.NET: Restore ambient client-header scope between non-streaming ClientHeadersAgent runs (#6517)

* Restore ambient client-header scope between non-streaming runs (#6516)

Make ClientHeadersAgent.RunCoreAsync async + await so the per-run
ClientHeadersScope is unwound on return, matching the streaming path.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Assert per-run on wire instead of brittle exact request count

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

.github/.linkspector.yml

@@ -20,7 +20,10 @@ ignorePatterns:
   - pattern: "https://your-resource.openai.azure.com/"
   - pattern: "http://host.docker.internal"
   - pattern: "https://openai.github.io/openai-agents-js/openai/agents/classes/"
-  - pattern: "https:\/\/dotnet.microsoft.com\/download"
+  # dotnet.microsoft.com bot-blocks CI link checkers with intermittent 403s on any
+  # path (including localized variants like /en-us/download/...), so ignore the
+  # whole domain rather than just /download.
+  - pattern: "https:\/\/dotnet.microsoft.com"
   - pattern: "https://github.com/Rel1cx/eslint-react"
 # excludedDirs:
   # Folders which include links to localhost, since it's not ignored with regular expressions

.github/pull_request_template.md

@@ -1,23 +1,43 @@
-### Motivation and Context
+### Motivation & Context
 
 <!-- Thank you for your contribution to the Agent Framework repo!
 Please help reviewers and future users, providing the following information:
   1. Why is this change required?
   2. What problem does it solve?
   3. What scenario does it contribute to?
-  4. If it fixes an open issue, please link to the issue here.
+  4. If it fixes an open issue, please link to the issue below.
 -->
 
-### Description
+### Description & Review Guide
 
 <!-- Describe your changes, the overall approach, the underlying design.
+     Highlight what you want the reviewers to focus on.
      These notes will help understanding how your code works. Thanks! -->
 
+- **What are the major changes?**
+- **What is the impact of these changes?**
+- **What do you want reviewers to focus on?**
+<!-- NOTE FOR AUTOMATED/AI REVIEWERS: the "What do you want reviewers to focus on?"
+     item above is intended for human reviewers only. Automated/AI reviewers should
+     ignore it and review the entire change rather than narrowing scope to it. -->
+
+
+### Related Issue
+
+<!-- Which issue does this PR fix? Link it using a GitHub closing keyword so it is
+     closed automatically when this PR is merged, e.g. "Fixes #123" or "Closes #123".
+     PRs that are not linked to an issue may be closed, no matter how valid the change is.
+     Also check whether an open PR already exists for this issue; if so,
+     explain how this PR is different. -->
+
+Fixes #
+
 ### Contribution Checklist
 
 <!-- Before submitting this PR, please make sure: -->
 
 - [ ] The code builds clean without any errors or warnings
-- [ ] The PR follows the [Contribution Guidelines](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md)
 - [ ] All unit tests pass, and I have added new tests where possible
-- [ ] **Is this a breaking change?** If yes, add "[BREAKING]" prefix to the title of the PR.
+- [ ] The PR follows the [Contribution Guidelines](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md)
+- [ ] This PR is linked to an issue and there is no other open PR for this issue (see Related Issue above).
+- [x] **This is not a breaking change.** If it _is_ a breaking change, add the `breaking change` label (or add "[BREAKING]" to the title prefix, before or after any language prefix) — a workflow keeps the label and title prefix in sync automatically.

.github/scripts/title_prefix.js

@@ -0,0 +1,253 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+const BREAKING_CHANGE_LABEL = 'breaking change';
+const BREAKING_PREFIX = '[BREAKING]';
+
+const DEFAULT_PREFIX_LABELS = Object.freeze({
+  python: 'Python',
+  '.NET': '.NET',
+});
+
+const DEFAULT_BRACKET_PREFIX_LABELS = Object.freeze({
+  [BREAKING_CHANGE_LABEL]: BREAKING_PREFIX,
+});
+
+function escapeRegExp(value) {
+  return value.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
+}
+
+function getMatchingValueByKey(valuesByKey, keyToFind) {
+  const matchingKey = Object.keys(valuesByKey).find((key) => key.toLowerCase() === keyToFind.toLowerCase());
+  return matchingKey === undefined ? null : valuesByKey[matchingKey];
+}
+
+function getPrefixPattern(prefixes) {
+  return prefixes.map(escapeRegExp).join('|');
+}
+
+function canonicalizePrefix(prefix, prefixes) {
+  return prefixes.find((knownPrefix) => knownPrefix.toLowerCase() === prefix.toLowerCase()) ?? prefix;
+}
+
+function normalizeLeadingBracketPrefix(title, bracketPrefixes) {
+  const bracketPattern = getPrefixPattern(bracketPrefixes);
+  if (!bracketPattern) {
+    return title;
+  }
+
+  const leadingBracketPrefix = new RegExp(`^(${bracketPattern})(?=\\s|$)`, 'i');
+  return title.replace(
+    leadingBracketPrefix,
+    (bracketPrefix) => canonicalizePrefix(bracketPrefix, bracketPrefixes),
+  );
+}
+
+function parseLeadingTitlePrefix(title, titlePrefixes) {
+  const titlePrefixPattern = getPrefixPattern(titlePrefixes);
+  if (!titlePrefixPattern) {
+    return null;
+  }
+
+  const match = title.match(new RegExp(`^(${titlePrefixPattern}):\\s*`, 'i'));
+  if (!match) {
+    return null;
+  }
+
+  return {
+    prefix: canonicalizePrefix(match[1], titlePrefixes),
+    rest: title.slice(match[0].length).trimStart(),
+  };
+}
+
+function removeBracketPrefixToken(title, bracketPrefix) {
+  const bracketPrefixPattern = escapeRegExp(bracketPrefix);
+  return title
+    .replace(new RegExp(`(^|\\s+)${bracketPrefixPattern}(?=\\s|$)`, 'ig'), '$1')
+    .replace(/\s{2,}/g, ' ')
+    .trim();
+}
+
+function addTitlePrefix(title, prefix, bracketPrefixes = Object.values(DEFAULT_BRACKET_PREFIX_LABELS)) {
+  const bracketPattern = getPrefixPattern(bracketPrefixes);
+  const prefixPattern = escapeRegExp(prefix);
+
+  if (bracketPattern) {
+    const bracketThenTitlePrefix = new RegExp(`^(${bracketPattern})(\\s+)(${prefixPattern})(?=:)`, 'i');
+    if (bracketThenTitlePrefix.test(title)) {
+      return title.replace(
+        bracketThenTitlePrefix,
+        (match, bracketPrefix, spacing) => `${canonicalizePrefix(bracketPrefix, bracketPrefixes)}${spacing}${prefix}`,
+      );
+    }
+
+    title = normalizeLeadingBracketPrefix(title, bracketPrefixes);
+  }
+
+  if (!title.startsWith(`${prefix}: `)) {
+    const existingTitlePrefix = new RegExp(`^${prefixPattern}:\\s*`, 'i');
+    if (existingTitlePrefix.test(title)) {
+      return title.replace(existingTitlePrefix, `${prefix}: `);
+    }
+
+    return `${prefix}: ${title}`;
+  }
+
+  return title;
+}
+
+function hasBracketPrefix(title, bracketPrefix, titlePrefixes = Object.values(DEFAULT_PREFIX_LABELS)) {
+  const bracketPrefixPattern = escapeRegExp(bracketPrefix);
+  const leadingBracketPrefix = new RegExp(`^${bracketPrefixPattern}(?=\\s|$)`, 'i');
+  if (leadingBracketPrefix.test(title)) {
+    return true;
+  }
+
+  const leadingTitlePrefix = parseLeadingTitlePrefix(title, titlePrefixes);
+  if (!leadingTitlePrefix) {
+    return false;
+  }
+
+  return leadingBracketPrefix.test(leadingTitlePrefix.rest);
+}
+
+function addBracketPrefix(title, bracketPrefix, titlePrefixes = Object.values(DEFAULT_PREFIX_LABELS)) {
+  const bracketPrefixPattern = escapeRegExp(bracketPrefix);
+  const leadingBracketPrefix = new RegExp(`^${bracketPrefixPattern}(?=\\s|$)`, 'i');
+  if (leadingBracketPrefix.test(title)) {
+    return title.replace(leadingBracketPrefix, bracketPrefix);
+  }
+
+  const leadingTitlePrefix = parseLeadingTitlePrefix(title, titlePrefixes);
+  if (leadingTitlePrefix) {
+    if (leadingBracketPrefix.test(leadingTitlePrefix.rest)) {
+      const normalizedRest = leadingTitlePrefix.rest.replace(leadingBracketPrefix, bracketPrefix);
+      return `${leadingTitlePrefix.prefix}: ${normalizedRest}`;
+    }
+
+    const titleWithoutBracketPrefix = removeBracketPrefixToken(leadingTitlePrefix.rest, bracketPrefix);
+    return `${leadingTitlePrefix.prefix}: ${bracketPrefix}`
+      + (titleWithoutBracketPrefix ? ` ${titleWithoutBracketPrefix}` : '');
+  }
+
+  const titleWithoutBracketPrefix = removeBracketPrefixToken(title, bracketPrefix);
+  return `${bracketPrefix}${titleWithoutBracketPrefix ? ` ${titleWithoutBracketPrefix}` : ''}`;
+}
+
+function hasLabel(labels, labelName) {
+  return labels.some((label) => label.toLowerCase() === labelName.toLowerCase());
+}
+
+function getCurrentTitle(context) {
+  switch (context.eventName) {
+    case 'issues':
+      return context.payload.issue.title;
+    case 'pull_request_target':
+      return context.payload.pull_request.title;
+    default:
+      throw new Error(`Unrecognized eventName: ${context.eventName}`);
+  }
+}
+
+async function updateTitleForAddedLabel({
+  github,
+  context,
+  core,
+  prefixLabels = DEFAULT_PREFIX_LABELS,
+  bracketPrefixLabels = DEFAULT_BRACKET_PREFIX_LABELS,
+}) {
+  const labelAdded = context.payload.label?.name;
+  if (!labelAdded) {
+    throw new Error('This script must be run from a labeled event.');
+  }
+
+  const currentTitle = getCurrentTitle(context);
+  let newTitle = null;
+
+  const titlePrefix = getMatchingValueByKey(prefixLabels, labelAdded);
+  if (titlePrefix !== null) {
+    newTitle = addTitlePrefix(currentTitle, titlePrefix, Object.values(bracketPrefixLabels));
+  }
+
+  const bracketPrefix = getMatchingValueByKey(bracketPrefixLabels, labelAdded);
+  if (bracketPrefix !== null) {
+    newTitle = addBracketPrefix(currentTitle, bracketPrefix, Object.values(prefixLabels));
+  }
+
+  if (newTitle === null) {
+    core.info(`No title prefix configured for label "${labelAdded}".`);
+    return { updated: false, newTitle: currentTitle };
+  }
+
+  if (newTitle === currentTitle) {
+    core.info(`Title already includes the prefix for label "${labelAdded}".`);
+    return { updated: false, newTitle };
+  }
+
+  switch (context.eventName) {
+    case 'issues':
+      await github.rest.issues.update({
+        issue_number: context.issue.number,
+        owner: context.repo.owner,
+        repo: context.repo.repo,
+        title: newTitle,
+      });
+      break;
+
+    case 'pull_request_target':
+      await github.rest.pulls.update({
+        pull_number: context.issue.number,
+        owner: context.repo.owner,
+        repo: context.repo.repo,
+        title: newTitle,
+      });
+      break;
+
+    default:
+      throw new Error(`Unrecognized eventName: ${context.eventName}`);
+  }
+
+  return { updated: true, newTitle };
+}
+
+async function syncBreakingChangeLabelFromTitle({
+  github,
+  context,
+  core,
+  labelName = BREAKING_CHANGE_LABEL,
+  bracketPrefix = BREAKING_PREFIX,
+  titlePrefixes = Object.values(DEFAULT_PREFIX_LABELS),
+}) {
+  const pullRequest = context.payload.pull_request;
+  if (!pullRequest) {
+    throw new Error('This script must be run from a pull_request_target event.');
+  }
+
+  const title = pullRequest.title || '';
+  if (!hasBracketPrefix(title, bracketPrefix, titlePrefixes)) {
+    core.info(`Title does not include ${bracketPrefix} in the title prefix.`);
+    return { added: false };
+  }
+
+  const labels = pullRequest.labels?.map((label) => label.name).filter(Boolean) ?? [];
+  if (hasLabel(labels, labelName)) {
+    core.info(`PR already has the "${labelName}" label.`);
+    return { added: false };
+  }
+
+  await github.rest.issues.addLabels({
+    issue_number: context.issue.number,
+    owner: context.repo.owner,
+    repo: context.repo.repo,
+    labels: [labelName],
+  });
+
+  return { added: true };
+}
+
+module.exports = {
+  addBracketPrefix,
+  addTitlePrefix,
+  hasBracketPrefix,
+  syncBreakingChangeLabelFromTitle,
+  updateTitleForAddedLabel,
+};

