mirror of
https://github.com/Alishahryar1/free-claude-code.git
synced 2026-07-03 14:05:26 +02:00
6bee3104fe
## Problem The CLI package preserved a generic adapter layer and managed Codex parser path that did not match the supported customer workflows. Messaging runs Claude Code sessions, while Codex is supported through `fcc-codex` and extensions. ## Changes | Before | After | | --- | --- | | `fcc-claude` and `fcc-codex` shared generic adapter plumbing. | `fcc-claude` and `fcc-codex` use explicit launcher modules. | | Messaging depended on a generic CLI session abstraction. | Messaging depends on managed Claude Code sessions. | | Codex catalog generation lived as a top-level CLI helper. | Codex catalog generation lives under the Codex launcher owner. | | Tests asserted deleted internal adapter shapes. | Tests assert launcher, managed-Claude, and customer-surface behavior. |
187 lines
5.8 KiB
Python
187 lines
5.8 KiB
Python
"""Build Codex model catalogs from the FCC model-list route."""
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from __future__ import annotations
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import json
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import uuid
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from collections.abc import Mapping
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any
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from api.gateway_model_ids import (
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GATEWAY_MODEL_ID_PREFIX,
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NO_THINKING_GATEWAY_MODEL_ID_PREFIX,
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)
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from config.provider_ids import SUPPORTED_PROVIDER_IDS
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SUPPORTED_REASONING_LEVELS = [
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{"effort": "low", "description": "Fast responses with lighter reasoning"},
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{
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"effort": "medium",
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"description": "Balances speed and reasoning depth for everyday tasks",
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},
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{"effort": "high", "description": "Greater reasoning depth for complex problems"},
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{
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"effort": "xhigh",
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"description": "Extra high reasoning depth for complex problems",
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},
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]
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CODEX_BASE_INSTRUCTIONS = (
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"You are Codex, a coding agent. Help the user understand, modify, test, "
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"and review code in their workspace. Follow the user's instructions, use "
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"tools when needed, and communicate concise progress and verification."
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)
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@dataclass(frozen=True, slots=True)
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class _CatalogCandidate:
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slug: str
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provider_model_ref: str
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display_name: str
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force_no_thinking: bool
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def build_codex_model_catalog(models_response: Mapping[str, Any]) -> dict[str, Any]:
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"""Convert FCC `/v1/models` data into Codex `model_catalog_json` payload."""
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candidates = list(_catalog_candidates(models_response))
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normal_provider_refs = {
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candidate.provider_model_ref
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for candidate in candidates
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if not candidate.force_no_thinking
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}
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models: list[dict[str, Any]] = []
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seen_slugs: set[str] = set()
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for candidate in candidates:
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if (
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candidate.force_no_thinking
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and candidate.provider_model_ref in normal_provider_refs
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):
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continue
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if candidate.slug in seen_slugs:
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continue
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seen_slugs.add(candidate.slug)
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models.append(_codex_catalog_entry(candidate, priority=len(models)))
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return {"models": models}
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def write_codex_model_catalog(catalog_path: Path, catalog: Mapping[str, Any]) -> None:
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"""Atomically write a Codex model catalog JSON file."""
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catalog_path.parent.mkdir(parents=True, exist_ok=True)
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temp_path = catalog_path.with_name(f".{catalog_path.name}.{uuid.uuid4().hex}.tmp")
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temp_path.write_text(
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json.dumps(catalog, ensure_ascii=True, indent=2) + "\n",
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encoding="utf-8",
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)
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temp_path.replace(catalog_path)
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def _catalog_candidates(
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models_response: Mapping[str, Any],
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) -> list[_CatalogCandidate]:
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data = models_response.get("data")
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if not isinstance(data, list):
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return []
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candidates: list[_CatalogCandidate] = []
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for item in data:
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if not isinstance(item, Mapping):
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continue
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model_id = _string_value(item.get("id"))
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if model_id is None:
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continue
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candidate = _candidate_from_model_id(
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model_id,
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display_name=_string_value(item.get("display_name")) or model_id,
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)
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if candidate is not None:
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candidates.append(candidate)
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return candidates
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def _candidate_from_model_id(
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model_id: str, *, display_name: str
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) -> _CatalogCandidate | None:
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prefix, separator, remainder = model_id.partition("/")
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if not separator:
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return None
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if prefix == GATEWAY_MODEL_ID_PREFIX:
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if not _is_provider_model_ref(remainder):
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return None
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return _CatalogCandidate(
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slug=remainder,
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provider_model_ref=remainder,
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display_name=display_name,
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force_no_thinking=False,
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)
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if prefix == NO_THINKING_GATEWAY_MODEL_ID_PREFIX:
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if not _is_provider_model_ref(remainder):
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return None
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return _CatalogCandidate(
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slug=model_id,
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provider_model_ref=remainder,
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display_name=display_name,
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force_no_thinking=True,
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)
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if prefix in SUPPORTED_PROVIDER_IDS and remainder:
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return _CatalogCandidate(
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slug=model_id,
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provider_model_ref=model_id,
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display_name=display_name,
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force_no_thinking=False,
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)
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return None
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def _codex_catalog_entry(
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candidate: _CatalogCandidate, *, priority: int
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) -> dict[str, Any]:
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return {
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"slug": candidate.slug,
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"display_name": candidate.display_name,
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"description": "Free Claude Code provider model",
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"default_reasoning_level": "medium",
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"supported_reasoning_levels": SUPPORTED_REASONING_LEVELS,
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"shell_type": "shell_command",
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"visibility": "list",
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"supported_in_api": True,
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"priority": priority,
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"additional_speed_tiers": [],
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"service_tiers": [],
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"base_instructions": CODEX_BASE_INSTRUCTIONS,
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"supports_reasoning_summaries": True,
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"default_reasoning_summary": "none",
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"support_verbosity": True,
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"default_verbosity": "low",
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"apply_patch_tool_type": "freeform",
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"web_search_tool_type": "text_and_image",
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"truncation_policy": {"mode": "tokens", "limit": 10000},
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"supports_parallel_tool_calls": True,
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"supports_image_detail_original": True,
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"context_window": 200000,
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"max_context_window": 200000,
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"effective_context_window_percent": 95,
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"experimental_supported_tools": [],
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"input_modalities": ["text"],
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"supports_search_tool": True,
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"use_responses_lite": False,
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}
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def _is_provider_model_ref(value: str) -> bool:
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provider_id, separator, provider_model = value.partition("/")
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return bool(separator and provider_model and provider_id in SUPPORTED_PROVIDER_IDS)
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def _string_value(value: Any) -> str | None:
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return value if isinstance(value, str) else None
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