+                await github.rest.issues.removeLabel({
+                  owner: context.repo.owner,
+                  repo: context.repo.repo,
+                  issue_number: context.payload.pull_request.number,
+                  name: label.name
+                });
+              }
+            }
+            
+            // Determine and apply new size label
+            let sizeLabel;
+            if (totalChanges <= 20) sizeLabel = 'size/xs';
+            else if (totalChanges <= 100) sizeLabel = 'size/s';
+            else if (totalChanges <= 500) sizeLabel = 'size/m';
+            else if (totalChanges <= 1000) sizeLabel = 'size/l';
+            else {
+              sizeLabel = 'size/xl';
+            }
+            
+            await github.rest.issues.addLabels({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: context.payload.pull_request.number,
+              labels: [sizeLabel]
+            });
+
+            if (sizeLabel === 'size/xl') {
+              core.setFailed(`PR is too large (${totalChanges} lines). Please split into smaller PRs.`);
+            }

.github/workflows/test-lint.yml

@@ -66,6 +66,11 @@ jobs:
         id: tests
         run: hatch test tests --cover
         continue-on-error: false
+
+      - name: Upload coverage reports to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
   lint:
     name: Lint
     runs-on: ubuntu-latest
@@ -90,5 +95,5 @@ jobs:
 
       - name: Run lint
         id: lint
-        run: hatch run test-lint
+        run: hatch fmt --linter --check
         continue-on-error: false

.gitignore

@@ -11,4 +11,5 @@ __pycache__*
 .vscode
 dist
 repl_state
-.kiro
+.kiro
+uv.lock

.pre-commit-config.yaml

@@ -3,14 +3,14 @@ repos:
     hooks:
       - id: hatch-format
         name: Format code
-        entry: hatch run test-format
+        entry: hatch fmt --formatter --check
         language: system
         pass_filenames: false
         types: [python]
         stages: [pre-commit]
       - id: hatch-lint
         name: Lint code
-        entry: hatch run test-lint
+        entry: hatch fmt --linter --check
         language: system
         pass_filenames: false
         types: [python]

CONTRIBUTING.md

@@ -36,6 +36,18 @@ Before starting work on any issue:
 3. Wait for maintainer confirmation before beginning significant work
 
 
+## Development Tenets
+Our team follows these core principles when designing and implementing features. These tenets help us make consistent decisions, resolve trade-offs, and maintain the quality and coherence of the SDK. When contributing, please consider how your changes align with these principles:
+
+1. **Simple at any scale:** We believe that simple things should be simple. The same clean abstractions that power a weekend prototype should scale effortlessly to production workloads. We reject the notion that enterprise-grade means enterprise-complicated - Strands remains approachable whether it's your first agent or your millionth.
+2. **Extensible by design:** We allow for as much configuration as possible, from hooks to model providers, session managers, tools, etc. We meet customers where they are with flexible extension points that are simple to integrate with.
+3. **Composability:** Primitives are building blocks with each other. Each feature of Strands is developed with all other features in mind, they are consistent and complement one another.
+4. **The obvious path is the happy path:** Through intuitive naming, helpful error messages, and thoughtful API design, we guide developers toward correct patterns and away from common pitfalls.
+5. **We are accessible to humans and agents:** Strands is designed for both humans and AI to understand equally well. We don’t take shortcuts on curated DX for humans and we go the extra mile to make sure coding assistants can help you use those interfaces the right way.
+6. **Embrace common standards:** We respect what came before, and do not want to reinvent something that is already widely adopted or done better.
+
+When proposing solutions or reviewing code, we reference these principles to guide our decisions. If two approaches seem equally valid, we choose the one that best aligns with our tenets.
+
 ## Development Environment
 
 This project uses [hatchling](https://hatch.pypa.io/latest/build/#hatchling) as the build backend and [hatch](https://hatch.pypa.io/latest/) for development workflow management.

README.md

@@ -37,7 +37,7 @@ Strands Agents is a simple yet powerful SDK that takes a model-driven approach t
 ## Feature Overview
 
 - **Lightweight & Flexible**: Simple agent loop that just works and is fully customizable
-- **Model Agnostic**: Support for Amazon Bedrock, Anthropic, LiteLLM, Llama, Ollama, OpenAI, Writer, and custom providers
+- **Model Agnostic**: Support for Amazon Bedrock, Anthropic, Gemini, LiteLLM, Llama, Ollama, OpenAI, Writer, and custom providers
 - **Advanced Capabilities**: Multi-agent systems, autonomous agents, and streaming support
 - **Built-in MCP**: Native support for Model Context Protocol (MCP) servers, enabling access to thousands of pre-built tools
 
@@ -129,6 +129,7 @@ from strands import Agent
 from strands.models import BedrockModel
 from strands.models.ollama import OllamaModel
 from strands.models.llamaapi import LlamaAPIModel
+from strands.models.gemini import GeminiModel
 from strands.models.llamacpp import LlamaCppModel
 
 # Bedrock
@@ -140,6 +141,17 @@ bedrock_model = BedrockModel(
 agent = Agent(model=bedrock_model)
 agent("Tell me about Agentic AI")
 
