Merge pull request #85 from MarketSquare/feature/temperature_option

feature: added temperature option for models

Author: jublankeviadee

README.md

@@ -173,31 +173,35 @@ REQUEST_LIMIT=5
 TOTAL_TOKENS_LIMIT=6000
 ORCHESTRATOR_AGENT_PROVIDER="openai"
 ORCHESTRATOR_AGENT_MODEL="gpt-4o-mini"
+ORCHESTRATOR_AGENT_TEMPERATURE=0.1
 LOCATOR_AGENT_PROVIDER="openai"
 LOCATOR_AGENT_MODEL="gpt-4o-mini"
+LOCATOR_AGNET_TEMPERATURE=0.1
 LOCATOR_TYPE="css"
 ```
 
 ### 📝 Configuration Parameters
 
-| Name                               | Default         | Required?                | Description                                                                |
-|------------------------------------|-----------------|--------------------------|----------------------------------------------------------------------------|
-| **OPENAI_API_KEY**                 | `None`          | If using OpenAI          | Your OpenAI API key                                                        |
-| **LITELLM_API_KEY**                | `None`          | If using LiteLLM         | Your LiteLLM API key                                                       |
-| **AZURE_API_KEY**                  | `None`          | If using Azure           | Your Azure OpenAI API key                                                  |
-| **AZURE_API_VERSION**              | `None`          | If using Azure           | Azure OpenAI API version                                                   |
-| **AZURE_ENDPOINT**                 | `None`          | If using Azure           | Azure OpenAI endpoint                                                      |
-| **BASE_URL**                       | `None`          | No                       | Endpoint to connect to (if required)                                       |
-| **ENABLE_SELF_HEALING**            | `True`          | No                       | Enable or disable SelfhealingAgents                                        |
-| **USE_LLM_FOR_LOCATOR_GENERATION** | `True`          | No                       | If `True`, LLM generates locator suggestions directly (see note below)     |
-| **MAX_RETRIES**                    | `3`             | No                       | Number of self-healing attempts per locator                                |
-| **REQUEST_LIMIT**                  | `5`             | No                       | Internal agent-level limit for valid LLM response attempts                 |
-| **TOTAL_TOKENS_LIMIT**             | `6000`          | No                       | Maximum input tokens per LLM request                                       |
-| **ORCHESTRATOR_AGENT_PROVIDER**    | `"openai"`      | No                       | Provider for the orchestrator agent (`"openai"`, `"azure"` or `"litellm"`) |
+| Name                               | Default        | Required?                | Description                                                                |
+|------------------------------------|----------------|--------------------------|----------------------------------------------------------------------------|
+| **OPENAI_API_KEY**                 | `None`         | If using OpenAI          | Your OpenAI API key                                                        |
+| **LITELLM_API_KEY**                | `None`         | If using LiteLLM         | Your LiteLLM API key                                                       |
+| **AZURE_API_KEY**                  | `None`         | If using Azure           | Your Azure OpenAI API key                                                  |
+| **AZURE_API_VERSION**              | `None`         | If using Azure           | Azure OpenAI API version                                                   |
+| **AZURE_ENDPOINT**                 | `None`         | If using Azure           | Azure OpenAI endpoint                                                      |
+| **BASE_URL**                       | `None`         | No                       | Endpoint to connect to (if required)                                       |
+| **ENABLE_SELF_HEALING**            | `True`         | No                       | Enable or disable SelfhealingAgents                                        |
+| **USE_LLM_FOR_LOCATOR_GENERATION** | `True`         | No                       | If `True`, LLM generates locator suggestions directly (see note below)     |
+| **MAX_RETRIES**                    | `3`            | No                       | Number of self-healing attempts per locator                                |
+| **REQUEST_LIMIT**                  | `5`            | No                       | Internal agent-level limit for valid LLM response attempts                 |
+| **TOTAL_TOKENS_LIMIT**             | `6000`         | No                       | Maximum input tokens per LLM request                                       |
+| **ORCHESTRATOR_AGENT_PROVIDER**    | `"openai"`     | No                       | Provider for the orchestrator agent (`"openai"`, `"azure"` or `"litellm"`) |
 | **ORCHESTRATOR_AGENT_MODEL**       | `"gpt-4o-mini"` | No                       | Model for the orchestrator agent                                           |
-| **LOCATOR_AGENT_PROVIDER**         | `"openai"`      | No                       | Provider for the locator agent (`"openai"`, `"azure"` or `"litellm"`)      |
+| **ORCHESTRATOR_AGENT_TEMPERATURE** | `0.1`          | No                       | Orchestrator model temperature.                                            |
+| **LOCATOR_AGENT_PROVIDER**         | `"openai"`     | No                       | Provider for the locator agent (`"openai"`, `"azure"` or `"litellm"`)      |
 | **LOCATOR_AGENT_MODEL**            | `"gpt-4o-mini"` | No                       | Model for the locator agent                                                |
-| **LOCATOR_TYPE**                   | `"css"`         | No                       | Restricts the locator suggestions of the agent to the given type           |
+| **LOCATOR_AGENT_TEMPERATURE**      | `0.1`          | No                       | Locator model temperature.                                                 |
+| **LOCATOR_TYPE**                   | `"css"`        | No                       | Restricts the locator suggestions of the agent to the given type           |
 
 > **Note:**  
 > Locator suggestions can be generated either by assembling strings from the DOM tree (with an LLM selecting the best option), or by having the LLM generate suggestions directly itself with the context given (DOM included). Set `USE_LLM_FOR_LOCATOR_GENERATION` to `True` to enable direct LLM generation (default is True).

