nihalashetty
ae67bff5a3
Self-hosted platform for building, testing, and shipping LangChain/LangGraph agents. Deep-agent sub-agents on the canvas, a live tracing/observability timeline, auto-provisioned built-in tools with import/export, per-environment tool variables, streamed evaluations, and per-user auth token forwarding.
65 lines
1.7 KiB
Python
65 lines
1.7 KiB
Python
"""Model catalog - drives every model picker in the console (chat, embedding, reranker).
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Served from `forge.model_catalog`, the same lists the built-in pricing rates derive from, so a
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dropdown can only ever offer models the backend can actually run (and, for chat, price). This is
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the single source of truth: the frontend hardcodes no model lists.
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"""
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from __future__ import annotations
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from fastapi import APIRouter
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from pydantic import BaseModel
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from forge.model_catalog import CHAT_MODELS, EMBEDDING_MODELS, RERANKER_MODELS
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router = APIRouter(prefix="/v1/models", tags=["catalog"])
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class ChatModelOut(BaseModel):
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id: str
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name: str
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provider: str
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ctx: str
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tools: bool
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vision: bool
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class EmbeddingModelOut(BaseModel):
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id: str
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name: str
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provider: str
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dim: int
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billed: bool
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default: bool
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class RerankerModelOut(BaseModel):
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id: str
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name: str
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note: str
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default: bool
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class ModelCatalogOut(BaseModel):
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chat: list[ChatModelOut]
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embedding: list[EmbeddingModelOut]
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reranker: list[RerankerModelOut]
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@router.get("", response_model=ModelCatalogOut)
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async def list_models() -> ModelCatalogOut:
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return ModelCatalogOut(
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chat=[
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ChatModelOut(id=m.id, name=m.name, provider=m.provider, ctx=m.ctx, tools=m.tools, vision=m.vision)
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for m in CHAT_MODELS
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],
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embedding=[
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EmbeddingModelOut(id=m.id, name=m.name, provider=m.provider, dim=m.dim, billed=m.billed, default=m.default)
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for m in EMBEDDING_MODELS
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],
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reranker=[
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RerankerModelOut(id=m.id, name=m.name, note=m.note, default=m.default)
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for m in RERANKER_MODELS
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],
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)
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