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BeamBridge

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Publish BeamBridge v2 Platform + Full Python Source & Empirical Ledger

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"""
BeamBridge Live Beam-1.0-501B-A23B Multi-Provider Client & Sovereign FinOps Router.
Supports:
  1. OpenRouter (`https://openrouter.ai/api/v1` — `reflection/beam-1.0-501b-a23b` + automatic FinOps Failover)
  2. Reflection AI Official API (`https://api.reflection.ai/v1` — `Beam-1.0-501B-A23B`)
  3. Hugging Face Inference Router (`https://router.huggingface.co/v1` — `reflection/Beam-1.0-501B-A23B`)
  4. Sovereign On-Prem vLLM / SGLang (`--reasoning-parser beam`)
When invoked without an API key, replays the genuine cryptographically audited OpenRouter `gen-...`
execution record and real synthesized `MCPServer` code from `runs/verifiable_empirical_ledger.json`.
"""
from __future__ import annotations
import os
import time
from pathlib import Path
from typing import Any

import httpx

from backend.ast_analyzer import pack_whole_repository_prompt
from backend.parity_verifier import get_empirical_ledger
from backend.real_oracles import exact_beam_token_count

BASE_DIR = Path(__file__).resolve().parent.parent

PROVIDER_DEFAULTS: dict[str, tuple[str, str]] = {
    "openrouter": ("https://openrouter.ai/api/v1", "reflection/beam-1.0-501b-a23b"),
    "reflection": ("https://api.reflection.ai/v1", "Beam-1.0-501B-A23B"),
    "huggingface": ("https://router.huggingface.co/v1", "reflection/Beam-1.0-501B-A23B"),
    "vllm_local": ("http://127.0.0.1:8000/v1", "reflection/Beam-1.0-501B-A23B"),
}


async def synthesize_with_beam(
    repo_id: str,
    api_key: str | None = None,
    provider: str = "openrouter",
    custom_base_url: str | None = None,
    reasoning_effort: str = "medium",
    preserve_thinking: bool = True,
    user_directive: str | None = None,
) -> dict[str, Any]:
    resolved_key = (
        (api_key or "").strip()
        or os.getenv("OPENROUTER_API_KEY", "").strip()
        or os.getenv("REFLECTION_API_KEY", "").strip()
        or os.getenv("HF_TOKEN", "").strip()
    )

    packed_repo = pack_whole_repository_prompt(repo_id)
    mcp_source_path = BASE_DIR / "modernized_mcp" / f"{repo_id}_mcp.py"
    verified_mcp_code = mcp_source_path.read_text(encoding="utf-8") if mcp_source_path.exists() else ""

    if not resolved_key and provider != "vllm_local":
        ledger = get_empirical_ledger()
        repo_rec = ledger["repositories"][repo_id]
        wr = repo_rec["whole_repo_1m"]
        last_turn = wr["turns"][-1]
        all_req_ids = [t["request_id"] for t in wr["turns"]]
        combined_reasoning = "\n\n---\n\n".join(
            f"[Turn {t['turn']} · {t['model']} · {t['request_id']} · {t['passed']}/{t['total']} ({t['pass_rate_pct']}%)]\n{t['reasoning_excerpt']}"
            for t in wr["turns"]
            if t.get("reasoning_excerpt")
        )
        return {
            "mode": "recorded_verifiable_openrouter_run",
            "provider": last_turn.get("provider", "OpenRouter"),
            "model": last_turn["model"],
            "request_ids": all_req_ids,
            "reasoning_effort": reasoning_effort,
            "preserve_thinking": preserve_thinking,
            "latency_ms": wr["total_latency_ms"],
            "usage": {
                "prompt_tokens": wr["total_prompt_tokens"],
                "completion_tokens": wr["total_completion_tokens"],
                "reasoning_tokens": wr["total_reasoning_tokens"],
                "total_tokens": wr["total_prompt_tokens"] + wr["total_completion_tokens"],
                "cost_usd": wr["total_cost_usd"],
            },
            "turns_executed": len(wr["turns"]),
            "verified_parity": f"{wr['final_passed']}/{wr['final_total']} ({wr['final_pass_rate_pct']}%)",
            "reasoning_content": combined_reasoning or "Verified multi-turn synthesis trace recorded in empirical ledger.",
            "synthesized_code": verified_mcp_code,
        }

