fix(codex): parse tool calls and reasoning in conversation API
The Codex conversation parser was only handling "message" payload types, missing tool calls entirely. Codex uses separate response_items: - function_call: tool invocations with name, arguments, call_id - reasoning: thinking summaries (encrypted content, visible summary) - message: user/assistant text (previously the only type handled) Changes: - Parse function_call payloads and accumulate as tool_calls array - Attach tool_calls to the next assistant message, or flush standalone - Parse reasoning payloads and extract summary text as thinking - Add _parse_codex_arguments() helper to handle JSON string arguments This fixes the dashboard not showing Codex tool calls like exec_command, read_file, etc. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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teernisse
@@ -108,8 +108,15 @@ class ConversationMixin:
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return messages
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def _parse_codex_conversation(self, session_id):
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"""Parse Codex JSONL conversation format."""
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"""Parse Codex JSONL conversation format.
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Codex uses separate response_items for different content types:
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- message: user/assistant text messages
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- function_call: tool invocations (name, arguments, call_id)
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- reasoning: thinking summaries (encrypted content, visible summary)
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"""
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messages = []
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pending_tool_calls = [] # Accumulate tool calls to attach to next assistant message
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conv_file = self._find_codex_transcript_file(session_id)
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@@ -123,53 +130,132 @@ class ConversationMixin:
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if not isinstance(entry, dict):
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continue
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# Codex format: type="response_item", payload.type="message"
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if entry.get("type") != "response_item":
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continue
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payload = entry.get("payload", {})
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if not isinstance(payload, dict):
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continue
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if payload.get("type") != "message":
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payload_type = payload.get("type")
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timestamp = entry.get("timestamp", "")
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# Handle function_call (tool invocations)
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if payload_type == "function_call":
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tool_call = {
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"name": payload.get("name", "unknown"),
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"input": self._parse_codex_arguments(payload.get("arguments", "{}")),
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}
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pending_tool_calls.append(tool_call)
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continue
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role = payload.get("role", "")
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content_parts = payload.get("content", [])
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if not isinstance(content_parts, list):
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# Handle reasoning (thinking summaries)
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if payload_type == "reasoning":
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summary_parts = payload.get("summary", [])
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if summary_parts:
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thinking_text = []
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for part in summary_parts:
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if isinstance(part, dict) and part.get("type") == "summary_text":
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thinking_text.append(part.get("text", ""))
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if thinking_text:
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# Flush any pending tool calls first
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if pending_tool_calls:
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messages.append({
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"role": "assistant",
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"content": "",
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"tool_calls": pending_tool_calls,
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"timestamp": timestamp,
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})
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pending_tool_calls = []
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# Add thinking as assistant message
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messages.append({
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"role": "assistant",
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"content": "",
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"thinking": "\n".join(thinking_text),
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"timestamp": timestamp,
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})
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continue
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# Skip developer role (system context/permissions)
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if role == "developer":
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continue
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# Handle message (user/assistant text)
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if payload_type == "message":
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role = payload.get("role", "")
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content_parts = payload.get("content", [])
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if not isinstance(content_parts, list):
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continue
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# Extract text from content array
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text_parts = []
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for part in content_parts:
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if isinstance(part, dict):
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# Codex uses "input_text" for user, "output_text" for assistant
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text = part.get("text", "")
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if text:
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# Skip injected context (AGENTS.md, environment, permissions)
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skip_prefixes = (
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"<INSTRUCTIONS>",
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"<environment_context>",
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"<permissions instructions>",
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"# AGENTS.md instructions",
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)
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if any(text.startswith(p) for p in skip_prefixes):
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continue
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text_parts.append(text)
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# Skip developer role (system context/permissions)
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if role == "developer":
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continue
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if text_parts and role in ("user", "assistant"):
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messages.append({
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"role": role,
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"content": "\n".join(text_parts),
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"timestamp": entry.get("timestamp", ""),
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})
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# Extract text from content array
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text_parts = []
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for part in content_parts:
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if isinstance(part, dict):
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text = part.get("text", "")
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if text:
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# Skip injected context (AGENTS.md, environment, permissions)
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skip_prefixes = (
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"<INSTRUCTIONS>",
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"<environment_context>",
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"<permissions instructions>",
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"# AGENTS.md instructions",
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)
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if any(text.startswith(p) for p in skip_prefixes):
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continue
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text_parts.append(text)
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if role == "user" and text_parts:
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# Flush any pending tool calls before user message
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if pending_tool_calls:
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messages.append({
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"role": "assistant",
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"content": "",
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"tool_calls": pending_tool_calls,
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"timestamp": timestamp,
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})
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pending_tool_calls = []
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messages.append({
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"role": "user",
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"content": "\n".join(text_parts),
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"timestamp": timestamp,
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})
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elif role == "assistant":
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msg = {
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"role": "assistant",
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"content": "\n".join(text_parts) if text_parts else "",
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"timestamp": timestamp,
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}
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# Attach any pending tool calls to this assistant message
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if pending_tool_calls:
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msg["tool_calls"] = pending_tool_calls
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pending_tool_calls = []
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if text_parts or msg.get("tool_calls"):
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messages.append(msg)
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except json.JSONDecodeError:
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continue
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# Flush any remaining pending tool calls
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if pending_tool_calls:
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messages.append({
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"role": "assistant",
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"content": "",
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"tool_calls": pending_tool_calls,
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"timestamp": "",
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})
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except OSError:
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pass
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return messages
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def _parse_codex_arguments(self, arguments_str):
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"""Parse Codex function_call arguments (JSON string or dict)."""
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if isinstance(arguments_str, dict):
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return arguments_str
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if isinstance(arguments_str, str):
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try:
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return json.loads(arguments_str)
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except json.JSONDecodeError:
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return {"raw": arguments_str}
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return {}
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