+# Google Gemini
+gemini_model = GeminiModel(
+  client_args={
+    "api_key": "your_gemini_api_key",
+  },
+  model_id="gemini-2.5-flash",
+  params={"temperature": 0.7}
+)
+agent = Agent(model=gemini_model)
+agent("Tell me about Agentic AI")
+
 # Ollama
 ollama_model = OllamaModel(
   host="http://localhost:11434",
@@ -159,12 +171,16 @@ response = agent("Tell me about Agentic AI")
 Built-in providers:
  - [Amazon Bedrock](https://strandsagents.com/latest/user-guide/concepts/model-providers/amazon-bedrock/)
  - [Anthropic](https://strandsagents.com/latest/user-guide/concepts/model-providers/anthropic/)
+ - [Gemini](https://strandsagents.com/latest/user-guide/concepts/model-providers/gemini/)
+ - [Cohere](https://strandsagents.com/latest/user-guide/concepts/model-providers/cohere/)
  - [LiteLLM](https://strandsagents.com/latest/user-guide/concepts/model-providers/litellm/)
  - [llama.cpp](https://strandsagents.com/latest/user-guide/concepts/model-providers/llamacpp/)
  - [LlamaAPI](https://strandsagents.com/latest/user-guide/concepts/model-providers/llamaapi/)
+ - [MistralAI](https://strandsagents.com/latest/user-guide/concepts/model-providers/mistral/)
  - [Ollama](https://strandsagents.com/latest/user-guide/concepts/model-providers/ollama/)
  - [OpenAI](https://strandsagents.com/latest/user-guide/concepts/model-providers/openai/)
- - [Writer](https://strandsagents.com/latest/documentation/docs/user-guide/concepts/model-providers/writer/)
+ - [SageMaker](https://strandsagents.com/latest/user-guide/concepts/model-providers/sagemaker/)
+ - [Writer](https://strandsagents.com/latest/user-guide/concepts/model-providers/writer/)
 
 Custom providers can be implemented using [Custom Providers](https://strandsagents.com/latest/user-guide/concepts/model-providers/custom_model_provider/)
 

pyproject.toml

@@ -30,6 +30,7 @@ dependencies = [
     "boto3>=1.26.0,<2.0.0",
     "botocore>=1.29.0,<2.0.0",
     "docstring_parser>=0.15,<1.0",
+    "jsonschema>=4.0.0,<5.0.0",
     "mcp>=1.11.0,<2.0.0",
     "pydantic>=2.4.0,<3.0.0",
     "typing-extensions>=4.13.2,<5.0.0",
@@ -42,7 +43,8 @@ dependencies = [
 
 [project.optional-dependencies]
 anthropic = ["anthropic>=0.21.0,<1.0.0"]
-litellm = ["litellm>=1.75.9,<2.0.0", "openai>=1.68.0,<1.108.0"]
+gemini = ["google-genai>=1.32.0,<2.0.0"]
+litellm = ["litellm>=1.75.9,<2.0.0", "openai>=1.68.0,<1.110.0"]
 llamaapi = ["llama-api-client>=0.1.0,<1.0.0"]
 mistral = ["mistralai>=1.8.2"]
 ollama = ["ollama>=0.4.8,<1.0.0"]
@@ -54,9 +56,9 @@ sagemaker = [
 ]
 otel = ["opentelemetry-exporter-otlp-proto-http>=1.30.0,<2.0.0"]
 docs = [
-    "sphinx>=5.0.0,<6.0.0",
+    "sphinx>=5.0.0,<9.0.0",
     "sphinx-rtd-theme>=1.0.0,<2.0.0",
-    "sphinx-autodoc-typehints>=1.12.0,<2.0.0",
+    "sphinx-autodoc-typehints>=1.12.0,<4.0.0",
 ]
 
 a2a = [
@@ -67,7 +69,7 @@ a2a = [
     "fastapi>=0.115.12,<1.0.0",
     "starlette>=0.46.2,<1.0.0",
 ]
-all = ["strands-agents[a2a,anthropic,docs,litellm,llamaapi,mistral,ollama,openai,writer,sagemaker,otel]"]
+all = ["strands-agents[a2a,anthropic,docs,gemini,litellm,llamaapi,mistral,ollama,openai,writer,sagemaker,otel]"]
 
 dev = [
     "commitizen>=4.4.0,<5.0.0",
@@ -77,7 +79,7 @@ dev = [
     "pre-commit>=3.2.0,<4.4.0",
     "pytest>=8.0.0,<9.0.0",
     "pytest-cov>=7.0.0,<8.0.0",
-    "pytest-asyncio>=1.0.0,<1.2.0",
+    "pytest-asyncio>=1.0.0,<1.3.0",
     "pytest-xdist>=3.0.0,<4.0.0",
     "ruff>=0.13.0,<0.14.0",
 ]
@@ -130,7 +132,7 @@ extra-args = ["-n", "auto", "-vv"]
 dependencies = [
     "pytest>=8.0.0,<9.0.0",
     "pytest-cov>=7.0.0,<8.0.0",
-    "pytest-asyncio>=1.0.0,<1.2.0",
+    "pytest-asyncio>=1.0.0,<1.3.0",
     "pytest-xdist>=3.0.0,<4.0.0",
     "moto>=5.1.0,<6.0.0",
 ]
@@ -169,7 +171,8 @@ test = "hatch test {args}"
 test-integ = "hatch test tests_integ {args}"
 
 prepare = [
-    "hatch run test-format",
+    "hatch run format",
+    "hatch run lint",
     "hatch run test-lint",
     "hatch test --all"
 ]

src/strands/__init__.py

@@ -5,4 +5,12 @@
 from .tools.decorator import tool
 from .types.tools import ToolContext
 
-__all__ = ["Agent", "agent", "models", "tool", "types", "telemetry", "ToolContext"]
+__all__ = [
+    "Agent",
+    "agent",
+    "models",
+    "tool",
+    "ToolContext",
+    "types",
+    "telemetry",
+]