Add DocGen tool with comprehensive documentation generation capabilities (#109)

* WIP: new workflow architecture

* WIP: further improvements and cleanup

* WIP: cleanup and docks, replace old tool with new

* WIP: cleanup and docks, replace old tool with new

* WIP: new planner implementation using workflow

* WIP: precommit tool working as a workflow instead of a basic tool
Support for passing False to use_assistant_model to skip external models completely and use Claude only

* WIP: precommit workflow version swapped with old

* WIP: codereview

* WIP: replaced codereview

* WIP: replaced codereview

* WIP: replaced refactor

* WIP: workflow for thinkdeep

* WIP: ensure files get embedded correctly

* WIP: thinkdeep replaced with workflow version

* WIP: improved messaging when an external model's response is received

* WIP: analyze tool swapped

* WIP: updated tests
* Extract only the content when building history
* Use "relevant_files" for workflow tools only

* WIP: updated tests
* Extract only the content when building history
* Use "relevant_files" for workflow tools only

* WIP: fixed get_completion_next_steps_message missing param

* Fixed tests
Request for files consistently

* Fixed tests
Request for files consistently

* Fixed tests

* New testgen workflow tool
Updated docs

* Swap testgen workflow

* Fix CI test failures by excluding API-dependent tests

- Update GitHub Actions workflow to exclude simulation tests that require API keys
- Fix collaboration tests to properly mock workflow tool expert analysis calls
- Update test assertions to handle new workflow tool response format
- Ensure unit tests run without external API dependencies in CI

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* WIP - Update tests to match new tools

* WIP - Update tests to match new tools

* WIP - Update tests to match new tools

* Should help with https://github.com/BeehiveInnovations/zen-mcp-server/issues/97
Clear python cache when running script: https://github.com/BeehiveInnovations/zen-mcp-server/issues/96
Improved retry error logging
Cleanup

* WIP - chat tool using new architecture and improved code sharing

* Removed todo

* Removed todo

* Cleanup old name

* Tweak wordings

* Tweak wordings
Migrate old tests

* Support for Flash 2.0 and Flash Lite 2.0

* Support for Flash 2.0 and Flash Lite 2.0

* Support for Flash 2.0 and Flash Lite 2.0
Fixed test

* Improved consensus to use the workflow base class

* Improved consensus to use the workflow base class

* Allow images

* Allow images

* Replaced old consensus tool

* Cleanup tests

* Tests for prompt size

* New tool: docgen
Tests for prompt size
Fixes: https://github.com/BeehiveInnovations/zen-mcp-server/issues/107
Use available token size limits: https://github.com/BeehiveInnovations/zen-mcp-server/issues/105

* Improved docgen prompt
Exclude TestGen from pytest inclusion

* Updated errors

* Lint

* DocGen instructed not to fix bugs, surface them and stick to d

* WIP

* Stop claude from being lazy and only documenting a small handful

* More style rules

---------

Co-authored-by: Claude <noreply@anthropic.com>

providers/openai_compatible.py

@@ -409,8 +409,13 @@ class OpenAICompatibleProvider(ModelProvider):
         if not self.validate_model_name(model_name):
             raise ValueError(f"Model '{model_name}' not in allowed models list. Allowed models: {self.allowed_models}")
 
-        # Validate parameters
-        self.validate_parameters(model_name, temperature)
+        # Get effective temperature for this model
+        effective_temperature = self.get_effective_temperature(model_name, temperature)
+
+        # Only validate if temperature is not None (meaning the model supports it)
+        if effective_temperature is not None:
+            # Validate parameters with the effective temperature
+            self.validate_parameters(model_name, effective_temperature)
 
         # Prepare messages
         messages = []
@@ -452,20 +457,13 @@ class OpenAICompatibleProvider(ModelProvider):
         # Check model capabilities once to determine parameter support
         resolved_model = self._resolve_model_name(model_name)
 
-        # Get model capabilities once to avoid duplicate calls
-        try:
-            capabilities = self.get_capabilities(model_name)
-            # Defensive check for supports_temperature field (backward compatibility)
-            supports_temperature = getattr(capabilities, "supports_temperature", True)
-        except Exception as e:
-            # If capability check fails, fall back to conservative behavior
-            # Default to including temperature for most models (backward compatibility)
-            logging.debug(f"Failed to check temperature support for {model_name}: {e}")
+        # Use the effective temperature we calculated earlier
+        if effective_temperature is not None:
+            completion_params["temperature"] = effective_temperature
             supports_temperature = True
-
-        # Add temperature parameter if supported
-        if supports_temperature:
-            completion_params["temperature"] = temperature
+        else:
+            # Model doesn't support temperature
+            supports_temperature = False
 
         # Add max tokens if specified and model supports it
         # O3/O4 models that don't support temperature also don't support max_tokens