.github/skills/pull-requests/SKILL.md

@@ -0,0 +1,116 @@
+---
+name: pull-requests
+description: >
+  Guidance for creating pull requests and handling PR review comments in the
+  Agent Framework repository. Use this when writing a PR description (filling out
+  the PR template) or when responding to and resolving review comments on an
+  existing PR.
+---
+
+# Pull Request Workflow
+
+This skill covers two tasks: (1) writing a high-quality PR description, and
+(2) handling review comments on an existing PR.
+
+## 1. Writing the PR description
+
+Always follow the repository PR template at
+[`.github/pull_request_template.md`](../../pull_request_template.md). Keep its
+exact structure and headings. Fill every section:
+
+### `### Motivation & Context`
+Explain *why* the change is needed: the problem it solves and the scenario it
+contributes to. Describe the net change relative to `main` — this is implied, so
+do **not** spell out "vs main" explicitly.
+
+### `### Description & Review Guide`
+Describe the changes, the overall approach, and the design. Answer the three
+prompts:
+- **What are the major changes?**
+- **What is the impact of these changes?**
+- **What do you want reviewers to focus on?** — This item is for **human
+  reviewers only**. Automated/AI reviewers must ignore it and review the entire
+  change rather than narrowing scope to it.
+
+### `### Related Issue`
+Link the issue the PR fixes using a GitHub closing keyword (`Fixes #123` /
+`Closes #123`) so it closes automatically on merge. A PR with no linked issue may
+be closed regardless of how valid the change is. Before opening, confirm there is
+no other open PR for the same issue; if there is, explain how this PR differs.
+
+### `### Contribution Checklist`
+Check every item that applies. For the breaking-change item:
+- Leave **"This is not a breaking change."** checked for the common case.
+- If the change **is** breaking, add the `breaking change` label **or** put
+  `[BREAKING]` in the title prefix, before or after a language prefix such as
+  `Python:` or `.NET:` — workflows keep the label and the title prefix in sync
+  automatically (see `.github/workflows/label-title-prefix.yml` and
+  `.github/workflows/label-pr.yml`).
+
+### Do not
+- Do **not** add ad-hoc sections such as "Validation" or "Tests run"; CI/CD and
+  the checklist already cover validation status.
+- Do **not** remove or reorder the template's headings.
+
+### Creating the PR
+Open new PRs as **drafts** until they are ready for review. Example:
+
+```bash
+gh pr create --repo microsoft/agent-framework --base main \
+  --head <your-fork-owner>:<branch> --draft \
+  --title "<concise title>" --body "<body following the template>"
+```
+
+## 2. Handling review comments
+
+When a PR receives review comments, follow this sequence — **do not start editing
+code before the user has reviewed the plan**:
+
+1. **Review the comments.** Read every review comment and thread on the PR,
+   including inline code comments and general review summaries.
+2. **Make a plan.** Produce a concrete plan describing how each comment will be
+   addressed (or why it should not be, with reasoning).
+3. **Let the user review the plan.** Present the plan and wait for the user's
+   approval or adjustments before implementing anything.
+4. **Implement.** Make the agreed changes.
+5. **Reply to every comment.** Add a reply to **all** comments explaining how it
+   was addressed (or the agreed outcome) — leave none unanswered.
+6. **Resolve resolved threads.** Mark a review thread as resolved only when the
+   comment has actually been addressed.
+
+### Useful commands
+
+List review comments and threads:
+
+```bash
+# Inline review comments
+gh api repos/{owner}/{repo}/pulls/{pr}/comments
+
+# Review threads with resolution state (GraphQL)
+gh api graphql -f query='
+  query($owner:String!,$repo:String!,$pr:Int!){
+    repository(owner:$owner,name:$repo){
+      pullRequest(number:$pr){
+        reviewThreads(first:100){
+          nodes{ id isResolved comments(first:50){ nodes{ id body author{login} } } }
+        }
+      }
+    }
+  }' -F owner={owner} -F repo={repo} -F pr={pr}
+```
+
+Reply to an inline review comment:
+
+```bash
+gh api repos/{owner}/{repo}/pulls/{pr}/comments/{comment_id}/replies \
+  -f body="Addressed in <commit>: <explanation>"
+```
+
+Resolve a review thread (needs the thread node id from the GraphQL query above):
+
+```bash
+gh api graphql -f query='
+  mutation($threadId:ID!){
+    resolveReviewThread(input:{threadId:$threadId}){ thread{ isResolved } }
+  }' -F threadId={thread_id}
+```

.github/workflows/dotnet-build-and-test.yml

@@ -48,6 +48,10 @@ jobs:
           filters: |
             dotnet:
               - 'dotnet/**'
+              - '!dotnet/AGENTS.md'
+              - '!dotnet/**/AGENTS.md'
+              - '!dotnet/.github/skills/*'
+              - '!dotnet/.github/skills/**'
             cosmosdb:
               - 'dotnet/src/Microsoft.Agents.AI.CosmosNoSql/**'
             # The Foundry hosted-agent IT is costly (builds a container, pushes to ACR,

