diff --git a/cecli/coders/base_coder.py b/cecli/coders/base_coder.py index 40af87cea47..8a97d577c0c 100755 --- a/cecli/coders/base_coder.py +++ b/cecli/coders/base_coder.py @@ -4310,13 +4310,9 @@ def calculate_and_show_tokens_and_cost(self, messages, completion=None): cache_write_tokens = getattr(completion.usage, "cache_creation_input_tokens", 0) or 0 self.message_cached_tokens += cache_hit_tokens - if hasattr(completion.usage, "cache_read_input_tokens") or hasattr( - completion.usage, "cache_creation_input_tokens" - ): - self.message_tokens_sent += prompt_tokens - self.message_tokens_sent += cache_write_tokens - else: - self.message_tokens_sent += prompt_tokens + # ``prompt_tokens`` is normalized to the full input (including any + # cache read/write) for anthropic usage, so no separate add here. + self.message_tokens_sent += prompt_tokens else: prompt_tokens = self.get_active_model().token_count(messages) diff --git a/cecli/helpers/conversation/manager.py b/cecli/helpers/conversation/manager.py index ed7e644cda6..8c42a4addcc 100644 --- a/cecli/helpers/conversation/manager.py +++ b/cecli/helpers/conversation/manager.py @@ -367,6 +367,7 @@ def get_messages_dict( and coder.add_cache_headers and hasattr(coder, "main_model") and not coder.main_model.caches_by_default + and not getattr(coder.main_model, "uses_messages_api", False) ): messages_dict = self._add_cache_control(messages_dict) return messages_dict diff --git a/cecli/helpers/llms/config.py b/cecli/helpers/llms/config.py index 74f16b7bd8f..10cbeedf1d9 100644 --- a/cecli/helpers/llms/config.py +++ b/cecli/helpers/llms/config.py @@ -28,6 +28,14 @@ "github_copilot": {"api_base": "https://api.githubcopilot.com", "api_key_env": None}, "meta": {"api_base": "https://api.meta.ai/v1", "api_key_env": "META_API_KEY"}, "chutes": {"api_base": "https://llm.chutes.ai/v1/", "api_key_env": "CHUTES_API_KEY"}, + "opencode-go": { + "api_base": "https://opencode.ai/zen/go/v1", + "api_key_env": "OPENCODE_GO_API_KEY", + }, + "opencode-zen": { + "api_base": "https://opencode.ai/zen/zen/v1", + "api_key_env": "OPENCODE_ZEN_API_KEY", + }, } @@ -40,12 +48,39 @@ def resolve_model_config(model: str) -> Dict[str, Any]: cfg = get_default_config(model) llm_block = cfg.get("llm") or {} api_block = cfg.get("api") or {} - provider = llm_block.get("litellm_provider") or ( - model.split("/", 1)[0] if "/" in model else None - ) + agent_block = dict(cfg.get("agent") or {}) + prefix = model.split("/", 1)[0] if "/" in model else None + provider = llm_block.get("litellm_provider") or prefix route = model.split("/", 1)[1] if "/" in model else model + is_claude = "claude" in route.lower() mpm = ModelProviderManager() + + # Providers with dedicated routing semantics (authenticated session, AWS + # SigV4 signing, dedicated endpoint templates) win over the metadata + # record's ``litellm_provider`` for every model under their prefix, so a + # ``github_copilot/`` / ``bedrock/`` / ``bedrock_mantle/`` model never + # falls back to a bare (anthropic/openai) record (e.g. + # ``github_copilot/claude-sonnet-4-5`` resolving to the bare + # ``claude-sonnet-4-5`` anthropic entry). + if prefix in ("github_copilot", "bedrock", "bedrock_mantle"): + provider = prefix + + # Anthropic models hosted by a third-party provider (openrouter, deepseek, + # ...) authenticate against THAT provider, not anthropic: ``{provider}/claude-*`` + # must route through the provider prefix even when the record lookup lands + # on the bare anthropic entry (e.g. ``openrouter/claude-sonnet-5``). + elif prefix and prefix != "anthropic" and is_claude: + provider = prefix + + # A configured provider (built-in providers.json entry or a user-defined + # ``model-providers`` entry such as ``bifrost``) wins over the metadata + # record's ``litellm_provider`` for every model under its prefix, so + # ``bifrost/gemini/gemini-2.5-pro`` routes through bifrost (its api_base) + # rather than falling back to the bare ``gemini/gemini-2.5-pro`` record. + elif prefix and provider != prefix and mpm.supports_provider(prefix): + provider = prefix + pcfg = mpm.get_provider_config(provider) or {} env_base = os.environ.get(f"{provider.upper()}_API_BASE") if provider else None @@ -88,6 +123,12 @@ def resolve_model_config(model: str) -> Dict[str, Any]: # Mantle is an OpenAI-compatible chat wire (SigV4-signed via the chat # family's signer hook); see providers/bedrock_mantle.py. family = "chat" + elif is_claude and provider != "anthropic": + # A claude model on a non-anthropic provider uses that provider's + # OpenAI-compatible chat completions wire (openrouter, deepseek, + # azure_ai, ...); only native anthropic (or copilot's anthropic-native + # /v1/messages proxy, handled above) speaks the messages API. + family = "chat" elif mode == "responses" or "/v1/responses" in endpoints: family = "responses" elif provider == "anthropic": @@ -100,6 +141,14 @@ def resolve_model_config(model: str) -> Dict[str, Any]: extra_headers = dict(pcfg.get("default_headers") or {}) extra_body = dict(api_block.get("extra_body") or {}) + # Effective cache flags for the domain adapters. Anthropic messages-API + # models never cache "by default": prompt caching only happens when the + # request carries explicit ``cache_control`` breakpoints, so the messages + # domain injects them (agent.cache_control True + caches_by_default False). + if family == "messages": + agent_block["cache_control"] = True + agent_block["caches_by_default"] = False + return { "model": model, "provider": provider, @@ -112,6 +161,7 @@ def resolve_model_config(model: str) -> Dict[str, Any]: "extra_query": dict(pcfg.get("extra_query") or {}), "api_block": api_block, "llm_block": llm_block, + "agent_block": agent_block, } diff --git a/cecli/helpers/llms/domains/chat.py b/cecli/helpers/llms/domains/chat.py index 8b7499a7c03..7aa4a29aca8 100644 --- a/cecli/helpers/llms/domains/chat.py +++ b/cecli/helpers/llms/domains/chat.py @@ -5,12 +5,20 @@ handles the three wild shapes (reasoning_content / reasoning / reasoning_details). Reasoning tokens reported without streamed text are marked redacted (``Message.reasoning_redacted``). + +At request time the ``OPENAI_API_BASE`` / ``OPENAI_API_KEY`` env vars +(docs/llms/openai-compat.md) can redirect the wire to any OpenAI-compatible +endpoint: ``OPENAI_API_BASE`` wins over the resolved base and +``OPENAI_API_KEY`` replaces the provider key when the base is a well-formed +http(s) URL. """ from __future__ import annotations import json -from typing import Any, AsyncIterator, Dict, List, Optional +import os +from typing import Any, AsyncIterator, Dict, List, Optional, Tuple +from urllib.parse import urlparse from ..runtime import VERIFY_SSL, make_client from ..types import ( @@ -94,12 +102,18 @@ async def chat_complete( headers: Dict[str, str], kwargs: Dict[str, Any], ) -> CompletionResponse: - url = f"{resolved['api_base']}/chat/completions" + env = _openai_env_override() + base = env[0] if env else resolved["api_base"] + url = f"{base}/chat/completions" payload = chat_payload(resolved, messages, tools, False, kwargs) hdrs = {"Content-Type": "application/json", **headers} body: Optional[bytes] = None signer = resolved.get("_signer") + if env and env[1]: + key = env[1] + hdrs["Authorization"] = f"Bearer {key}" + if signer: url, hdrs, body = signer(url, payload, hdrs, key) @@ -127,12 +141,18 @@ async def chat_stream( headers: Dict[str, str], kwargs: Dict[str, Any], ) -> AsyncIterator[CompletionChunk]: - url = f"{resolved['api_base']}/chat/completions" + env = _openai_env_override() + base = env[0] if env else resolved["api_base"] + url = f"{base}/chat/completions" payload = chat_payload(resolved, messages, tools, True, kwargs) hdrs = {"Content-Type": "application/json", **headers} body: Optional[bytes] = None signer = resolved.get("_signer") + if env and env[1]: + key = env[1] + hdrs["Authorization"] = f"Bearer {key}" + if signer: url, hdrs, body = signer(url, payload, hdrs, key) @@ -364,6 +384,30 @@ def _map_reasoning_content(msg: Dict[str, Any]) -> str: return "\n".join(texts) +def _openai_env_override() -> Optional[Tuple[str, Optional[str]]]: + """Return (api_base, api_key) from the OPENAI_API_* env vars when the base + is a well-formed http(s) URL (docs/llms/openai-compat.md). + + Lets a custom OpenAI-compatible endpoint take over the chat completions + wire at request time: the env base wins over the resolved provider base and + OPENAI_API_KEY replaces the provider's own key for that request. A base + that is not a well-formed URL (no http(s) scheme / host, e.g. + ``localhost:8000``) is ignored so unrelated OPENAI_API_* leftovers cannot + hijack requests. + """ + raw = os.environ.get("OPENAI_API_BASE") + + if not raw: + return None + + parsed = urlparse(raw.strip()) + + if parsed.scheme not in ("http", "https") or not parsed.netloc: + return None + + return (raw.strip().rstrip("/"), os.environ.get("OPENAI_API_KEY") or None) + + __all__ = [ "chat_payload", "chat_complete", diff --git a/cecli/helpers/llms/domains/messages.py b/cecli/helpers/llms/domains/messages.py index 412e5e7bea9..fabe17b1867 100644 --- a/cecli/helpers/llms/domains/messages.py +++ b/cecli/helpers/llms/domains/messages.py @@ -33,6 +33,9 @@ DEFAULT_TIMEOUT = 120.0 +#: Anthropic allows at most 4 ``cache_control`` breakpoints per request. +MAX_CACHE_BREAKPOINTS = 4 + def anthropic_payload( resolved: Dict[str, Any], @@ -58,6 +61,7 @@ def anthropic_payload( payload["tools"] = [anthropic_tool(t) for t in tools] api_block = resolved.get("api_block") or {} + agent_block = resolved.get("agent_block") or {} # Caller/system overrides ride in ``kwargs["extra_body"]`` (models.py's # ``set_reasoning_effort`` / ``set_thinking_tokens``). Merge them into the @@ -90,6 +94,16 @@ def anthropic_payload( extra_body.pop("reasoning_effort", None) extra_body.pop("thinking", None) payload.update(extra_body) + + # Anthropic prompt caching is a byte-exact prefix match: it only happens + # when the request carries explicit ``cache_control`` breakpoints. The + # model config flags messages-API models ``cache_control`` True and + # ``caches_by_default`` False (see config.resolve_model_config), so the + # messages domain owns the marking here rather than the conversation + # manager. + if agent_block.get("cache_control") and not agent_block.get("caches_by_default"): + _apply_anthropic_cache_control(payload) + return payload @@ -465,11 +479,20 @@ def _finish_reason(stop_reason: Optional[str]) -> Optional[str]: def _anthropic_usage(usage_raw: Dict[str, Any]) -> Usage: - """Build a normalized Usage from an Anthropic usage block.""" + """Build a normalized Usage from an Anthropic usage block. + + Anthropic's ``input_tokens`` excludes cached input, so ``prompt_tokens`` + is normalized to the full input (``input_tokens + cache_read + + cache_creation``) to match the OpenAI-style semantics + ``base_coder.calculate_and_show_tokens_and_cost`` expects: its hit-rate + and cost math rely on ``prompt_tokens`` being the total input + (``cache_creation + cache_read + input == total``). + """ input_tokens = usage_raw.get("input_tokens") or 0 output_tokens = usage_raw.get("output_tokens") or 0 cache_read = usage_raw.get("cache_read_input_tokens") or 0 cache_creation = usage_raw.get("cache_creation_input_tokens") or 0 + prompt_tokens = input_tokens + cache_read + cache_creation details: Dict[str, Any] = {} output_details = usage_raw.get("output_tokens_details") or {} @@ -484,9 +507,9 @@ def _anthropic_usage(usage_raw: Dict[str, Any]) -> Usage: details["service_tier"] = service_tier return Usage( - prompt_tokens=input_tokens or None, + prompt_tokens=prompt_tokens or None, completion_tokens=output_tokens or None, - total_tokens=(input_tokens + cache_read + cache_creation) or None, + total_tokens=prompt_tokens or None, cache_read_input_tokens=usage_raw.get("cache_read_input_tokens"), cache_creation_input_tokens=usage_raw.get("cache_creation_input_tokens"), completion_tokens_details=details or None, @@ -586,6 +609,140 @@ def _anthropic_user_blocks(content: List[Dict[str, Any]]) -> List[Dict[str, Any] return blocks +def _apply_anthropic_cache_control(payload: Dict[str, Any]) -> None: + """Attach ephemeral ``cache_control`` breakpoints to a copy of the stream. + + Anthropic prompt caching is a byte-exact prefix match: a breakpoint on the + last content block of a message caches every token up to and including it. + Following the conversation manager's placement (``manager.py + _add_cache_control``), we mark the three stable boundaries of a multi-turn + exchange: + + - the last system block at the start of the stream (which also covers the + tool definitions rendered before it), and + - the last content block of the two most recent non-tool user/assistant + turns. + + The message stream is copied and only the key messages are replaced, so + caller-owned lists are never mutated. Anthropic allows at most + ``MAX_CACHE_BREAKPOINTS`` breakpoints per request, so the marking stops + early once that budget (including any caller-supplied markers) is + exhausted. + """ + import copy + + budget = MAX_CACHE_BREAKPOINTS - _count_cache_breakpoints(payload) + + if budget <= 0: + return + + system = payload.get("system") + + if isinstance(system, str): + payload["system"] = [ + {"type": "text", "text": system, "cache_control": {"type": "ephemeral"}} + ] + budget -= 1 + + elif isinstance(system, list) and system: + system = list(system) + last = system[-1] + + if isinstance(last, dict): + last = copy.deepcopy(last) + system[-1] = last + + if _mark_cache_breakpoint(last): + budget -= 1 + + payload["system"] = system + + messages = payload.get("messages") or [] + result = list(messages) + marked = 0 + + for i in range(len(result) - 1, -1, -1): + if marked >= 2 or budget <= 0: + break + + msg = result[i] + + if _is_tool_turn(msg): + continue + + content = msg.get("content") + + if isinstance(content, str): + msg = copy.deepcopy(msg) + msg["content"] = [ + {"type": "text", "text": content, "cache_control": {"type": "ephemeral"}} + ] + result[i] = msg + marked += 1 + budget -= 1 + + elif isinstance(content, list) and content: + msg = copy.deepcopy(msg) + blocks = list(msg["content"]) + + if _mark_cache_breakpoint(blocks[-1]): + marked += 1 + budget -= 1 + + msg["content"] = blocks + result[i] = msg + + payload["messages"] = result + + +def _count_cache_breakpoints(payload: Dict[str, Any]) -> int: + """Count existing ``cache_control`` markers in a payload (system + messages).""" + count = 0 + system = payload.get("system") + + if isinstance(system, list): + count += sum(isinstance(block, dict) and "cache_control" in block for block in system) + + for tool in payload.get("tools") or []: + if isinstance(tool, dict) and "cache_control" in tool: + count += 1 + + for msg in payload.get("messages") or []: + content = msg.get("content") + + if isinstance(content, list): + count += sum(isinstance(block, dict) and "cache_control" in block for block in content) + + return count + + +def _mark_cache_breakpoint(block: Any) -> bool: + """Add an ephemeral breakpoint to ``block`` unless it already has one.""" + if not isinstance(block, dict) or "cache_control" in block: + return False + + block["cache_control"] = {"type": "ephemeral"} + + return True + + +def _is_tool_turn(msg: Dict[str, Any]) -> bool: + """True when a wire message is a tool turn (transient content). + + Matches the conversation manager's placement, which skips tool messages + and assistant tool-call turns when choosing cache breakpoints. + """ + content = msg.get("content") + + if not isinstance(content, list) or not content: + return False + + return any( + isinstance(block, dict) and block.get("type") in ("tool_result", "tool_use") + for block in content + ) + + __all__ = [ "anthropic_payload", "anthropic_message", diff --git a/cecli/helpers/llms/litellm_compat.py b/cecli/helpers/llms/litellm_compat.py index fba671364ab..e9744d6c82c 100644 --- a/cecli/helpers/llms/litellm_compat.py +++ b/cecli/helpers/llms/litellm_compat.py @@ -936,7 +936,12 @@ def stream_chunk_builder( ) def completion_cost(self, completion_response: Optional[Any] = None, **kwargs: Any) -> float: - """Estimate cost from usage tokens and cecli's own model metadata.""" + """Estimate cost from usage tokens and