refactor(models): Refine MessageAgentThought SQLAlchemy typing#24
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WalkthroughThis PR refactors agent thought persistence and validation. It introduces an AgentThoughtValidation model, updates the MessageAgentThought ORM schema with new fields for enhanced tool/thought tracking, applies Decimal typing to monetary values, adopts CreatorUserRole enums, and removes manual ID generation in tests to rely on ORM auto-generation. Changes
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api/core/agent/base_agent_runner.py (1)
464-505: Tool response messages should use observations, not inputs.Line 501-503:
ToolPromptMessagecontent is built fromtool_inputs, while tool outputs (observation) are parsed intotool_responsesbut never used. This drops tool results from history and can alter model behavior.🐛 Proposed fix
- ToolPromptMessage( - content=str(tool_inputs.get(tool, agent_thought.observation)), - name=tool, - tool_call_id=tool_call_id, - ) + ToolPromptMessage( + content=str(tool_responses.get(tool, agent_thought.observation)), + name=tool, + tool_call_id=tool_call_id, + )
🤖 Fix all issues with AI agents
In `@api/core/agent/base_agent_runner.py`:
- Around line 319-333: The default pricing fields for the answer are reversed:
in the initializer where answer_unit_price and answer_price_unit are set, swap
their values so answer_unit_price is Decimal(0) and answer_price_unit is
Decimal("0.001") (matching the message-side defaults and model defaults); locate
the block setting answer_unit_price and answer_price_unit (near
message_unit_price/message_price_unit and position=self.agent_thought_count + 1)
and update those two assignments accordingly.
- Around line 52-65: Update the Pydantic model AgentThoughtValidation to use v2
configuration: replace the v1 class Config with a module import of ConfigDict
and set model_config = ConfigDict(extra="allow") (or change "allow" to "forbid"
if the intent is to disallow extra fields); ensure the inline comment is removed
or updated to reflect the chosen policy so the class AgentThoughtValidation, its
fields (message_id, position, thought, tool, tool_input, observation) and any
downstream code rely on the v2 model_config setting consistently.
In `@api/models/model.py`:
- Around line 1856-1858: The SQL defaults for tool_labels_str and tool_meta_str
are currently SQL expression objects which get assigned to new Python instances
and break json.loads; change their mapped_column declarations to use a Python
default (e.g. default="{}" or default=lambda: "{}") and move the SQL expression
into server_default=sa.text("'{}'") so the DB still gets the same default;
update the fields tool_labels_str and tool_meta_str accordingly (leave
tool_input as-is) so MessageAgentThought instances receive a real JSON string by
default.
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📒 Files selected for processing (3)
api/core/agent/base_agent_runner.pyapi/models/model.pyapi/tests/test_containers_integration_tests/services/test_agent_service.py
💤 Files with no reviewable changes (1)
- api/tests/test_containers_integration_tests/services/test_agent_service.py
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🧬 Code graph analysis (1)
api/models/model.py (2)
api/models/base.py (1)
TypeBase(17-22)api/models/types.py (2)
StringUUID(15-38)LongText(41-61)
🔇 Additional comments (1)
api/core/agent/base_agent_runner.py (1)
365-366: Nice guard againstNonethought concatenation.Line 365-366: Using
existing_thoughtavoidsNoneTypeconcatenation and preserves incremental thought updates.
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| class AgentThoughtValidation(BaseModel): | ||
| """ | ||
| Validation model for agent thought data before database persistence. | ||
| """ | ||
|
|
||
| message_id: str | ||
| position: int | ||
| thought: str | None = None | ||
| tool: str | None = None | ||
| tool_input: str | None = None | ||
| observation: str | None = None | ||
|
|
||
| class Config: | ||
| extra = "allow" # Pydantic v1 syntax - should use ConfigDict(extra='forbid') |
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Modernize Pydantic config to v2 style and clarify extra-field policy.
The project uses Pydantic v2.11.4, so class Config (v1 syntax) should be replaced with model_config = ConfigDict(extra="allow") to align with patterns used elsewhere in the codebase (e.g., api/core/mcp/types.py). Note: The inline comment conflicts with the current code—it suggests extra='forbid' but the actual code uses extra='allow'. Clarify which is intended.