.github/workflows/dotnet-format.yml

@@ -10,6 +10,10 @@ on:
     branches: ["main", "feature*"]
     paths:
       - dotnet/**
+      - '!dotnet/AGENTS.md'
+      - '!dotnet/**/AGENTS.md'
+      - '!dotnet/.github/skills/*'
+      - '!dotnet/.github/skills/**'
       - '.github/workflows/dotnet-format.yml'
 
 concurrency:

.github/workflows/dotnet-integration-tests.yml

@@ -88,6 +88,7 @@ jobs:
         env:
           COSMOSDB_ENDPOINT: https://localhost:8081
           COSMOSDB_KEY: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==
+          COPILOT_GITHUB_TOKEN: ${{ secrets.COPILOT_GITHUB_TOKEN }}
           OpenAI__ApiKey: ${{ secrets.OPENAI__APIKEY }}
           OpenAI__ChatModelId: ${{ vars.OPENAI__CHATMODELID }}
           OpenAI__ChatReasoningModelId: ${{ vars.OPENAI__CHATREASONINGMODELID }}

.github/workflows/label-pr.yml

@@ -6,16 +6,34 @@
 # https://github.com/actions/labeler
 
 name: Label pull request
-on: [pull_request_target]
+on:
+  pull_request_target:
+    types: [opened, synchronize, reopened, edited]
 
 jobs:
   add_label:
     runs-on: ubuntu-latest
     permissions:
       contents: read
+      issues: write
       pull-requests: write
 
     steps:
       - uses: actions/labeler@f27b608878404679385c85cfa523b85ccb86e213 # v6
         with:
           repo-token: "${{ secrets.GH_ACTIONS_PR_WRITE }}"
+
+      - name: Checkout scripts
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
+        with:
+          sparse-checkout: .github/scripts
+          fetch-depth: 1
+          persist-credentials: false
+
+      - name: "PR: add breaking change label from title"
+        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
+        with:
+          github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
+          script: |
+            const { syncBreakingChangeLabelFromTitle } = require('./.github/scripts/title_prefix.js');
+            await syncBreakingChangeLabelFromTitle({ github, context, core });

.github/workflows/label-title-prefix.yml

@@ -15,58 +15,17 @@ jobs:
       pull-requests: write
 
     steps:
+      - name: Checkout scripts
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
+        with:
+          sparse-checkout: .github/scripts
+          fetch-depth: 1
+          persist-credentials: false
+
       - uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8
         name: "Issue/PR: update title"
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           script: |
-            let prefixLabels = {
+            const { updateTitleForAddedLabel } = require('./.github/scripts/title_prefix.js');
-              "python": "Python",
+            await updateTitleForAddedLabel({ github, context, core });
-              ".NET": ".NET"
-            };
-
-            function addTitlePrefix(title, prefix)
-            {
-              // Update the title based on the label and prefix
-              // Check if the title starts with the prefix (case-sensitive)
-              if (!title.startsWith(prefix + ": ")) {
-                // If not, check if the first word is the label (case-insensitive)
-                if (title.match(new RegExp(`^${prefix}`, 'i'))) {
-                  // If yes, replace it with the prefix (case-sensitive)
-                  title = title.replace(new RegExp(`^${prefix}`, 'i'), prefix);
-                } else {
-                  // If not, prepend the prefix to the title
-                  title = prefix + ": " + title;
-                }
-              }
-
-              return title;
-            }
-
-            labelAdded = context.payload.label.name
-
-            // Check if the issue or PR has the label
-            if (labelAdded in prefixLabels) {
-              let prefix = prefixLabels[labelAdded];
-              switch(context.eventName) {
-                case 'issues':
-                  github.rest.issues.update({
-                    issue_number: context.issue.number,
-                    owner: context.repo.owner,
-                    repo: context.repo.repo,
-                    title: addTitlePrefix(context.payload.issue.title, prefix)
-                  });
-                  break
-
-                case 'pull_request_target':
-                  github.rest.pulls.update({
-                    pull_number: context.issue.number,
-                    owner: context.repo.owner,
-                    repo: context.repo.repo,
-                    title: addTitlePrefix(context.payload.pull_request.title, prefix)
-                  });
-                  break
-                default:
-                  core.setFailed('Unrecognited eventName: ' + context.eventName);
-              }
-            }

.github/workflows/merge-gatekeeper.yml

@@ -27,7 +27,7 @@ jobs:
           # "Cleanup artifacts", "Agent", "Prepare", and "Upload results" are check runs
           # created by an org-level GitHub App (MSDO), not by any workflow in this repo.
           # They are outside our control and their transient failures should not block merges.
-          IGNORED_NAMES: "CodeQL,CodeQL analysis (csharp),Cleanup artifacts,Agent,Prepare,Upload results"
+          IGNORED_NAMES: "CodeQL,CodeQL analysis (csharp),Cleanup artifacts,Agent,Prepare,Upload results,review"
         with:
           script: |
             const timeoutSeconds = Number(process.env.TIMEOUT_SECONDS);

.github/workflows/python-code-quality.yml

@@ -6,6 +6,10 @@ on:
     branches: ["main"]
     paths:
       - "python/**"
+      - "!python/AGENTS.md"
+      - "!python/**/AGENTS.md"
+      - "!python/.github/skills/*"
+      - "!python/.github/skills/**"
 
 env:
   # Configure a constant location for the uv cache

.github/workflows/python-lab-tests.yml

@@ -31,6 +31,10 @@ jobs:
           filters: |
             python:
               - 'python/**'
+              - '!python/AGENTS.md'
+              - '!python/**/AGENTS.md'
+              - '!python/.github/skills/*'
+              - '!python/.github/skills/**'
       # run only if 'python' files were changed
       - name: python tests
         if: steps.filter.outputs.python == 'true'

.github/workflows/python-merge-tests.yml

@@ -49,6 +49,10 @@ jobs:
           filters: |
             python:
               - 'python/**'
+              - '!python/AGENTS.md'
+              - '!python/**/AGENTS.md'
+              - '!python/.github/skills/*'
+              - '!python/.github/skills/**'
               - '.github/actions/setup-local-mcp-server/**'
               - '.github/workflows/python-merge-tests.yml'
               - '.github/workflows/python-integration-tests.yml'

.github/workflows/python-tests.yml

@@ -5,6 +5,10 @@ on:
     branches: ["main", "feature*"]
     paths:
       - "python/**"
+      - "!python/AGENTS.md"
+      - "!python/**/AGENTS.md"
+      - "!python/.github/skills/*"
+      - "!python/.github/skills/**"
 env:
   # Configure a constant location for the uv cache
   UV_CACHE_DIR: /tmp/.uv-cache

.gitignore

@@ -206,6 +206,7 @@ temp*/
 .temp/
 
 # AI
+**/.checkpoints/
 .claude/
 .omc/
 .omx/
@@ -213,6 +214,7 @@ WARP.md
 **/memory-bank/
 **/projectBrief.md
 **/tmpclaude*
+.kiro/
 # Dependency-bound validation reports
 python/scripts/dependency-*-results.json
 python/scripts/dependencies/dependency-*-results.json

docs/decisions/0007-agent-filtering-middleware.md

@@ -1125,7 +1125,7 @@ Naming (Python): N/A (Composable Components)
 Supports: N  
 Observation: No explicit middleware/filters; modularity allows composable units but no dedicated interception hooks or callbacks for custom reading/modification mid-execution.
 
-For more details, see the official documentation: [Atomic Agents Docs](https://brainblend-ai.github.io/atomic-agents/). No specific code examples available for interception.
+No specific code examples available for interception.
 
 #### Smolagents (Hugging Face)
 

dotnet/.github/skills/pull-requests

@@ -0,0 +1 @@
+../../../.github/skills/pull-requests

dotnet/AGENTS.md

@@ -10,6 +10,10 @@ See `./.github/skills/build-and-test/SKILL.md` for detailed instructions on buil
 
 See `./.github/skills/project-structure/SKILL.md` for an overview of the project structure.
 
