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feat: route AI model selection through action-type config

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Update get_ai_provider() to accept an optional model override parameter
(applied only to AnthropicProvider; Gemini always uses its own model).
Thread action_type-based model resolution through send_message() and
generate_final_tree() in the AI chat service.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
chihlasm
2026-03-06 23:24:55 -05:00
parent 41b7cd86b8
commit d1d21152d7
2 changed files with 11 additions and 5 deletions
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6
backend/app/core/ai_chat_service.py
View File

@@ -465,7 +465,9 @@ async def send_message(
for msg in history for msg in history
] ]
provider = get_ai_provider() # Resolve model for this action type
action_model = settings.get_model_for_action(action_type)
provider = get_ai_provider(model=action_model)
response_text, input_tokens, output_tokens = await provider.generate_text( response_text, input_tokens, output_tokens = await provider.generate_text(
system_prompt=system_prompt, system_prompt=system_prompt,
messages=provider_messages, messages=provider_messages,
@@ -584,7 +586,7 @@ Also provide metadata as a separate JSON object after the tree:
provider_messages.append({"role": "user", "content": generation_instruction}) provider_messages.append({"role": "user", "content": generation_instruction})
provider = get_ai_provider() provider = get_ai_provider(model=settings.get_model_for_action("generate_full"))
for attempt in range(2): # One try + one retry for attempt in range(2): # One try + one retry
response_text, input_tokens, output_tokens = await provider.generate_text( response_text, input_tokens, output_tokens = await provider.generate_text(

10
backend/app/core/ai_provider.py
View File

@@ -209,9 +209,13 @@ class AnthropicProvider(AIProvider):
return await self.generate_json(system_prompt, messages, max_tokens) return await self.generate_json(system_prompt, messages, max_tokens)
def get_ai_provider() -> AIProvider: def get_ai_provider(model: str | None = None) -> AIProvider:
"""Factory that returns the configured AI provider. """Factory that returns the configured AI provider.
Args:
model: Optional model override (Anthropic model ID). Only applied to
AnthropicProvider; Gemini always uses settings.AI_MODEL_GEMINI.
Selection logic: Selection logic:
1. If AI_PROVIDER == "gemini" and GOOGLE_AI_API_KEY is set -> GeminiProvider 1. If AI_PROVIDER == "gemini" and GOOGLE_AI_API_KEY is set -> GeminiProvider
2. If AI_PROVIDER == "anthropic" and ANTHROPIC_API_KEY is set -> AnthropicProvider 2. If AI_PROVIDER == "anthropic" and ANTHROPIC_API_KEY is set -> AnthropicProvider
@@ -230,7 +234,7 @@ def get_ai_provider() -> AIProvider:
if settings.ANTHROPIC_API_KEY: if settings.ANTHROPIC_API_KEY:
return AnthropicProvider( return AnthropicProvider(
api_key=settings.ANTHROPIC_API_KEY, api_key=settings.ANTHROPIC_API_KEY,
model=settings.AI_MODEL_ANTHROPIC, model=model or settings.AI_MODEL_ANTHROPIC,
timeout=settings.AI_REQUEST_TIMEOUT_SECONDS, timeout=settings.AI_REQUEST_TIMEOUT_SECONDS,
) )
@@ -238,7 +242,7 @@ def get_ai_provider() -> AIProvider:
if settings.ANTHROPIC_API_KEY: if settings.ANTHROPIC_API_KEY:
return AnthropicProvider( return AnthropicProvider(
api_key=settings.ANTHROPIC_API_KEY, api_key=settings.ANTHROPIC_API_KEY,
model=settings.AI_MODEL_ANTHROPIC, model=model or settings.AI_MODEL_ANTHROPIC,
timeout=settings.AI_REQUEST_TIMEOUT_SECONDS, timeout=settings.AI_REQUEST_TIMEOUT_SECONDS,
) )
# Fallback to Gemini # Fallback to Gemini