    base_url, model_name = PROVIDER_DEFAULTS.get(provider, PROVIDER_DEFAULTS["openrouter"])
    if custom_base_url:
        base_url = custom_base_url.rstrip("/")

    directive = user_directive or (
        "Synthesize a standalone Anthropic MCP v2 server (`from mcp.server.mcpserver import MCPServer`) "
        "preserving exact Decimal quantization, check-digit tables, and structured dict schemas."
    )

    payload: dict[str, Any] = {
        "model": model_name,
        "messages": [
            {
                "role": "system",
                "content": (
                    "You are BeamBridge, powered by Reflection AI's Beam-1.0-501B-A23B (501B total, 23B active MoE, "
                    "1,048,576 context window). Analyze the full repository context and synthesize a standalone "
                    "Python MCP v2 module (`from mcp.server.mcpserver import MCPServer`) with zero legacy imports."
                ),
            },
            {
                "role": "user",
                "content": f"{directive}\n\n{packed_repo}",
            },
        ],
        "temperature": 0.15,
        "max_tokens": 4096,
    }

    if provider == "openrouter":
        payload["reasoning"] = {"effort": reasoning_effort if reasoning_effort in ("minimal", "low", "medium", "high") else "low"}
    else:
        payload["reasoning_effort"] = reasoning_effort
        payload["chat_template_kwargs"] = {
            "reasoning_effort": reasoning_effort,
            "preserve_thinking": preserve_thinking,
        }

    headers = {"Content-Type": "application/json"}
    if resolved_key:
        headers["Authorization"] = f"Bearer {resolved_key}"
    if provider == "openrouter":
        headers["HTTP-Referer"] = "https://huggingface.co/spaces/BeamBridge"
        headers["X-Title"] = "BeamBridge-Enterprise-MCP"

    t0 = time.perf_counter()
    async with httpx.AsyncClient(timeout=180.0) as client:
        resp = await client.post(f"{base_url}/chat/completions", headers=headers, json=payload)
        if resp.status_code == 402 and provider == "openrouter":
            payload["model"] = "nvidia/nemotron-3-ultra-550b-a55b:free"
            payload.pop("reasoning", None)
            payload["max_tokens"] = 8192
            resp = await client.post(f"{base_url}/chat/completions", headers=headers, json=payload)
    latency_ms = round((time.perf_counter() - t0) * 1000.0, 1)

    if resp.status_code >= 400:
        return {
            "mode": "live_api_error",
            "status_code": resp.status_code,
            "error": resp.text[:600],
            "provider": provider,
            "model": payload["model"],
        }

    body = resp.json()
    choice = (body.get("choices") or [{}])[0]
    msg = choice.get("message") or {}
    usage = body.get("usage") or {}
    comp_details = usage.get("completion_tokens_details") or {}
    content = msg.get("content") or ""
    reasoning_text = msg.get("reasoning") or msg.get("reasoning_content") or ""

    return {
        "mode": "live_beam_api",
        "provider": body.get("provider", provider),
        "model": body.get("model", payload["model"]),
        "request_ids": [body.get("id")],
        "reasoning_effort": reasoning_effort,
        "preserve_thinking": preserve_thinking,
        "latency_ms": latency_ms,
        "usage": {
            "prompt_tokens": usage.get("prompt_tokens", exact_beam_token_count(packed_repo)),
            "completion_tokens": usage.get("completion_tokens", exact_beam_token_count(content)),
            "reasoning_tokens": comp_details.get("reasoning_tokens", exact_beam_token_count(reasoning_text)),
            "total_tokens": usage.get("total_tokens", 0),
            "cost_usd": usage.get("cost", 0.0),
        },
        "reasoning_content": reasoning_text,
        "synthesized_code": content,
    }

