Chore/rename ms agent starter#220
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@Arindam200 Please review and approve these feature I have added Added Microsoft agent framework agents with full Monocle observability. and verified output into the Observability Reference |
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Code Review SummaryStatus: No Issues Found | Recommendation: Merge Files Reviewed (1 file)
Note: The only change is adding a trailing newline to the README file. This is a common practice for file formatting and doesn't affect functionality. Review completed in incremental mode since last review at fa35654 Reviewed by glm-4.7-flash-20260119 · 95,508 tokens |
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thanks for your contributions, but why this change?
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@shivaylamba sorry this wrongly updated , please check now i have added main advance_ai_agents/flowsentinal_audittrail/README.md
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Can you use Nebius Token Factory LLM
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Caution Review failedFailed to post review comments. GitHub was unavailable or timed out while CodeRabbit was posting the review. Please request a new review later if the pull request still needs one. This happened while posting 2 inline comments. Use ⚙️ Run configurationConfiguration used: defaults Review profile: CHILL Plan: Pro Run ID: ⛔ Files ignored due to path filters (1)
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💤 Files with no reviewable changes (20)
✅ Files skipped from review due to trivial changes (13)
🚧 Files skipped from review as they are similar to previous changes (1)
🧰 Additional context used🪛 dotenv-linter (4.0.0)starter_ai_agents/microsoft_agents_starter/.env.example[warning] 1-1: [EndingBlankLine] No blank line at the end of the file (EndingBlankLine) 📝 WalkthroughWalkthroughAdds a new ChangesMicrosoft Agent Framework Starter
Sequence Diagram(s)sequenceDiagram
participant Script
participant MagenticManager
participant SpecialistAgent
participant OpenAIChatCompletionClient
participant NebiusTokenFactory
participant MonocleTracer
Script->>MonocleTracer: setup_monocle_telemetry(workflow_name)
Script->>MagenticManager: MagenticBuilder(...).build().run(task)
MagenticManager->>OpenAIChatCompletionClient: plan + assign specialists
OpenAIChatCompletionClient->>NebiusTokenFactory: POST /v1/chat/completions (Qwen model)
NebiusTokenFactory-->>OpenAIChatCompletionClient: team plan response
loop per specialist round
MagenticManager->>SpecialistAgent: AgentExecutor.execute(instruction)
SpecialistAgent->>OpenAIChatCompletionClient: tool call (search_flights / search_hotels / estimate_costs)
OpenAIChatCompletionClient->>NebiusTokenFactory: POST /v1/chat/completions
NebiusTokenFactory-->>OpenAIChatCompletionClient: specialist output
SpecialistAgent-->>MagenticManager: result
MonocleTracer->>MonocleTracer: record span (AgentExecutor + OpenAI)
end
MagenticManager-->>Script: final itinerary + cost breakdown
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Suggested labels
Suggested reviewers
🚥 Pre-merge checks | ✅ 3 | ❌ 2❌ Failed checks (2 warnings)
✅ Passed checks (3 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches🧪 Generate unit tests (beta)
Warning There were issues while running some tools. Please review the errors and either fix the tool's configuration or disable the tool if it's a critical failure. 🔧 Biome (2.5.0)starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_a262a1005533d3dc6fd375c37d31ee95_2026-06-11_15.01.07.jsonFile contains syntax errors that prevent linting: Line 497: expected Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
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@shivaylamba please check now We have using Nebius Token Factory LLM. |
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thanks can you share a quick 10-15 second video recording of this in action with Nebius? |
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Actionable comments posted: 5
🧹 Nitpick comments (3)
starter_ai_agents/microsoft_agents_starter/agents/orchestrations/handoff_travel.py (1)
93-98: 🧹 Nitpick | 🔵 Trivial | ⚡ Quick winClient factory creates a new instance per agent; consider implications for resource efficiency.