cecli's own model metadata. + + Mirrors ``base_coder.compute_costs_from_tokens`` so normalized usage + (``prompt_tokens`` = full input including cache read/write) is billed + with the cache discounts instead of the plain input price. + """ usage = getattr(completion_response, "usage", None) if not usage: return 0.0 @@ -945,9 +950,38 @@ def completion_cost(self, completion_response: Optional[Any] = None, **kwargs: A info = self.get_model_info(model) if model else {} input_cost = info.get("input_cost_per_token") or 0.0 output_cost = info.get("output_cost_per_token") or 0.0 - return (usage.prompt_tokens or 0) * input_cost + ( - usage.completion_tokens or 0 - ) * output_cost + cache_hit_cost = ( + info.get("input_cost_per_token_cache_hit") + or info.get("cache_read_input_token_cost") + or 0.0 + ) + prompt = usage.prompt_tokens or 0 + completion = usage.completion_tokens or 0 + cache_hit = ( + getattr(usage, "cache_read_input_tokens", None) + or getattr(usage, "prompt_cache_hit_tokens", None) + or 0 + ) + cache_write = getattr(usage, "cache_creation_input_tokens", None) or 0 + + if cache_hit_cost: + return ( + cache_hit * cache_hit_cost + + (prompt - cache_hit) * input_cost + + completion * output_cost + ) + + if cache_hit or cache_write: + # Hard-coded Anthropic adjustments, no-ops for other providers + # since their cache fields are zero. + return ( + cache_write * input_cost * 1.25 + + cache_hit * input_cost * 0.10 + + (prompt - cache_hit) * input_cost + + completion * output_cost + ) + + return prompt * input_cost + completion * output_cost # -- model metadata --------------------------------------------------- diff --git a/cecli/helpers/model_config/agent.py b/cecli/helpers/model_config/agent.py index f25a41da3ee..633ce712080 100644 --- a/cecli/helpers/model_config/agent.py +++ b/cecli/helpers/model_config/agent.py @@ -13,6 +13,30 @@ from .utils import supports_reasoning +def _uses_anthropic_messages_api( + provider: Optional[str], route: str, record: Optional[Dict] +) -> bool: + """True when the model speaks the Anthropic /v1/messages wire format. + + Only the native Anthropic provider (explicit prefix, or a bare claude + name that resolves to the anthropic record) and GitHub Copilot's + anthropic-native proxy (``github_copilot/claude-*``) route through the + messages family. Other claude routes (openrouter, deepseek, bedrock, + ...) use chat completions / converse and keep their own caching + semantics. + """ + if provider == "anthropic": + return True + + if provider == "github_copilot": + return "claude" in (route or "").lower() + + if provider is None: + return (record or {}).get("litellm_provider") == "anthropic" + + return False + + def derive_agent_config(provider: Optional[str], route: str, record: Optional[Dict]) -> Dict: """Return the ``agent`` config block for a model. @@ -25,13 +49,22 @@ def derive_agent_config(provider: Optional[str], route: str, record: Optional[Di A dict of ModelSettings overrides (caching, temperature handling). """ reasoning = supports_reasoning(record) - record = record or {} + uses_messages_api = _uses_anthropic_messages_api(provider, route, record) agent: Dict = { "cache_control": is_anthropic(provider, route, record), # ``cache_read_input_token_cost`` in the metadata is the determinant for # whether a model supports prompt caching. Unknown models default to # assuming caching support. - "caches_by_default": bool(record.get("cache_read_input_token_cost")) if record else True, + # + # Anthropic messages-API models never cache "by default": prompt + # caching only happens when the request carries explicit + # ``cache_control`` breakpoints (injected by the llms messages + # domain), so keep ``caches_by_default`` off for them. + "caches_by_default": ( + not uses_messages_api + and (bool(record.get("cache_read_input_token_cost")) if record else True) + ), + "uses_messages_api": uses_messages_api, } if reasoning or record.get("supports_adaptive_thinking"): diff --git a/cecli/helpers/model_config/pipeline.py b/cecli/helpers/model_config/pipeline.py index 6b107a0a0e4..2ff83805c34 100644 --- a/cecli/helpers/model_config/pipeline.py +++ b/cecli/helpers/model_config/pipeline.py @@ -29,7 +29,10 @@ #: Suffix segments dropped when looking for a nearby model family. #: ``gpt-5.6-luna`` -> ``gpt-5.6`` -> ``gpt-5`` -> ``gpt`` -_TRAILING_SEGMENT_RE = re.compile(r"[-.][^.]+$") +#: ``claude-sonnet-4-5`` -> ``claude-sonnet-4`` -> ``claude-sonnet`` -> ``claude`` +#: ``[^.-]`` (no dots, no hyphens) ensures exactly one trailing ``-X`` / ``.X`` +#: segment is dropped per pass instead of collapsing the whole remainder. +_TRAILING_SEGMENT_RE = re.compile(r"[-.][^.-]+$") #: Lazily loaded raw text of the bundled metadata file (never json.loads-ed). _BUNDLED_RAW_CACHE: Optional[str] = None diff --git a/cecli/io.py b/cecli/io.py index 06b54902c2c..caf97bacfa6 100644 --- a/cecli/io.py +++ b/cecli/io.py @@ -1741,39 +1741,42 @@ def get_default_notification_command(self, bell=True): # 2. Define the Notification component notif_cmd = None - if system == "Darwin": - if shutil.which("terminal-notifier"): - notif_cmd = f"terminal-notifier -title 'cecli' -message '{NOTIFICATION_MESSAGE}'" - else: - notif_cmd = f'osascript -e \'display notification "{NOTIFICATION_MESSAGE}" with title "cecli"\'' - - elif system == "Linux": - for cmd in ["notify-send", "zenity"]: - if shutil.which(cmd): - if cmd == "notify-send": - notif_cmd = f"notify-send 'cecli' '{NOTIFICATION_MESSAGE}'" - elif cmd == "zenity": - notif_cmd = f"zenity --notification --text='{NOTIFICATION_MESSAGE}'" - break + if self.notifications: + if system == "Darwin": + if shutil.which("terminal-notifier"): + notif_cmd = ( + f"terminal-notifier -title 'cecli' -message '{NOTIFICATION_MESSAGE}'" + ) + else: + notif_cmd = f'osascript -e \'display notification "{NOTIFICATION_MESSAGE}" with title "cecli"\'' + + elif system == "Linux": + for cmd in ["notify-send", "zenity"]: + if shutil.which(cmd): + if cmd == "notify-send": + notif_cmd = f"notify-send 'cecli' '{NOTIFICATION_MESSAGE}'" + elif cmd == "zenity": + notif_cmd = f"zenity --notification --text='{NOTIFICATION_MESSAGE}'" + break - elif system == "Windows": - ps_body = ( - ' "try {{ Add-Type -AssemblyName System.Runtime.WindowsRuntime; $null =' - " [Windows.UI.Notifications.ToastNotificationManager, Windows.UI.Notifications," - " ContentType = WindowsRuntime] }} catch {{}}; " - "$template =" - " [Windows.UI.Notifications.ToastNotificationManager]::GetTemplateContent" - "([Windows.UI.Notifications.ToastTemplateType]::ToastText02); " - "$toastXml = $template.GetXml(); " - "$toastXml.GetElementsByTagName('text')[0].AppendChild" - "($template.CreateTextNode('cecli')) > $null; " - "$toastXml.GetElementsByTagName('text')[1].AppendChild" - f"($template.CreateTextNode('{NOTIFICATION_MESSAGE}')) > $null; " - "$toast = [Windows.UI.Notifications.ToastNotification]::new($toastXml); " - "[Windows.UI.Notifications.ToastNotificationManager]::CreateToastNotifier('cecli')" - '.Show($toast)"' - ) - notif_cmd = f"powershell -WindowStyle Hidden -Command {ps_body}" + elif system == "Windows": + ps_body = ( + ' "try {{ Add-Type -AssemblyName System.Runtime.WindowsRuntime; $null =' + " [Windows.UI.Notifications.ToastNotificationManager, Windows.UI.Notifications," + " ContentType = WindowsRuntime] }} catch {{}}; " + "$template =" + " [Windows.UI.Notifications.ToastNotificationManager]::GetTemplateContent" + "([Windows.UI.Notifications.ToastTemplateType]::ToastText02); " + "$toastXml = $template.GetXml(); " + "$toastXml.GetElementsByTagName('text')[0].AppendChild" + "($template.CreateTextNode('cecli')) > $null; " + "$toastXml.GetElementsByTagName('text')[1].AppendChild" + f"($template.CreateTextNode('{NOTIFICATION_MESSAGE}')) > $null; " + "$toast = [Windows.UI.Notifications.ToastNotification]::new($toastXml); " + "[Windows.UI.Notifications.ToastNotificationManager]::CreateToastNotifier('cecli')" + '.Show($toast)"' + ) + notif_cmd = f"powershell -WindowStyle Hidden -Command {ps_body}" # 3. Concatenate them based on bell preference if notif_cmd: @@ -1802,8 +1805,10 @@ def _send_notification(self): # Determine if this is a terminal bell command that should not be suppressed is_bell_cmd = ( - "\\a" in self.notifications_command or "\a" in self.notifications_command - ) and re.search(r"(?:echo|print)", self.notifications_command, re.IGNORECASE) + "\\a" in self.notifications_command + or "\a" in self.notifications_command + or "bel" in self.notifications_command + ) and re.search(r"(?:echo|print|tput)", self.notifications_command, re.IGNORECASE) kwargs = { "shell": True, diff --git a/cecli/models.py b/cecli/models.py index 510c6d8fe1f..f66744f7936 100644 --- a/cecli/models.py +++ b/cecli/models.py @@ -116,6 +116,7 @@ class ModelSettings: extra_params: Optional[dict] = None cache_control: bool = False caches_by_default: bool = False + uses_messages_api: bool = False use_system_prompt: bool = True use_temperature: Union[bool, float] = True streaming: bool = True diff --git a/cecli/reasoning_tags.py b/cecli/reasoning_tags.py index 83842a599b6..dc380fe26a9 100644 --- a/cecli/reasoning_tags.py +++ b/cecli/reasoning_tags.py @@ -44,7 +44,8 @@ def remove_reasoning_content(res, reasoning_tag): def replace_reasoning_tags(text, tag_name): """ Replace opening and closing reasoning tags with standard formatting. - Ensures exactly one blank line before START and END markers. + Content is kept flush with the START and END markers, with exactly one + blank line after the END marker. Args: text (str): The text containing the tags @@ -58,10 +59,10 @@ def replace_reasoning_tags(text, tag_name): return text # Replace opening tag with proper spacing - text = re.sub(f"\\s*<{tag_name}>\\s*", f"\n{REASONING_START}\n\n", text) + text = re.sub(f"\\s*<{tag_name}>\\s*", f"\n{REASONING_START}", text) # Replace closing tag with proper spacing - text = re.sub(f"\\s*\\s*", f"\n\n{REASONING_END}\n\n", text) + text = re.sub(f"\\s*\\s*", f"\n{REASONING_END}\n", text) return text diff --git a/cecli/resources/model-metadata.ext.json b/cecli/resources/model-metadata.ext.json new file mode 100644 index 00000000000..faa87a4e689 --- /dev/null +++ b/cecli/resources/model-metadata.ext.json @@ -0,0 +1,38884 @@ +{ + "ai21.j2-mid-v1": { + "input_cost_per_token": 0.0000125, + "litellm_provider": "bedrock", + "max_input_tokens": 8191, + "max_output_tokens": 8191, + "max_tokens": 8191, + "mode": "chat", + "output_cost_per_token": 0.0000125 + }, + "ai21.j2-ultra-v1": { + "input_cost_per_token": 0.0000188, + "litellm_provider": "bedrock", + "max_input_tokens": 8191, + "max_output_tokens": 8191, + "max_tokens": 8191, + "mode": "chat", + "output_cost_per_token": 0.0000188 + }, + "ai21.jamba-1-5-large-v1:0": { + "input_cost_per_token": 0.000002, + "litellm_provider": "bedrock", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 0.000008 + }, + "ai21.jamba-1-5-mini-v1:0": { + "input_cost_per_token": 2e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 4e-7 + }, + "ai21.jamba-instruct-v1:0": { + "input_cost_per_token": 5e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 70000, + "max_output_tokens": 4096, + "max_tokens": 4096, + "mode": "chat", + "output_cost_per_token": 7e-7, + "supports_system_messages": true + }, + "amazon-nova/nova-lite-v1": { + "input_cost_per_token": 6e-8, + "litellm_provider": "amazon_nova", + "max_input_tokens": 300000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 2.4e-7, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_vision": true + }, + "amazon-nova/nova-micro-v1": { + "input_cost_per_token": 3.5e-8, + "litellm_provider": "amazon_nova", + "max_input_tokens": 128000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 1.4e-7, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true + }, + "amazon-nova/nova-premier-v1": { + "input_cost_per_token": 0.0000025, + "litellm_provider": "amazon_nova", + "max_input_tokens": 1000000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 0.0000125, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": false, + "supports_response_schema": true, + "supports_vision": true + }, + "amazon-nova/nova-pro-v1": { + "input_cost_per_token": 8e-7, + "litellm_provider": "amazon_nova", + "max_input_tokens": 300000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 0.0000032, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_vision": true + }, + "amazon.nova-2-lite-v1:0": { + "cache_read_input_token_cost": 7.5e-8, + "input_cost_per_token": 3e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 0.0000025, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_video_input": true, + "supports_vision": true + }, + "amazon.nova-2-pro-preview-20251202-v1:0": { + "cache_read_input_token_cost": 5.46875e-7, + "input_cost_per_token": 0.0000021875, + "input_cost_per_image_token": 0.0000021875, + "input_cost_per_audio_token": 0.0000021875, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 0.0000175, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_video_input": true, + "supports_vision": true + }, + "amazon.nova-lite-v1:0": { + "input_cost_per_token": 6e-8, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 300000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 2.4e-7, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_vision": true + }, + "amazon.nova-micro-v1:0": { + "input_cost_per_token": 3.5e-8, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 128000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 1.4e-7, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true + }, + "amazon.nova-pro-v1:0": { + "input_cost_per_token": 8e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 300000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 0.0000032, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_vision": true + }, + "amazon.titan-text-express-v1": { + "input_cost_per_token": 0.0000013, + "litellm_provider": "bedrock", + "max_input_tokens": 42000, + "max_output_tokens": 8000, + "max_tokens": 8000, + "mode": "chat", + "output_cost_per_token": 0.0000017 + }, + "amazon.titan-text-lite-v1": { + "input_cost_per_token": 3e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 42000, + "max_output_tokens": 4000, + "max_tokens": 4000, + "mode": "chat", + "output_cost_per_token": 4e-7 + }, + "amazon.titan-text-premier-v1:0": { + "input_cost_per_token": 5e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 42000, + "max_output_tokens": 32000, + "max_tokens": 32000, + "mode": "chat", + "output_cost_per_token": 0.0000015 + }, + "anthropic.claude-3-5-haiku-20241022-v1:0": { + "cache_creation_input_token_cost": 0.000001, + "cache_read_input_token_cost": 8e-8, + "input_cost_per_token": 8e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 200000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.000004, + "supports_assistant_prefill": true, + "supports_function_calling": 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Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 3.9998000000000007e-7, + "output_dbu_cost_per_token": 0.000005714000000000001, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-oss-120b": { + "input_cost_per_token": 1.5000999999999998e-7, + "input_dbu_cost_per_token": 0.0000021429999999999996, + "litellm_provider": "databricks", + "max_input_tokens": 131072, + "max_output_tokens": 131072, + "max_tokens": 131072, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 5.9997e-7, + "output_dbu_cost_per_token": 0.000008571, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-gpt-oss-20b": { + "input_cost_per_token": 7e-8, + "input_dbu_cost_per_token": 0.000001, + "litellm_provider": "databricks", + "max_input_tokens": 131072, + "max_output_tokens": 131072, + "max_tokens": 131072, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 3.0001999999999996e-7, + "output_dbu_cost_per_token": 0.000004285999999999999, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-llama-2-70b-chat": { + "input_cost_per_token": 5.0001e-7, + "input_dbu_cost_per_token": 0.000007143, + "litellm_provider": "databricks", + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "max_tokens": 4096, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. 