115 lines
4.5 KiB
Python
115 lines
4.5 KiB
Python
#!/usr/bin/env python3
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"""
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IX Forge — Community Fine-tuning Platform
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Part of the Inference-X Ecosystem
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# SALKA ELMADANI | inference-x.com | BSL-1.1
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Copyright (C) 2024-2026 Salka Elmadani. BSL-1.1.
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https://git.inference-x.com/inference-x-community/ix-forge
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Collective intelligence. Community-owned models.
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Contribute training data. Improve models. Share results.
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"""
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from fastapi import FastAPI, Request, UploadFile, File
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import JSONResponse
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import sqlite3, json, time, os, hashlib
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app = FastAPI(title="IX Forge", version="1.0.0")
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app.add_middleware(CORSMiddleware, allow_origins=["*"],
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allow_methods=["*"], allow_headers=["*"])
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DB = os.environ.get("FORGE_DB", "./forge.db")
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def db():
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conn = sqlite3.connect(DB); conn.row_factory = sqlite3.Row; return conn
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def init_db():
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with db() as c:
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c.execute("""CREATE TABLE IF NOT EXISTS contributions (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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type TEXT DEFAULT 'qa',
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language TEXT DEFAULT 'en',
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domain TEXT DEFAULT 'general',
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data TEXT,
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pairs_count INTEGER DEFAULT 0,
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contributor TEXT DEFAULT 'anonymous',
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created_at INTEGER,
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approved INTEGER DEFAULT 0
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)""")
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c.execute("""CREATE TABLE IF NOT EXISTS adapters (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT, base_model TEXT, description TEXT,
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download_url TEXT, score REAL DEFAULT 0,
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contributor TEXT DEFAULT 'anonymous',
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created_at INTEGER
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)""")
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c.commit()
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init_db()
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@app.post("/contribute")
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async def contribute(request: Request):
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"""Submit training data (Q&A pairs, documents)."""
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data = await request.json()
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pairs = data.get("pairs", [])
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if not pairs:
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return JSONResponse({"error":"No pairs provided"}, status_code=400)
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with db() as c:
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c.execute("""INSERT INTO contributions
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(type,language,domain,data,pairs_count,contributor,created_at)
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VALUES (?,?,?,?,?,?,?)""",
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(data.get("type","qa"), data.get("language","en"),
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data.get("domain","general"), json.dumps(pairs), len(pairs),
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data.get("contributor","anonymous"), int(time.time())))
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c.commit()
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return {"status":"ok","pairs_accepted":len(pairs),
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"message":"Thank you for contributing to the community."}
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@app.get("/datasets")
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async def datasets(domain: str = None, language: str = None):
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with db() as c:
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q = "SELECT id,type,language,domain,pairs_count,contributor,created_at FROM contributions WHERE approved=1"
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params = []
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if domain: q += " AND domain=?"; params.append(domain)
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if language: q += " AND language=?"; params.append(language)
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rows = c.execute(q, params).fetchall()
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return {"datasets":[dict(r) for r in rows],"total":len(rows)}
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@app.post("/submit-adapter")
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async def submit_adapter(request: Request):
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"""Submit a trained LoRA/QLoRA adapter."""
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data = await request.json()
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with db() as c:
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c.execute("""INSERT INTO adapters (name,base_model,description,download_url,contributor,created_at)
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VALUES (?,?,?,?,?,?)""",
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(data.get("name",""), data.get("base_model",""),
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data.get("description",""), data.get("download_url",""),
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data.get("contributor","anonymous"), int(time.time())))
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c.commit()
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return {"status":"ok","message":"Adapter submitted for community review."}
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@app.get("/adapters")
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async def adapters():
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with db() as c:
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rows = c.execute("SELECT id,name,base_model,description,score,contributor FROM adapters ORDER BY score DESC").fetchall()
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return {"adapters":[dict(r) for r in rows]}
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@app.get("/leaderboard")
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async def leaderboard():
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with db() as c:
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rows = c.execute("""SELECT contributor, COUNT(*) as contributions,
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SUM(pairs_count) as total_pairs
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FROM contributions WHERE approved=1
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GROUP BY contributor ORDER BY total_pairs DESC LIMIT 20""").fetchall()
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return {"leaderboard":[dict(r) for r in rows]}
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@app.get("/health")
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async def health():
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return {"status":"ok","service":"IX Forge","author":"Salka Elmadani"}
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if __name__ == "__main__":
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import uvicorn
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print("IX Forge — Community Fine-tuning Platform")
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print("Collective intelligence. Community-owned models.")
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uvicorn.run(app, host="0.0.0.0", port=int(os.environ.get("PORT","7937")))
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