	"""
	BeamBridge Live Beam-1.0-501B-A23B Multi-Provider Client & Sovereign FinOps Router.
	Supports:
	1. OpenRouter (`https://openrouter.ai/api/v1` — `reflection/beam-1.0-501b-a23b` + automatic FinOps Failover)
	2. Reflection AI Official API (`https://api.reflection.ai/v1` — `Beam-1.0-501B-A23B`)
	3. Hugging Face Inference Router (`https://router.huggingface.co/v1` — `reflection/Beam-1.0-501B-A23B`)
	4. Sovereign On-Prem vLLM / SGLang (`--reasoning-parser beam`)
	When invoked without an API key, replays the genuine cryptographically audited OpenRouter `gen-...`
	execution record and real synthesized `MCPServer` code from `runs/verifiable_empirical_ledger.json`.
	"""
	from __future__ import annotations
	import os
	import time
	from pathlib import Path
	from typing import Any

	import httpx

	from backend.ast_analyzer import pack_whole_repository_prompt
	from backend.parity_verifier import get_empirical_ledger
	from backend.real_oracles import exact_beam_token_count

	BASE_DIR = Path(__file__).resolve().parent.parent

	PROVIDER_DEFAULTS: dict[str, tuple[str, str]] = {
	"openrouter": ("https://openrouter.ai/api/v1", "reflection/beam-1.0-501b-a23b"),
	"reflection": ("https://api.reflection.ai/v1", "Beam-1.0-501B-A23B"),
	"huggingface": ("https://router.huggingface.co/v1", "reflection/Beam-1.0-501B-A23B"),
	"vllm_local": ("http://127.0.0.1:8000/v1", "reflection/Beam-1.0-501B-A23B"),
	}


	async def synthesize_with_beam(
	repo_id: str,
	api_key: str \| None = None,
	provider: str = "openrouter",
	custom_base_url: str \| None = None,
	reasoning_effort: str = "medium",
	preserve_thinking: bool = True,
	user_directive: str \| None = None,
	) -> dict[str, Any]:
	resolved_key = (
	(api_key or "").strip()
	or os.getenv("OPENROUTER_API_KEY", "").strip()
	or os.getenv("REFLECTION_API_KEY", "").strip()
	or os.getenv("HF_TOKEN", "").strip()
	)

	packed_repo = pack_whole_repository_prompt(repo_id)
	mcp_source_path = BASE_DIR / "modernized_mcp" / f"{repo_id}_mcp.py"
	verified_mcp_code = mcp_source_path.read_text(encoding="utf-8") if mcp_source_path.exists() else ""

	if not resolved_key and provider != "vllm_local":
	ledger = get_empirical_ledger()
	repo_rec = ledger["repositories"][repo_id]
	wr = repo_rec["whole_repo_1m"]
	last_turn = wr["turns"][-1]
	all_req_ids = [t["request_id"] for t in wr["turns"]]
	combined_reasoning = "\n\n---\n\n".join(
	f"[Turn {t['turn']} · {t['model']} · {t['request_id']} · {t['passed']}/{t['total']} ({t['pass_rate_pct']}%)]\n{t['reasoning_excerpt']}"
	for t in wr["turns"]
	if t.get("reasoning_excerpt")
	)
	return {
	"mode": "recorded_verifiable_openrouter_run",
	"provider": last_turn.get("provider", "OpenRouter"),
	"model": last_turn["model"],
	"request_ids": all_req_ids,
	"reasoning_effort": reasoning_effort,
	"preserve_thinking": preserve_thinking,
	"latency_ms": wr["total_latency_ms"],
	"usage": {
	"prompt_tokens": wr["total_prompt_tokens"],
	"completion_tokens": wr["total_completion_tokens"],
	"reasoning_tokens": wr["total_reasoning_tokens"],
	"total_tokens": wr["total_prompt_tokens"] + wr["total_completion_tokens"],
	"cost_usd": wr["total_cost_usd"],
	},
	"turns_executed": len(wr["turns"]),
	"verified_parity": f"{wr['final_passed']}/{wr['final_total']} ({wr['final_pass_rate_pct']}%)",
	"reasoning_content": combined_reasoning or "Verified multi-turn synthesis trace recorded in empirical ledger.",
	"synthesized_code": verified_mcp_code,
	}

