Update backend/main.py

backend/main.py

@@ -1,23 +1,16 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-# SPDX-License-Identifier: Apache-2.0
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
 #
-# http://www.apache.org/licenses/LICENSE-2.0
+#     http://www.apache.org/licenses/LICENSE-2.0
 #
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""
-Universal Deep Research Backend (UDR-B) - FastAPI Application
-
-This module provides the main FastAPI application for the Universal Deep Research Backend,
-offering intelligent research and reporting capabilities through streaming APIs.
-"""
 
 import asyncio
 import json
@@ -30,12 +23,12 @@ import uvicorn
 from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import StreamingResponse
+from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
 from uvicorn.config import LOGGING_CONFIG
 
+# Локальные импорты из вашего оригинального файла
 import items
-
-# Import configuration
 from config import get_config
 from frame.clients import Client, HuggingFaceClient, OpenAIClient
 from frame.harness4 import FrameConfigV4, FrameV4
@@ -46,50 +39,36 @@ from scan_research import generate_session_key
 from scan_research_dry import do_reporting as dry_reporting
 from scan_research_dry import do_research as dry_research
 
-# Get configuration
+# Получаем конфигурацию
 config = get_config()
 
-app = FastAPI(
+# ========================================================================================
+#                    ИЗМЕНЕНИЕ ДЛЯ HUGGING FACE SPACES
+#
+# 1. Создаем отдельное приложение (sub-app) для API.
+# ========================================================================================
+api_app = FastAPI(
     title="Universal Deep Research Backend API",
     description="Intelligent research and reporting service using LLMs and web search",
     version="1.0.0",
 )
 
+# Настройка логирования
+LOGGING_CONFIG["formatters"]["default"]["fmt"] = "%(asctime)s [%(name)s] %(levelprefix)s %(message)s"
 
-# раздача Next.js
-frontend_dir = pathlib.Path(__file__).parent.parent / "frontend"
-app.mount("/", StaticFiles(directory=frontend_dir / ".next" / "static"), name="static")
-
-# fallback на index.html
-@app.get("/{full_path:path}")
-async def spa(full_path: str):
-    return FileResponse(frontend_dir / "public" / "index.html")
-
-
-
-
-
-
-
-# Configure logging
-LOGGING_CONFIG["formatters"]["default"][
-    "fmt"
-] = "%(asctime)s [%(name)s] %(levelprefix)s %(message)s"
-
-# Configure CORS
-app.add_middleware(
+# Настройка CORS (можно удалить, если развертывание в одном домене)
+api_app.add_middleware(
     CORSMiddleware,
-    allow_origins=[config.cors.frontend_url],  # Frontend URL from config
-    allow_credentials=config.cors.allow_credentials,
-    allow_methods=config.cors.allow_methods,
-    allow_headers=config.cors.allow_headers,
+    allow_origins=["*"],  # Разрешаем все источники для простоты
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
 )
 
-
+# Модели Pydantic из вашего файла
 class Message(BaseModel):
     text: str
 
-
 class ResearchRequest(BaseModel):
     dry: bool = False
     session_key: Optional[str] = None
@@ -99,18 +78,10 @@ class ResearchRequest(BaseModel):
     prompt: Optional[str] = None
     mock_directory: str = "mock_instances/stocks_24th_3_sections"
 
-
-@app.get("/")
-async def root():
-    return {
-        "message": "The Deep Research Backend is running. Use the /api/research endpoint to start a new research session."
-    }
-
-
+# Вспомогательные функции из вашего файла
 def build_events_path(session_key: str) -> str:
     return f"instances/{session_key}.events.jsonl"
 
-
 def make_message(
     event: Dict[str, Any],
     session_key: str | None = None,
@@ -118,370 +89,135 @@ def make_message(
 ) -> str:
     if timestamp_the_event:
         event = {**event, "timestamp": datetime.now().isoformat()}
-
     if session_key:
         items.register_item(build_events_path(session_key), event)
-
     return json.dumps({"event": event, "session_key": session_key}) + "\n"
 
+# ========================================================================================
+#                    ИЗМЕНЕНИЕ ДЛЯ HUGGING FACE SPACES
+#
+# 2. Все эндпоинты @app.post(...) заменяем на @api_app.post(...)
+# ========================================================================================
 
