mirror of
https://github.com/hoshikawa2/openclaw-oci.git
synced 2026-03-06 10:11:06 +00:00
317 lines
8.6 KiB
Python
317 lines
8.6 KiB
Python
import os
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import time
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import json
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import uuid
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from typing import List, Optional, Dict, Any, Iterable
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import requests
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import oci
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from fastapi import FastAPI, HTTPException
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from fastapi import Request
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from fastapi.responses import JSONResponse, StreamingResponse
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from pydantic import BaseModel, ConfigDict
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# ============================================================
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# CONFIG
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# ============================================================
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OCI_CONFIG_FILE = os.getenv("OCI_CONFIG_FILE", os.path.expanduser("~/.oci/config"))
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OCI_PROFILE = os.getenv("OCI_PROFILE", "DEFAULT")
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OCI_COMPARTMENT_ID = os.getenv("OCI_COMPARTMENT_ID", "<YOUR_COMPARTMENT_ID>")
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OCI_GENAI_ENDPOINT = os.getenv(
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"OCI_GENAI_ENDPOINT",
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"https://inference.generativeai.<region>.oci.oraclecloud.com"
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)
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MODEL_MAP = {
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"gpt-4o-mini": "openai.gpt-4.1",
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"text-embedding-3-small": "cohere.embed-multilingual-v3.0",
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}
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app = FastAPI(title="OCI OpenAI-Compatible Gateway")
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# ============================================================
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# Pydantic Models (OpenAI-compatible)
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# ============================================================
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class Message(BaseModel):
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role: str
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content: str
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class EmbeddingRequest(BaseModel):
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model: str
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input: List[str] | str
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class ChatRequest(BaseModel):
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model: str
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messages: List[Message]
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temperature: Optional[float] = None
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max_tokens: Optional[int] = None
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max_completion_tokens: Optional[int] = None
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top_p: Optional[float] = None
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stream: Optional[bool] = False
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tools: Optional[Any] = None
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tool_choice: Optional[Any] = None
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model_config = ConfigDict(extra="allow")
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# ============================================================
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# OCI SIGNER
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# ============================================================
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def get_signer():
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config = oci.config.from_file(OCI_CONFIG_FILE, OCI_PROFILE)
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signer = oci.signer.Signer(
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tenancy=config["tenancy"],
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user=config["user"],
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fingerprint=config["fingerprint"],
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private_key_file_location=config["key_file"],
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pass_phrase=config.get("pass_phrase"),
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)
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return signer
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# ============================================================
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# CONVERSION HELPERS
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# ============================================================
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def openai_to_oci_messages(messages: list, model_id: str) -> list:
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oci_messages = []
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for m in messages:
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role = m.get("role", "").upper()
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if role == "SYSTEM":
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role = "SYSTEM"
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elif role == "ASSISTANT":
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role = "ASSISTANT"
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else:
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role = "USER"
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oci_messages.append({
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"role": role,
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"content": [
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{
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"type": "TEXT",
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"text": m.get("content", "")
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}
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]
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})
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return oci_messages
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def build_openai_response(model: str, text: str) -> Dict[str, Any]:
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return {
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"id": f"chatcmpl-{uuid.uuid4().hex}",
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"object": "chat.completion",
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"created": int(time.time()),
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"model": model,
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"choices": [
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{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": text,
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},
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"finish_reason": "stop",
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}
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],
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"usage": {
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"prompt_tokens": None,
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"completion_tokens": None,
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"total_tokens": None,
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},
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}
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def normalize_messages(messages: list) -> list:
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normalized = []
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for m in messages:
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content = m.get("content")
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# Caso OpenClaw envie array [{type:"text", text:"..."}]
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if isinstance(content, list):
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text_parts = []
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for item in content:
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if isinstance(item, dict) and item.get("type") == "text":
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text_parts.append(item.get("text", ""))
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content = "\n".join(text_parts)
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normalized.append({
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"role": m.get("role"),
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"content": content
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})
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return normalized
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def fake_stream(text: str, model: str):
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completion_id = f"chatcmpl-{uuid.uuid4().hex}"
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created = int(time.time())
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yield f"data: {json.dumps({
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'id': completion_id,
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'object': 'chat.completion.chunk',
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'created': created,
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'model': model,
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'choices': [{
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'index': 0,
