Introduce to weak model

docs/docs/usage-guide/changing_a_model.md

@@ -5,7 +5,7 @@ To use a different model than the default (GPT-4), you need to edit in the [conf
 ```
 [config]
 model = "..."
-model_turbo = "..."
+model_weak = "..."
 fallback_models = ["..."]
 ```
 
@@ -28,7 +28,7 @@ and set in your configuration file:
 ```
 [config]
 model="" # the OpenAI model you've deployed on Azure (e.g. gpt-3.5-turbo)
-model_turbo="" # the OpenAI model you've deployed on Azure (e.g. gpt-3.5-turbo)
+model_weak="" # the OpenAI model you've deployed on Azure (e.g. gpt-3.5-turbo)
 fallback_models=["..."] # the OpenAI model you've deployed on Azure (e.g. gpt-3.5-turbo)
 ```
 
@@ -52,7 +52,7 @@ MAX_TOKENS={
 
 [config] # in configuration.toml
 model = "ollama/llama2"
-model_turbo = "ollama/llama2"
+model_weak = "ollama/llama2"
 fallback_models=["ollama/llama2"]
 
 [ollama] # in .secrets.toml
@@ -76,7 +76,7 @@ MAX_TOKENS={
 }
 [config] # in configuration.toml
 model = "huggingface/meta-llama/Llama-2-7b-chat-hf"
-model_turbo = "huggingface/meta-llama/Llama-2-7b-chat-hf"
+model_weak = "huggingface/meta-llama/Llama-2-7b-chat-hf"
 fallback_models=["huggingface/meta-llama/Llama-2-7b-chat-hf"]
 
 [huggingface] # in .secrets.toml
@@ -91,7 +91,7 @@ To use Llama2 model with Replicate, for example, set:
 ```
 [config] # in configuration.toml
 model = "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"
-model_turbo = "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"
+model_weak = "replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"
 fallback_models=["replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1"]
 [replicate] # in .secrets.toml
 key = ...
@@ -107,7 +107,7 @@ To use Llama3 model with Groq, for example, set:
 ```
 [config] # in configuration.toml
 model = "llama3-70b-8192"
-model_turbo = "llama3-70b-8192"
+model_weak = "llama3-70b-8192"
 fallback_models = ["groq/llama3-70b-8192"]
 [groq] # in .secrets.toml
 key = ... # your Groq api key
@@ -121,7 +121,7 @@ To use Google's Vertex AI platform and its associated models (chat-bison/codecha
 ```
 [config] # in configuration.toml
 model = "vertex_ai/codechat-bison"
-model_turbo = "vertex_ai/codechat-bison"
+model_weak = "vertex_ai/codechat-bison"
 fallback_models="vertex_ai/codechat-bison"
 
 [vertexai] # in .secrets.toml
@@ -140,7 +140,7 @@ To use [Google AI Studio](https://aistudio.google.com/) models, set the relevant
 ```toml
 [config] # in configuration.toml
 model="google_ai_studio/gemini-1.5-flash"
-model_turbo="google_ai_studio/gemini-1.5-flash"
+model_weak="google_ai_studio/gemini-1.5-flash"
 fallback_models=["google_ai_studio/gemini-1.5-flash"]
 
 [google_ai_studio] # in .secrets.toml
@@ -156,7 +156,7 @@ To use Anthropic models, set the relevant models in the configuration section of
 ```
 [config]
 model="anthropic/claude-3-opus-20240229"
-model_turbo="anthropic/claude-3-opus-20240229"
+model_weak="anthropic/claude-3-opus-20240229"
 fallback_models=["anthropic/claude-3-opus-20240229"]
 ```
 
@@ -173,7 +173,7 @@ To use Amazon Bedrock and its foundational models, add the below configuration:
 ```
 [config] # in configuration.toml
 model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
-model_turbo="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
+model_weak="bedrock/anthropic.claude-3-sonnet-20240229-v1:0"
 fallback_models=["bedrock/anthropic.claude-v2:1"]
 ```
 
@@ -195,7 +195,7 @@ If the relevant model doesn't appear [here](https://github.com/Codium-ai/pr-agen
 ```
 [config]
 model="custom_model_name"
-model_turbo="custom_model_name"
+model_weak="custom_model_name"
 fallback_models=["custom_model_name"]
 ```
 (2) Set the maximal tokens for the model:

pr_agent/algo/pr_processing.py

@@ -333,7 +333,7 @@ def generate_full_patch(convert_hunks_to_line_numbers, file_dict, max_tokens_mod
     return total_tokens, patches, remaining_files_list_new, files_in_patch_list
 