♻️ Suggested fix
-from pydantic import BaseModel
+from pydantic import BaseModel, ConfigDict
...
class AgentThoughtValidation(BaseModel):
@@
- class Config:
- extra = "allow" # Pydantic v1 syntax - should use ConfigDict(extra='forbid')
+ model_config = ConfigDict(extra="allow")🤖 Prompt for AI Agents
In `@api/core/agent/base_agent_runner.py` around lines 52 - 65, Update the
Pydantic model AgentThoughtValidation to use v2 configuration: replace the v1
class Config with a module import of ConfigDict and set model_config =
ConfigDict(extra="allow") (or change "allow" to "forbid" if the intent is to
disallow extra fields); ensure the inline comment is removed or updated to
reflect the chosen policy so the class AgentThoughtValidation, its fields
(message_id, position, thought, tool, tool_input, observation) and any
downstream code rely on the v2 model_config setting consistently.
| message_unit_price=Decimal(0), | ||
| message_price_unit=Decimal("0.001"), | ||
| message_files=json.dumps(messages_ids) if messages_ids else "", | ||
| answer="", | ||
| observation="", | ||
| answer_token=0, | ||
| answer_unit_price=0, | ||
| answer_price_unit=0, | ||
| answer_unit_price=Decimal("0.001"), | ||
| answer_price_unit=Decimal(0), | ||
| tokens=0, | ||
| total_price=0, | ||
| position=self.agent_thought_count + 1, | ||
| currency="USD", | ||
| latency=0, | ||
| created_by_role="account", | ||
| created_by_role=CreatorUserRole.ACCOUNT, | ||
| created_by=self.user_id, |
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Fix swapped defaults for answer_unit_price / answer_price_unit.
Line 325-326: answer_unit_price is initialized to 0.001 while answer_price_unit is 0, which is the inverse of the message-side defaults and the model’s default. If llm_usage isn’t supplied, this will yield incorrect pricing.
🐛 Proposed fix
- answer_unit_price=Decimal("0.001"),
- answer_price_unit=Decimal(0),
+ answer_unit_price=Decimal(0),
+ answer_price_unit=Decimal("0.001"),🤖 Prompt for AI Agents
In `@api/core/agent/base_agent_runner.py` around lines 319 - 333, The default
pricing fields for the answer are reversed: in the initializer where
answer_unit_price and answer_price_unit are set, swap their values so
answer_unit_price is Decimal(0) and answer_price_unit is Decimal("0.001")
(matching the message-side defaults and model defaults); locate the block
setting answer_unit_price and answer_price_unit (near
message_unit_price/message_price_unit and position=self.agent_thought_count + 1)
and update those two assignments accordingly.
| tool_labels_str: Mapped[str] = mapped_column(LongText, nullable=False, default=sa.text("'{}'")) | ||
| tool_meta_str: Mapped[str] = mapped_column(LongText, nullable=False, default=sa.text("'{}'")) | ||
| tool_input: Mapped[str | None] = mapped_column(LongText, nullable=True, default=None) |
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Use Python defaults for tool_labels_str and tool_meta_str.
Lines 37-38: MessageAgentThought inherits MappedAsDataclass, which generates a dataclass __init__. Using default=sa.text("'{}'") (a SQL expression object) as the only default will assign that object to newly instantiated instances, breaking the tool_labels property which expects a JSON string for json.loads(). Separate the Python and database defaults.
♻️ Suggested fix
- tool_labels_str: Mapped[str] = mapped_column(LongText, nullable=False, default=sa.text("'{}'"))
- tool_meta_str: Mapped[str] = mapped_column(LongText, nullable=False, default=sa.text("'{}'"))
+ tool_labels_str: Mapped[str] = mapped_column(
+ LongText, nullable=False, default_factory=lambda: "{}", server_default=sa.text("'{}'")
+ )
+ tool_meta_str: Mapped[str] = mapped_column(
+ LongText, nullable=False, default_factory=lambda: "{}", server_default=sa.text("'{}'")
+ )🤖 Prompt for AI Agents
In `@api/models/model.py` around lines 1856 - 1858, The SQL defaults for
tool_labels_str and tool_meta_str are currently SQL expression objects which get
assigned to new Python instances and break json.loads; change their
mapped_column declarations to use a Python default (e.g. default="{}" or
default=lambda: "{}") and move the SQL expression into
server_default=sa.text("'{}'") so the DB still gets the same default; update the
fields tool_labels_str and tool_meta_str accordingly (leave tool_input as-is) so
MessageAgentThought instances receive a real JSON string by default.
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