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"per_query" + }, + "gemini/gemini-3.1-flash-lite-preview": { + "cache_read_input_token_cost": 2.5e-8, + "deprecation_date": "2026-05-25", + "input_cost_per_audio_token": 5e-7, + "input_cost_per_token": 2.5e-7, + "litellm_provider": "gemini", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_reasoning_token": 0.0000015, + "output_cost_per_token": 0.0000015, + "rpm": 15, + "source": "https://ai.google.dev/gemini-api/docs/models", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/completions", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "supports_audio_output": false, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, 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"supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text", + "audio" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_function_calling": true, + "supports_vision": true, + "supports_web_search": true, + "tpm": 250000, + "rpm": 10, + "gemini_audio_only_live": true + }, + "gemini/gemini-3.1-pro-preview": { + "cache_read_input_token_cost": 2e-7, + "cache_read_input_token_cost_above_200k_tokens": 4e-7, + "input_cost_per_token": 0.000002, + "input_cost_per_token_above_200k_tokens": 0.000004, + "input_cost_per_token_batches": 0.000001, + "litellm_provider": "gemini", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_token": 0.000012, + "output_cost_per_token_above_200k_tokens": 0.000018, + "output_cost_per_token_batches": 0.000006, + "rpm": 2000, + "source": "https://ai.google.dev/gemini-api/docs/models#gemini-3.1-pro-preview", + 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"supports_video_input": true, + "supports_vision": true, + "supports_web_search": true, + "supports_native_streaming": true, + "tpm": 250000, + "search_context_cost_per_query": { + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014, + "search_context_size_high": 0.014 + }, + "web_search_billing_unit": "per_query" + }, + "gemini/gemini-3.6-flash": { + "cache_read_input_token_cost": 1.5e-7, + "cache_read_input_token_cost_flex": 7.5e-8, + "input_cost_per_token": 0.0000015, + "input_cost_per_token_batches": 7.5e-7, + "input_cost_per_token_flex": 7.5e-7, + "litellm_provider": "gemini", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_reasoning_token": 0.0000075, + "output_cost_per_token": 0.0000075, + "output_cost_per_token_batches": 0.00000375, + "output_cost_per_token_flex": 0.00000375, + "rpm": 2000, + "source": "https://ai.google.dev/pricing/gemini-3", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/completions", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_output": false, + "supports_audio_input": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_url_context": true, + "supports_video_input": true, + "supports_vision": true, + "supports_web_search": true, + "supports_native_streaming": true, + "tpm": 800000, + "input_cost_per_token_priority": 0.0000027, + "output_cost_per_token_priority": 0.0000135, + "cache_read_input_token_cost_priority": 2.7e-7, + "search_context_cost_per_query": { + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014, + "search_context_size_high": 0.014 + }, + "web_search_billing_unit": "per_query" + }, + "gemini/gemini-exp-1114": { + "input_cost_per_token": 0, + "input_cost_per_token_above_128k_tokens": 0, + "litellm_provider": "gemini", + "max_input_tokens": 1048576, + "max_output_tokens": 8192, + "max_tokens": 8192, + "metadata": { + "notes": "Rate limits not documented for gemini-exp-1114. Assuming same as gemini-1.5-pro.", + "supports_tool_choice": true + }, + "mode": "chat", + "output_cost_per_token": 0, + "output_cost_per_token_above_128k_tokens": 0, + "rpm": 1000, + "source": "https://ai.google.dev/pricing", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "tpm": 4000000 + }, + "gemini/gemini-exp-1206": { + "input_cost_per_token": 0, + "input_cost_per_token_above_128k_tokens": 0, + "litellm_provider": "gemini", + "max_input_tokens": 2097152, + "max_output_tokens": 8192, + "max_tokens": 8192, + "metadata": { + "notes": "Rate limits not documented for gemini-exp-1206. Assuming same as gemini-1.5-pro.", + "supports_tool_choice": true + }, + "mode": "chat", + "output_cost_per_token": 0, + "output_cost_per_token_above_128k_tokens": 0, + "rpm": 1000, + "source": "https://ai.google.dev/pricing", + "supports_function_calling": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "tpm": 4000000 + }, + "gemini/gemini-flash-latest": { + "cache_read_input_token_cost": 7.5e-8, + "input_cost_per_audio_token": 0.000001, + "input_cost_per_token": 3e-7, + "litellm_provider": "gemini", + "max_input_tokens": 1048576, + "max_output_tokens": 65535, + "max_tokens": 65535, + "mode": "chat", + "output_cost_per_reasoning_token": 0.0000025, + "output_cost_per_token": 0.0000025, + "rpm": 15, + "source": "https://developers.googleblog.com/en/continuing-to-bring-you-our-latest-models-with-an-improved-gemini-2-5-flash-and-flash-lite-release/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/completions", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_output": false, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_url_context": true, + "supports_vision": true, + "supports_web_search": true, + "tpm": 250000, + "search_context_cost_per_query": { + "search_context_size_low": 0.035, + "search_context_size_medium": 0.035, + "search_context_size_high": 0.035 + } + }, + "gemini/gemini-flash-lite-latest": { + "cache_read_input_token_cost": 2.5e-8, + "input_cost_per_audio_token": 3e-7, + "input_cost_per_token": 1e-7, + "litellm_provider": "gemini", + "max_input_tokens": 1048576, + "max_output_tokens": 65535, + "max_tokens": 65535, + "mode": "chat", + "output_cost_per_reasoning_token": 4e-7, + "output_cost_per_token": 4e-7, + "rpm": 15, + "source": "https://developers.googleblog.com/en/continuing-to-bring-you-our-latest-models-with-an-improved-gemini-2-5-flash-and-flash-lite-release/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/completions", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_output": false, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_url_context": true, + "supports_vision": true, + "supports_web_search": true, + "tpm": 250000, + "search_context_cost_per_query": { + "search_context_size_low": 0.035, + "search_context_size_medium": 0.035, + "search_context_size_high": 0.035 + } + }, + "gemini/gemini-gemma-2-27b-it": { + "input_cost_per_token": 3.5e-7, + "litellm_provider": "gemini", + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.00000105, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_tool_choice": true, + "supports_vision": true, + "tpm": 250000, + "rpm": 10 + }, + "gemini/gemini-gemma-2-9b-it": { + "input_cost_per_token": 3.5e-7, + "litellm_provider": "gemini", + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.00000105, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_tool_choice": true, + "supports_vision": true, + "tpm": 250000, + "rpm": 10 + }, + 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+ "zai/glm-5.1": { + "cache_creation_input_token_cost": 0, + "cache_read_input_token_cost": 2.6e-7, + "input_cost_per_token": 0.0000014, + "output_cost_per_token": 0.0000044, + "litellm_provider": "zai", + "max_input_tokens": 200000, + "max_output_tokens": 128000, + "mode": "chat", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_tool_choice": true, + "source": "https://docs.z.ai/guides/overview/pricing" + } +} diff --git a/cecli/resources/model-metadata.json b/cecli/resources/model-metadata.json index c2048a93d1a..f0f1988ff95 100644 --- a/cecli/resources/model-metadata.json +++ b/cecli/resources/model-metadata.json @@ -18,6 +18,7 @@ "output_cost_per_token": 0.0000188 }, "ai21.jamba-1-5-large-v1:0": { + "deprecation_date": "2026-11-26", "input_cost_per_token": 0.000002, "litellm_provider": "bedrock", "max_input_tokens": 256000, @@ -27,6 +28,7 @@ "output_cost_per_token": 0.000008 }, "ai21.jamba-1-5-mini-v1:0": { + "deprecation_date": "2026-11-26", "input_cost_per_token": 2e-7, "litellm_provider": "bedrock", "max_input_tokens": 256000, @@ -304,6 +306,7 @@ "supports_vision": true }, "anthropic.claude-3-haiku-20240307-v1:0": { + "deprecation_date": "2026-09-10", "input_cost_per_token": 2.5e-7, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -335,6 +338,7 @@ "cache_creation_input_token_cost": 0.00001875 }, "anthropic.claude-3-sonnet-20240229-v1:0": { + "deprecation_date": "2026-07-30", "input_cost_per_token": 0.000003, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -392,6 +396,7 @@ "cache_read_input_token_cost": 1e-7, "input_cost_per_token": 0.000001, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -417,6 +422,7 @@ "cache_read_input_token_cost": 1e-7, "input_cost_per_token": 0.000001, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -465,6 +471,7 @@ "anthropic.claude-opus-4-1-20250805-v1:0": { "cache_creation_input_token_cost": 0.00001875, "cache_read_input_token_cost": 0.0000015, + "deprecation_date": "2027-01-08", "input_cost_per_token": 0.000015, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -520,6 +527,7 @@ "cache_read_input_token_cost": 5e-7, "input_cost_per_token": 0.000005, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -552,6 +560,7 @@ "cache_read_input_token_cost": 5e-7, "input_cost_per_token": 0.000005, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -586,6 +595,7 @@ "cache_read_input_token_cost": 5e-7, "input_cost_per_token": 0.000005, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -690,6 +700,7 @@ "anthropic.claude-sonnet-4-20250514-v1:0": { "cache_creation_input_token_cost": 0.00000375, "cache_read_input_token_cost": 3e-7, + "deprecation_date": "2026-10-14", "input_cost_per_token": 0.000003, "input_cost_per_token_above_200k_tokens": 0.000006, "output_cost_per_token_above_200k_tokens": 0.0000225, @@ -729,6 +740,7 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 0.000012, "cache_read_input_token_cost_above_200k_tokens": 6e-7, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -759,6 +771,7 @@ "cache_read_input_token_cost": 3e-7, "input_cost_per_token": 0.000003, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -1035,6 +1048,7 @@ "supports_vision": true }, "apac.anthropic.claude-3-5-sonnet-20240620-v1:0": { + "deprecation_date": "2026-07-30", "input_cost_per_token": 0.000003, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -1053,6 +1067,7 @@ "apac.anthropic.claude-3-5-sonnet-20241022-v2:0": { "cache_creation_input_token_cost": 0.00000375, "cache_read_input_token_cost": 3e-7, + "deprecation_date": "2026-07-30", "input_cost_per_token": 0.000003, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -1070,6 +1085,7 @@ "supports_vision": true }, "apac.anthropic.claude-3-haiku-20240307-v1:0": { + "deprecation_date": "2026-09-10", "input_cost_per_token": 2.5e-7, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -1086,6 +1102,7 @@ "cache_creation_input_token_cost": 3.125e-7 }, "apac.anthropic.claude-3-sonnet-20240229-v1:0": { + "deprecation_date": "2026-07-30", "input_cost_per_token": 0.000003, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -1106,6 +1123,7 @@ "cache_read_input_token_cost": 1.1e-7, "input_cost_per_token": 0.0000011, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -1128,6 +1146,7 @@ "apac.anthropic.claude-sonnet-4-20250514-v1:0": { "cache_creation_input_token_cost": 0.00000375, "cache_read_input_token_cost": 3e-7, + "deprecation_date": "2026-10-14", "input_cost_per_token": 0.000003, "input_cost_per_token_above_200k_tokens": 0.000006, "output_cost_per_token_above_200k_tokens": 0.0000225, @@ -1162,6 +1181,7 @@ "cache_read_input_token_cost": 1.1e-7, "input_cost_per_token": 0.0000011, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -1187,6 +1207,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -1221,6 +1242,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -1333,6 +1355,7 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 0.0000132, "cache_read_input_token_cost_above_200k_tokens": 6.6e-7, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -1363,6 +1386,7 @@ "cache_read_input_token_cost": 3.3e-7, "input_cost_per_token": 0.0000033, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -1718,7 +1742,10 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true }, "azure/eu/gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.8e-7, @@ -1754,7 +1781,10 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true }, "azure/eu/gpt-5.5": { "cache_read_input_token_cost": 5.5e-7, @@ -1771,6 +1801,11 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -1813,6 +1848,11 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -1852,6 +1892,11 @@ "output_cost_per_token": 0.000033, "output_cost_per_token_above_272k_tokens": 0.0000495, "output_cost_per_token_priority": 0.0000825, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -1895,6 +1940,11 @@ "output_cost_per_token": 0.00000132, "output_cost_per_token_above_272k_tokens": 0.00000198, "output_cost_per_token_priority": 0.0000033, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -1938,6 +1988,11 @@ "output_cost_per_token": 0.000033, "output_cost_per_token_above_272k_tokens": 0.0000495, "output_cost_per_token_priority": 0.0000825, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -1981,6 +2036,11 @@ "output_cost_per_token": 0.0000132, "output_cost_per_token_above_272k_tokens": 0.0000198, "output_cost_per_token_priority": 0.000033, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3403,7 +3463,10 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true }, "azure/gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.5e-7, @@ -3445,7 +3508,10 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true }, "azure/gpt-5.4-mini": { "cache_read_input_token_cost": 7.5e-8, @@ -3456,6 +3522,11 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 0.0000045, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3479,8 +3550,8 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true }, "azure/gpt-5.4-mini-2026-03-17": { "cache_read_input_token_cost": 7.5e-8, @@ -3492,6 +3563,11 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 0.0000045, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3515,8 +3591,8 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true }, "azure/gpt-5.4-nano": { "cache_read_input_token_cost": 2e-8, @@ -3527,6 +3603,11 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 0.00000125, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3550,8 +3631,8 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true }, "azure/gpt-5.4-nano-2026-03-17": { "cache_read_input_token_cost": 2e-8, @@ -3563,6 +3644,11 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 0.00000125, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3586,8 +3672,8 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_none_reasoning_effort": false, - "supports_xhigh_reasoning_effort": false + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true }, "azure/gpt-5.5": { "cache_read_input_token_cost": 5e-7, @@ -3607,6 +3693,11 @@ "output_cost_per_token_above_272k_tokens": 0.000045, "output_cost_per_token_priority": 0.00006, "output_cost_per_token_above_272k_tokens_priority": 0.00009, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3652,6 +3743,11 @@ "output_cost_per_token_above_272k_tokens": 0.000045, "output_cost_per_token_priority": 0.00006, "output_cost_per_token_above_272k_tokens_priority": 0.00009, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3694,6 +3790,11 @@ "output_cost_per_token_above_272k_tokens": 0.000045, "output_cost_per_token_priority": 0.00006, "output_cost_per_token_above_272k_tokens_priority": 0.00009, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3740,6 +3841,11 @@ "output_cost_per_token_above_272k_tokens": 0.0000018, "output_cost_per_token_priority": 0.0000024, "output_cost_per_token_above_272k_tokens_priority": 0.0000036, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3786,6 +3892,11 @@ "output_cost_per_token_above_272k_tokens": 0.000045, "output_cost_per_token_priority": 0.00006, "output_cost_per_token_above_272k_tokens_priority": 0.00009, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -3832,6 +3943,11 @@ "output_cost_per_token_above_272k_tokens": 0.000018, "output_cost_per_token_priority": 0.000024, "output_cost_per_token_above_272k_tokens_priority": 0.000036, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -4136,6 +4252,11 @@ "max_tokens": 100000, "mode": "responses", "output_cost_per_token": 0.00004, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -4649,7 +4770,10 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true }, "azure/us/gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.8e-7, @@ -4685,7 +4809,10 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true }, "azure/us/gpt-5.5": { "cache_read_input_token_cost": 5.5e-7, @@ -4702,6 +4829,11 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -4744,6 +4876,11 @@ "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -4783,6 +4920,11 @@ "output_cost_per_token": 0.000033, "output_cost_per_token_above_272k_tokens": 0.0000495, "output_cost_per_token_priority": 0.0000825, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -4826,6 +4968,11 @@ "output_cost_per_token": 0.00000132, "output_cost_per_token_above_272k_tokens": 0.00000198, "output_cost_per_token_priority": 0.0000033, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -4869,6 +5016,11 @@ "output_cost_per_token": 0.000033, "output_cost_per_token_above_272k_tokens": 0.0000495, "output_cost_per_token_priority": 0.0000825, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -4912,6 +5064,11 @@ "output_cost_per_token": 0.0000132, "output_cost_per_token_above_272k_tokens": 0.0000198, "output_cost_per_token_priority": 0.000033, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -5050,6 +5207,268 @@ "supports_tool_choice": true, "supports_vision": true }, + "azure_ai/FW-DeepSeek-V3.2": { + "cache_read_input_token_cost": 3.1e-7, + "input_cost_per_token": 6.2e-7, + "litellm_provider": "azure_ai", + "max_input_tokens": 163840, + "max_output_tokens": 163840, + "max_tokens": 163840, + "mode": "chat", + "output_cost_per_token": 0.00000185, + 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"supports_web_search": true }, + "azure_ai/grok-4.3": { + "cache_read_input_token_cost": 2e-7, + "input_cost_per_token": 0.00000125, + "litellm_provider": "azure_ai", + "max_input_tokens": 200000, + "max_output_tokens": 200000, + "max_tokens": 200000, + "mode": "chat", + "output_cost_per_token": 0.0000025, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-grok-4-3-on-microsoft-foundry-latest-generation-agentic-capabilities/4517096", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure_ai/grok-code-fast-1": { "input_cost_per_token": 2e-7, "litellm_provider": "azure_ai", @@ -6609,6 +7046,7 @@ "output_cost_per_token": 0.00000222, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -6687,6 +7125,7 @@ "output_cost_per_token": 0.00000222, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -6797,6 +7236,7 @@ "output_cost_per_token": 0.00000222, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -7009,6 +7449,7 @@ "output_cost_per_token": 0.00000222, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -7294,6 +7735,7 @@ "output_cost_per_token": 0.00000222, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -7478,6 +7920,7 @@ "output_cost_per_token": 0.00000185, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -7604,6 +8047,7 @@ "supports_function_calling": true, "supports_reasoning": true, "supports_system_messages": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -7617,6 +8061,7 @@ "output_cost_per_token": 0.00000185, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true, "source": "https://aws.amazon.com/bedrock/pricing/" }, @@ -7727,6 +8172,7 @@ "output_cost_per_token": 0.0000015 }, "bedrock/us-gov-east-1/anthropic.claude-3-5-sonnet-20240620-v1:0": { + "deprecation_date": 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"supports_function_calling": true, + "supports_native_structured_output": true, "supports_pdf_input": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -9766,6 +10228,7 @@ "supports_tool_choice": true }, "cohere.command-r-plus-v1:0": { + "deprecation_date": "2026-08-19", "input_cost_per_token": 0.000003, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -9776,6 +10239,7 @@ "supports_tool_choice": true }, "cohere.command-r-v1:0": { + "deprecation_date": "2026-08-19", "input_cost_per_token": 5e-7, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -10025,6 +10489,103 @@ "supports_system_messages": true, "supports_tool_choice": true }, + "dashscope/deepseek-v4-flash": { + "cache_read_input_token_cost": 4e-8, + "input_cost_per_token": 2e-7, + "litellm_provider": "dashscope", + "max_input_tokens": 1000000, + "max_output_tokens": 393216, + "max_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 4e-7, + "source": 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"mode": "chat", + "output_cost_per_token": 0.0000048, + "source": "https://www.alibabacloud.com/help/en/model-studio/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "dashscope/glm-5.1": { + "cache_read_input_token_cost": 2.6e-7, + "input_cost_per_token": 0.0000014, + "litellm_provider": "dashscope", + "max_input_tokens": 202745, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 0.0000044, + "source": "https://www.alibabacloud.com/help/en/model-studio/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "dashscope/glm-5.2": { + "cache_read_input_token_cost": 2.8e-7, + "input_cost_per_token": 0.0000014, + "litellm_provider": "dashscope", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 0.0000044, + "source": "https://www.alibabacloud.com/help/en/model-studio/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "dashscope/kimi-k2.7-code": { + "cache_read_input_token_cost": 1.9e-7, + "input_cost_per_token": 9.5e-7, + "litellm_provider": "dashscope", + "max_input_tokens": 229376, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 0.000004, + "source": "https://www.alibabacloud.com/help/en/model-studio/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "dashscope/qwen-coder": { "input_cost_per_token": 3e-7, "litellm_provider": "dashscope", @@ -10818,6 +11379,23 @@ } ] }, + "dashscope/qwen3.8-max": { + "cache_read_input_token_cost": 2.5e-7, + "input_cost_per_token": 0.000002, + "litellm_provider": "dashscope", + "max_input_tokens": 991808, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 0.000006, + "source": "https://www.alibabacloud.com/help/en/model-studio/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, "dashscope/qwq-plus": { "input_cost_per_token": 8e-7, "litellm_provider": "dashscope", @@ -11991,6 +12569,17 @@ "supports_tool_choice": true, "supports_function_calling": true }, + "deepinfra/nvidia/NVIDIA-Nemotron-3.5-Lightning": { + "max_input_tokens": 262144, + "input_cost_per_token": 5e-8, + "output_cost_per_token": 2e-7, + "litellm_provider": "deepinfra", + "mode": "chat", + "source": "https://deepinfra.com/nvidia/NVIDIA-Nemotron-3.5-Lightning", + "supports_tool_choice": true, + "supports_function_calling": true, + "supports_reasoning": true + }, "deepinfra/nvidia/NVIDIA-Nemotron-Nano-9B-v2": { "max_tokens": 131072, "max_input_tokens": 131072, @@ -12099,8 +12688,8 @@ "input_cost_per_token_cache_hit": 2.8e-9, "litellm_provider": "deepseek", "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_tokens": 8192, + "max_output_tokens": 393216, + "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 2.8e-7, "source": "https://api-docs.deepseek.com/quick_start/pricing", @@ -12125,8 +12714,8 @@ "input_cost_per_token_cache_hit": 3.625e-9, "litellm_provider": "deepseek", "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_tokens": 8192, + "max_output_tokens": 393216, + "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 8.7e-7, "source": "https://api-docs.deepseek.com/quick_start/pricing", @@ -12286,8 +12875,8 @@ "input_cost_per_token_cache_hit": 2.8e-9, "litellm_provider": "deepseek", "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_tokens": 8192, + "max_output_tokens": 393216, + "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 2.8e-7, "source": "https://api-docs.deepseek.com/quick_start/pricing", @@ -12312,8 +12901,8 @@ "input_cost_per_token_cache_hit": 3.625e-9, "litellm_provider": "deepseek", "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_tokens": 8192, + "max_output_tokens": 393216, + "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 8.7e-7, "source": "https://api-docs.deepseek.com/quick_start/pricing", @@ -12482,6 +13071,7 @@ "cache_creation_input_token_cost": 0.00000375 }, "eu.anthropic.claude-3-haiku-20240307-v1:0": { + "deprecation_date": "2026-09-10", "input_cost_per_token": 2.5e-7, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -12513,6 +13103,7 @@ "cache_creation_input_token_cost": 0.00001875 }, "eu.anthropic.claude-3-sonnet-20240229-v1:0": { + "deprecation_date": "2026-07-30", "input_cost_per_token": 0.000003, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -12571,6 +13162,7 @@ "input_cost_per_token": 0.0000011, "deprecation_date": "2026-10-15", "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -12647,6 +13239,7 @@ "cache_read_input_token_cost": 5e-7, "input_cost_per_token": 0.000005, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -12679,6 +13272,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -12713,6 +13307,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -12817,6 +13412,7 @@ "eu.anthropic.claude-sonnet-4-20250514-v1:0": { "cache_creation_input_token_cost": 0.00000375, "cache_read_input_token_cost": 3e-7, + "deprecation_date": "2026-10-14", "input_cost_per_token": 0.000003, "input_cost_per_token_above_200k_tokens": 0.000006, "output_cost_per_token_above_200k_tokens": 0.0000225, @@ -12856,6 +13452,7 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 0.0000132, "cache_read_input_token_cost_above_200k_tokens": 6.6e-7, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -12886,6 +13483,7 @@ "cache_read_input_token_cost": 3.3e-7, "input_cost_per_token": 0.0000033, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -12958,6 +13556,7 @@ "output_cost_per_token": 0.00000222, "supports_function_calling": true, "supports_reasoning": true, + "supports_native_structured_output": true, "supports_tool_choice": true }, "eu.meta.llama3-2-1b-instruct-v1:0": { @@ -15842,6 +16441,7 @@ "supports_tool_choice": true }, "ft:gpt-3.5-turbo-0613": { + "deprecation_date": "2026-10-23", "input_cost_per_token": 0.000003, "litellm_provider": "openai", "max_input_tokens": 4096, @@ -15853,6 +16453,7 @@ "supports_tool_choice": true }, "ft:gpt-3.5-turbo-1106": { + "deprecation_date": "2026-10-23", "input_cost_per_token": 0.000003, "litellm_provider": "openai", "max_input_tokens": 16385, @@ -17270,6 +17871,61 @@ }, "web_search_billing_unit": "per_query" }, + "gemini-3.7-flash": { + "cache_read_input_token_cost": 7.5e-8, + "cache_read_input_token_cost_flex": 3.75e-8, + "input_cost_per_token": 7.5e-7, + "input_cost_per_token_batches": 3.75e-7, + "input_cost_per_token_flex": 3.75e-7, + "litellm_provider": "vertex_ai-language-models", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_reasoning_token": 0.00000375, + "output_cost_per_token": 0.00000375, + "output_cost_per_token_batches": 0.000001875, + "output_cost_per_token_flex": 0.000001875, + "source": "https://ai.google.dev/pricing/gemini-3", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/completions", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_output": false, + "supports_audio_input": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_url_context": true, + "supports_video_input": true, + "supports_vision": true, + "supports_web_search": true, + "supports_native_streaming": true, + "input_cost_per_token_priority": 0.00000135, + "output_cost_per_token_priority": 0.00000675, + "cache_read_input_token_cost_priority": 1.35e-7, + "search_context_cost_per_query": { + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014, + "search_context_size_high": 0.014 + }, + "web_search_billing_unit": "per_query" + }, "gemini-exp-1206": { "cache_read_input_token_cost": 3e-8, "input_cost_per_audio_token": 0.000001, @@ -18065,6 +18721,7 @@ }, "gemini/gemini-2.5-flash-preview-09-2025": { "cache_read_input_token_cost": 7.5e-8, + "deprecation_date": "2026-02-17", "input_cost_per_audio_token": 0.000001, "input_cost_per_token": 3e-7, "litellm_provider": "gemini", @@ -18902,6 +19559,63 @@ }, "web_search_billing_unit": "per_query" }, + "gemini/gemini-3.7-flash": { + "cache_read_input_token_cost": 7.5e-8, + "cache_read_input_token_cost_flex": 3.75e-8, + "input_cost_per_token": 7.5e-7, + "input_cost_per_token_batches": 3.75e-7, + "input_cost_per_token_flex": 3.75e-7, + "litellm_provider": "gemini", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 65536, + "mode": "chat", + "output_cost_per_reasoning_token": 0.00000375, + "output_cost_per_token": 0.00000375, + "output_cost_per_token_batches": 0.000001875, + "output_cost_per_token_flex": 0.000001875, + "rpm": 2000, + "source": "https://ai.google.dev/pricing/gemini-3", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/completions", + "/v1/batch" + ], + "supported_modalities": [ + "text", + "image", + "audio", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_output": false, + "supports_audio_input": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_url_context": true, + "supports_video_input": true, + "supports_vision": true, + "supports_web_search": true, + "supports_native_streaming": true, + "tpm": 800000, + "input_cost_per_token_priority": 0.00000135, + "output_cost_per_token_priority": 0.00000675, + "cache_read_input_token_cost_priority": 1.35e-7, + "search_context_cost_per_query": { + "search_context_size_low": 0.014, + "search_context_size_medium": 0.014, + "search_context_size_high": 0.014 + }, + "web_search_billing_unit": "per_query" + }, "gemini/gemini-exp-1114": { "input_cost_per_token": 0, "input_cost_per_token_above_128k_tokens": 0, @@ -19834,6 +20548,7 @@ "cache_read_input_token_cost": 1e-7, "input_cost_per_token": 0.000001, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -19859,6 +20574,7 @@ "cache_read_input_token_cost": 5e-7, "input_cost_per_token": 0.000005, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -19891,6 +20607,7 @@ "cache_read_input_token_cost": 5e-7, "input_cost_per_token": 0.000005, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -19925,6 +20642,7 @@ "cache_read_input_token_cost": 5e-7, "input_cost_per_token": 0.000005, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -20029,6 +20747,7 @@ "global.anthropic.claude-sonnet-4-20250514-v1:0": { "cache_creation_input_token_cost": 0.00000375, "cache_read_input_token_cost": 3e-7, + "deprecation_date": "2026-10-14", "input_cost_per_token": 0.000003, "input_cost_per_token_above_200k_tokens": 0.000006, "output_cost_per_token_above_200k_tokens": 0.0000225, @@ -20068,6 +20787,7 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 0.000012, "cache_read_input_token_cost_above_200k_tokens": 6e-7, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -20098,6 +20818,7 @@ "cache_read_input_token_cost": 3e-7, "input_cost_per_token": 0.000003, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -20414,6 +21135,7 @@ "supports_tool_choice": true }, "gpt-3.5-turbo-16k": { + "deprecation_date": "2026-10-23", "input_cost_per_token": 0.000003, "litellm_provider": "openai", "max_input_tokens": 16385, @@ -20530,6 +21252,7 @@ "supports_vision": true }, "gpt-4-turbo-preview": { + "deprecation_date": "2026-03-26", "input_cost_per_token": 0.00001, "litellm_provider": "openai", "max_input_tokens": 128000, @@ -20558,6 +21281,11 @@ "output_cost_per_token": 0.000008, "output_cost_per_token_batches": 0.000004, "output_cost_per_token_priority": 0.000014, + "search_context_cost_per_query": { + "search_context_size_high": 0.025, + "search_context_size_low": 0.025, + "search_context_size_medium": 0.025 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -20595,6 +21323,11 @@ "output_cost_per_token": 0.000008, "output_cost_per_token_priority": 0.000014, "output_cost_per_token_batches": 0.000004, + "search_context_cost_per_query": { + "search_context_size_high": 0.025, + "search_context_size_low": 0.025, + "search_context_size_medium": 0.025 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -20632,6 +21365,11 @@ "output_cost_per_token": 0.0000016, "output_cost_per_token_batches": 8e-7, "output_cost_per_token_priority": 0.0000028, + "search_context_cost_per_query": { + "search_context_size_high": 0.025, + "search_context_size_low": 