SelfhealingAgents/self_healing_system/agents/locator_agent/base_locator_agent.py

@@ -30,6 +30,7 @@ class BaseLocatorAgent(ABC):
     Defines the common interface and shared functionality for all locator agent flavors.
 
     Attributes:
+        _cfg (Cfg): An instance of the Cfg config class containing user-defined application configuration.
         _usage_limits (UsageLimits): Usage token and request limits.
         _dom_utility (BaseDomUtils): DOM utility instance for the specific library.
         _use_llm_for_locator_generation (bool): Whether to use LLM for locator generation.
@@ -45,6 +46,7 @@ def __init__(self, cfg: Cfg, dom_utility: BaseDomUtils) -> None:
             cfg (Cfg): Instance of Cfg config class containing user-defined app configuration.
             dom_utility (BaseDomUtils): DOM utility instance for validation.
         """
+        self._cfg = cfg
         self._usage_limits: UsageLimits = UsageLimits(
             request_limit=cfg.request_limit, total_tokens_limit=cfg.total_tokens_limit
         )
@@ -217,7 +219,7 @@ async def _heal_with_llm(
             PromptsLocatorGenerationAgent.get_user_msg(ctx),
             deps=ctx.deps,
             usage_limits=self._usage_limits,
-            model_settings={"temperature": 0.1},
+            model_settings={"temperature": self._cfg.locator_agent_temperature},
         )
         if not isinstance(response.output, LocatorHealingResponse):
             raise ModelRetry(
@@ -319,7 +321,7 @@ async def _heal_with_dom_utils(
                 ),
                 deps=ctx.deps,
                 usage_limits=self._usage_limits,
-                model_settings={"temperature": 0.1},
+                model_settings={"temperature": self._cfg.locator_agent_temperature},
             )
 
             # Parse the selected locator from the response

SelfhealingAgents/self_healing_system/agents/orchestrator_agent/orchestrator_agent.py

@@ -78,7 +78,7 @@ async def run_async(
             PromptsOrchestrator.get_user_msg(robot_ctx_payload),
             deps=robot_ctx_payload,
             usage_limits=self._usage_limits,
-            model_settings={"temperature": 0.1, "parallel_tool_calls": False},
+            model_settings={"temperature": self._cfg.orchestrator_agent_temperature, "parallel_tool_calls": False},
         )
         self._catch_token_limit_exceedance(response.output)
         return response.output

SelfhealingAgents/utils/cfg.py

@@ -32,6 +32,9 @@ class Cfg(BaseSettings):
         "gpt-4o-mini", env="ORCHESTRATOR_AGENT_MODEL",
         description="Model selection for orchestrator agent."
     )
+    orchestrator_agent_temperature: float = Field(
+        0.1, gt=0, env="ORCHESTRATOR_AGENT_TEMPERATURE"
+    )
     locator_agent_provider: str = Field(
         "openai", env="LOCATOR_AGENT_PROVIDER",
         description="LLM Provider for Locator agent - Options: 'openai', 'azure'."
@@ -40,6 +43,9 @@ class Cfg(BaseSettings):
         "gpt-4o-mini", env="LOCATOR_AGENT_MODEL",
         description="Model selection for locator agent."