+## Pull Requests
+
+See `./.github/skills/pull-requests/SKILL.md` for guidance on writing PR descriptions and handling/resolving PR review comments.
+
 ### Core types
 
 - `AIAgent`: The abstract base class that all agents derive from, providing common methods for interacting with an agent.

dotnet/Directory.Packages.props

@@ -21,6 +21,7 @@
     <PackageVersion Include="Aspire.Hosting.Azure.CognitiveServices" Version="$(AspireAppHostSdkVersion)" />
     <PackageVersion Include="Aspire.Microsoft.Azure.Cosmos" Version="$(AspireAppHostSdkVersion)" />
     <PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0" />
+    <PackageVersion Include="MessagePack" Version="3.1.7" /> <!-- Transitive dependency of Aspire pinned to newer version due to vulnerability in 2.5.192 -->
     <!-- Azure.* -->
     <PackageVersion Include="Azure.AI.AgentServer.Core" Version="1.0.0-beta.25" />
     <PackageVersion Include="Azure.AI.AgentServer.Invocations" Version="1.0.0-beta.4" />
@@ -41,19 +42,19 @@
     <!-- Newtonsoft.Json -->
     <PackageVersion Include="Newtonsoft.Json" Version="13.0.4" />
     <!-- System.* -->
-    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.6" />
+    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.8" />
     <PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
     <PackageVersion Include="Microsoft.Bcl.Memory" Version="10.0.5" />
     <PackageVersion Include="System.ClientModel" Version="1.12.0" />
     <PackageVersion Include="System.CodeDom" Version="10.0.0" />
     <PackageVersion Include="System.Collections.Immutable" Version="10.0.1" />
     <PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
-    <PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.6" />
+    <PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.8" />
     <PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.5" />
     <PackageVersion Include="System.Net.Http.Json" Version="10.0.0" />
     <PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.5" />
-    <PackageVersion Include="System.Text.Json" Version="10.0.6" />
+    <PackageVersion Include="System.Text.Json" Version="10.0.8" />
-    <PackageVersion Include="System.Threading.Channels" Version="10.0.6" />
+    <PackageVersion Include="System.Threading.Channels" Version="10.0.8" />
     <PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
     <PackageVersion Include="System.Net.Security" Version="4.3.2" />
     <!-- OpenTelemetry -->
@@ -72,12 +73,12 @@
     <PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="10.0.0" />
     <PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
     <!-- Microsoft.Extensions.* -->
-    <PackageVersion Include="Microsoft.Extensions.AI" Version="10.5.1" />
+    <PackageVersion Include="Microsoft.Extensions.AI" Version="10.6.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.5.1" />
+    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.6.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation" Version="10.4.0" />
+    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation" Version="10.6.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="10.4.0" />
+    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="10.6.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Safety" Version="10.3.0-preview.1.26109.11" />
+    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Safety" Version="10.6.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.5.1" />
+    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.6.0" />
     <PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
     <PackageVersion Include="Microsoft.Extensions.Compliance.Abstractions" Version="10.5.0" />
     <PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.1" />
@@ -86,12 +87,12 @@
     <PackageVersion Include="Microsoft.Extensions.Configuration.Json" Version="10.0.1" />
     <PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.1" />
     <PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.6" />
+    <PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.8" />
     <PackageVersion Include="Microsoft.Extensions.FileSystemGlobbing" Version="10.0.6" />
     <PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.1" />
     <PackageVersion Include="Microsoft.Extensions.Http.Resilience" Version="10.0.0" />
     <PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.6" />
+    <PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.8" />
     <PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="10.0.1" />
     <PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="10.0.0" />
     <PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
@@ -138,10 +139,15 @@
     <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" Version="2.1.0" />
     <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Mcp" Version="1.0.0" />
     <PackageVersion Include="Microsoft.Azure.Functions.Worker.Sdk" Version="2.0.7" />
+    <!-- Valkey -->
     <!-- Redis -->
     <PackageVersion Include="StackExchange.Redis" Version="2.10.1" />
+    <!-- Valkey -->
+    <PackageVersion Include="Valkey.Glide" Version="1.1.0" />
     <!-- Console UX -->
     <PackageVersion Include="Spectre.Console" Version="0.49.1" />
+    <!-- AWS -->
+    <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.6.10" />
     <!-- Test -->
     <PackageVersion Include="FluentAssertions" Version="8.8.0" />
     <PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net8.0'" Version="8.0.22" />

dotnet/agent-framework-dotnet.slnx

@@ -24,7 +24,6 @@
     <File Path="samples/02-agents/AgentProviders/README.md" />
     <Project Path="samples/02-agents/AgentProviders/Agent_With_A2A/Agent_With_A2A.csproj" />
     <Project Path="samples/02-agents/AgentProviders/Agent_With_Anthropic/Agent_With_Anthropic.csproj" />
-    <Project Path="samples/02-agents/AgentProviders/Agent_With_AzureAIAgentsPersistent/Agent_With_AzureAIAgentsPersistent.csproj" />
     <Project Path="samples/02-agents/AgentProviders/Agent_With_AzureAIProject/Agent_With_AzureAIProject.csproj" />
     <Project Path="samples/02-agents/AgentProviders/Agent_With_AzureFoundryModel/Agent_With_AzureFoundryModel.csproj" />
     <Project Path="samples/02-agents/AgentProviders/Agent_With_AzureOpenAIChatCompletion/Agent_With_AzureOpenAIChatCompletion.csproj" />
@@ -129,6 +128,7 @@
     <Project Path="samples/02-agents/Harness/Harness_Step02_Research_WithBackgroundAgents/Harness_Step02_Research_WithBackgroundAgents.csproj" />
     <Project Path="samples/02-agents/Harness/Harness_Step03_DataProcessing/Harness_Step03_DataProcessing.csproj" />
     <Project Path="samples/02-agents/Harness/Harness_Step04_CodeExecution/Harness_Step04_CodeExecution.csproj" />
+    <Project Path="samples/02-agents/Harness/Harness_Step05_Loop/Harness_Step05_Loop.csproj" />
   </Folder>
   <Folder Name="/Samples/02-agents/AGUI/Step05_StateManagement/">
     <Project Path="samples/02-agents/AGUI/Step05_StateManagement/Client/Client.csproj" />
@@ -194,6 +194,8 @@
     <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step02_MemoryUsingMem0/AgentWithMemory_Step02_MemoryUsingMem0.csproj" />
     <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/AgentWithMemory_Step04_MemoryUsingFoundry.csproj" />
     <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/AgentWithMemory_Step05_BoundedChatHistory.csproj" />
+    <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey/AgentWithMemory_Step03_MemoryUsingValkey.csproj" />
+    <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock.csproj" />
   </Folder>
   <Folder Name="/Samples/02-agents/AgentWithOpenAI/">
     <File Path="samples/02-agents/AgentWithOpenAI/README.md" />
@@ -344,6 +346,9 @@
   <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox/">
     <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox/HostedToolbox.csproj" />
   </Folder>
+  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox-AuthPaths/">
+    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox-AuthPaths/Hosted-Toolbox-AuthPaths.csproj" />
+  </Folder>
   <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-ToolboxMcpSkills/">
     <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-ToolboxMcpSkills/HostedToolboxMcpSkills.csproj" />
   </Folder>
@@ -622,6 +627,7 @@
     <Project Path="src/Microsoft.Agents.AI.Workflows.Generators/Microsoft.Agents.AI.Workflows.Generators.csproj" />
     <Project Path="src/Microsoft.Agents.AI.Workflows/Microsoft.Agents.AI.Workflows.csproj" />
     <Project Path="src/Microsoft.Agents.AI/Microsoft.Agents.AI.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.Valkey/Microsoft.Agents.AI.Valkey.csproj" />
   </Folder>
   <Folder Name="/Tests/" />
   <Folder Name="/Tests/IntegrationTests/">
@@ -675,5 +681,6 @@
     <Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Workflows.Generators.UnitTests/Microsoft.Agents.AI.Workflows.Generators.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Workflows.UnitTests/Microsoft.Agents.AI.Workflows.UnitTests.csproj" />
+    <Project Path="tests/Microsoft.Agents.AI.Valkey.UnitTests/Microsoft.Agents.AI.Valkey.UnitTests.csproj" />
   </Folder>
 </Solution>

dotnet/eng/verify-samples/AgentsSamples.cs

@@ -50,19 +50,6 @@ internal static class AgentsSamples
             ],
         },
 
-        new SampleDefinition
-        {
-            Name = "Agent_With_AzureAIAgentsPersistent",
-            ProjectPath = "samples/02-agents/AgentProviders/Agent_With_AzureAIAgentsPersistent",
-            RequiredEnvironmentVariables = ["AZURE_AI_PROJECT_ENDPOINT"],
-            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
-            ExpectedOutputDescription =
-            [
-                "The output should contain a joke about a pirate.",
-                "The output should not contain error messages or stack traces.",
-            ],
-        },
-
         new SampleDefinition
         {
             Name = "Agent_With_AzureAIProject",

dotnet/nuget/nuget-package.props

@@ -1,14 +1,14 @@
 <Project>
   <PropertyGroup>
     <!-- Central version prefix - applies to all nuget packages. -->
-    <VersionPrefix>1.9.0</VersionPrefix>
+    <VersionPrefix>1.10.0</VersionPrefix>
     <RCNumber>1</RCNumber>
-    <DateSuffix>260603</DateSuffix>
+    <DateSuffix>260610</DateSuffix>
     <PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
     <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).$(DateSuffix).1</PackageVersion>
     <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.$(DateSuffix).1</PackageVersion>
     <PackageVersion Condition="'$(IsReleased)' == 'true'">$(VersionPrefix)</PackageVersion>
-    <GitTag>1.9.0</GitTag>
+    <GitTag>1.10.0</GitTag>
 
     <Configurations>Debug;Release;Publish</Configurations>
     <IsPackable>true</IsPackable>

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIAgentsPersistent/Program.cs

