feat: conversational agent support

[mike-deem-uipath]

Depends on UiPath/uipath-runtime-python#65

Adds support for conversational agents:

• Adds some optional overrides for local testing with CAS (configured using env vars)
• Log conversation error events received from CAS over the websocket bridge
• Adds an is_conversational getter to AgentDefinition
• Adds --keep-state-file cli option that causes the state.db to be preserved. This allows conversational agent runs to accumulate conversation history.

Also

• Fixed a minor typo in the autonomous agent system prompt.

[cristipufu]

let's replace this with:

@click.option(
    "--state-file",
    required=False,
    type=click.Path(exists=True),
    help="Full path to the state file (takes priority over default location)"
)

Trying to shoot two birds with one stone, if we have this specified, we just use it as an override and don't delete it. Updated the runtime PR as well https://github.com/UiPath/uipath-runtime-python/pull/65/changes

We need to update the pyproject.toml with the new runtime version range + increment the minor here as well

[cristipufu]

state_file_path=state_file

[cristipufu]

let's change this method's signature to only use what it needs from LowCodeAgentDefinition (agent_name str, model str, system_message). we need to re-use it for the conversion flow

[cristipufu]

for reference, this is how a converted autonomous low-code agent looks today:

class AgentInput(BaseModel):
    pass

class AgentOutput(BaseModel):
    content: str | None = Field(None, description="Output content")

# Agent Messages Function
def create_messages(state: AgentInput) -> Sequence[SystemMessage | HumanMessage]:
    # Apply system prompt template
    current_date = datetime.now(timezone.utc).strftime('%Y-%m-%d')
    system_prompt_content = f"""You are an agentic assistant."""
    enhanced_system_prompt = (
        AGENT_SYSTEM_PROMPT_TEMPLATE
        .replace('{{systemPrompt}}', system_prompt_content)
        .replace('{{currentDate}}', current_date)
        .replace('{{agentName}}', 'Mr Assistant')
    )

    return [
        SystemMessage(content=enhanced_system_prompt),
        HumanMessage(content=f"""What is the current date?"""),
    ]

# Create agent graph
graph = create_agent(model=llm, messages=create_messages, tools=all_tools, input_schema=AgentInput, output_schema=AgentOutput)

[cristipufu]

we use buit-in types (dict not Dict, x | None instead of Optional etc)