0.025, + "search_context_size_medium": 0.025 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -20669,6 +21407,11 @@ "output_cost_per_token": 0.0000016, "output_cost_per_token_priority": 0.0000028, "output_cost_per_token_batches": 8e-7, + "search_context_cost_per_query": { + "search_context_size_high": 0.025, + "search_context_size_low": 0.025, + "search_context_size_medium": 0.025 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21035,6 +21778,11 @@ "mode": "chat", "output_cost_per_token": 6e-7, "output_cost_per_token_batches": 3e-7, + "search_context_cost_per_query": { + "search_context_size_high": 0.03, + "search_context_size_low": 0.025, + "search_context_size_medium": 0.0275 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -21082,6 +21830,11 @@ "mode": "chat", "output_cost_per_token": 0.00001, "output_cost_per_token_batches": 0.000005, + "search_context_cost_per_query": { + "search_context_size_high": 0.05, + "search_context_size_low": 0.03, + "search_context_size_medium": 0.035 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -21106,6 +21859,11 @@ "output_cost_per_token": 0.00001, "output_cost_per_token_flex": 0.000005, "output_cost_per_token_priority": 0.00002, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21149,6 +21907,11 @@ "output_cost_per_token": 0.00001, "output_cost_per_token_flex": 0.000005, "output_cost_per_token_priority": 0.00002, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21262,6 +22025,11 @@ "output_cost_per_token": 0.000002, "output_cost_per_token_flex": 0.000001, "output_cost_per_token_priority": 0.0000036, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21305,6 +22073,11 @@ "output_cost_per_token": 0.000002, "output_cost_per_token_flex": 0.000001, "output_cost_per_token_priority": 0.0000036, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21345,6 +22118,11 @@ "mode": "chat", "output_cost_per_token": 4e-7, "output_cost_per_token_flex": 2e-7, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21386,6 +22164,11 @@ "mode": "chat", "output_cost_per_token": 4e-7, "output_cost_per_token_flex": 2e-7, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21422,6 +22205,11 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 0.00001, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -21444,6 +22232,11 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 0.00001, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -21468,6 +22261,11 @@ "mode": "chat", "output_cost_per_token": 0.00001, "output_cost_per_token_priority": 0.00002, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -21507,6 +22305,11 @@ "mode": "chat", "output_cost_per_token": 0.00001, "output_cost_per_token_priority": 0.00002, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -21547,6 +22350,11 @@ "mode": "chat", "output_cost_per_token": 0.00001, "output_cost_per_token_priority": 0.00002, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -21586,6 +22394,11 @@ "mode": "chat", "output_cost_per_token": 0.000014, "output_cost_per_token_priority": 0.000028, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21626,6 +22439,11 @@ "mode": "chat", "output_cost_per_token": 0.000014, "output_cost_per_token_priority": 0.000028, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21667,6 +22485,11 @@ "mode": "chat", "output_cost_per_token": 0.000014, "output_cost_per_token_priority": 0.000028, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -21706,6 +22529,11 @@ "mode": "chat", "output_cost_per_token": 0.000014, "output_cost_per_token_priority": 0.000028, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -21823,7 +22651,10 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "supports_none_reasoning_effort": true, + "supports_xhigh_reasoning_effort": true, + "supports_minimal_reasoning_effort": true }, "gpt-5.4-mini": { "cache_read_input_token_cost": 7.5e-8, @@ -21844,6 +22675,11 @@ "output_cost_per_token_priority": 0.000009, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21890,6 +22726,11 @@ "output_cost_per_token_priority": 0.000009, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21933,6 +22774,11 @@ "output_cost_per_token_batches": 6.25e-7, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -21976,6 +22822,11 @@ "output_cost_per_token_batches": 6.25e-7, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -22025,6 +22876,11 @@ "output_cost_per_token_priority": 0.00006, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -22074,6 +22930,11 @@ "output_cost_per_token_priority": 0.00006, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -22131,6 +22992,11 @@ "output_cost_per_token_priority": 0.00006, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -22188,6 +23054,11 @@ "output_cost_per_token_priority": 0.0000024, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -22245,6 +23116,11 @@ "output_cost_per_token_priority": 0.00006, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -22302,6 +23178,11 @@ "output_cost_per_token_priority": 0.000024, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -22761,11 +23642,12 @@ "supports_tool_choice": true }, "groq/llama-3.1-8b-instant": { + "deprecation_date": "2026-08-16", "input_cost_per_token": 5e-8, "litellm_provider": "groq", - "max_input_tokens": 128000, - "max_output_tokens": 8192, - "max_tokens": 8192, + "max_input_tokens": 131072, + "max_output_tokens": 131072, + "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 8e-8, "supports_function_calling": true, @@ -22773,9 +23655,10 @@ "supports_tool_choice": true }, "groq/llama-3.3-70b-versatile": { + "deprecation_date": "2026-08-16", "input_cost_per_token": 5.9e-7, "litellm_provider": "groq", - "max_input_tokens": 128000, + "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", @@ -22785,6 +23668,7 @@ "supports_tool_choice": true }, "groq/meta-llama/llama-4-maverick-17b-128e-instruct": { + "deprecation_date": "2026-03-09", "input_cost_per_token": 2e-7, "litellm_provider": "groq", "max_input_tokens": 131072, @@ -22798,6 +23682,7 @@ "supports_vision": true }, "groq/meta-llama/llama-4-scout-17b-16e-instruct": { + "deprecation_date": "2026-07-17", "input_cost_per_token": 1.1e-7, "litellm_provider": "groq", "max_input_tokens": 131072, @@ -22811,6 +23696,7 @@ "supports_vision": true }, "groq/meta-llama/llama-guard-4-12b": { + "deprecation_date": "2026-03-05", "input_cost_per_token": 2e-7, "litellm_provider": "groq", "max_input_tokens": 8192, @@ -22819,7 +23705,28 @@ "mode": "chat", "output_cost_per_token": 2e-7 }, + "groq/meta-llama/llama-prompt-guard-2-22m": { + "input_cost_per_token": 3e-8, + "litellm_provider": "groq", + "max_input_tokens": 512, + "max_output_tokens": 512, + "max_tokens": 512, + "mode": "chat", + "output_cost_per_token": 3e-8, + "source": "https://console.groq.com/docs/models" + }, + "groq/meta-llama/llama-prompt-guard-2-86m": { + "input_cost_per_token": 4e-8, + "litellm_provider": "groq", + "max_input_tokens": 512, + "max_output_tokens": 512, + "max_tokens": 512, + "mode": "chat", + "output_cost_per_token": 4e-8, + "source": "https://console.groq.com/docs/model/meta-llama/llama-prompt-guard-2-86m" + }, "groq/moonshotai/kimi-k2-instruct-0905": { + "deprecation_date": "2026-04-15", "input_cost_per_token": 0.000001, "output_cost_per_token": 0.000003, "cache_read_input_token_cost": 5e-7, @@ -22837,8 +23744,8 @@ "input_cost_per_token": 1.5e-7, "litellm_provider": "groq", "max_input_tokens": 131072, - "max_output_tokens": 32766, - "max_tokens": 32766, + "max_output_tokens": 65536, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 6e-7, "search_context_cost_per_query": { @@ -22858,8 +23765,8 @@ "input_cost_per_token": 7.5e-8, "litellm_provider": "groq", "max_input_tokens": 131072, - "max_output_tokens": 32768, - "max_tokens": 32768, + "max_output_tokens": 65536, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 3e-7, "search_context_cost_per_query": { @@ -22895,6 +23802,7 @@ "supports_web_search": true }, "groq/qwen/qwen3-32b": { + "deprecation_date": "2026-07-17", "input_cost_per_token": 2.9e-7, "litellm_provider": "groq", "max_input_tokens": 131000, @@ -22907,6 +23815,21 @@ "supports_response_schema": false, "supports_tool_choice": true }, + "groq/qwen/qwen3.6-27b": { + "input_cost_per_token": 6e-7, + "litellm_provider": "groq", + "max_input_tokens": 131072, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 0.000003, + "source": "https://console.groq.com/docs/model/qwen/qwen3.6-27b", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_response_schema": false, + "supports_tool_choice": true, + "supports_vision": true + }, "heroku/claude-3-5-haiku": { "litellm_provider": "heroku", "max_tokens": 8192, @@ -23266,6 +24189,7 @@ "cache_read_input_token_cost": 1.1e-7, "input_cost_per_token": 0.0000011, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -23291,6 +24215,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -23403,6 +24328,7 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 0.0000132, "cache_read_input_token_cost_above_200k_tokens": 6.6e-7, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -23433,6 +24359,7 @@ "cache_read_input_token_cost": 3.3e-7, "input_cost_per_token": 0.0000033, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -24351,6 +25278,93 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 0.00000425, + "search_context_cost_per_query": { + "search_context_size_high": 0.0025, + "search_context_size_low": 0.0025, + "search_context_size_medium": 0.0025 + }, + "source": "https://dev.meta.ai/docs/getting-started/pricing-rate-limits", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supported_modalities": [ + "text", + "image", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_minimal_reasoning_effort": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, + "meta/muse-spark-1.2": { + "cache_read_input_token_cost": 1.5e-7, + "input_cost_per_token": 0.00000125, + "litellm_provider": "meta", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 0.00000425, + "search_context_cost_per_query": { + "search_context_size_high": 0.0025, + "search_context_size_low": 0.0025, + "search_context_size_medium": 0.0025 + }, + "source": "https://dev.meta.ai/docs/getting-started/pricing-rate-limits", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages" + ], + "supported_modalities": [ + "text", + "image", + "video" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_minimal_reasoning_effort": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true, + "supports_xhigh_reasoning_effort": true + }, + "meta/muse-spark-1.2-contributor": { + "cache_read_input_token_cost": 2e-9, + "input_cost_per_token": 1e-7, + "litellm_provider": "meta", + "max_input_tokens": 1048576, + "max_output_tokens": 131072, + "max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 2e-7, + "search_context_cost_per_query": { + "search_context_size_high": 0.0025, + "search_context_size_low": 0.0025, + "search_context_size_medium": 0.0025 + }, "source": "https://dev.meta.ai/docs/getting-started/pricing-rate-limits", "supported_endpoints": [ "/v1/chat/completions", @@ -24723,6 +25737,7 @@ "supports_native_structured_output": true }, "mistral/codestral-2405": { + "deprecation_date": "2025-06-16", "input_cost_per_token": 0.000001, "litellm_provider": "mistral", "max_input_tokens": 32000, @@ -24773,6 +25788,7 @@ "supports_tool_choice": true }, "mistral/devstral-2512": { + "deprecation_date": "2026-07-31", "input_cost_per_token": 4e-7, "litellm_provider": "mistral", "max_input_tokens": 256000, @@ -24801,6 +25817,7 @@ "supports_tool_choice": true }, "mistral/devstral-medium-2507": { + "deprecation_date": "2026-05-31", "input_cost_per_token": 4e-7, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -24829,6 +25846,7 @@ "supports_tool_choice": true }, "mistral/devstral-small-2505": { + "deprecation_date": "2025-11-30", "input_cost_per_token": 1e-7, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -24843,6 +25861,7 @@ "supports_tool_choice": true }, "mistral/devstral-small-2507": { + "deprecation_date": "2026-05-31", "input_cost_per_token": 1e-7, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -24871,6 +25890,7 @@ "supports_tool_choice": true }, "mistral/labs-devstral-small-2512": { + "deprecation_date": "2026-03-31", "input_cost_per_token": 1e-7, "litellm_provider": "mistral", "max_input_tokens": 256000, @@ -24898,6 +25918,7 @@ "supports_tool_choice": true }, "mistral/magistral-medium-1-2-2509": { + "deprecation_date": "2026-07-31", "input_cost_per_token": 0.000002, "litellm_provider": "mistral", "max_input_tokens": 40000, @@ -24913,6 +25934,7 @@ "supports_tool_choice": true }, "mistral/magistral-medium-2506": { + "deprecation_date": "2025-11-30", "input_cost_per_token": 0.000002, "litellm_provider": "mistral", "max_input_tokens": 40000, @@ -24928,6 +25950,7 @@ "supports_tool_choice": true }, "mistral/magistral-medium-2509": { + "deprecation_date": "2026-07-31", "input_cost_per_token": 0.000002, "litellm_provider": "mistral", "max_input_tokens": 40000, @@ -24958,6 +25981,7 @@ "supports_tool_choice": true }, "mistral/magistral-small-1-2-2509": { + "deprecation_date": "2026-07-31", "input_cost_per_token": 5e-7, "litellm_provider": "mistral", "max_input_tokens": 40000, @@ -24973,6 +25997,7 @@ "supports_tool_choice": true }, "mistral/magistral-small-2506": { + "deprecation_date": "2025-11-30", "input_cost_per_token": 5e-7, "litellm_provider": "mistral", "max_input_tokens": 40000, @@ -25078,6 +26103,7 @@ "supports_vision": true }, "mistral/mistral-large-2402": { + "deprecation_date": "2025-06-16", "input_cost_per_token": 0.000004, "litellm_provider": "mistral", "max_input_tokens": 32000, @@ -25091,6 +26117,7 @@ "supports_tool_choice": true }, "mistral/mistral-large-2407": { + "deprecation_date": "2025-03-30", "input_cost_per_token": 0.000003, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -25104,6 +26131,7 @@ "supports_tool_choice": true }, "mistral/mistral-large-2411": { + "deprecation_date": "2026-05-31", "input_cost_per_token": 0.000002, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -25174,6 +26202,7 @@ "supports_tool_choice": true }, "mistral/mistral-medium-2312": { + "deprecation_date": "2025-06-16", "input_cost_per_token": 0.0000027, "litellm_provider": "mistral", "max_input_tokens": 32000, @@ -25186,6 +26215,7 @@ "supports_tool_choice": true }, "mistral/mistral-medium-2505": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 4e-7, "litellm_provider": "mistral", "max_input_tokens": 131072, @@ -25199,6 +26229,7 @@ "supports_tool_choice": true }, "mistral/mistral-medium-2508": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 4e-7, "litellm_provider": "mistral", "max_input_tokens": 131072, @@ -25230,6 +26261,7 @@ "supports_vision": true }, "mistral/mistral-medium-3-1-2508": { + "deprecation_date": "2026-08-31", "input_cost_per_token": 4e-7, "litellm_provider": "mistral", "max_input_tokens": 131072, @@ -25305,6 +26337,7 @@ "supports_tool_choice": true }, "mistral/mistral-small-3-2-2506": { + "deprecation_date": "2026-07-31", "input_cost_per_token": 6e-8, "litellm_provider": "mistral", "max_input_tokens": 131072, @@ -25347,6 +26380,7 @@ "supports_tool_choice": true }, "mistral/open-codestral-mamba": { + "deprecation_date": "2025-06-06", "input_cost_per_token": 2.5e-7, "litellm_provider": "mistral", "max_input_tokens": 256000, @@ -25359,6 +26393,7 @@ "supports_tool_choice": true }, "mistral/open-mistral-7b": { + "deprecation_date": "2025-03-30", "input_cost_per_token": 2.5e-7, "litellm_provider": "mistral", "max_input_tokens": 32000, @@ -25384,6 +26419,7 @@ "supports_tool_choice": true }, "mistral/open-mistral-nemo-2407": { + "deprecation_date": "2026-07-31", "input_cost_per_token": 3e-7, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -25397,6 +26433,7 @@ "supports_tool_choice": true }, "mistral/open-mixtral-8x22b": { + "deprecation_date": "2025-03-30", "input_cost_per_token": 0.000002, "litellm_provider": "mistral", "max_input_tokens": 65336, @@ -25410,6 +26447,7 @@ "supports_tool_choice": true }, "mistral/open-mixtral-8x7b": { + "deprecation_date": "2025-03-30", "input_cost_per_token": 7e-7, "litellm_provider": "mistral", "max_input_tokens": 32000, @@ -25423,6 +26461,7 @@ "supports_tool_choice": true }, "mistral/pixtral-12b-2409": { + "deprecation_date": "2025-12-31", "input_cost_per_token": 