Merge remote-tracking branch 'origin/main'

pr_agent/algo/__init__.py

@@ -52,4 +52,10 @@ MAX_TOKENS = {
     'groq/llama-3.1-70b-versatile': 131072,
     'groq/llama-3.1-405b-reasoning': 131072,
     'ollama/llama3': 4096,
+    'watsonx/meta-llama/llama-3-8b-instruct': 4096,
+    "watsonx/meta-llama/llama-3-70b-instruct": 4096,
+    "watsonx/meta-llama/llama-3-405b-instruct": 16384,
+    "watsonx/ibm/granite-13b-chat-v2": 8191,
+    "watsonx/ibm/granite-34b-code-instruct": 8191,
+    "watsonx/mistralai/mistral-large": 32768,
 }

pr_agent/algo/utils.py

@@ -557,7 +557,7 @@ def _fix_key_value(key: str, value: str):
 
 
 def load_yaml(response_text: str, keys_fix_yaml: List[str] = [], first_key="", last_key="") -> dict:
-    response_text = response_text.removeprefix('```yaml').rstrip('`')
+    response_text = response_text.strip('\n').removeprefix('```yaml').rstrip('`')
     try:
         data = yaml.safe_load(response_text)
     except Exception as e:
@@ -693,15 +693,25 @@ def get_user_labels(current_labels: List[str] = None):
 
 
 def get_max_tokens(model):
+    """
+    Get the maximum number of tokens allowed for a model.
+    logic:
+    (1) If the model is in './pr_agent/algo/__init__.py', use the value from there.
+    (2) else, the user needs to define explicitly 'config.custom_model_max_tokens'
+
+    For both cases, we further limit the number of tokens to 'config.max_model_tokens' if it is set.
+    This aims to improve the algorithmic quality, as the AI model degrades in performance when the input is too long.
+    """
     settings = get_settings()
     if model in MAX_TOKENS:
         max_tokens_model = MAX_TOKENS[model]
+    elif settings.config.custom_model_max_tokens > 0:
+        max_tokens_model = settings.config.custom_model_max_tokens
     else:
-        raise Exception(f"MAX_TOKENS must be set for model {model} in ./pr_agent/algo/__init__.py")
+        raise Exception(f"Ensure {model} is defined in MAX_TOKENS in ./pr_agent/algo/__init__.py or set a positive value for it in config.custom_model_max_tokens")
 
-    if settings.config.max_model_tokens:
+    if settings.config.max_model_tokens and settings.config.max_model_tokens > 0:
         max_tokens_model = min(settings.config.max_model_tokens, max_tokens_model)
-        # get_logger().debug(f"limiting max tokens to {max_tokens_model}")
     return max_tokens_model
 
 

pr_agent/settings/configuration.toml

@@ -18,6 +18,8 @@ ai_timeout=120 # 2minutes
 max_description_tokens = 500
 max_commits_tokens = 500
 max_model_tokens = 32000 # Limits the maximum number of tokens that can be used by any model, regardless of the model's default capabilities.
+custom_model_max_tokens=-1 # for models not in the default list
+#
 patch_extra_lines = 1
 secret_provider=""
 cli_mode=false
@@ -251,6 +253,11 @@ pr_commands = [
 # URL to the BitBucket Server instance
 # url = "https://git.bitbucket.com"
 url = ""
+pr_commands = [
+    "/describe",
+    "/review --pr_reviewer.num_code_suggestions=0",
+    "/improve --pr_code_suggestions.commitable_code_suggestions=true --pr_code_suggestions.suggestions_score_threshold=7",
+]
 
 [litellm]
 # use_client = false

pr_agent/tools/pr_code_suggestions.py

@@ -100,8 +100,8 @@ class PRCodeSuggestions:
                 data = {"code_suggestions": []}
 
             if data is None or 'code_suggestions' not in data or not data['code_suggestions']:
-                get_logger().error('No code suggestions found for PR.')
-                pr_body = "## PR Code Suggestions ✨\n\nNo code suggestions found for PR."
+                get_logger().error('No code suggestions found for the PR.')
+                pr_body = "## PR Code Suggestions ✨\n\nNo code suggestions found for the PR."
                 get_logger().debug(f"PR output", artifact=pr_body)
                 if self.progress_response:
                     self.git_provider.edit_comment(self.progress_response, body=pr_body)