The
_client()function is called five times (once per agent creation at lines 102, 114, 126, 136, 144), resulting in five separateOpenAIChatCompletionClientinstances with identical configuration. For a production system, sharing a single client or using a session pool could reduce resource overhead. However, this isolation pattern may be intentional for agent autonomy, and for a starter/demo project, the impact is minimal.If consolidation is desired, consider:
_shared_client = _client() # Create once # Then reuse in agent definitions[optional_refactor]
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@starter_ai_agents/microsoft_agents_starter/agents/orchestrations/handoff_travel.py` around lines 93 - 98, The `_client()` function is being called multiple times to create separate OpenAIChatCompletionClient instances with identical configuration (at agent creation points for each agent). To improve resource efficiency, create a single shared client instance at the module level by defining a variable that calls `_client()` once, and then reuse this shared instance across all five agent definitions instead of calling `_client()` repeatedly. This reduces the overhead of creating multiple identical client instances while maintaining the same functionality.starter_ai_agents/microsoft_agents_starter/agents/multi_travel_agents.py (1)
10-13: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winGive this workflow a distinct Monocle
workflow_name.Line 11 reuses the single-agent workflow name (
okahu_demos_ms_openai_travel_agent), which makes traces from different scripts harder to separate. Use a unique name for this multi-agent flow.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@starter_ai_agents/microsoft_agents_starter/agents/multi_travel_agents.py` around lines 10 - 13, The setup_monocle_telemetry function call uses a generic workflow_name parameter value that matches the single-agent workflow, making it difficult to distinguish traces from this multi-agent script. Replace the current workflow_name value "okahu_demos_ms_openai_travel_agent" with a distinct name that clearly identifies this as a multi-agent travel workflow (for example, incorporating "multi" or similar identifier to differentiate it from the single-agent version).starter_ai_agents/microsoft_agents_starter/pyproject.toml (1)
9-15: 🩺 Stability & Availability | 🔵 TrivialPin all core runtime dependencies for starter reproducibility.
Lines 9–15 contain 7 unbounded dependencies that can break as upstream APIs evolve. While
agent-framework-azure-aiandmonocle-apptraceare pinned elsewhere in this file, the remaining dependencies lack constraints. For sample/starter repos, consistent bounded versions (matching the pattern of>=or==constraints used in other starters like autogen_starter) make onboarding deterministic.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@starter_ai_agents/microsoft_agents_starter/pyproject.toml` around lines 9 - 15, Add version constraints to all seven unbounded dependencies in the dependencies list (agent-framework-core, agent-framework-orchestrations, opentelemetry-semantic-conventions, opentelemetry-semantic-conventions-ai, openai, agent-framework-openai, and python-dotenv). Apply bounded version constraints using >= or == operators similar to the pattern used for agent-framework-azure-ai and monocle-apptrace elsewhere in the pyproject.toml file. This ensures reproducible installations for starter repositories and prevents breaking changes from upstream API evolution.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In
`@starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_concurrent_travel_74d8fd8b49678022698b5d61aad37dac_2026-06-11_15.02.14.json`:
- Around line 16-24: The trace file contains sensitive configuration details and
machine-specific paths that should not be committed. Regenerate the trace files
to match the Nebius-backed starter configuration by removing or replacing
references to api.openai.com and gpt-4o-mini with appropriate Nebius endpoints
and models, and sanitize the span_source field by removing the absolute local
file path and replacing it with a generic or relative reference. Apply these
same sanitization changes to all other committed trace files in the repository
to ensure consistency and prevent leaking machine-specific details.
In
`@starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_a262a1005533d3dc6fd375c37d31ee95_2026-06-11_14.59.02.json`:
- Line 18: The span_source field in the monocle trace JSON file contains an
absolute filesystem path including a username that leaks local machine details
when committed. Replace the absolute path value with a relative path or a
redacted/generic version that does not expose the full filesystem structure or
username information.
In
`@starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_sequential_travel_b1bde859279004d933dc0d1eba2e68da_2026-06-23_02.04.07.json`:
- Around line 1-685: The .monocle/ directory containing runtime trace artifacts
with execution-specific metadata (timestamps, span IDs, trace IDs) is being
committed to version control, which bloats repository history and violates
OpenTelemetry best practices. Add .monocle/ as a new entry to the .gitignore
file to prevent these transient observability outputs from being tracked in
version control, ensuring only meaningful source code and configuration files
are committed.