	base_url, model_name = PROVIDER_DEFAULTS.get(provider, PROVIDER_DEFAULTS["openrouter"])
	if custom_base_url:
	base_url = custom_base_url.rstrip("/")

	directive = user_directive or (
	"Synthesize a standalone Anthropic MCP v2 server (`from mcp.server.mcpserver import MCPServer`) "
	"preserving exact Decimal quantization, check-digit tables, and structured dict schemas."
	)

	payload: dict[str, Any] = {
	"model": model_name,
	"messages": [
	{
	"role": "system",
	"content": (
	"You are BeamBridge, powered by Reflection AI's Beam-1.0-501B-A23B (501B total, 23B active MoE, "
	"1,048,576 context window). Analyze the full repository context and synthesize a standalone "
	"Python MCP v2 module (`from mcp.server.mcpserver import MCPServer`) with zero legacy imports."
	),
	},
	{
	"role": "user",
	"content": f"{directive}\n\n{packed_repo}",
	},
	],
	"temperature": 0.15,
	"max_tokens": 4096,
	}

	if provider == "openrouter":
	payload["reasoning"] = {"effort": reasoning_effort if reasoning_effort in ("minimal", "low", "medium", "high") else "low"}
	else:
	payload["reasoning_effort"] = reasoning_effort
	payload["chat_template_kwargs"] = {
	"reasoning_effort": reasoning_effort,
	"preserve_thinking": preserve_thinking,
	}

	headers = {"Content-Type": "application/json"}
	if resolved_key:
	headers["Authorization"] = f"Bearer {resolved_key}"
	if provider == "openrouter":
	headers["HTTP-Referer"] = "https://huggingface.co/spaces/BeamBridge"
	headers["X-Title"] = "BeamBridge-Enterprise-MCP"

	t0 = time.perf_counter()
	async with httpx.AsyncClient(timeout=180.0) as client:
	resp = await client.post(f"{base_url}/chat/completions", headers=headers, json=payload)
	if resp.status_code == 402 and provider == "openrouter":
	payload["model"] = "nvidia/nemotron-3-ultra-550b-a55b:free"
	payload.pop("reasoning", None)
	payload["max_tokens"] = 8192
	resp = await client.post(f"{base_url}/chat/completions", headers=headers, json=payload)
	latency_ms = round((time.perf_counter() - t0) * 1000.0, 1)

	if resp.status_code >= 400:
	return {
	"mode": "live_api_error",
	"status_code": resp.status_code,
	"error": resp.text[:600],
	"provider": provider,
	"model": payload["model"],
	}

	body = resp.json()
	choice = (body.get("choices") or [{}])[0]
	msg = choice.get("message") or {}
	usage = body.get("usage") or {}
	comp_details = usage.get("completion_tokens_details") or {}
	content = msg.get("content") or ""
	reasoning_text = msg.get("reasoning") or msg.get("reasoning_content") or ""

	return {
	"mode": "live_beam_api",
	"provider": body.get("provider", provider),
	"model": body.get("model", payload["model"]),
	"request_ids": [body.get("id")],
	"reasoning_effort": reasoning_effort,
	"preserve_thinking": preserve_thinking,
	"latency_ms": latency_ms,
	"usage": {
	"prompt_tokens": usage.get("prompt_tokens", exact_beam_token_count(packed_repo)),
	"completion_tokens": usage.get("completion_tokens", exact_beam_token_count(content)),
	"reasoning_tokens": comp_details.get("reasoning_tokens", exact_beam_token_count(reasoning_text)),
	"total_tokens": usage.get("total_tokens", 0),
	"cost_usd": usage.get("cost", 0.0),
	},
	"reasoning_content": reasoning_text,
	"synthesized_code": content,
	}