feat(api): 🔌 build Enterprise-Ready RESTful FastAPI backend to allow external integration of the Epistemic Engine

Author: Arena AI Agent

Makefile

@@ -10,6 +10,7 @@ help:
 	@echo "  make lint       - Run Ruff to check code formatting and errors"
 	@echo "  make clean      - Remove __pycache__, .pytest_cache, and build files"
 	@echo "  make cli        - Test the CLI interface directly"
+	@echo "  make serve      - Launch the RESTful FastAPI backend server"
 
 install:
 	@echo "Installing Epistemic Forge..."
@@ -32,3 +33,7 @@ clean:
 cli:
 	@echo "Running CLI test query..."
 	epistemic-forge --query "Is RAG strictly better than Long-Context LLMs?"
+
+serve:
+	@echo "Booting Enterprise API Server..."
+	uvicorn epistemic_forge.ui.api:app --host 0.0.0.0 --port 8000 --reload

epistemic_forge/ui/api.py

@@ -0,0 +1,79 @@
+"""FastAPI Backend for Epistemic Forge.
+
+Provides a RESTful Enterprise-Ready API to integrate the Neuro-Symbolic 
+engine into any larger MLOps or business workflow.
+"""
+from fastapi import FastAPI, HTTPException, BackgroundTasks
+from pydantic import BaseModel
+from typing import List, Optional, Dict, Any
+from epistemic_forge.models import ProjectSpec
+from epistemic_forge.pipeline.arsenal_run import run_pipeline
+
+app = FastAPI(
+    title="Epistemic Forge API",
+    description="Neuro-Symbolic State Machine API for Deterministic Reasoning.",
+    version="1.0.0-rc1"
+)
+
+class ForgeRequest(BaseModel):
+    title: str
+    question: str
+    domain: str = "hybrid"
+    target_model: str = "openai/gpt-4o-mini"
+    keywords: List[str] = []
+    api_key: Optional[str] = None
+    api_base: Optional[str] = None
+    budget_tokens: int = 15000
+
+class ForgeResponse(BaseModel):
+    status: str
+    score: float
+    claims: List[Dict[str, Any]]
+    final_memo: str
+    peer_review: Dict[str, Any]
+
+@app.post("/api/v1/forge", response_model=ForgeResponse)
+async def generate_claim_lattice(req: ForgeRequest):
+    """Executes the full L0-L6 pipeline and returns a structured lattice and synthesis."""
+    try:
+        spec = ProjectSpec(
+            title=req.title,
+            question=req.question,
+            domain=req.domain,
+            target_model=req.target_model,
+            keywords=req.keywords,
+            api_key=req.api_key,
+            api_base=req.api_base,
+            budget_tokens=req.budget_tokens
+        )
+        
+        result = run_pipeline(
+            title=spec.title,
+            question=spec.question,
+            domain=spec.domain.value
+        )
+        
+        final_memo = ""
+        for art in getattr(result, "artifacts", []):
+            if art.name == "Final Synthesis Memo":
+                final_memo = art.content
+                break
+                
+        # Handle claims safely
+        raw_claims = getattr(result, "claims", [])
+        claims_list = [c.model_dump() if hasattr(c, "model_dump") else c for c in raw_claims]
+                
+        return ForgeResponse(
+            status="success",
+            score=getattr(result, "final_score", 0.0),
+            claims=claims_list,
+            final_memo=final_memo,
+            peer_review=getattr(result, "peer_review", {})
+        )
+        
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/health")
+async def health_check():
+    return {"status": "operational", "engine": "neuro-symbolic-v1"}

pyproject.toml

@@ -31,7 +31,7 @@ classifiers = [
   "Topic :: Scientific/Engineering :: Artificial Intelligence",
   "Topic :: Text Processing :: Linguistic",
 ]
-dependencies = ["litellm>=1.40.0", "duckduckgo-search>=5.0.0", "chromadb>=0.4.0", "nbformat>=5.0.0", "pydantic>=2.0.0", "loguru>=0.7.0", "tenacity>=8.0.0", "instructor>=1.3.0", "rich>=13.0.0", "streamlit>=1.35.0"]
+dependencies = ["litellm>=1.40.0", "duckduckgo-search>=5.0.0", "chromadb>=0.4.0", "nbformat>=5.0.0", "fastapi>=0.100.0", "uvicorn>=0.20.0", "pydantic>=2.0.0", "loguru>=0.7.0", "tenacity>=8.0.0", "instructor>=1.3.0", "rich>=13.0.0", "streamlit>=1.35.0"]
 
 [project.optional-dependencies]
 dev = ["pytest>=7.0", "pytest-mock"]