feat: Phase 7 - Multi-Model Agent System (v0.7.0)

- Model Registry: 5 Gemini models (3.1 Pro, 3 Pro, 3 Flash, 3.1 Flash Lite, 2.5 Flash) with capability scores, costs, context windows
- Smart Task Router: 3 strategies (performance/balanced/economy), complexity-aware routing, fallback chains
- Multi-Agent: 5 specialized agents (Analyzer, CodeGen, Reviewer, DocsWriter, Planner) with AgentCoordinator pipeline
- Env var fallback: GitHub token from GITHUB_TOKEN/gh CLI, LLM keys from GEMINI/OPENAI/ANTHROPIC_API_KEY
- Vertex AI: Google Cloud support via vertex_project + vertex_location in config
- CLI: contribai models command to list models and task assignments
- MultiModelConfig with strategy and per-task model overrides
- Tests: 35 new (total: 286), fixed StrEnum lint

Author: tang-vu

contribai/__init__.py

@@ -1,4 +1,4 @@
 """ContribAI - AI Agent for Open Source Contributions."""
 
-__version__ = "0.6.0"
+__version__ = "0.7.0"
 __app_name__ = "contribai"

contribai/cli/main.py

@@ -88,7 +88,7 @@ def run(ctx, language, stars, max_prs, dry_run):
         console.print("Set it in config.yaml or run: contribai config set github.token <token>")
         sys.exit(1)
 
-    if not config.llm.api_key:
+    if not config.llm.api_key and not config.llm.use_vertex:
         console.print("[red]❌ LLM API key not configured![/red]")
         sys.exit(1)
 
@@ -126,7 +126,7 @@ def target(ctx, url, types, dry_run):
         console.print("[red]❌ GitHub token not configured![/red]")
         sys.exit(1)
 
-    if not config.llm.api_key:
+    if not config.llm.api_key and not config.llm.use_vertex:
         console.print("[red]❌ LLM API key not configured![/red]")
         sys.exit(1)
 
@@ -154,7 +154,7 @@ def analyze(ctx, url):
         console.print("[red]❌ GitHub token not configured![/red]")
         sys.exit(1)
 
-    if not config.llm.api_key:
+    if not config.llm.api_key and not config.llm.use_vertex:
         console.print("[red]❌ LLM API key not configured![/red]")
         sys.exit(1)
 
@@ -222,7 +222,7 @@ def solve(ctx, url, max_issues, dry_run):
         console.print("[red]❌ GitHub token not configured![/red]")
         sys.exit(1)
 
-    if not config.llm.api_key:
+    if not config.llm.api_key and not config.llm.use_vertex:
         console.print("[red]❌ LLM API key not configured![/red]")
         sys.exit(1)
 
@@ -574,6 +574,70 @@ def _print_result(result, dry_run: bool):
             console.print(f"  • {e}")
 
 
+@cli.command("models")
+@click.option("--task", default=None, help="Filter by task type")
+@click.pass_context
+def show_models(ctx, task):
+    """List available models and their capabilities."""
+    from contribai.llm.models import (
+        ALL_MODELS,
+        TaskType,
+        get_models_for_task,
+    )
+    from contribai.llm.router import TaskRouter
+
+    if task:
+        try:
+            tt = TaskType(task)
+        except ValueError:
+            console.print(
+                f"[red]Unknown task type: {task}[/red]\n"
+                f"Valid: {', '.join(t.value for t in TaskType)}"
+            )
+            return
+        models = get_models_for_task(tt)
+        console.print(f"\n[bold]Best models for [cyan]{task}[/cyan]:[/bold]\n")
+    else:
+        models = ALL_MODELS
+        console.print("\n[bold]Available Models:[/bold]\n")
+
+    table = Table()
+    table.add_column("Model", style="cyan")
+    table.add_column("Tier")
+    table.add_column("Code", justify="right")
+    table.add_column("Analysis", justify="right")
+    table.add_column("Speed", justify="right")
+    table.add_column("Cost (in/out)")
+    table.add_column("Best For")
+
+    for m in models:
+        tier_color = {
+            "pro": "red",
+            "flash": "yellow",
+            "lite": "green",
+        }.get(m.tier.value, "white")
+
+        table.add_row(
+            m.display_name,
+            f"[{tier_color}]{m.tier.value.upper()}[/{tier_color}]",
+            str(m.coding),
+            str(m.analysis),
+            str(m.speed),
+            f"${m.input_cost:.2f}/${m.output_cost:.2f}",
+            ", ".join(t.value for t in m.best_for[:3]),
+        )
+
+    console.print(table)
+
+    # Show default assignments
+    router = TaskRouter()
+    defaults = router.get_default_assignments()
+    console.print("\n[bold]Default Task Assignments:[/bold]")
+    for task_type, model_name in defaults.items():
+        console.print(f"  {task_type}: [cyan]{model_name}[/cyan]")
+    console.print()
+
+
 @cli.command("interactive")
 @click.pass_context
 def interactive(ctx):

contribai/core/config.py

@@ -52,7 +52,7 @@ class LLMConfig(BaseModel):
     base_url: str | None = None  # for ollama or custom endpoints
     # Vertex AI (Google Cloud)
     vertex_project: str = ""
-    vertex_location: str = "us-central1"
+    vertex_location: str = "global"
 
     @model_validator(mode="after")
     def resolve_api_key_and_defaults(self):
@@ -185,8 +185,17 @@ class NotificationConfig(BaseModel):
     on_run_complete: bool = True
 
 
+class MultiModelConfig(BaseModel):
+    """Multi-model routing configuration."""
+
+    enabled: bool = False
+    strategy: str = "balanced"  # performance | balanced | economy
+    # Per-task model overrides (task_type → model_name)
+    model_overrides: dict[str, str] = Field(default_factory=dict)
+
+
 class ContribAIConfig(BaseModel):
-    """Root configuration for ContribAI."""
+    """Root configuration for ContribAIConfig."""
 
     github: GitHubConfig = Field(default_factory=GitHubConfig)
     llm: LLMConfig = Field(default_factory=LLMConfig)
@@ -199,6 +208,7 @@ class ContribAIConfig(BaseModel):
     pipeline: PipelineConfig = Field(default_factory=PipelineConfig)
     quota: QuotaConfig = Field(default_factory=QuotaConfig)
     notifications: NotificationConfig = Field(default_factory=NotificationConfig)
+    multi_model: MultiModelConfig = Field(default_factory=MultiModelConfig)
 
 
 def load_config(path: str | Path | None = None) -> ContribAIConfig: