feat(rag): add --embed-model flag with nomic-embed-text default
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@@ -12,7 +12,7 @@ from rich.panel import Panel
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from rich.rule import Rule
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from rich.rule import Rule
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from rich.text import Text
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from rich.text import Text
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from tai.ai_client import DEFAULT_AI_HOST, DEFAULT_MODEL, AIClient, AIConfig
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from tai.ai_client import DEFAULT_AI_HOST, DEFAULT_EMBED_MODEL, DEFAULT_MODEL, AIClient, AIConfig
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from tai.ai_guardrails import validate_ai_response
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from tai.ai_guardrails import validate_ai_response
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from tai.collectors import CollectionReport, collect_from_plan
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from tai.collectors import CollectionReport, collect_from_plan
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from tai.input_parser import InputValidationError, build_request
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from tai.input_parser import InputValidationError, build_request
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@@ -110,6 +110,13 @@ def run(
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help="Disable RAG; send full diagnostics to AI instead of retrieved chunks.",
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help="Disable RAG; send full diagnostics to AI instead of retrieved chunks.",
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),
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),
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] = False,
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] = False,
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embed_model: Annotated[
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str,
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typer.Option(
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"--embed-model",
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help="Embedding model for RAG. Must be pulled in Ollama on the AI host.",
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),
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] = DEFAULT_EMBED_MODEL,
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) -> None:
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) -> None:
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"""Start an interactive troubleshooting session scaffold."""
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"""Start an interactive troubleshooting session scaffold."""
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try:
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try:
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@@ -145,7 +152,7 @@ def run(
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if not (probe or collect or analyze or interactive):
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if not (probe or collect or analyze or interactive):
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return # nothing SSH-related requested
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return # nothing SSH-related requested
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ai_config = AIConfig(host=ai_host, model=model, api_key=ai_key)
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ai_config = AIConfig(host=ai_host, model=model, api_key=ai_key, embed_model=embed_model)
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logger = SessionLogger.create(log_file) if log_file else None
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logger = SessionLogger.create(log_file) if log_file else None
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if analyze or interactive:
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if analyze or interactive:
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console.print(f"[cyan]AI:[/cyan] {AIClient(ai_config).summary()}")
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console.print(f"[cyan]AI:[/cyan] {AIClient(ai_config).summary()}")
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