Surface LLM errors in CLI, use pi-ai credential detection, and implement model fallback

[Priyanshu-Priyam]

Summary

• Surface LLM errors in CLI: When a model returns stopReason: "error" (e.g. Bedrock rejecting a model ID), the CLI now prints the error message in red instead of showing a blank line. Also fires on_error hooks and audit logging for these failures.

• Use pi-ai's getEnvApiKey() for credential detection: Replaces the hardcoded 6-provider API key map with pi-ai's provider-aware function, which supports all providers including Amazon Bedrock, Google Vertex, Azure OpenAI, GitHub Copilot, and others.

• Implement model.fallback support: When the preferred model fails, automatically retry with the next model from agent.yaml's model.fallback list. Works in both CLI (REPL + single-shot) and SDK (query()) paths. This activates the already-declared but previously unused fallback field in the agent manifest.

Motivation

When using amazon-bedrock:anthropic.claude-opus-4-6-v1, Bedrock returns an error ("on-demand throughput isn't supported, use an inference profile"). The CLI showed a blank response with no error -- making it impossible to diagnose. The SDK path (sdk.ts) already handled this correctly; the CLI did not.

Test plan

• npm run build passes
• All 19 existing tests pass
• Manual: run with a model that returns an error -- error now visible in red
• Manual: set fallback in agent.yaml with a broken preferred model -- agent falls back automatically

[shreyas-lyzr]

This PR adds error surfacing and model fallback — good goals. However the diff is against a very old base and will have massive merge conflicts with current main. The codebase has changed significantly since this was opened.

Recommend closing this and re-opening against current main if the features are still desired.