fix(predict-diabetes): update dependency mlflow to v2.9.2

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
mlflow (source)	2.9.1 -> 2.9.2

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Release Notes

mlflow/mlflow (mlflow)

v2.9.2

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MLflow 2.9.2 is a patch release, containing several critical security fixes and configuration updates to support extremely large model artifacts.

Features:

• [Deployments] Add the mlflow.deployments.openai API to simplify direct access to OpenAI services through the deployments API (#​10473, @​prithvikannan)
• [Server-infra] Add a new environment variable that permits disabling http redirects within the Tracking Server for enhanced security in publicly accessible tracking server deployments (#​10673, @​daniellok-db)
• [Artifacts] Add environment variable configurations for both Multi-part upload and Multi-part download that permits modifying the per-chunk size to support extremely large model artifacts (#​10648, @​harupy)

Security fixes:

• [Server-infra] Disable the ability to inject malicious code via manipulated YAML files by forcing YAML rendering to be performed in a secure Sandboxed mode (#​10676, @​BenWilson2, #​10640, @​harupy)
• [Artifacts] Prevent path traversal attacks when querying artifact URI locations by disallowing .. path traversal queries (#​10653, @​B-Step62)
• [Data] Prevent a mechanism for conducting a malicious file traversal attack on Windows when using tracking APIs that interface with HTTPDatasetSource (#​10647, @​BenWilson2)
• [Artifacts] Prevent a potential path traversal attack vector via encoded url traversal paths by decoding paths prior to evaluation (#​10650, @​B-Step62)
• [Artifacts] Prevent the ability to conduct path traversal attacks by enforcing the use of sanitized paths with the tracking server (#​10666, @​harupy)
• [Artifacts] Prevent path traversal attacks when using an FTP server as a backend store by enforcing base path declarations prior to accessing user-supplied paths (#​10657, @​harupy)

Documentation updates:

• [Docs] Add an end-to-end tutorial for RAG creation and evaluation (#​10661, @​AbeOmor)
• [Docs] Add Tensorflow landing page (#​10646, @​chenmoneygithub)
• [Deployments / Tracking] Add endpoints to LLM evaluation docs (#​10660, @​prithvikannan)
• [Examples] Add retriever evaluation tutorial for LangChain and improve the Question Generation tutorial notebook (#​10419, @​liangz1)

Small bug fixes and documentation updates:

#​10677, #​10636, @​serena-ruan; #​10652, #​10649, #​10641, @​harupy; #​10643, #​10632, @​BenWilson2

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[github-actions]

🎉 This PR is included in version 1.98.2 🎉

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