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'delta': {'role': 'assistant'},
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'finish_reason': None
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}]
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})}\n\n"
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for i in range(0, len(text), 40):
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chunk = text[i:i+40]
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yield f"data: {json.dumps({
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'id': completion_id,
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'object': 'chat.completion.chunk',
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'created': created,
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'model': model,
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'choices': [{
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'index': 0,
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'delta': {'content': chunk},
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'finish_reason': None
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}]
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})}\n\n"
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yield "data: [DONE]\n\n"
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# ============================================================
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# OCI CHAT CALL (REST 20231130)
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# ============================================================
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def call_oci_chat(request: dict) -> str:
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signer = get_signer()
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model = request.get("model")
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oci_model = MODEL_MAP.get(model, model)
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url = f"{OCI_GENAI_ENDPOINT}/20231130/actions/chat"
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oci_messages = []
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for m in request.get("messages", []):
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oci_messages.append({
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"role": m["role"].upper(),
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"content": [
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{
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"type": "TEXT",
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"text": m["content"]
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}
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]
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})
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payload = {
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"compartmentId": OCI_COMPARTMENT_ID,
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"servingMode": {
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"servingType": "ON_DEMAND",
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"modelId": oci_model
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},
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"chatRequest": {
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"apiFormat": "GENERIC",
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"messages": oci_messages,
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"maxTokens": request.get("max_tokens", 512),
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"temperature": request.get("temperature", 0.7),
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"topP": request.get("top_p", 0.9)
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}
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}
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print("\n================ OCI PAYLOAD ================")
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print(json.dumps(payload, indent=2, ensure_ascii=False))
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print("=============================================\n")
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response = requests.post(
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url,
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json=payload,
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auth=signer,
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headers={"Content-Type": "application/json"},
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)
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if response.status_code != 200:
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print("\n================ OCI ERROR =================")
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print(response.text)
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print("===========================================\n")
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raise HTTPException(status_code=500, detail=response.text)
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data = response.json()
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# Caminho correto da resposta GENERIC
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choices = data["chatResponse"]["choices"]
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message = choices[0]["message"]
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content = message["content"]
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return content[0]["text"]
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# ============================================================
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# ENDPOINTS
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# ============================================================
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@app.get("/v1/models")
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def list_models():
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return {
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"object": "list",
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"data": [
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{"id": k, "object": "model", "owned_by": "oci"}
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for k in MODEL_MAP.keys()
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],
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}
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@app.post("/v1/chat/completions")
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async def chat_completions(request: Request):
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body = await request.json()
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print("\n=== OPENCLAW BODY ===")
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print(json.dumps(body, indent=2))
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print("=====================\n")
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body["messages"] = normalize_messages(body["messages"])
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text = call_oci_chat(body)
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if body.get("stream"):
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return StreamingResponse(
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fake_stream(text, body["model"]),
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media_type="text/event-stream"
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)
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return build_openai_response(body["model"], text)
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# ============================================================
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# HEALTHCHECK
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# ============================================================
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@app.get("/health")
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def health():
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return {"status": "ok"}
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@app.middleware("http")
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async def log_requests(request: Request, call_next):
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body = await request.body()
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try:
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body_json = json.loads(body.decode())
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except:
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body_json = body.decode()
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print("\n>>> HIT:", request.method, request.url.path)
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print(">>> BODY:", json.dumps(body_json, indent=2, ensure_ascii=False))
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# NÃO mexe no request._receive
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response = await call_next(request)
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return response
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@app.post("/v1/responses")
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async def responses_passthrough(request: Request):
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body = await request.json()
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body["messages"] = normalize_messages(body.get("messages", []))
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text = call_oci_chat(body)
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if body.get("stream"):
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return StreamingResponse(
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fake_stream(text, body["model"]),
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media_type="text/event-stream"
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)
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return build_openai_response(body["model"], text)
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