In `@starter_ai_agents/microsoft_agents_starter/agents/multi_travel_agents.py`:
- Around line 70-80: The code is storing full AgentRunResponse objects instead
of extracting their text content, which causes issues when interpolating
responses into prompts and returning them in the dictionary. Extract the `.text`
property from each agent response: after the await planner_agent.run() call that
assigns to itinerary (around line 70) and after the await critic_agent.run()
call that assigns to critique (around line 74), so that the critic_prompt string
interpolation on line 73 uses clean text instead of a response object, and the
return dictionary on lines 75-80 contains plain strings for the itinerary and
critique keys instead of response objects.
In `@starter_ai_agents/microsoft_agents_starter/agents/travel_agents.py`:
- Around line 40-43: The OpenAIChatCompletionClient instantiation can receive
None for the api_key parameter if NEBIUS_API_KEY environment variable is not
set, causing the failure to be deferred until the first request. Add an explicit
validation check before the client initialization where you retrieve the
NEBIUS_API_KEY environment variable and raise a clear, actionable exception if
it is not set. This ensures the script fails immediately at startup with a
helpful error message rather than during runtime when making requests.
---
Nitpick comments:
In `@starter_ai_agents/microsoft_agents_starter/agents/multi_travel_agents.py`:
- Around line 10-13: The setup_monocle_telemetry function call uses a generic
workflow_name parameter value that matches the single-agent workflow, making it
difficult to distinguish traces from this multi-agent script. Replace the
current workflow_name value "okahu_demos_ms_openai_travel_agent" with a distinct
name that clearly identifies this as a multi-agent travel workflow (for example,
incorporating "multi" or similar identifier to differentiate it from the
single-agent version).
In
`@starter_ai_agents/microsoft_agents_starter/agents/orchestrations/handoff_travel.py`:
- Around line 93-98: The `_client()` function is being called multiple times to
create separate OpenAIChatCompletionClient instances with identical
configuration (at agent creation points for each agent). To improve resource
efficiency, create a single shared client instance at the module level by
defining a variable that calls `_client()` once, and then reuse this shared
instance across all five agent definitions instead of calling `_client()`
repeatedly. This reduces the overhead of creating multiple identical client
instances while maintaining the same functionality.
In `@starter_ai_agents/microsoft_agents_starter/pyproject.toml`:
- Around line 9-15: Add version constraints to all seven unbounded dependencies
in the dependencies list (agent-framework-core, agent-framework-orchestrations,
opentelemetry-semantic-conventions, opentelemetry-semantic-conventions-ai,
openai, agent-framework-openai, and python-dotenv). Apply bounded version
constraints using >= or == operators similar to the pattern used for
agent-framework-azure-ai and monocle-apptrace elsewhere in the pyproject.toml
file. This ensures reproducible installations for starter repositories and
prevents breaking changes from upstream API evolution.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro
Run ID: da78c813-8919-4803-a2e2-6cc0fc359c17
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📒 Files selected for processing (39)