1.5e-7, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -25437,6 +26476,7 @@ "supports_vision": true }, "mistral/pixtral-large-2411": { + "deprecation_date": "2026-05-31", "input_cost_per_token": 0.000002, "litellm_provider": "mistral", "max_input_tokens": 128000, @@ -27449,6 +28489,11 @@ "output_cost_per_token": 0.000008, "output_cost_per_token_flex": 0.000004, "output_cost_per_token_priority": 0.000014, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/responses", "/v1/chat/completions", @@ -27488,6 +28533,11 @@ "output_cost_per_token": 0.000008, "output_cost_per_token_flex": 0.000004, "output_cost_per_token_priority": 0.000014, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/responses", "/v1/chat/completions", @@ -27523,6 +28573,11 @@ "mode": "responses", "output_cost_per_token": 0.00004, "output_cost_per_token_batches": 0.00002, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -27558,6 +28613,11 @@ "mode": "responses", "output_cost_per_token": 0.00004, "output_cost_per_token_batches": 0.00002, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -27633,6 +28693,11 @@ "output_cost_per_token": 0.0000044, "output_cost_per_token_flex": 0.0000022, "output_cost_per_token_priority": 0.000008, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -27659,6 +28724,11 @@ "output_cost_per_token": 0.0000044, "output_cost_per_token_flex": 0.0000022, "output_cost_per_token_priority": 0.000008, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -27681,6 +28751,11 @@ "mode": "responses", "output_cost_per_token": 0.000008, "output_cost_per_token_batches": 0.000004, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -27716,6 +28791,11 @@ "mode": "responses", "output_cost_per_token": 0.000008, "output_cost_per_token_batches": 0.000004, + "search_context_cost_per_query": { + "search_context_size_high": 0.01, + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01 + }, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28452,6 +29532,455 @@ "litellm_provider": "openai", "mode": "chat" }, + "opencode-go/deepseek-v4-flash": { + "litellm_provider": "opencode-go", + "max_input_tokens": 1000000, + "max_output_tokens": 384000, + "max_tokens": 384000, + "mode": "chat", + "source": "https://opencode.ai", + "supported_endpoints": [ + "/v1/chat/completions" + ], + 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"litellm_provider": "opencode-go", + "source": "https://opencode.ai", + "supported_endpoints": [ + "/v1/chat/completions" + ] + }, "openrouter/anthropic/claude-3-haiku": { "input_cost_per_image": 0.0004, "input_cost_per_token": 2.5e-7, @@ -29254,6 +30783,17 @@ "supports_video_input": true, "supports_vision": true }, + "openrouter/nvidia/nemotron-3.5-lightning": { + "input_cost_per_token": 5e-8, + "litellm_provider": "openrouter", + "max_input_tokens": 262144, + "mode": "chat", + "output_cost_per_token": 2e-7, + "source": "https://openrouter.ai/nvidia/nemotron-3.5-lightning", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, "openrouter/openai/gpt-3.5-turbo": { "input_cost_per_token": 0.0000015, "litellm_provider": "openrouter", @@ -32573,6 +34113,7 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 0.0000144, "cache_read_input_token_cost_above_200k_tokens": 7.2e-7, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -32654,6 +34195,7 @@ "supports_response_schema": true }, "us.amazon.nova-premier-v1:0": { + "deprecation_date": "2026-09-14", "input_cost_per_token": 0.0000025, "litellm_provider": "bedrock_converse", "max_input_tokens": 1000000, @@ -32755,6 +34297,7 @@ "supports_vision": true }, "us.anthropic.claude-3-haiku-20240307-v1:0": { + "deprecation_date": "2026-09-10", "input_cost_per_token": 2.5e-7, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -32786,6 +34329,7 @@ "cache_creation_input_token_cost": 0.00001875 }, "us.anthropic.claude-3-sonnet-20240229-v1:0": { + "deprecation_date": "2026-07-30", "input_cost_per_token": 0.000003, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -32843,6 +34387,7 @@ "cache_read_input_token_cost": 1.1e-7, "input_cost_per_token": 0.0000011, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -32865,6 +34410,7 @@ "us.anthropic.claude-opus-4-1-20250805-v1:0": { "cache_creation_input_token_cost": 0.00001875, "cache_read_input_token_cost": 0.0000015, + "deprecation_date": "2027-01-08", "input_cost_per_token": 0.000015, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -32920,6 +34466,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -32952,6 +34499,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -32986,6 +34534,7 @@ "cache_read_input_token_cost": 5.5e-7, "input_cost_per_token": 0.0000055, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 128000, "max_tokens": 128000, @@ -33090,6 +34639,7 @@ "us.anthropic.claude-sonnet-4-20250514-v1:0": { "cache_creation_input_token_cost": 0.00000375, "cache_read_input_token_cost": 3e-7, + "deprecation_date": "2026-10-14", "input_cost_per_token": 0.000003, "input_cost_per_token_above_200k_tokens": 0.000006, "output_cost_per_token_above_200k_tokens": 0.0000225, @@ -33129,6 +34679,7 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 0.0000132, "cache_read_input_token_cost_above_200k_tokens": 6.6e-7, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 200000, "max_output_tokens": 64000, "max_tokens": 64000, @@ -33159,6 +34710,7 @@ "cache_read_input_token_cost": 3.3e-7, "input_cost_per_token": 0.0000033, "litellm_provider": "bedrock_converse", + "supports_tool_search": true, "max_input_tokens": 1000000, "max_output_tokens": 64000, 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"input_cost_per_audio_token": 0.000001, + "litellm_provider": "vertex_ai", "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "max_tokens": 65536, + "max_output_tokens": 65535, + "max_tokens": 65535, "mode": "chat", - "output_cost_per_reasoning_token": 0.0000015, - "output_cost_per_token": 0.0000015, - "output_cost_per_token_batches": 7.5e-7, - "output_cost_per_token_flex": 7.5e-7, - "output_cost_per_token_priority": 0.0000027, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "output_cost_per_reasoning_token": 0.000009, + "output_cost_per_token": 0.000009, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -35833,7 +37596,6 @@ "text" ], "supports_audio_input": true, - "supports_audio_output": false, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -35847,6 +37609,10 @@ "supports_vision": true, "supports_web_search": true, "supports_native_streaming": true, + "input_cost_per_token_priority": 0.0000027, + "input_cost_per_audio_token_priority": 0.0000018, + "output_cost_per_token_priority": 0.0000162, + "cache_read_input_token_cost_priority": 2.7e-7, "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -35854,17 +37620,24 @@ }, "web_search_billing_unit": "per_query" }, - "vertex_ai/gemini-3.1-flash-lite-preview": { - "cache_read_input_token_cost": 2.5e-8, - "input_cost_per_audio_token": 5e-7, - "input_cost_per_token": 2.5e-7, + "vertex_ai/gemini-3.5-flash-lite": { + "cache_read_input_token_cost": 3e-8, + "cache_read_input_token_cost_flex": 2e-8, + "cache_read_input_token_cost_priority": 5e-8, + "input_cost_per_token": 3e-7, + "input_cost_per_token_batches": 1.5e-7, + "input_cost_per_token_flex": 1.5e-7, + "input_cost_per_token_priority": 5.4e-7, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65536, "max_tokens": 65536, "mode": "chat", - "output_cost_per_reasoning_token": 0.0000015, - "output_cost_per_token": 0.0000015, + "output_cost_per_reasoning_token": 0.0000025, + "output_cost_per_token": 0.0000025, + "output_cost_per_token_batches": 0.00000125, + "output_cost_per_token_flex": 0.00000125, + "output_cost_per_token_priority": 0.0000045, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", "supported_endpoints": [ "/v1/chat/completions", @@ -35902,131 +37675,21 @@ }, "web_search_billing_unit": "per_query" }, - "vertex_ai/gemini-3.1-pro-preview": { - "cache_read_input_token_cost": 2e-7, - "cache_read_input_token_cost_above_200k_tokens": 4e-7, - "cache_creation_input_token_cost_above_200k_tokens": 2.5e-7, - "input_cost_per_token": 0.000002, - "input_cost_per_token_above_200k_tokens": 0.000004, - "input_cost_per_token_batches": 0.000001, - "litellm_provider": "vertex_ai", - "max_input_tokens": 1048576, - 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"cache_read_input_token_cost_priority": 5e-8, - "input_cost_per_token": 3e-7, - "input_cost_per_token_batches": 1.5e-7, - "input_cost_per_token_flex": 1.5e-7, - "input_cost_per_token_priority": 5.4e-7, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "max_tokens": 65536, - "mode": "chat", - "output_cost_per_reasoning_token": 0.0000025, - "output_cost_per_token": 0.0000025, - "output_cost_per_token_batches": 0.00000125, - "output_cost_per_token_flex": 0.00000125, - "output_cost_per_token_priority": 0.0000045, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", - "supported_endpoints": [ - "/v1/chat/completions", - "/v1/completions", - "/v1/batch" - ], - "supported_modalities": [ - "text", - "image", - "audio", - "video" - ], - "supported_output_modalities": [ - "text" - ], - "supports_audio_input": true, - "supports_audio_output": false, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_url_context": true, - "supports_video_input": true, - "supports_vision": true, - "supports_web_search": true, - "supports_native_streaming": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "web_search_billing_unit": "per_query" - }, - "vertex_ai/gemini-3.6-flash": { - "cache_read_input_token_cost": 1.5e-7, - "cache_read_input_token_cost_flex": 7.5e-8, - "input_cost_per_token": 0.0000015, - "input_cost_per_token_batches": 7.5e-7, - "input_cost_per_token_flex": 7.5e-7, + "vertex_ai/gemini-3.7-flash": { + "cache_read_input_token_cost": 7.5e-8, + "cache_read_input_token_cost_flex": 3.75e-8, + "input_cost_per_token": 7.5e-7, + "input_cost_per_token_batches": 3.75e-7, + "input_cost_per_token_flex": 3.75e-7, "litellm_provider": "vertex_ai", "max_input_tokens": 1048576, "max_output_tokens": 65536, "max_tokens": 65536, "mode": "chat", - "output_cost_per_reasoning_token": 0.0000075, - "output_cost_per_token": 0.0000075, - "output_cost_per_token_batches": 0.00000375, - "output_cost_per_token_flex": 0.00000375, + "output_cost_per_reasoning_token": 0.00000375, + "output_cost_per_token": 0.00000375, + "output_cost_per_token_batches": 0.000001875, + "output_cost_per_token_flex": 0.000001875, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -36166,9 +37773,9 @@ "supports_vision": true, "supports_web_search": true, "supports_native_streaming": true, - "input_cost_per_token_priority": 0.0000027, - "output_cost_per_token_priority": 0.0000135, - "cache_read_input_token_cost_priority": 2.7e-7, + "input_cost_per_token_priority": 0.00000135, + "output_cost_per_token_priority": 0.00000675, + "cache_read_input_token_cost_priority": 1.35e-7, "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -38114,6 +39721,27 @@ "supports_vision": true, "supports_web_search": true }, + "xai/grok-4.6": { + "cache_read_input_token_cost": 5e-7, + "cache_read_input_token_cost_above_200k_tokens": 0.000001, + "input_cost_per_token": 0.000002, + "input_cost_per_token_above_200k_tokens": 0.000004, + "litellm_provider": "xai", + "max_input_tokens": 500000, + "max_output_tokens": 500000, + "max_tokens": 500000, + "mode": "chat", + "output_cost_per_token": 0.000006, + "output_cost_per_token_above_200k_tokens": 0.000012, + "source": "https://docs.x.ai/developers/models", + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "xai/grok-beta": { "input_cost_per_token": 0.000005, "litellm_provider": "xai", diff --git a/cecli/resources/model-settings.yml b/cecli/resources/model-settings.yml index 3be10dab32f..43eeb8094cd 100644 --- a/cecli/resources/model-settings.yml +++ b/cecli/resources/model-settings.yml @@ -659,6 +659,240 @@ max_tokens: 65536 caches_by_default: true +- name: opencode-go/deepseek-v4-flash + edit_format: diff + use_repo_map: true + use_temperature: false + streaming: true + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/deepseek-v4-pro + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/glm-5 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/glm-5.1 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/glm-5.2 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/glm-5.3 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/gpt-5.6-luna + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/grok-4.5 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/hy3 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/hy3-preview + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/kimi-k2.5 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/kimi-k2.6 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/kimi-k2.7-code + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/kimi-k3 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/mimo-v2-omni + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/mimo-v2-pro + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/mimo-v2.5 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/mimo-v2.5-pro + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/minimax-m2.5 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/minimax-m2.7 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + extra_params: + temperature: 0.0 + +- name: opencode-go/minimax-m3 + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/qwen3.5-plus + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/qwen3.6-plus + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/qwen3.7-max + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/qwen3.7-plus + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + +- name: opencode-go/qwen3.8-max + edit_format: diff + use_repo_map: true + use_temperature: false + editor_edit_format: editor-diff + accepts_settings: ["reasoning_effort"] + extra_params: + temperature: 0.0 + - name: openrouter/openai/gpt-4o edit_format: diff weak_model_name: openrouter/openai/gpt-4o-mini @@ -3125,4 +3359,4 @@ weak_model_name: openrouter/openai/gpt-5.1-codex-mini use_repo_map: true use_temperature: false - accepts_settings: ["reasoning_effort"] \ No newline at end of file + accepts_settings: ["reasoning_effort"] diff --git a/cecli/resources/providers.json b/cecli/resources/providers.json index 9edc89bb551..20f87122be4 100644 --- a/cecli/resources/providers.json +++ b/cecli/resources/providers.json @@ -321,6 +321,20 @@ ], "display_name": "ollama" }, + "opencode-go": { + "api_base": "https://opencode.ai/zen/go/v1", + "api_key_env": [ + "OPENCODE_GO_API_KEY" + ], + "display_name": "opencode-go" + }, + "opencode-zen": { + "api_base": "https://opencode.ai/zen/v1", + "api_key_env": [ + "OPENCODE_ZEN_API_KEY" + ], + "display_name": "opencode-zen" + }, "ovhcloud": { "api_base": "https://oai.endpoints.kepler.ai.cloud.ovh.net/v1", "api_key_env": [ diff --git a/cecli/tui/app.py b/cecli/tui/app.py index 1d47b2fdd9e..1b7cb8f9541 100644 --- a/cecli/tui/app.py +++ b/cecli/tui/app.py @@ -874,6 +874,13 @@ def on_input_area_submit(self, message: InputArea.Submit): self._switch_to_container(target_uuid) return + # Intercept /spawn-agent command to handle immediately without LLM + # processing so a new agent can be spawned even while the primary + # coder is generating. + if stripped == "/spawn-agent" or stripped.startswith("/spawn-agent "): + self._handle_spawn_agent_command(user_input, stripped) + return + # Intercept queue management commands (/queue, /list-queue, /remove-queue) # to dispatch immediately without a full generation cycle - they only # modify the active coder's prompt_queue. @@ -1041,6 +1048,38 @@ def _handle_queue_command(self, stripped: str) -> None: f"Removed queued prompt {index}: {removed['text'][:80]}" ) + def _handle_spawn_agent_command(self, user_input: str, stripped: str) -> None: + """Dispatch /spawn-agent immediately without a full generation cycle. + + The spawn is scheduled on the worker's event loop so a new agent can + be started even while the primary coder is generating. + """ + from cecli.commands.spawn_agent import SpawnAgentCommand + + parts = stripped.split(maxsplit=1) + spawn_args = parts[1].strip() if len(parts) > 1 else "" + + input_area = self.query_one("#input", InputArea) + input_area.value = "" + + if not spawn_args: + self.show_error("Usage: /spawn-agent []") + return + + # Save to history and echo the command before dispatching + input_area.save_to_history(user_input) + self.add_user_message(user_input) + + coder = self.worker.coder + if self.worker.loop is None: + self.show_error("Worker loop not available. Cannot spawn sub-agent.") + return + + async def _run_spawn(): + await SpawnAgentCommand.execute(coder.io, coder, spawn_args) + + self.worker.loop.call_soon_threadsafe(lambda: self.worker.loop.create_task(_run_spawn())) + def set_input_value(self, text) -> None: """Find the input widget and set focus to it.""" input_area = self.query_one("#input", InputArea) diff --git a/cecli/tui/widgets/output.py b/cecli/tui/widgets/output.py index c18bd3a126a..8958591c478 100644 --- a/cecli/tui/widgets/output.py +++ b/cecli/tui/widgets/output.py @@ -37,9 +37,6 @@ class OutputContainer(SelectableRichLog): } """ - _last_write_type = None - _write_history = [] - def __init__(self, **kwargs): super().