@@ -1,44 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-#pragma warning disable CS0618 // Type or member is obsolete - sample uses deprecated PersistentAgentsClientExtensions
-
-// This sample shows how to create and use a simple AI agent with Microsoft Foundry Agents as the backend.
-
-using Azure.AI.Agents.Persistent;
-using Azure.Identity;
-using Microsoft.Agents.AI;
-
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
-
-const string JokerName = "Joker";
-const string JokerInstructions = "You are good at telling jokes.";
-
-// Get a client to create/retrieve server side agents with.
-// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
-// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
-// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
-var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());
-
-// You can create a server side persistent agent with the Azure.AI.Agents.Persistent SDK.
-var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
-    model: deploymentName,
-    name: JokerName,
-    instructions: JokerInstructions);
-
-// You can retrieve an already created server side persistent agent as an AIAgent.
-AIAgent agent1 = await persistentAgentsClient.GetAIAgentAsync(agentMetadata.Value.Id);
-
-// You can also create a server side persistent agent and return it as an AIAgent directly.
-AIAgent agent2 = await persistentAgentsClient.CreateAIAgentAsync(
-    model: deploymentName,
-    name: JokerName,
-    instructions: JokerInstructions);
-
-// You can then invoke the agent like any other AIAgent.
-AgentSession session = await agent1.CreateSessionAsync();
-Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", session));
-
-// Cleanup for sample purposes.
-await persistentAgentsClient.Administration.DeleteAgentAsync(agent1.Id);
-await persistentAgentsClient.Administration.DeleteAgentAsync(agent2.Id);

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIAgentsPersistent/README.md

@@ -1,26 +0,0 @@
-# Classic Foundry Agents 
-
-This sample demonstrates how to create an agent using the classic Foundry Agents experience.
-
-# Classic vs New Foundry Agents
-
-Below is a comparison between the classic and new Foundry Agents approaches:
-
-[Migration Guide](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/migrate?view=foundry)
-
-# Prerequisites
-
-Before you begin, ensure you have the following prerequisites:
-
-- .NET 10 SDK or later
-- Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (for Azure credential authentication)
-
-**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
-
-Set the following environment variables:
-
-```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
-```

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIProject/Program.cs

@@ -8,8 +8,8 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Foundry;
 
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 const string JokerName = "JokerAgent";
 

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIProject/README.md

@@ -1,4 +1,4 @@
-# New Foundry Agents 
+# New Foundry Agents 
 
 This sample demonstrates how to create an agent using the new Foundry Agents experience. 
 
@@ -21,6 +21,6 @@ Before you begin, ensure you have the following prerequisites:
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:FOUNDRY_MODEL="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureFoundryModel/Program.cs

@@ -13,7 +13,7 @@ using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var apiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_API_KEY");
-var model = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "Phi-4-mini-instruct";
+var model = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "Phi-4-mini-instruct";
 
 // Since we are using the OpenAI Client SDK, we need to override the default endpoint to point to Microsoft Foundry.
 var clientOptions = new OpenAIClientOptions() { Endpoint = new Uri(endpoint) };

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureFoundryModel/README.md

@@ -1,4 +1,4 @@
-## Overview
+## Overview
 
 This sample shows how to use the OpenAI SDK to create and use a simple AI agent with any model hosted in Microsoft Foundry.
 
@@ -13,7 +13,7 @@ Before you begin, ensure you have the following prerequisites:
 - .NET 10 SDK or later
 - Microsoft Foundry resource
 - A model deployment in your Microsoft Foundry resource. This example defaults to using the `Phi-4-mini-instruct` model,
-so if you want to use a different model, ensure that you set your `AZURE_AI_MODEL_DEPLOYMENT_NAME` environment
+so if you want to use a different model, ensure that you set your `FOUNDRY_MODEL` environment
 variable to the name of your deployed model.
 - An API key or role based authentication to access the Microsoft Foundry resource
 
@@ -30,5 +30,5 @@ $env:AZURE_OPENAI_ENDPOINT="https://ai-foundry-<myresourcename>.services.ai.azur
 $env:AZURE_OPENAI_API_KEY="************"
 