README.mdadvance_ai_agents/flowsentinal_audittrail/README.mdstarter_ai_agents/microsoft_agents_starter/.env.examplestarter_ai_agents/microsoft_agents_starter/.github/instructions/okahu.instructions.mdstarter_ai_agents/microsoft_agents_starter/.monocle/.copilot_sessions/.monocle_copilot_0d5e091c-a178-4488-9803-b8ed32ce2022.jsonlstarter_ai_agents/microsoft_agents_starter/.monocle/.copilot_sessions/.monocle_copilot_0d5e091c-a178-4488-9803-b8ed32ce2022.state.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/.monocle_copilot_trace.jsonlstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_concurrent_travel_74d8fd8b49678022698b5d61aad37dac_2026-06-11_15.02.14.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_concurrent_travel_dc0df2336109c8a390d917ce5aacd52d_2026-06-23_02.08.28.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_groupchat_travel_309ea6131cbf6f3baa63342285812aa3_2026-06-11_15.02.54.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_groupchat_travel_75dc4b0586f8003d165b1045380ceb20_2026-06-23_02.11.35.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_groupchat_travel_75dc4b0586f8003d165b1045380ceb20_2026-06-23_02.13.10.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_91c7db155f3ab910b5f75b8a782031e5_2026-06-23_02.05.23.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_91c7db155f3ab910b5f75b8a782031e5_2026-06-23_02.06.23.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_91c7db155f3ab910b5f75b8a782031e5_2026-06-23_02.07.23.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_a262a1005533d3dc6fd375c37d31ee95_2026-06-11_14.59.02.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_a262a1005533d3dc6fd375c37d31ee95_2026-06-11_15.00.02.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_handoff_travel_a262a1005533d3dc6fd375c37d31ee95_2026-06-11_15.01.07.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_magentic_travel_55d727e05bc67d4248cb78e52e76b14d_2026-06-23_02.09.35.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_magentic_travel_55d727e05bc67d4248cb78e52e76b14d_2026-06-23_02.11.05.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_sequential_travel_b1bde859279004d933dc0d1eba2e68da_2026-06-23_02.04.07.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_sequential_travel_b1bde859279004d933dc0d1eba2e68da_2026-06-23_02.05.07.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_sequential_travel_c68417ff7cfe2389011fbc2104b382f5_2026-06-11_13.42.02.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_travel_agent_150d5de2abe288e7fd28bd6041a1e221_2026-06-23_01.57.15.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_travel_agent_36e95f4717aea8ce27d699550e17fb7c_2026-06-23_01.56.59.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_travel_agent_53f6ed6227ed7060f045dc47da2f7330_2026-06-23_01.55.33.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_travel_agent_70b101e041d86b7a15460df7f4f4de64_2026-06-11_12.25.36.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_travel_agent_91a6b83d0ec4d895ce67d40d5cd9e1e1_2026-06-11_12.24.12.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_travel_agent_933ec10a2f3efc9ba59b3929e3d6bddc_2026-06-11_13.22.52.jsonstarter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_travel_agent_ca9d31ffd24a0a22c754d20df0e0b7b0_2026-06-11_13.22.57.jsonstarter_ai_agents/microsoft_agents_starter/README.mdstarter_ai_agents/microsoft_agents_starter/agents/multi_travel_agents.pystarter_ai_agents/microsoft_agents_starter/agents/orchestrations/concurrent_travel.pystarter_ai_agents/microsoft_agents_starter/agents/orchestrations/group_chat_travel.pystarter_ai_agents/microsoft_agents_starter/agents/orchestrations/handoff_travel.pystarter_ai_agents/microsoft_agents_starter/agents/orchestrations/magentic_travel.pystarter_ai_agents/microsoft_agents_starter/agents/orchestrations/sequential_travel.pystarter_ai_agents/microsoft_agents_starter/agents/travel_agents.pystarter_ai_agents/microsoft_agents_starter/pyproject.toml
…y updated in README.md file.
…y updated in README.md file.
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Actionable comments posted: 2
🧹 Nitpick comments (1)
starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_concurrent_travel_dc0df2336109c8a390d917ce5aacd52d_2026-06-23_02.08.28.json (1)
1-632: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winConsider excluding trace files from version control.