__init__(**kwargs) # Line buffer for streaming text to avoid word-per-line issue @@ -47,6 +44,10 @@ def __init__(self, **kwargs): # Track if we're on the first line of the current response self._first_line_of_response = True + # Per-instance duplicate-check state (do not share across containers) + self._write_history = [] + self._last_write_type = None + # Enable markup for rich formatting self.highlight = True self.markup = True @@ -58,7 +59,7 @@ async def start_response(self): # Insert blank line between consecutive assistant responses if self._last_write_type == "assistant": - self.output("", check_duplicates=False) + self.output("") # Clear the line buffer for new response self._line_buffer = "" @@ -104,20 +105,28 @@ async def stream_chunk(self, text: str): # Process complete lines from buffer while "\n" in self._line_buffer: line, self._line_buffer = self._line_buffer.split("\n", 1) - if line.rstrip(): - # Format with prefix on first line, proper indentation on subsequent lines - if self._first_line_of_response: - wrapped_line = self._wrap_text_with_prefix(line.rstrip(), prefix="• ") - self._first_line_of_response = False - else: - # For subsequent lines, we need to wrap with proper indentation - # but without the bullet prefix - wrapped_line = self._wrap_text_with_prefix(line.rstrip(), prefix=" ") + # Preserve blank lines as single paragraph breaks (collapsed to one + # blank line by output()'s duplicate check) so streamed markdown + # paragraphs stay visually separated instead of being merged. + if not line.rstrip(): + if not self._first_line_of_response: + self.output("") + + continue + + # Format with prefix on first line, proper indentation on subsequent lines + if self._first_line_of_response: + wrapped_line = self._wrap_text_with_prefix(line.rstrip(), prefix="• ") + self._first_line_of_response = False + else: + # For subsequent lines, we need to wrap with proper indentation + # but without the bullet prefix + wrapped_line = self._wrap_text_with_prefix(line.rstrip(), prefix=" ") - # Output each wrapped line - for wrapped in wrapped_line.split("\n"): - if wrapped.strip(): - self.output(escape(wrapped), render_markdown=True) + # Output each wrapped line + for wrapped in wrapped_line.split("\n"): + if wrapped.strip(): + self.output(escape(wrapped), render_markdown=True) async def end_response(self): """End the current LLM response.""" @@ -150,22 +159,30 @@ def add_user_message(self, text: str): is_first_line = True for line in lines: - if line.rstrip(): - # Wrap each line with proper prefix - if is_first_line: - wrapped_line = self._wrap_text_with_prefix(line, prefix="> ") - is_first_line = False - else: - wrapped_line = self._wrap_text_with_prefix(line, prefix=" ") + # Preserve blank lines as single paragraph breaks (collapsed to one + # blank line by output()'s duplicate check) so multi-paragraph user + # messages stay visually separated. + if not line.rstrip(): + if not is_first_line: + self.output("") + + continue + + # Wrap each line with proper prefix + if is_first_line: + wrapped_line = self._wrap_text_with_prefix(line, prefix="> ") + is_first_line = False + else: + wrapped_line = self._wrap_text_with_prefix(line, prefix=" ") - # Output each wrapped line with green styling - for wrapped in wrapped_line.split("\n"): - if wrapped.strip(): - self.output( - "[bold medium_spring_green]" - f"{escape(wrapped)}" - "[/bold medium_spring_green]" - ) + # Output each wrapped line with green styling + for wrapped in wrapped_line.split("\n"): + if wrapped.strip(): + self.output( + "[bold medium_spring_green]" + f"{escape(wrapped)}" + "[/bold medium_spring_green]" + ) self.scroll_end(animate=False) @@ -271,6 +288,34 @@ def _check_cost(self, text: str): except (ValueError, AttributeError): pass + @staticmethod + def _plain_text(text) -> str: + """Extract the plain text of a renderable for duplicate checking. + + Args: + text: The text or Rich renderable to extract plain text from + + Returns: + The plain text content used for blank-line duplicate detection + """ + if isinstance(text, str): + return text + + if isinstance(text, Text): + return text.plain + + if isinstance(text, Markdown): + # Markdown objects expose their source through the markup attribute + return text.markup if hasattr(text, "markup") else str(text) + + if isinstance(text, Padding): + # Recurse into Padding so we track the actual content rather than + # the renderable's string representation (which is not plain text) + return OutputContainer._plain_text(text.renderable) + + # Fall back to the string representation for other renderables + return str(text) + def start_task(self, task_id: str, title: str, task_type: str = "general"): """Start a new task section.""" self.set_last_write_type(f"{task_id}-{title}-{task_type}") @@ -278,6 +323,10 @@ def start_task(self, task_id: str, title: str, task_type: str = "general"): def clear_output(self): """Clear all output.""" self._line_buffer = "" + # Reset tracking state so a fresh screen starts with no write-type + # context or duplicate-check history. + self._write_history = [] + self._last_write_type = None self.clear() def set_last_write_type(self, type): @@ -295,18 +344,7 @@ def output(self, text, check_duplicates=True, render_markdown=False): render_markdown: If True and app config allows, render as markdown """ # Get plain text for duplicate checking BEFORE any markdown conversion - plain_text = "" - if isinstance(text, str): - plain_text = text - elif isinstance(text, Text): - plain_text = text.plain - elif isinstance(text, Markdown): - # For Markdown objects, we need to get the source markdown text - # Markdown objects have a .markup attribute with the source - plain_text = text.markup if hasattr(text, "markup") else str(text) - else: - # For other types, convert to string - plain_text = str(text) + plain_text = self._plain_text(text) # Check if we should render as markdown if render_markdown and hasattr(self.app, "render_markdown") and self.app.render_markdown: @@ -314,15 +352,17 @@ def output(self, text, check_duplicates=True, render_markdown=False): if isinstance(text, str): text = Markdown(text) - # Check for duplicate newlines using the plain text we extracted - if check_duplicates and len(self._write_history) >= 2: + # Check for duplicate newlines using the plain text we extracted. + # Allow a single blank line between blocks of content (paragraph + # breaks, section separators) but never more than one in a row, so + # multiple paragraph breaks or a trailing blank plus a section + # separator collapse into a single blank line. + if check_duplicates and len(self._write_history) >= 1: nl_check = plain_text in ["", "\n", "\\n"] - nl_last = self._write_history[-1] in ["", "\n", "\\n"] - nl_penultimate = self._write_history[-2] in ["", "\n", "\\n"] or self._write_history[ - -2 - ].endswith("\n") + last_was_blank = self._write_history[-1] in ["", "\n", "\\n"] + last_ended_with_newline = self._write_history[-1].endswith("\n") - if nl_check and nl_last and nl_penultimate: + if nl_check and (last_was_blank or last_ended_with_newline): return # Call the actual write method diff --git a/cecli/website/docmd.config.json b/cecli/website/docmd.config.json index 09052ed7c74..46ef2a55e38 100644 --- a/cecli/website/docmd.config.json +++ b/cecli/website/docmd.config.json @@ -175,6 +175,10 @@ "title": "Ollama", "path": "/llms/ollama/" }, + { + "title": "OpenCode Go", + "path": "/llms/opencode-go/" + }, { "title": "OpenAI compatible APIs", "path": "/llms/openai-compat/" diff --git a/cecli/website/docs/llms/opencode-go.md b/cecli/website/docs/llms/opencode-go.md new file mode 100644 index 00000000000..0d275065856 --- /dev/null +++ b/cecli/website/docs/llms/opencode-go.md @@ -0,0 +1,35 @@ +--- +parent: Connecting to LLMs +nav_order: 700 +--- + +# OpenCode Go + +Cecli can connect to [OpenCode Go](https://opencode.ai/go), a subscription that provides access to many coding models. You'll need an OpenCode Go API key. + +First, install cecli: + +```bash +uv tool install cecli-dev +``` + +Then configure your API key: + +``` +export OPENCODE_GO_API_KEY= # Mac/Linux +setx OPENCODE_GO_API_KEY # Windows, restart shell after setx +``` + +Start working with cecli and OpenCode Go on your codebase: + +```bash +# Change directory into your codebase +cd /to/your/project + +# Use the DeepSeek V4 Flash model +cecli --model opencode-go/deepseek-v4-flash + +# List models available from OpenCode Go +cecli --list-models opencode-go/ +``` + diff --git a/scripts/filter-chat-mode.js b/scripts/filter-chat-mode.js index a929b6f0c12..06fbef3b7ae 100644 --- a/scripts/filter-chat-mode.js +++ b/scripts/filter-chat-mode.js @@ -12,6 +12,9 @@ * - An object where values are objects with a "mode" field * * It will filter to keep only entries where "mode" === "chat" + * + * After filtering, any models from cecli/resources/model-metadata.ext.json that + * are not already present in the source data are merged into the output. */ const fs = require('fs'); @@ -110,7 +113,10 @@ function main() { ? sortObjectKeysTopLevel(filteredData) : filteredData; - const outputJson = JSON.stringify(sortedData, null, 2); + // Merge in extension models not already present in the source data + const mergedData = mergeExtModels(sortedData, inputData); + + const outputJson = JSON.stringify(mergedData, null, 2); if (outputPath) { fs.writeFileSync(outputPath, outputJson, 'utf8'); @@ -132,4 +138,39 @@ if (require.main === module) { main(); } +/** + * Merge extension models into the filtered output. + * Adds every model from cecli/resources/model-metadata.ext.json whose key is not + * already present in the source data (the original input). + * @param {object} data - Filtered result object to merge into + * @param {object} sourceData - Original input data used as the reference for existing models + * @returns {object} - Merged result + */ +function mergeExtModels(data, sourceData) { + const extPath = path.resolve(__dirname, '..', 'cecli', 'resources', 'model-metadata.ext.json'); + let extData; + + try { + extData = JSON.parse(fs.readFileSync(extPath, 'utf8')); + } catch (error) { + throw new Error(`Failed to read extension models from ${extPath}: ${error.message}`); + } + + if (typeof data !== 'object' || Array.isArray(data) || + typeof sourceData !== 'object' || Array.isArray(sourceData) || + typeof extData !== 'object' || Array.isArray(extData)) { + return data; + } + + const merged = { ...data }; + + for (const [key, value] of Object.entries(extData)) { + if (!Object.prototype.hasOwnProperty.call(sourceData, key)) { + merged[key] = value; + } + } + + return merged; +} + module.exports = { filterChatMode }; diff --git a/tests/helpers/test_llms_api_base.py b/tests/helpers/test_llms_api_base.py index dac5f461d28..e65cb30c1c0 100644 --- a/tests/helpers/test_llms_api_base.py +++ b/tests/helpers/test_llms_api_base.py @@ -8,6 +8,7 @@ """ import asyncio +import json import cecli.helpers.llms as llms_pkg import cecli.helpers.llms.pipeline as pipeline @@ -48,6 +49,47 @@ def test_env_api_base_trailing_slash_stripped(monkeypatch): assert resolved["api_base"] == "https://env.example.com/v1" +def test_configured_provider_prefix_wins_over_metadata_record(): + """A user-configured provider (model-providers) overrides a metadata record. + + ``bifrost/gemini/gemini-2.5-pro`` collides with the bundled + ``gemini/gemini-2.5-pro`` record (``litellm_provider: gemini``); because + ``bifrost`` is a configured provider, it must route through bifrost's + api_base on the chat wire instead of the native gemini family. + """ + from cecli.helpers.model_providers import PROVIDER_CONFIGS, ModelProviderManager + + # Without the provider configured, the colliding route stays native gemini. + baseline = resolve_model_config("bifrost/gemini/gemini-2.5-pro") + + assert baseline["provider"] == "gemini" + assert baseline["family"] == "gemini" + + original = dict(PROVIDER_CONFIGS) + + try: + ModelProviderManager().merge_provider_configs( + { + "bifrost": { + "api_base": "http://localhost:8090/v1", + "requires_api_key": False, + "display_name": "bifrost", + "models_url": "http://localhost:8090/v1/models", + } + } + ) + + resolved = resolve_model_config("bifrost/gemini/gemini-2.5-pro") + + assert resolved["provider"] == "bifrost" + assert resolved["family"] == "chat" + assert resolved["api_base"] == "http://localhost:8090/v1" + assert resolved["api_key_env"] is None + finally: + PROVIDER_CONFIGS.clear() + PROVIDER_CONFIGS.update(original) + + # --------------------------------------------------------------------------- # Per-request override via the pipeline # --------------------------------------------------------------------------- @@ -115,3 +157,153 @@ async def fake_dispatch(**kwargs): ) assert captured.get("api_base") == "https://my-proxy.example.com/v1" + + +# --------------------------------------------------------------------------- +# Request-time OPENAI_API_BASE / OPENAI_API_KEY override +# (docs/llms/openai-compat.md) +# --------------------------------------------------------------------------- + + +class _FakeResponse: + def raise_for_status(self): + return None + + def json(self): + return { + "id": "x", + "model": "m", + "choices": [{"index": 0, "message": {"role": "assistant", "content": "hi"}}], + "usage": {}, + } + + +class _FakeClient: + def __init__(self): + self.calls = [] + + async def __aenter__(self): + return self + + async def __aexit__(self, *args): + return None + + async def post(self, url, **kwargs): + self.calls.append({"url": url, **kwargs}) + return _FakeResponse() + + def stream(self, method, url, **kwargs): + self.calls.append({"url": url, **kwargs}) + return self + + def raise_for_status(self): + return None + + async def aiter_lines(self): + yield "data: " + json.dumps( + { + "id": "x", + "choices": [{"index": 0, "delta": {"content": "hi"}, "finish_reason": "stop"}], + } + ) + yield "data: [DONE]" + + +def test_chat_domain_openai_api_base_overrides_request_url(monkeypatch): + import cecli.helpers.llms.domains.chat as chat_domain + + client = _FakeClient() + monkeypatch.setattr(chat_domain, "make_client", lambda *a, **k: client) + monkeypatch.setenv("OPENAI_API_BASE", "https://my-proxy.example.com/v1") + monkeypatch.setenv("OPENAI_API_KEY", "sk-env-key") + + resolved = resolve_model_config("deepseek/deepseek-v4-flash") + + asyncio.run( + chat_domain.chat_complete( + resolved, + MSGS, + None, + "sk-deepseek", + {"Authorization": "Bearer sk-deepseek"}, + {}, + ) + ) + + call = client.calls[0] + assert call["url"] == "https://my-proxy.example.com/v1/chat/completions" + assert call["headers"]["Authorization"] == "Bearer sk-env-key" + + +def test_chat_domain_malformed_openai_api_base_ignored(monkeypatch): + import cecli.helpers.llms.domains.chat as chat_domain + + client = _FakeClient() + monkeypatch.setattr(chat_domain, "make_client", lambda *a, **k: client) + monkeypatch.setenv("OPENAI_API_BASE", "localhost:8000") + monkeypatch.setenv("OPENAI_API_KEY", "sk-env-key") + + resolved = resolve_model_config("deepseek/deepseek-v4-flash") + + asyncio.run( + chat_domain.chat_complete( + resolved, + MSGS, + None, + "sk-deepseek", + {"Authorization": "Bearer sk-deepseek"}, + {}, + ) + ) + + call = client.calls[0] + assert