 # Optional, defaults to Phi-4-mini-instruct
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="Phi-4-mini-instruct"
+$env:FOUNDRY_MODEL="Phi-4-mini-instruct"
 ```

dotnet/samples/02-agents/AgentProviders/README.md

@@ -16,7 +16,6 @@ See the README.md for each sample for the prerequisites for that sample.
 |---|---|
 |[Creating an AIAgent with A2A](./Agent_With_A2A/)|This sample demonstrates how to create AIAgent for an existing A2A agent.|
 |[Creating an AIAgent with Anthropic](./Agent_With_Anthropic/)|This sample demonstrates how to create an AIAgent using Anthropic Claude models as the underlying inference service|
-|[Creating an AIAgent with Foundry Agents using Azure.AI.Agents.Persistent](./Agent_With_AzureAIAgentsPersistent/)|This sample demonstrates how to create a Foundry Persistent agent and expose it as an AIAgent using the Azure.AI.Agents.Persistent SDK|
 |[Creating an AIAgent with Foundry Agents using Azure.AI.Project](./Agent_With_AzureAIProject/)|This sample demonstrates how to create an Foundry Project agent and expose it as an AIAgent using the Azure.AI.Project SDK|
 |[Creating an AIAgent with Foundry Model](./Agent_With_AzureFoundryModel/)|This sample demonstrates how to use any model deployed to Microsoft Foundry to create an AIAgent|
 |[Creating an AIAgent with Azure OpenAI ChatCompletion](./Agent_With_AzureOpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using Azure OpenAI ChatCompletion as the underlying inference service|

dotnet/samples/02-agents/AgentSkills/Agent_Step01_FileBasedSkills/Program.cs

@@ -26,6 +26,9 @@ var skillsProvider = new AgentSkillsProvider(
     SubprocessScriptRunner.RunAsync);
 
 // --- Agent Setup ---
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
     .GetResponsesClient()
     .AsAIAgent(new ChatClientAgentOptions

dotnet/samples/02-agents/AgentSkills/Agent_Step02_CodeDefinedSkills/Program.cs

@@ -67,6 +67,9 @@ var unitConverterSkill = new AgentInlineSkill(
 var skillsProvider = new AgentSkillsProvider(unitConverterSkill);
 
 // --- Agent Setup ---
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
     .GetResponsesClient()
     .AsAIAgent(new ChatClientAgentOptions

dotnet/samples/02-agents/AgentSkills/Agent_Step03_ClassBasedSkills/Program.cs

@@ -22,6 +22,9 @@ var unitConverter = new UnitConverterSkill();
 var skillsProvider = new AgentSkillsProvider(unitConverter);
 
 // --- Agent Setup ---
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
     .GetResponsesClient()
     .AsAIAgent(new ChatClientAgentOptions

dotnet/samples/02-agents/AgentSkills/Agent_Step04_MixedSkills/Program.cs

@@ -64,6 +64,9 @@ var skillsProvider = new AgentSkillsProviderBuilder()
     .Build();
 
 // --- Agent Setup ---
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
     .GetResponsesClient()
     .AsAIAgent(new ChatClientAgentOptions

dotnet/samples/02-agents/AgentSkills/Agent_Step05_SkillsWithDI/Program.cs

@@ -80,6 +80,9 @@ var weightSkill = new WeightConverterSkill();
 var skillsProvider = new AgentSkillsProvider(distanceSkill, weightSkill);
 
 // --- Agent Setup ---
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
     .GetResponsesClient()
     .AsAIAgent(

dotnet/samples/02-agents/AgentWithCodeAct/AgentWithCodeAct_Step01_Interpreter/Program.cs

@@ -16,6 +16,9 @@ var guestPath = Environment.GetEnvironmentVariable("HYPERLIGHT_PYTHON_GUEST_PATH
 
 using var codeAct = new HyperlightCodeActProvider(HyperlightCodeActProviderOptions.CreateForWasm(guestPath));
 
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new DefaultAzureCredential())

dotnet/samples/02-agents/AgentWithCodeAct/AgentWithCodeAct_Step02_ToolEnabled/Program.cs

@@ -39,6 +39,9 @@ options.Tools = [fetchDocs, queryData, sendEmail];
 
 using var codeAct = new HyperlightCodeActProvider(options);
 
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new DefaultAzureCredential())

dotnet/samples/02-agents/AgentWithCodeAct/AgentWithCodeAct_Step03_ManualWiring/Program.cs

@@ -31,6 +31,9 @@ var instructions =
     + "and calling `execute_code` instead of computing values yourself.\n\n"
     + executeCode.BuildInstructions(toolsVisibleToModel: false);
 
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new DefaultAzureCredential())

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey/AgentWithMemory_Step03_MemoryUsingValkey.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Valkey\Microsoft.Agents.AI.Valkey.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey/Program.cs

@@ -0,0 +1,55 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates using Valkey for persistent chat history with the Agent Framework.
+// ValkeyChatHistoryProvider persists conversation history across sessions using Valkey lists.
+//
+// Prerequisites:
+//   - A running Valkey server (any version):
+//       docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
+//   - Azure OpenAI endpoint and deployment configured via environment variables
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Valkey;
+using Microsoft.Extensions.AI;
+using OpenAI.Chat;
+using Valkey.Glide;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var valkeyConnection = Environment.GetEnvironmentVariable("VALKEY_CONNECTION") ?? "localhost:6379";
+
+var connection = await ConnectionMultiplexer.ConnectAsync(valkeyConnection);
+
+Console.WriteLine("=== ValkeyChatHistoryProvider — Persistent Chat History ===\n");
+
+var historyProvider = new ValkeyChatHistoryProvider(
+    connection,
+    _ => new ValkeyChatHistoryProvider.State($"sample-{Guid.NewGuid():N}"),
+    new ValkeyChatHistoryProviderOptions
+    {
+        KeyPrefix = "sample_chat",
+        MaxMessages = 20
+    });
+
+AIAgent historyAgent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
+    .GetChatClient(deploymentName)
+    .AsAIAgent(new ChatClientAgentOptions()
+    {
+        ChatOptions = new() { Instructions = "You are a helpful assistant that remembers our conversation." },
+        ChatHistoryProvider = historyProvider
+    });
+
+AgentSession session1 = await historyAgent.CreateSessionAsync();
+Console.WriteLine(await historyAgent.RunAsync("Hello! My name is Alex and I'm a software engineer.", session1));
+Console.WriteLine(await historyAgent.RunAsync("I'm working on a project using Valkey for caching.", session1));
+Console.WriteLine(await historyAgent.RunAsync("What do you remember about me?", session1));
+
+var messageCount = await historyProvider.GetMessageCountAsync(session1);
+Console.WriteLine($"\n  Stored {messageCount} messages in Valkey.\n");
+
+// Clean up
+connection.Dispose();
+
+Console.WriteLine("Done!");

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey/README.md

@@ -0,0 +1,30 @@
+# Agent with Memory Using Valkey
+
+This sample demonstrates using Valkey for persistent chat history with the Agent Framework.
+
+## Components
+
+- **ValkeyChatHistoryProvider** — Persists conversation history across sessions using Valkey lists. Works with any Valkey or Redis OSS server (no search module required).
+
+## Prerequisites
+
+- Azure OpenAI endpoint and deployment
+- A running Valkey server (any version):
+
+```bash
+docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
+```
+
+## Environment Variables
+
+| Variable | Description | Default |
+|---|---|---|
+| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI endpoint URL | (required) |
+| `AZURE_OPENAI_DEPLOYMENT_NAME` | Model deployment name | `gpt-5.4-mini` |
+| `VALKEY_CONNECTION` | Valkey connection string | `localhost:6379` |
+
+## Running
+
+```bash
+dotnet run
+```

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="AWSSDK.Extensions.Bedrock.MEAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Valkey\Microsoft.Agents.AI.Valkey.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock/Program.cs

@@ -0,0 +1,57 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates using Valkey for persistent chat history with the Agent Framework,
+// powered by Amazon Bedrock.
+//
+// Prerequisites:
+//   - A running Valkey server (any version):
+//       docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
+//   - AWS credentials configured (environment variables, AWS profile, or IAM role)
+//   - Access to an Amazon Bedrock model (e.g., Anthropic Claude)
+
+using Amazon;
+using Amazon.BedrockRuntime;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Valkey;
+using Microsoft.Extensions.AI;
+using Valkey.Glide;
+
+var awsRegion = Environment.GetEnvironmentVariable("AWS_REGION") ?? "us-east-1";
+var modelId = Environment.GetEnvironmentVariable("BEDROCK_MODEL_ID") ?? "anthropic.claude-3-5-sonnet-20241022-v2:0";
+var valkeyConnection = Environment.GetEnvironmentVariable("VALKEY_CONNECTION") ?? "localhost:6379";
+
+// Create the Bedrock runtime client.
+var bedrockRuntime = new AmazonBedrockRuntimeClient(RegionEndpoint.GetBySystemName(awsRegion));
+IChatClient chatClient = bedrockRuntime.AsIChatClient(modelId);
+
+var connection = await ConnectionMultiplexer.ConnectAsync(valkeyConnection);
+
+Console.WriteLine("=== ValkeyChatHistoryProvider — Persistent Chat History (Bedrock) ===\n");
+
+var historyProvider = new ValkeyChatHistoryProvider(
+    connection,
+    _ => new ValkeyChatHistoryProvider.State($"bedrock-sample-{Guid.NewGuid():N}"),
+    new ValkeyChatHistoryProviderOptions
+    {
+        KeyPrefix = "bedrock_chat",
+        MaxMessages = 20
+    });
+
+AIAgent historyAgent = chatClient.AsAIAgent(new ChatClientAgentOptions()
+{
+    ChatOptions = new() { Instructions = "You are a helpful assistant that remembers our conversation." },
+    ChatHistoryProvider = historyProvider
+});
+
+AgentSession session1 = await historyAgent.CreateSessionAsync();
+Console.WriteLine(await historyAgent.RunAsync("Hello! My name is Alex and I'm a software engineer.", session1));
+Console.WriteLine(await historyAgent.RunAsync("I'm working on a project using Valkey for caching.", session1));
+Console.WriteLine(await historyAgent.RunAsync("What do you remember about me?", session1));
+
+var messageCount = await historyProvider.GetMessageCountAsync(session1);
+Console.WriteLine($"\n  Stored {messageCount} messages in Valkey.\n");
+
+// Clean up
+connection.Dispose();
+
+Console.WriteLine("Done!");

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step03_MemoryUsingValkey_Bedrock/README.md

@@ -0,0 +1,41 @@
+# Agent with Memory Using Valkey + Amazon Bedrock
+
+This sample demonstrates using Valkey for persistent chat history with the Agent Framework, powered by Amazon Bedrock via the `AWSSDK.Extensions.Bedrock.MEAI` adapter.
+
+## Components
+
+- **ValkeyChatHistoryProvider** — Persists conversation history across sessions using Valkey lists. Works with any Valkey or Redis OSS server (no search module required).
+- **Amazon Bedrock** — Provides the LLM via `AWSSDK.Extensions.Bedrock.MEAI`, which implements `IChatClient` from `Microsoft.Extensions.AI`.
+
+## Prerequisites
+
+- AWS credentials configured (environment variables, AWS CLI profile, or IAM role)
+- Access to an Amazon Bedrock model (e.g., Anthropic Claude 3.5 Sonnet)
+- A running Valkey server (any version):
+
+```bash
+docker run -d --name valkey -p 6379:6379 valkey/valkey:latest
+```
+
+## Environment Variables
+
+| Variable | Description | Default |
+|---|---|---|
+| `AWS_REGION` | AWS region for Bedrock | `us-east-1` |
+| `BEDROCK_MODEL_ID` | Bedrock model identifier | `anthropic.claude-3-5-sonnet-20241022-v2:0` |
+| `VALKEY_CONNECTION` | Valkey connection string | `localhost:6379` |
+| `AWS_ACCESS_KEY_ID` | AWS access key (if not using profile/role) | — |
+| `AWS_SECRET_ACCESS_KEY` | AWS secret key (if not using profile/role) | — |
+
+## Running
+
+```bash
+# Using default AWS credential chain (profile, env vars, or IAM role)
+dotnet run
+
+# Or with explicit credentials
+export AWS_ACCESS_KEY_ID="your-access-key"
+export AWS_SECRET_ACCESS_KEY="your-secret-key"
+export AWS_REGION="us-east-1"
+dotnet run
+```

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/Program.cs

@@ -13,9 +13,9 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Foundry;
 
-string foundryEndpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string foundryEndpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
 string memoryStoreName = Environment.GetEnvironmentVariable("AZURE_AI_MEMORY_STORE_ID") ?? "memory-store-sample";
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 string embeddingModelName = Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-ada-002";
 
 // Create an AIProjectClient for Foundry with Azure Identity authentication.

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/README.md

@@ -1,4 +1,4 @@
-# Agent with Memory Using Microsoft Foundry
+# Agent with Memory Using Microsoft Foundry
 
 This sample demonstrates how to create and run an agent that uses Microsoft Foundry's managed memory service to extract and retrieve individual memories across sessions.
 
@@ -22,11 +22,11 @@ This sample demonstrates how to create and run an agent that uses Microsoft Foun
 
 ```bash
 # Microsoft Foundry project endpoint and memory store name
-export AZURE_AI_PROJECT_ENDPOINT="https://your-account.services.ai.azure.com/api/projects/your-project"
+export FOUNDRY_PROJECT_ENDPOINT="https://your-account.services.ai.azure.com/api/projects/your-project"
 export AZURE_AI_MEMORY_STORE_ID="my_memory_store"
 
