my prefect server setup
prefect-metrics.waow.tech
python
orchestration
use prefect Variable for weave model selection
reads `weave-model` variable at runtime (default: claude-sonnet-4-6).
changeable via `prefect variable set weave-model <model>` without redeploy.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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flows/weave.py
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flows/weave.py
···
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from prefect.blocks.system import Secret
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from prefect.cache_policies import CachePolicy
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from prefect.context import TaskRunContext
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from prefect.variables import Variable
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from mps.phi import TagMerge, TagRelationship
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···
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tag_info: dict[str, dict],
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tag_embeddings: dict[str, list[float]],
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api_key: str,
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model_name: str = "claude-sonnet-4-6",
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) -> list[dict[str, Any]]:
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"""Give the LLM the full tag inventory and let it propose consolidations."""
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# format every tag with usage context so the LLM can make informed decisions
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inventory = "\n".join(tag_lines)
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model = AnthropicModel(
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"claude-sonnet-4-6", provider=AnthropicProvider(api_key=api_key)
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model_name, provider=AnthropicProvider(api_key=api_key)
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)
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agent = Agent(
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model,
···
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user_tag_sets: dict[str, list[str]],
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merged_aliases: set[str],
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api_key: str,
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model_name: str = "claude-sonnet-4-6",
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) -> list[dict[str, Any]]:
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"""Give the LLM the full tag list with co-occurrence context to find relationships."""
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tags = [t for t in sorted(tag_info.keys()) if t not in merged_aliases]
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inventory = "\n".join(tag_lines)
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model = AnthropicModel(
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"claude-sonnet-4-6", provider=AnthropicProvider(api_key=api_key)
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model_name, provider=AnthropicProvider(api_key=api_key)
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)
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agent = Agent(
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model,
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tpuf_key = (await Secret.load("turbopuffer-api-key")).get()
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openai_key = (await Secret.load("openai-api-key")).get()
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anthropic_key = (await Secret.load("anthropic-api-key")).get()
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model_name = await Variable.get("weave-model", default="claude-sonnet-4-6")
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print(f"using model: {model_name}")
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# --- phase 1: collect and deduplicate tags ---
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tag_data = collect_all_tags(tpuf_key)
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tags_text = "\n".join(tags)
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merge_dicts = await identify_tag_merges(
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tags_text, tag_info, tag_embeddings, anthropic_key
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tags_text, tag_info, tag_embeddings, anthropic_key, model_name=model_name
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)
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# collect all aliases for filtering in phase 2
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user_tag_sets,
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merged_aliases,
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anthropic_key,
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model_name=model_name,
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)
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print(f"phase 2: discovered {len(rel_dicts)} tag relationships")
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