call["url"] == "https://api.deepseek.com/v1/chat/completions" + assert call["headers"]["Authorization"] == "Bearer sk-deepseek" + + +def test_chat_domain_stream_uses_openai_api_base(monkeypatch): + import cecli.helpers.llms.domains.chat as chat_domain + + client = _FakeClient() + monkeypatch.setattr(chat_domain, "make_client", lambda *a, **k: client) + monkeypatch.setenv("OPENAI_API_BASE", "https://my-proxy.example.com/v1/") + monkeypatch.setenv("OPENAI_API_KEY", "sk-env-key") + + resolved = resolve_model_config("deepseek/deepseek-v4-flash") + + async def collect(): + out = [] + + async for chunk in chat_domain.chat_stream( + resolved, + MSGS, + None, + "sk-deepseek", + {"Authorization": "Bearer sk-deepseek"}, + {}, + ): + out.append(chunk) + + return out + + asyncio.run(collect()) + + call = client.calls[0] + assert call["url"] == "https://my-proxy.example.com/v1/chat/completions" + assert call["headers"]["Authorization"] == "Bearer sk-env-key" + + +def test_pipeline_openai_env_overrides_chat_request(monkeypatch): + import cecli.helpers.llms.domains.chat as chat_domain + + client = _FakeClient() + monkeypatch.setattr(chat_domain, "make_client", lambda *a, **k: client) + monkeypatch.setenv("OPENAI_API_BASE", "https://my-proxy.example.com/v1") + monkeypatch.setenv("OPENAI_API_KEY", "sk-env-key") + monkeypatch.setenv("DEEPSEEK_API_KEY", "sk-deepseek") + + asyncio.run(pipeline.acompletion(model="deepseek/deepseek-v4-flash", messages=MSGS)) + + call = client.calls[0] + assert call["url"] == "https://my-proxy.example.com/v1/chat/completions" + assert call["headers"]["Authorization"] == "Bearer sk-env-key" diff --git a/tests/helpers/test_llms_cache_control.py b/tests/helpers/test_llms_cache_control.py new file mode 100644 index 00000000000..6da9410714b --- /dev/null +++ b/tests/helpers/test_llms_cache_control.py @@ -0,0 +1,192 @@ +"""Cache-control breakpoint injection tests for the anthropic messages domain. + +``anthropic_payload`` must attach ephemeral ``cache_control`` breakpoints at the +stable boundaries of a multi-turn exchange (last system block + the two most +recent non-tool user/assistant turns), following the conversation manager's +placement, while: + +- never mutating caller-owned message dicts (key messages are replaced with + copies), and +- never exceeding Anthropic's 4-breakpoint per-request limit, even when the + caller already supplied markers (so breakpoints never pile up between turns). + +No network: only the offline payload builder and helpers are exercised. +""" + +from cecli.helpers.llms.config import resolve_model_config +from cecli.helpers.llms.domains.messages import ( + MAX_CACHE_BREAKPOINTS, + _anthropic_usage, + _apply_anthropic_cache_control, + _count_cache_breakpoints, + anthropic_payload, +) + +SYS = "You are cecli, an agentic coding assistant. " * 30 + +MULTI_TURN = [ + {"role": "system", "content": SYS}, + {"role": "user", "content": "first question"}, + {"role": "assistant", "content": "first answer"}, + {"role": "user", "content": "second question"}, + { + "role": "assistant", + "content": "I'll check", + "tool_calls": [ + {"id": "t1", "type": "function", "function": {"name": "read", "arguments": "{}"}} + ], + }, + {"role": "tool", "tool_call_id": "t1", "content": "result of tool"}, + {"role": "assistant", "content": "second answer"}, + {"role": "user", "content": "current question"}, +] + + +def _block_cache_control(block): + return block.get("cache_control") if isinstance(block, dict) else None + + +def _last_block(msg): + content = msg["content"] + return content[-1] if isinstance(content, list) else content + + +def _resolve_no_inject(): + """Resolved config with auto-injection disabled (for helper-level tests).""" + resolved = resolve_model_config("github_copilot/claude-sonnet-5") + return dict(resolved, agent_block={"cache_control": False, "caches_by_default": True}) + + +def test_messages_api_injects_system_and_last_two_turns(): + resolved = resolve_model_config("github_copilot/claude-sonnet-5") + payload = anthropic_payload(resolved, MULTI_TURN, None, False, {}) + + assert resolved["family"] == "messages" + assert isinstance(payload["system"], list) + assert _block_cache_control(payload["system"][-1]) == {"type": "ephemeral"} + + # Tool-result and tool-use turns are skipped; only the last two non-tool + # turns (assistant "second answer", user "current question") carry a + # breakpoint. + marked = [ + i + for i, msg in enumerate(payload["messages"]) + if _block_cache_control(_last_block(msg)) == {"type": "ephemeral"} + ] + assert marked == [5, 6] + assert _count_cache_breakpoints(payload) == 3 + + +def test_single_turn_marks_last_block_only(): + resolved = resolve_model_config("claude-sonnet-5") + payload = anthropic_payload(resolved, [{"role": "user", "content": "hi"}], None, False, {}) + + assert _block_cache_control(_last_block(payload["messages"][0])) == {"type": "ephemeral"} + assert _count_cache_breakpoints(payload) == 1 + + +def test_chat_family_claude_not_injected(): + resolved = resolve_model_config("openrouter/claude-sonnet-5") + payload = anthropic_payload( + resolved, + [{"role": "system", "content": SYS}, {"role": "user", "content": "hi"}], + None, + False, + {}, + ) + + # Chat-family claude keeps its own caching semantics: no injection. + assert resolved["family"] == "chat" + assert isinstance(payload["system"], str) + assert _count_cache_breakpoints(payload) == 0 + + +def test_apply_does_not_mutate_input_messages(): + payload = anthropic_payload(_resolve_no_inject(), MULTI_TURN, None, False, {}) + before = list(payload["messages"]) + _apply_anthropic_cache_control(payload) + + # Original wire message dicts are untouched; marked messages were replaced + # with copies. + for msg in before: + content = msg["content"] + + if isinstance(content, list): + for block in content: + assert "cache_control" not in block + + +def test_breakpoint_budget_never_exceeds_four(): + for pre in range(0, MAX_CACHE_BREAKPOINTS + 1): + payload = anthropic_payload(_resolve_no_inject(), MULTI_TURN, None, False, {}) + + for i in range(pre): + content = payload["messages"][i]["content"] + + if isinstance(content, str): + payload["messages"][i]["content"] = [ + {"type": "text", "text": content, "cache_control": {"type": "ephemeral"}} + ] + else: + content[-1]["cache_control"] = {"type": "ephemeral"} + + _apply_anthropic_cache_control(payload) + + assert _count_cache_breakpoints(payload) <= MAX_CACHE_BREAKPOINTS + + +def test_breakpoints_do_not_pile_up_across_turns(): + resolved = resolve_model_config("github_copilot/claude-sonnet-5") + history = [ + {"role": "user", "content": "q1"}, + {"role": "assistant", "content": "a1"}, + ] + + for turn in range(3): + history.append({"role": "user", "content": f"q{turn + 2}"}) + history.append({"role": "assistant", "content": f"a{turn + 2}"}) + payload = anthropic_payload( + resolved, [{"role": "system", "content": SYS}] + history, None, False, {} + ) + + # Always exactly system + the two most recent non-tool turns; older + # history never accumulates extra breakpoints. + assert _count_cache_breakpoints(payload) == 3 + + +def test_anthropic_usage_normalizes_full_input(): + """Prompt tokens include cached input so hit-rate and cost math stay sane. + + Anthropic's ``input_tokens`` excludes cached input; the cache read and write + tokens arrive in separate fields. ``base_coder.calculate_and_show_tokens_and_cost`` + expects ``prompt_tokens`` to be the total input (cache_creation + cache_read + + input), otherwise the cache hit-rate blows up (e.g. a 9249-token cache read + against a 2-token ``input_tokens`` shows a ~462450% hit rate). + """ + usage = _anthropic_usage( + { + "input_tokens": 2, + "output_tokens": 20, + "cache_read_input_tokens": 9249, + "cache_creation_input_tokens": 77, + "output_tokens_details": {"thinking_tokens": 0}, + } + ) + + assert usage.prompt_tokens == 2 + 9249 + 77 + assert usage.completion_tokens == 20 + assert usage.total_tokens == 2 + 9249 + 77 + assert usage.cache_read_input_tokens == 9249 + assert usage.cache_creation_input_tokens == 77 + assert usage.completion_tokens_details == {"reasoning_tokens": 0} + + +def test_anthropic_usage_without_cache_keys_keeps_openai_shape(): + """A usage block with no cache fields still normalizes to plain counts.""" + usage = _anthropic_usage({"input_tokens": 10, "output_tokens": 5}) + + assert usage.prompt_tokens == 10 + assert usage.completion_tokens == 5 + assert usage.total_tokens == 10 + assert usage.cache_read_input_tokens is None + assert usage.cache_creation_input_tokens is None diff --git a/tests/helpers/test_llms_github_copilot_auth.py b/tests/helpers/test_llms_github_copilot_auth.py index 188c2e872bf..e96ecbd6b60 100644 --- a/tests/helpers/test_llms_github_copilot_auth.py +++ b/tests/helpers/test_llms_github_copilot_auth.py @@ -355,6 +355,32 @@ def test_resolve_model_config_claude_family_messages(auth, tmp_path): assert resolved["family"] == "messages" +def test_resolve_model_config_hyphenated_claude_maps_to_copilot(auth, tmp_path): + """Hyphenated claude names without an exact copilot record must still + route through the copilot provider instead of falling back to the bare + anthropic record (e.g. ``github_copilot/claude-sonnet-4-5``).""" + _seed_api_key(tmp_path) + + resolved = llms_config.resolve_model_config("github_copilot/claude-sonnet-4-5") + + assert resolved["provider"] == "github_copilot" + assert resolved["family"] == "messages" + assert resolved["api_key_env"] is None + + +def test_resolve_model_config_unlisted_copilot_model_maps_to_copilot(auth, tmp_path): + """Any ``github_copilot/``-prefixed model routes through the copilot + provider even when no copilot metadata record exists at all (e.g. a brand + new gpt model, so it must not fall back to the bare openai record).""" + _seed_api_key(tmp_path) + + resolved = llms_config.resolve_model_config("github_copilot/o3") + + assert resolved["provider"] == "github_copilot" + assert resolved["family"] == "responses" + assert resolved["api_key_env"] is None + + def test_get_api_key_wiring_uses_cached_token(auth, tmp_path): _seed_api_key(tmp_path) resolved = llms_config.resolve_model_config("github_copilot/gpt-5") diff --git a/tests/helpers/test_llms_hyperscalers.py b/tests/helpers/test_llms_hyperscalers.py index a7514ce6994..036f16ead6d 100644 --- a/tests/helpers/test_llms_hyperscalers.py +++ b/tests/helpers/test_llms_hyperscalers.py @@ -304,3 +304,55 @@ def test_pipeline_bedrock_mantle_bearer_when_token_set(monkeypatch): def test_resolve_model_config_surfaces_extra_query(): resolved = resolve_model_config("azure/sample-model") assert resolved["extra_query"] == {"api-version": "2024-10-21"} + + +def test_resolve_model_config_bedrock_claude_maps_to_bedrock(): + """Hyphenated/newer claude names under ``bedrock/`` must route through the + bedrock provider (SigV4 Converse wire) instead of falling back to the bare + anthropic record (e.g. ``bedrock/claude-sonnet-5``).""" + resolved = resolve_model_config("bedrock/claude-sonnet-5") + + assert resolved["provider"] == "bedrock" + assert resolved["family"] == "bedrock" + assert resolved["api_key_env"] == "AWS_ACCESS_KEY_ID" + + +def test_resolve_model_config_bedrock_mantle_claude_maps_to_bedrock_mantle(): + """Newer claude names under ``bedrock_mantle/`` route through the mantle + provider (OpenAI-compatible chat wire with SigV4/Bearer) instead of the + bare anthropic record.""" + resolved = resolve_model_config("bedrock_mantle/claude-sonnet-5") + + assert resolved["provider"] == "bedrock_mantle" + assert resolved["family"] == "chat" + assert resolved["api_key_env"] == "BEDROCK_MANTLE_API_KEY" + + +def test_resolve_model_config_openrouter_claude_maps_to_openrouter(): + """Anthropic models hosted on a third-party backend authenticate against + THAT provider and speak its chat completions wire, not the anthropic + messages API (e.g. ``openrouter/claude-sonnet-5``).""" + resolved = resolve_model_config("openrouter/claude-sonnet-5") + + assert resolved["provider"] == "openrouter" + assert resolved["family"] == "chat" + assert resolved["api_key_env"] == "OPENROUTER_API_KEY" + + +def test_resolve_model_config_deepseek_claude_maps_to_deepseek(): + """Same provider-sensitive claude rule for deepseek.""" + resolved = resolve_model_config("deepseek/claude-sonnet-5") + + assert resolved["provider"] == "deepseek" + assert resolved["family"] == "chat" + assert resolved["api_key_env"] == "DEEPSEEK_API_KEY" + + +def test_resolve_model_config_anthropic_claude_stays_anthropic_messages(): + """Native anthropic claude models keep the anthropic provider and the + /v1/messages wire (the override applies only to non-anthropic prefixes).""" + resolved = resolve_model_config("anthropic/claude-sonnet-5") + + assert resolved["provider"] == "anthropic" + assert resolved["family"] == "messages" + assert resolved["api_key_env"] == "ANTHROPIC_API_KEY" diff --git a/tests/helpers/test_model_config.py b/tests/helpers/test_model_config.py index d6658663b20..3d3675a4ec7 100644 --- a/tests/helpers/test_model_config.py +++ b/tests/helpers/test_model_config.py @@ -105,6 +105,7 @@ def test_no_match_returns_defaults(): "cache_control": False, "caches_by_default": True, "use_temperature": False, + "uses_messages_api": False, } # Unknown models get a noop reasoning formatter (the default behavior in # set_reasoning_effort is used unchanged). diff --git a/tests/tui/test_app.py b/tests/tui/test_app.py index 72721450518..88f4fc7ddf0 100644 --- a/tests/tui/test_app.py +++ b/tests/tui/test_app.py @@ -1,4 +1,4 @@ -from unittest.mock import MagicMock, patch +from unittest.mock import AsyncMock, MagicMock, patch import pytest from textual import events @@ -280,3 +280,69 @@ def test_show_error_uses_query_one(tui_instance): timeout=5, agent_name=None, ) + + +def test_handle_spawn_agent_command_dispatches_to_worker_loop(tui_instance): + """Spawn dispatch is scheduled on the worker loop without a generate cycle.""" + worker = MagicMock() + worker.loop = MagicMock() + worker.coder = MagicMock() + worker.coder.io = MagicMock() + tui_instance.worker = worker + + input_area = MagicMock() + tui_instance.query_one = MagicMock(return_value=input_area) + tui_instance.add_user_message = MagicMock() + + tui_instance._handle_spawn_agent_command("/spawn-agent reviewer", "/spawn-agent reviewer") + + # Input cleared, history saved, command echoed + assert input_area.value == "" + input_area.save_to_history.assert_called_once_with("/spawn-agent reviewer") + tui_instance.add_user_message.assert_called_once_with("/spawn-agent reviewer") + + # Dispatch is scheduled on the worker loop + worker.loop.call_soon_threadsafe.assert_called_once() + callback = worker.loop.call_soon_threadsafe.call_args[0][0] + callback() + worker.loop.create_task.assert_called_once() + coro = worker.loop.create_task.call_args[0][0] + + # Running the scheduled coroutine invokes SpawnAgentCommand.execute + import asyncio + + with patch( + "cecli.commands.spawn_agent.SpawnAgentCommand.execute", new=AsyncMock() + ) as mock_execute: + asyncio.run(coro) + mock_execute.assert_awaited_once_with(worker.coder.io, worker.coder, "reviewer") + + +def test_handle_spawn_agent_command_no_args_shows_usage(tui_instance): + """Missing agent name shows usage error and does not dispatch.""" + worker = MagicMock() + worker.loop = MagicMock() + tui_instance.worker = worker + tui_instance.show_error = MagicMock() + tui_instance.query_one = MagicMock(return_value=MagicMock()) + + tui_instance._handle_spawn_agent_command("/spawn-agent", "/spawn-agent") + + tui_instance.show_error.assert_called_once_with("Usage: /spawn-agent []") + worker.loop.call_soon_threadsafe.assert_not_called() + + +def test_on_input_area_submit_intercepts_spawn_agent(tui_instance): + """'/spawn-agent' is handled directly without reaching the generate path.""" + tui_instance.query_one = MagicMock(return_value=MagicMock()) + tui_instance._handle_spawn_agent_command = MagicMock() + + message = MagicMock() + message.value = "/spawn-agent reviewer review the code" + + tui_instance.on_input_area_submit(message) + + tui_instance._handle_spawn_agent_command.assert_called_once_with( + "/spawn-agent reviewer review the code", + "/spawn-agent reviewer review the code", + )