 # Model deployment names (models deployed in your Foundry project)
-export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+export FOUNDRY_MODEL="gpt-5.4-mini"
 export AZURE_AI_EMBEDDING_DEPLOYMENT_NAME="text-embedding-ada-002"
 ```
 

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step04_FoundryServiceRAG/Program.cs

@@ -13,8 +13,8 @@ using OpenAI.Files;
 using OpenAI.Responses;
 using OpenAI.VectorStores;
 
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // Create an AI Project client and get an OpenAI client that works with the foundry service.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step05_Neo4jGraphRAG/AgentWithRAG_Step05_Neo4jGraphRAG.csproj

@@ -23,7 +23,7 @@
     <PackageReference Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
     <PackageReference Include="Azure.Identity" Version="1.19.0" />
     <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc4" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.4.0" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.6.0" />
     <PackageReference Include="Neo4j.AgentFramework.GraphRAG" Version="0.1.0-preview.2" />
     <PackageReference Include="Neo4j.Driver" Version="5.28.0" />
   </ItemGroup>

dotnet/samples/02-agents/Agents/Agent_Step07_AsMcpTool/Program.cs

@@ -10,8 +10,8 @@ using Microsoft.Extensions.DependencyInjection;
 using Microsoft.Extensions.Hosting;
 using ModelContextProtocol.Server;
 
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/Agents/Agent_Step07_AsMcpTool/README.md

@@ -1,4 +1,4 @@
-This sample demonstrates how to expose an existing AI agent as an MCP tool.
+This sample demonstrates how to expose an existing AI agent as an MCP tool.
 
 ## Run the sample
 
@@ -21,9 +21,9 @@ To use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector)
    ```
 1. Open a web browser and navigate to the URL displayed in the terminal. If not opened automatically, this will open the MCP Inspector interface.
 1. In the MCP Inspector interface, add the following environment variables to allow your MCP server to access Microsoft Foundry Project to create and run the agent:
-    - AZURE_AI_PROJECT_ENDPOINT = https://your-resource.openai.azure.com/ # Replace with your Microsoft Foundry Project endpoint
+    - FOUNDRY_PROJECT_ENDPOINT = https://your-resource.openai.azure.com/ # Replace with your Microsoft Foundry Project endpoint
-    - AZURE_AI_MODEL_DEPLOYMENT_NAME = gpt-5.4-mini # Replace with your model deployment name
+    - FOUNDRY_MODEL = gpt-5.4-mini # Replace with your model deployment name
 1. Find and click the `Connect` button in the MCP Inspector interface to connect to the MCP server.
 1. As soon as the connection is established, open the `Tools` tab in the MCP Inspector interface and select the `Joker` tool from the list.
 1. Specify your prompt as a value for the `query` argument, for example: `Tell me a joke about a pirate` and click the `Run Tool` button to run the tool.
-1. The agent will process the request and return a response in accordance with the provided instructions that instruct it to always start each joke with 'Aye aye, captain!'.
+1. The agent will process the request and return a response in accordance with the provided instructions that instruct it to always start each joke with 'Aye aye, captain!'.

dotnet/samples/02-agents/Agents/Agent_Step15_DeepResearch/Program.cs

@@ -8,9 +8,9 @@ using Azure.AI.Agents.Persistent;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
 var deepResearchDeploymentName = Environment.GetEnvironmentVariable("AZURE_AI_REASONING_DEPLOYMENT_NAME") ?? "o3-deep-research";
-var modelDeploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var modelDeploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 var bingConnectionId = Environment.GetEnvironmentVariable("AZURE_AI_BING_CONNECTION_ID") ?? throw new InvalidOperationException("AZURE_AI_BING_CONNECTION_ID is not set.");
 
 // Configure extended network timeout for long-running Deep Research tasks.

dotnet/samples/02-agents/Agents/Agent_Step15_DeepResearch/README.md

@@ -1,4 +1,4 @@
-# What this sample demonstrates
+# What this sample demonstrates
 
 This sample demonstrates how to create an Azure AI Agent with the Deep Research Tool, which leverages the o3-deep-research reasoning model to perform comprehensive research on complex topics.
 
@@ -37,7 +37,7 @@ Set the following environment variables:
 
 ```powershell
 # Replace with your Microsoft Foundry project endpoint
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-project.services.ai.azure.com/"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-project.services.ai.azure.com/"
 
 # Replace with your Bing Grounding connection ID (full ARM resource URI)
 $env:AZURE_AI_BING_CONNECTION_ID="/subscriptions/<sub-id>/resourceGroups/<rg>/providers/Microsoft.CognitiveServices/accounts/<account>/projects/<project>/connections/<connection-name>"
@@ -46,4 +46,4 @@ $env:AZURE_AI_BING_CONNECTION_ID="/subscriptions/<sub-id>/resourceGroups/<rg>/pr
 $env:AZURE_AI_REASONING_DEPLOYMENT_NAME="o3-deep-research"
 
 # Optional, defaults to gpt-5.4-mini
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"

dotnet/samples/02-agents/Agents/Agent_Step21_ShellWithEnvironment/Program.cs

@@ -40,6 +40,9 @@ using OpenAI.Chat;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step00_FoundryAgentLifecycle/Program.cs

@@ -9,13 +9,16 @@ using Azure.AI.Projects.Agents;
 using Azure.Identity;
 using Microsoft.Agents.AI.Foundry;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 const string JokerName = "JokerAgent";
 
 // Create the AIProjectClient to manage server-side agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
 
 // Create a server-side agent version using the native SDK.
 ProjectsAgentVersion agentVersion = await aiProjectClient.AgentAdministrationClient.CreateAgentVersionAsync(

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step00_FoundryAgentLifecycle/README.md

@@ -1,4 +1,4 @@
-# Agent Step 00 - FoundryAgent Lifecycle
+# Agent Step 00 - FoundryAgent Lifecycle
 
 This sample demonstrates the full lifecycle of a `FoundryAgent` backed by a server-side versioned agent in Microsoft Foundry: create → run → delete.
 
@@ -6,14 +6,14 @@ This sample demonstrates the full lifecycle of a `FoundryAgent` backed by a serv
 
 - A Microsoft Foundry project endpoint
 - A model deployment name (defaults to `gpt-5.4-mini`)
-- Azure CLI installed and authenticated
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 ## Environment Variables
 
 | Variable | Description | Required |
 | --- | --- | --- |
-| `AZURE_AI_PROJECT_ENDPOINT` | Microsoft Foundry project endpoint | Yes |
+| `FOUNDRY_PROJECT_ENDPOINT` | Microsoft Foundry project endpoint | Yes |
-| `AZURE_AI_MODEL_DEPLOYMENT_NAME` | Model deployment name | No (defaults to `gpt-5.4-mini`) |
+| `FOUNDRY_MODEL` | Model deployment name | No (defaults to `gpt-5.4-mini`) |
 
 ## Running the sample
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step01_Basics/Program.cs

@@ -6,8 +6,8 @@ using Azure.AI.Projects;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step01_Basics/README.md

@@ -14,15 +14,15 @@ Before you begin, ensure you have the following prerequisites:
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (for Azure credential authentication)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
-**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+**Note**: This sample uses `DefaultAzureCredential`. `az login` is the easiest local development path, but Visual Studio, VS Code, and managed identity credentials also work when available.
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step02.1_MultiturnConversation/Program.cs

@@ -7,8 +7,8 @@ using Azure.AI.Projects;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step02.1_MultiturnConversation/README.md

@@ -15,15 +15,15 @@ Before you begin, ensure you have the following prerequisites:
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (for Azure credential authentication)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
-**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+**Note**: This sample uses `DefaultAzureCredential`. `az login` is the easiest local development path, but Visual Studio, VS Code, and managed identity credentials also work when available.
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step02.2_MultiturnWithServerConversations/Program.cs

@@ -9,8 +9,8 @@ using Azure.AI.Projects;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step02.2_MultiturnWithServerConversations/README.md

@@ -15,15 +15,15 @@ Before you begin, ensure you have the following prerequisites:
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (for Azure credential authentication)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
-**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+**Note**: This sample uses `DefaultAzureCredential`. `az login` is the easiest local development path, but Visual Studio, VS Code, and managed identity credentials also work when available.
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step03_UsingFunctionTools/Program.cs

@@ -15,8 +15,8 @@ static string GetWeather([Description("The location to get the weather for.")] s
 // Define the function tool.
 AITool tool = AIFunctionFactory.Create(GetWeather);
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step03_UsingFunctionTools/README.md

@@ -16,15 +16,15 @@ Before you begin, ensure you have the following prerequisites:
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (for Azure credential authentication)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
-**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Microsoft Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+**Note**: This sample uses `DefaultAzureCredential`. `az login` is the easiest local development path, but Visual Studio, VS Code, and managed identity credentials also work when available.
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step04_UsingFunctionToolsWithApprovals/Program.cs

@@ -12,8 +12,8 @@ using Microsoft.Extensions.AI;
 static string GetWeather([Description("The location to get the weather for.")] string location)
     => $"The weather in {location} is cloudy with a high of 15°C.";
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step04_UsingFunctionToolsWithApprovals/README.md

@@ -13,13 +13,13 @@ This sample demonstrates how to use function tools that require human-in-the-loo
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step05_StructuredOutput/Program.cs

@@ -12,8 +12,8 @@ using SampleApp;
 
 #pragma warning disable CA5399
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step05_StructuredOutput/README.md

@@ -12,13 +12,13 @@ This sample demonstrates how to configure an agent to produce structured output
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step06_PersistedConversations/Program.cs

@@ -7,8 +7,8 @@ using Azure.AI.Projects;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step06_PersistedConversations/README.md

@@ -13,13 +13,13 @@ This sample demonstrates how to persist and resume agent conversations using ses
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step07_Observability/Program.cs