This trace file and ~20 others in
.monocle/are runtime observability artifacts that are typically excluded from version control via.gitignore. Committing large trace JSON files causes repository bloat and isn't standard practice for telemetry data.If the goal is to demonstrate observability capabilities (as suggested by the PR screenshot):
- Preferred approach: Add
.monocle/to.gitignoreand document trace generation in the README- Alternative: Include one compact example trace (< 100 lines) in
docs/examples/with explanatory comments- Current approach: The screenshot you provided already effectively demonstrates the feature
📝 Proposed .gitignore addition
Add to
.gitignoreat the project or repository root:+# Monocle observability traces (runtime artifacts) +.monocle/🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_concurrent_travel_dc0df2336109c8a390d917ce5aacd52d_2026-06-23_02.08.28.json` around lines 1 - 632, The trace JSON files in the .monocle/ directory are runtime observability artifacts that should not be committed to version control as they cause repository bloat. Add .monocle/ to the .gitignore file at the project root to exclude these telemetry files from future commits. Additionally, consider removing the already-committed trace files from the repository using git rm or similar commands. If demonstrating observability capabilities is important, document trace generation in the README instead of committing actual trace artifacts, or optionally include one small example trace file (under 100 lines) in a docs/examples/ directory with explanatory comments.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@starter_ai_agents/microsoft_agents_starter/.env.example`:
- Line 1: The `.env.example` file needs two improvements: first, add descriptive
comments above the NEBIUS_API_KEY variable that explain its purpose and guide
developers on where to obtain the API key, and second, ensure the file ends with
a trailing newline (which is a standard best practice for text files and
required by dotenv-linter). These changes will improve developer onboarding and
maintain proper file formatting standards.
In
`@starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_concurrent_travel_dc0df2336109c8a390d917ce5aacd52d_2026-06-23_02.08.28.json`:
- Line 18: The trace file contains absolute local filesystem paths in the
span_source attributes throughout the document (at lines 18, 86, 137, 205, 257,
325, 377, 445, 497, 564, and 614), which exposes sensitive development
environment information. To fix this, either add the monocle trace files to
.gitignore to prevent them from being committed to version control, or sanitize
the span_source attribute values throughout the trace file to use relative paths
or redacted placeholder values instead of the absolute filesystem paths.
---
Nitpick comments:
In
`@starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_concurrent_travel_dc0df2336109c8a390d917ce5aacd52d_2026-06-23_02.08.28.json`:
- Around line 1-632: The trace JSON files in the .monocle/ directory are runtime
observability artifacts that should not be committed to version control as they
cause repository bloat. Add .monocle/ to the .gitignore file at the project root
to exclude these telemetry files from future commits. Additionally, consider
removing the already-committed trace files from the repository using git rm or
similar commands. If demonstrating observability capabilities is important,
document trace generation in the README instead of committing actual trace
artifacts, or optionally include one small example trace file (under 100 lines)
in a docs/examples/ directory with explanatory comments.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro
Run ID: d57a436e-6dc1-4986-9f21-a6c67ef18d87
⛔ Files ignored due to path filters (1)
starter_ai_agents/microsoft_agents_starter/.monocle/.copilot_sessions/.0d5e091c-a178-4488-9803-b8ed32ce2022.lockis excluded by!**/*.lock
📒 Files selected for processing (39)
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💤 Files with no reviewable changes (20)
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✅ Files skipped from review due to trivial changes (13)
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🚧 Files skipped from review as they are similar to previous changes (1)
- starter_ai_agents/microsoft_agents_starter/.monocle/monocle_trace_okahu_demos_ms_openai_magentic_travel_55d727e05bc67d4248cb78e52e76b14d_2026-06-23_02.09.35.json
Collaborator
|
hey @anjijava16 have you shared a video demo for the project? |
Contributor
Author
|
@shivaylamba please see sample demo NEBIUS with Microsoft agent framework here with https://www.youtube.com/watch?v=WLbywg21YJY |
Collaborator
|
thanks for sharing |
Collaborator
|
thanks for taking out the time to make this contributio n |
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🔗 Linked Issue
Closes #
✅ Type of Change
📝 Summary
This PR adds a Microsoft Agent Framework starter project with full Monocle observability integration.
Key changes:
📖 README Checklist
README.mdfile for my project.README.mdfollows the official.github/README_TEMPLATE.md.README.md.assetsfolder and included it in myREADME.md.✔️ Contributor Checklist
advance_ai_agents,rag_apps).requirements.txtorpyproject.tomlfor dependencies..env.examplefile if environment variables are needed and ensured no secrets are committed.💬 Additional Comments
This integrates Microsoft's Agent Framework with Claude models via LiteLLM, with Monocle providing observability/tracing for agent execution. Feedback on directory placement and naming is welcome.
Summary by CodeRabbit
Release Notes