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Consolidates the incremental refactor work into a single change set: modular web tools (api/web_tools), native Anthropic request building and SSE block policy, OpenAI conversion and error handling, provider transports and rate limiting, messaging handler and tree queue, safe logging, smoke tests, and broad test coverage.
136 lines
4.5 KiB
Python
136 lines
4.5 KiB
Python
"""Request detection utilities for API optimizations.
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Detects quota checks, title generation, prefix detection, suggestion mode,
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and filepath extraction requests to enable fast-path responses.
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"""
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from core.anthropic import extract_text_from_content
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from .models.anthropic import MessagesRequest
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def is_quota_check_request(request_data: MessagesRequest) -> bool:
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"""Check if this is a quota probe request.
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Quota checks are typically simple requests with max_tokens=1
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and a single message containing the word "quota".
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"""
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if (
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request_data.max_tokens == 1
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and len(request_data.messages) == 1
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and request_data.messages[0].role == "user"
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):
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text = extract_text_from_content(request_data.messages[0].content)
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if "quota" in text.lower():
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return True
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return False
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def is_title_generation_request(request_data: MessagesRequest) -> bool:
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"""Check if this is a conversation title generation request.
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Title generation requests are detected by a system prompt containing
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title extraction instructions, no tools, and a single user message.
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Matches Claude Code session title prompts (sentence-case title, JSON
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\"title\" field, etc.).
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"""
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if not request_data.system or request_data.tools:
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return False
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system_text = extract_text_from_content(request_data.system).lower()
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if "title" not in system_text:
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return False
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return "sentence-case title" in system_text or (
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"return json" in system_text
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and "field" in system_text
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and ("coding session" in system_text or "this session" in system_text)
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)
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def is_prefix_detection_request(request_data: MessagesRequest) -> tuple[bool, str]:
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"""Check if this is a fast prefix detection request.
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Prefix detection requests contain a policy_spec block and
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a Command: section for extracting shell command prefixes.
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Returns:
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Tuple of (is_prefix_request, command_string)
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"""
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if len(request_data.messages) != 1 or request_data.messages[0].role != "user":
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return False, ""
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content = extract_text_from_content(request_data.messages[0].content)
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if "<policy_spec>" in content and "Command:" in content:
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try:
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cmd_start = content.rfind("Command:") + len("Command:")
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return True, content[cmd_start:].strip()
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except TypeError:
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return False, ""
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return False, ""
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def is_suggestion_mode_request(request_data: MessagesRequest) -> bool:
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"""Check if this is a suggestion mode request.
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Suggestion mode requests contain "[SUGGESTION MODE:" in the user's message,
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used for auto-suggesting what the user might type next.
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"""
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for msg in request_data.messages:
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if msg.role == "user":
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text = extract_text_from_content(msg.content)
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if "[SUGGESTION MODE:" in text:
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return True
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return False
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def is_filepath_extraction_request(
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request_data: MessagesRequest,
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) -> tuple[bool, str, str]:
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"""Check if this is a filepath extraction request.
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Filepath extraction requests have a single user message with
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"Command:" and "Output:" sections, asking to extract file paths
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from command output.
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Returns:
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Tuple of (is_filepath_request, command, output)
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"""
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if len(request_data.messages) != 1 or request_data.messages[0].role != "user":
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return False, "", ""
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if request_data.tools:
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return False, "", ""
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content = extract_text_from_content(request_data.messages[0].content)
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if "Command:" not in content or "Output:" not in content:
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return False, "", ""
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# Match if user content OR system block indicates filepath extraction
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user_has_filepaths = (
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"filepaths" in content.lower() or "<filepaths>" in content.lower()
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)
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system_text = (
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extract_text_from_content(request_data.system) if request_data.system else ""
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)
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system_has_extract = (
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"extract any file paths" in system_text.lower()
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or "file paths that this command" in system_text.lower()
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)
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if not user_has_filepaths and not system_has_extract:
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return False, "", ""
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cmd_start = content.find("Command:") + len("Command:")
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output_marker = content.find("Output:", cmd_start)
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if output_marker == -1:
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return False, "", ""
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command = content[cmd_start:output_marker].strip()
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output = content[output_marker + len("Output:") :].strip()
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for marker in ["<", "\n\n"]:
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if marker in output:
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output = output.split(marker)[0].strip()
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return True, command, output
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