@@ -10,8 +10,8 @@ using OpenTelemetry;
 using OpenTelemetry.Trace;
 
 string? applicationInsightsConnectionString = Environment.GetEnvironmentVariable("APPLICATIONINSIGHTS_CONNECTION_STRING");
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // Create TracerProvider with console exporter.
 string sourceName = Guid.NewGuid().ToString("N");

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step07_Observability/README.md

@@ -13,13 +13,13 @@ This sample demonstrates how to add OpenTelemetry observability to an agent usin
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 $env:APPLICATIONINSIGHTS_CONNECTION_STRING="..."  # Optional
 ```
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step08_DependencyInjection/Program.cs

@@ -9,8 +9,8 @@ using Microsoft.Extensions.DependencyInjection;
 using Microsoft.Extensions.Hosting;
 using SampleApp;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step08_DependencyInjection/README.md

@@ -13,13 +13,13 @@ This sample demonstrates how to register a `ChatClientAgent` in a dependency inj
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step09_UsingMcpClientAsTools/Program.cs

@@ -9,8 +9,8 @@ using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 using ModelContextProtocol.Client;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // Connect to the Microsoft Learn MCP server via HTTP (Streamable HTTP transport).
 Console.WriteLine("Connecting to MCP server at https://learn.microsoft.com/api/mcp ...");

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step09_UsingMcpClientAsTools/README.md

@@ -12,14 +12,14 @@ This sample shows how to use MCP (Model Context Protocol) client tools with a `C
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 - Node.js installed (for npx/MCP server)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step10_UsingImages/Program.cs

@@ -7,8 +7,8 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step10_UsingImages/README.md

@@ -13,13 +13,13 @@ This sample demonstrates how to use image multi-modality with an agent.
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and a vision-capable model deployment (e.g., `gpt-5.4-mini`)
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step11_AsFunctionTool/Program.cs

@@ -12,8 +12,8 @@ using Microsoft.Extensions.AI;
 static string GetWeather([Description("The location to get the weather for.")] string location)
     => $"The weather in {location} is cloudy with a high of 15°C.";
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step11_AsFunctionTool/README.md

@@ -13,13 +13,13 @@ This sample demonstrates how to use one agent as a function tool for another age
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step12_Middleware/Program.cs

@@ -20,8 +20,8 @@ static string GetWeather([Description("The location to get the weather for.")] s
 static string GetDateTime()
     => DateTimeOffset.Now.ToString();
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step12_Middleware/README.md

@@ -14,13 +14,13 @@ This sample demonstrates multiple middleware layers working together: PII filter
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step13_Plugins/Program.cs

@@ -16,8 +16,8 @@ using Microsoft.Extensions.AI;
 using Microsoft.Extensions.DependencyInjection;
 using SampleApp;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 const string AssistantInstructions = "You are a helpful assistant that helps people find information.";
 const string AssistantName = "PluginAssistant";

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step13_Plugins/README.md

@@ -13,13 +13,13 @@ This sample shows how to use plugins with a `ChatClientAgent` using the Response
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step14_CodeInterpreter/Program.cs

@@ -12,8 +12,8 @@ using OpenAI.Assistants;
 const string AgentInstructions = "You are a personal math tutor. When asked a math question, write and run code using the python tool to answer the question.";
 const string AgentName = "CoderAgent-RAPI";
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step14_CodeInterpreter/README.md

@@ -12,13 +12,13 @@ This sample shows how to use the Code Interpreter tool with a `ChatClientAgent`
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step15_ComputerUse/Program.cs

@@ -10,9 +10,12 @@ using Microsoft.Agents.AI.Foundry;
 using Microsoft.Extensions.AI;
 using OpenAI.Responses;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
 string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_COMPUTER_USE_DEPLOYMENT_NAME") ?? "computer-use-preview";
 
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIProjectClient projectClient = new(new Uri(endpoint), new DefaultAzureCredential());
 using IHostedFileClient fileClient = projectClient.GetProjectOpenAIClient().AsIHostedFileClient();
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step15_ComputerUse/README.md

@@ -1,4 +1,4 @@
-# Computer Use with the Responses API
+# Computer Use with the Responses API
 
 This sample shows how to use the Computer Use tool with `AIProjectClient.AsAIAgent(...)`.
 
@@ -39,12 +39,12 @@ The model receives a screenshot as input, analyzes it, and responds with a compu
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
 $env:AZURE_AI_COMPUTER_USE_DEPLOYMENT_NAME="computer-use-preview"
 ```
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step16_FileSearch/Program.cs

@@ -9,8 +9,8 @@ using Microsoft.Extensions.AI;
 using OpenAI.Assistants;
 using OpenAI.Files;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 const string AgentInstructions = "You are a helpful assistant that can search through uploaded files to answer questions.";
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step16_FileSearch/README.md

@@ -13,13 +13,13 @@ This sample shows how to use the File Search tool with a `ChatClientAgent` using
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step17_OpenAPITools/Program.cs

@@ -9,8 +9,8 @@ using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Foundry;
 using Microsoft.Extensions.AI;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 const string AgentInstructions = "You are a helpful assistant that can use the countries API to retrieve information about countries by their currency code.";
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step17_OpenAPITools/README.md

@@ -13,13 +13,13 @@ This sample shows how to use OpenAPI tools with a `ChatClientAgent` using the Re
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step18_BingCustomSearch/Program.cs

@@ -21,8 +21,8 @@ BingCustomSearchToolOptions bingCustomSearchToolParameters = new([
     new BingCustomSearchConfiguration(connectionId, instanceName)
 ]);
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step18_BingCustomSearch/README.md

@@ -12,14 +12,14 @@ This sample shows how to use the Bing Custom Search tool with a `ChatClientAgent
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 - Bing Custom Search resource configured with a connection ID
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 $env:AZURE_AI_CUSTOM_SEARCH_CONNECTION_ID="your-connection-id"  # The full ARM resource URI, e.g., "/subscriptions/.../connections/your-bing-connection"
 $env:AZURE_AI_CUSTOM_SEARCH_INSTANCE_NAME="your-instance-name"  # The Bing Custom Search configuration name (from Azure portal)
 ```

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step19_SharePoint/Program.cs

@@ -19,8 +19,8 @@ const string AgentInstructions = """
 var sharepointOptions = new SharePointGroundingToolOptions();
 sharepointOptions.ProjectConnections.Add(new ToolProjectConnection(sharepointConnectionId));
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step19_SharePoint/README.md

@@ -12,14 +12,14 @@ This sample shows how to use the SharePoint Grounding tool with a `ChatClientAge
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 - SharePoint connection configured in your Microsoft Foundry project
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 $env:SHAREPOINT_PROJECT_CONNECTION_ID="your-sharepoint-connection-id"  # The full ARM resource URI, e.g., "/subscriptions/.../connections/SharepointTestTool"
 ```
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step20_MicrosoftFabric/Program.cs

@@ -16,8 +16,8 @@ const string AgentInstructions = "You are a helpful assistant with access to Mic
 var fabricToolOptions = new FabricDataAgentToolOptions();
 fabricToolOptions.ProjectConnections.Add(new ToolProjectConnection(fabricConnectionId));
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step20_MicrosoftFabric/README.md

@@ -12,14 +12,14 @@ This sample shows how to use the Microsoft Fabric tool with a `ChatClientAgent`
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 - Microsoft Fabric connection configured in your Microsoft Foundry project
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 $env:FABRIC_PROJECT_CONNECTION_ID="your-fabric-connection-id"  # The full ARM resource URI, e.g., "/subscriptions/.../connections/FabricTestTool"
 ```
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step21_WebSearch/Program.cs

@@ -11,8 +11,8 @@ using OpenAI.Responses;
 const string AgentInstructions = "You are a helpful assistant that can search the web to find current information and answer questions accurately.";
 const string AgentName = "WebSearchAgent-RAPI";
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step21_WebSearch/README.md

@@ -12,13 +12,13 @@ This sample shows how to use the Web Search tool with a `ChatClientAgent` using
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step22_MemorySearch/Program.cs

@@ -14,8 +14,8 @@ using Microsoft.Agents.AI.Foundry;
 using Microsoft.Extensions.AI;
 using OpenAI.Responses;
 
-string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
 string embeddingModelName = Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-ada-002";
 string memoryStoreName = Environment.GetEnvironmentVariable("AZURE_AI_MEMORY_STORE_ID") ?? $"foundry-memory-sample-{Guid.NewGuid():N}";
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step22_MemorySearch/README.md

@@ -13,14 +13,14 @@ This sample demonstrates how to use the Memory Search tool with a `ChatClientAge
 
 - .NET 10 SDK or later
 - Microsoft Foundry service endpoint and deployment configured
-- Azure CLI installed and authenticated (`az login`)
+- An authenticated Azure identity (for example, sign in with `az login`)
 - A memory store created beforehand via Azure Portal or Python SDK
 
 Set the following environment variables:
 
 ```powershell
-$env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
 $env:AZURE_AI_MEMORY_STORE_ID="your-memory-store-name"
 ```