 
-async def retry_with_fallback_models(f: Callable, model_type: ModelType = ModelType.REGULAR):
+async def retry_with_fallback_models(f: Callable, model_type: ModelType = ModelType.WEAK):
     all_models = _get_all_models(model_type)
     all_deployments = _get_all_deployments(all_models)
     # try each (model, deployment_id) pair until one is successful, otherwise raise exception
@@ -354,8 +354,8 @@ async def retry_with_fallback_models(f: Callable, model_type: ModelType = ModelT
 
 
 def _get_all_models(model_type: ModelType = ModelType.REGULAR) -> List[str]:
-    if model_type == ModelType.TURBO:
-        model = get_settings().config.model_turbo
+    if get_settings().config.get('model_weak') and model_type == ModelType.WEAK:
+        model = get_settings().config.model_weak
     else:
         model = get_settings().config.model
     fallback_models = get_settings().config.fallback_models

pr_agent/algo/utils.py

@@ -35,8 +35,7 @@ class Range(BaseModel):
 
 class ModelType(str, Enum):
     REGULAR = "regular"
-    TURBO = "turbo"
-
+    WEAK = "weak"
 
 class PRReviewHeader(str, Enum):
     REGULAR = "## PR Reviewer Guide"

pr_agent/git_providers/utils.py

@@ -99,5 +99,5 @@ def set_claude_model():
     """
     model_claude = "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0"
     get_settings().set('config.model', model_claude)
-    get_settings().set('config.model_turbo', model_claude)
+    get_settings().set('config.model_weak', model_claude)
     get_settings().set('config.fallback_models', [model_claude])

pr_agent/settings/configuration.toml

@@ -1,7 +1,7 @@
 [config]
 # models
-model="gpt-4-turbo-2024-04-09"
-model_turbo="gpt-4o-2024-11-20"
+model_weak="gpt-4o-mini-2024-07-18"
+model="gpt-4o-2024-11-20"
 fallback_models=["gpt-4o-2024-08-06"]
 # CLI
 git_provider="github"

pr_agent/tools/pr_code_suggestions.py

@@ -111,9 +111,9 @@ async def run(self):
                     self.git_provider.publish_comment("Preparing suggestions...", is_temporary=True)
 
             if not self.is_extended:
-                data = await retry_with_fallback_models(self._prepare_prediction)
+                data = await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.REGULAR)
             else:
-                data = await retry_with_fallback_models(self._prepare_prediction_extended)
+                data = await retry_with_fallback_models(self._prepare_prediction_extended, model_type=ModelType.REGULAR)
             if not data:
                 data = {"code_suggestions": []}
 

pr_agent/tools/pr_description.py

@@ -99,7 +99,7 @@ async def run(self):
             # ticket extraction if exists
             await extract_and_cache_pr_tickets(self.git_provider, self.vars)
 
-            await retry_with_fallback_models(self._prepare_prediction, ModelType.TURBO)
+            await retry_with_fallback_models(self._prepare_prediction, ModelType.WEAK)
 
             if self.prediction:
                 self._prepare_data()

pr_agent/tools/pr_help_message.py

@@ -114,7 +114,7 @@ async def run(self):
                 self.vars['snippets'] = docs_prompt.strip()
 
                 # run the AI model
-                response = await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.REGULAR)
+                response = await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.WEAK)
                 response_yaml = load_yaml(response)
                 response_str = response_yaml.get('response')
                 relevant_sections = response_yaml.get('relevant_sections')

pr_agent/tools/pr_line_questions.py

@@ -79,7 +79,7 @@ async def run(self):
                                                                                                line_end=line_end,
                                                                                                side=side)
         if self.patch_with_lines:
-            response = await retry_with_fallback_models(self._get_prediction, model_type=ModelType.TURBO)
+            response = await retry_with_fallback_models(self._get_prediction, model_type=ModelType.WEAK)
 
             get_logger().info('Preparing answer...')
             if comment_id:

pr_agent/tools/pr_questions.py

@@ -63,7 +63,7 @@ async def run(self):
         if img_path:
             get_logger().debug(f"Image path identified", artifact=img_path)
 
-        await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.TURBO)
+        await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.WEAK)
 
         pr_comment = self._prepare_pr_answer()
         get_logger().debug(f"PR output", artifact=pr_comment)

pr_agent/tools/pr_reviewer.py

@@ -148,7 +148,7 @@ async def run(self) -> None:
             if get_settings().config.publish_output and not get_settings().config.get('is_auto_command', False):
                 self.git_provider.publish_comment("Preparing review...", is_temporary=True)
 
-            await retry_with_fallback_models(self._prepare_prediction)
+            await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.REGULAR)
             if not self.prediction:
                 self.git_provider.remove_initial_comment()
                 return None

pr_agent/tools/pr_update_changelog.py

@@ -73,7 +73,7 @@ async def run(self):
         if get_settings().config.publish_output:
             self.git_provider.publish_comment("Preparing changelog updates...", is_temporary=True)
 
-        await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.TURBO)
+        await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.WEAK)
 
         new_file_content, answer = self._prepare_changelog_update()