     )
+    locator_agent_temperature: float = Field(
+        0.1, gt=0, env="LOCATOR_AGENT_TEMPERATURE"
+    )
     request_limit: int = Field(
         5, env="REQUEST_LIMIT",
         description="Request limit for a each agent."

pyproject.toml

@@ -1,14 +1,14 @@
 [project]
 name = "robotframework-selfhealing-agents"
-version = "0.1.2"
+version = "0.1.3"
 description = ""
 authors = [
     { name = "viadee IT-Unternehmensberatung AG <[email protected]>" },
     { name = "Many Kasiriha <[email protected]>" },
 ]
 license = "Apache-2.0"
 readme = "README.md"
-requires-python = ">=3.12,<4.0"
+requires-python = ">=3.10,<4.0"
 dependencies = [
     "pydantic-ai-slim[logfire, openai, azure, litellm]",
     "robotframework >=7.1",

tests/utest/test_base_locator_agent.py

@@ -131,6 +131,8 @@ def __init__(self) -> None:
             self.use_llm_for_locator_generation: bool = True
             self.locator_agent_provider: str = "prov"
             self.locator_agent_model: str = "mod"
+            self.locator_agent_temperature: float = 0.1
+            self.orchestrator_agent_temperature: float = 0.1
 
     cfg_mod.Cfg = Cfg
     _force_module("SelfhealingAgents.utils", aid_utils)
@@ -332,6 +334,8 @@ class Cfg:
             use_llm_for_locator_generation: bool = use_llm
             locator_agent_provider: str = "prov"
             locator_agent_model: str = "mod"
+            locator_agent_temperature: float = 0.1
+            orchestrator_agent_temperature: float = 0.1
 
         return Impl(Cfg(), dom)
 
@@ -452,4 +456,4 @@ def test_sort_and_filter_helpers(mod_and_cls: Tuple[Any, Any, Any, Any]) -> None
     sorted_list = inst._sort_locators(["b", "a", "c"])
     assert sorted_list[:2] == ["a", "c"]
     filtered = inst._filter_clickable_locators(["a", "b", "c"])
-    assert filtered == ["a", "c"]
+    assert filtered == ["a", "c"]

tests/utest/test_orchestrator_agent.py

@@ -247,6 +247,7 @@ class FakeCfg:
         total_tokens_limit: int = 1000
         orchestrator_agent_provider: str = "prov"
         orchestrator_agent_model: str = "mod"
+        orchestrator_agent_temperature: float = 0.1
 
     orch = OrchestratorAgent(FakeCfg(), _FakeLocatorAgent(is_failed=False))
     payload = PromptPayload(
@@ -277,6 +278,7 @@ class FakeCfg:
         total_tokens_limit: int = 1000
         orchestrator_agent_provider: str = "prov"
         orchestrator_agent_model: str = "mod"
+        orchestrator_agent_temperature: float = 0.1
 
     orch = OrchestratorAgent(FakeCfg(), _FakeLocatorAgent(is_failed=True))
     payload = PromptPayload(
@@ -316,6 +318,7 @@ class FakeCfg:
         total_tokens_limit: int = 1000
         orchestrator_agent_provider: str = "prov"
         orchestrator_agent_model: str = "mod"
+        orchestrator_agent_temperature: float = 0.1
 
     orch = OrchestratorAgent(FakeCfg(), _FakeLocatorAgent(is_failed=True))
     payload = PromptPayload(
@@ -353,6 +356,7 @@ class FakeCfg:
         total_tokens_limit: int = 1000
         orchestrator_agent_provider: str = "prov"
         orchestrator_agent_model: str = "mod"
+        orchestrator_agent_temperature: float = 0.1
 
     orch = OrchestratorAgent(
         FakeCfg(),
@@ -373,6 +377,7 @@ class FakeCfg:
         total_tokens_limit: int = 1000
         orchestrator_agent_provider: str = "prov"
         orchestrator_agent_model: str = "mod"
+        orchestrator_agent_temperature: float = 0.1
 
     orch = OrchestratorAgent(
         FakeCfg(), _FakeLocatorAgent(is_failed=True, raise_on_heal=True)
@@ -390,4 +395,4 @@ def test_catch_token_limit_exceedance_logs(
     assert logger.infos == ["error: out of tokens"]
     logger.infos.clear()
     OrchestratorAgent._catch_token_limit_exceedance("ok")
-    assert logger.infos == []
+    assert logger.infos == []