-@app.post("/api/research")
+@api_app.post("/research")
 async def start_research(request: ResearchRequest):
-    """
-    Start or continue a research process and stream the results using JSON streaming.
-    
-    This endpoint initiates a comprehensive research workflow that includes:
-    - Query analysis and topic extraction
-    - Web search using Tavily API
-    - Content filtering and relevance scoring
-    - Report generation using LLMs
-    
-    The response is streamed as Server-Sent Events (SSE) with real-time progress updates.
-    
-    Args:
-        request (ResearchRequest): The research request containing:
-            - dry (bool): Use mock data for testing (default: False)
-            - session_key (str, optional): Existing session to continue
-            - start_from (str): "research" or "reporting" phase
-            - prompt (str): Research query (required for research phase)
-            - mock_directory (str): Directory for mock data
-    
-    Returns:
-        StreamingResponse: Server-Sent Events stream with research progress
-        
-    Raises:
-        HTTPException: 400 if request parameters are invalid
-        
-    Example:
-        ```bash
-        curl -X POST http://localhost:8000/api/research \\
-          -H "Content-Type: application/json" \\
-          -d '{
-            "prompt": "What are the latest developments in quantum computing?",
-            "start_from": "research"
-          }'
-        ```
-    """
-    # Validate request parameters
     if request.start_from not in ["research", "reporting"]:
-        raise HTTPException(
-            status_code=400,
-            detail="start_from must be either 'research' or 'reporting'",
-        )
-
+        raise HTTPException(status_code=400, detail="start_from must be either 'research' or 'reporting'")
     if request.start_from == "reporting" and not request.session_key:
-        raise HTTPException(
-            status_code=400,
-            detail="session_key is required when starting from reporting phase",
-        )
-
+        raise HTTPException(status_code=400, detail="session_key is required when starting from reporting phase")
     if request.start_from == "research" and not request.prompt:
-        raise HTTPException(
-            status_code=400,
-            detail="prompt is required when starting from research phase",
-        )
-
-    # Use configured mock directory
+        raise HTTPException(status_code=400, detail="prompt is required when starting from research phase")
+    
     mock_dir = request.mock_directory or config.research.mock_directory
-
-    # Choose implementation
-    research_impl = (
-        (lambda session_key, prompt: dry_research(session_key, prompt, mock_dir))
-        if request.dry
-        else real_research
-    )
-    reporting_impl = (
-        (lambda session_key: dry_reporting(session_key, mock_dir))
-        if request.dry
-        else real_reporting
-    )
-
-    # Generate or use provided session key
+    research_impl = (lambda session_key, prompt: dry_research(session_key, prompt, mock_dir)) if request.dry else real_research
+    reporting_impl = (lambda session_key: dry_reporting(session_key, mock_dir)) if request.dry else real_reporting
     session_key = request.session_key or generate_session_key()
-
-    # Prepare generators
-    research_gen = (
-        research_impl(session_key, request.prompt)
-        if request.start_from == "research"
-        else None
-    )
+    research_gen = research_impl(session_key, request.prompt) if request.start_from == "research" else None
     reporting_gen = reporting_impl(session_key)
-
+    
     return StreamingResponse(
-        stream_research_events(
-            research_gen, reporting_gen, request.start_from == "research", session_key
-        ),
+        stream_research_events(research_gen, reporting_gen, request.start_from == "research", session_key),
         media_type="application/x-ndjson",
-        headers={
-            "Cache-Control": "no-cache",
-            "Connection": "keep-alive",
-            "Content-Encoding": "none",
-        },
+        headers={"Cache-Control": "no-cache", "Connection": "keep-alive", "Content-Encoding": "none"},
     )
 
+@api_app.post("/research2")
+async def start_research2(request: ResearchRequest):
+    if request.start_from not in ["research"]:
+        raise HTTPException(status_code=400, detail="start_from must be 'research'")
+    if request.start_from == "research" and not request.prompt:
+        raise HTTPException(status_code=400, detail="prompt is required when starting from research phase")
 
+    session_key = generate_session_key()
+    if request.strategy_id is None or request.strategy_id == "default":
+        research_impl = (lambda session_key, prompt: dry_research(session_key, prompt, "mock_instances/stocks_24th_3_sections")) if request.dry else real_research
+        reporting_impl = (lambda session_key: dry_reporting(session_key, "mock_instances/stocks_24th_3_sections")) if request.dry else real_reporting
+        session_key = request.session_key or generate_session_key()
+        research_gen = research_impl(session_key, request.prompt) if request.start_from == "research" else None
+        reporting_gen = reporting_impl(session_key)
+        return StreamingResponse(
+            stream_research_events(research_gen, reporting_gen, request.start_from == "research", session_key),
+            media_type="application/x-ndjson",
+            headers={"Cache-Control": "no-cache", "Connection": "keep-alive", "Content-Encoding": "none"},
+        )
+    
+    return StreamingResponse(
+        stream_research2_events(session_key, request.prompt, request.strategy_id, request.strategy_content),
+        media_type="application/x-ndjson",
+        headers={"Cache-Control": "no-cache", "Connection": "keep-alive", "Content-Encoding": "none"},
+    )
+
+# Асинхронные генераторы событий остаются без изменений
 async def stream_research_events(
     research_fn: AsyncGenerator[Dict[str, Any], None],
     reporting_fn: AsyncGenerator[Dict[str, Any], None],
     do_research: bool,
     session_key: str,
 ) -> AsyncGenerator[str, None]:
-    """
-    Stream research or reporting events using JSON streaming format.
-
-    Args:
-        research_fn: Research phase generator
-        reporting_fn: Reporting phase generator
-        do_research: Whether to run research phase
-        session_key: Session identifier
-
-    Yields:
-        JSON formatted event strings, one per line
-    """
     try:
-        yield make_message(
-            {
-                "type": "started",
-                "description": "Waking up the Deep Research Backend",
-            },
-            session_key,
-        )
-
-        error_event_encountered: bool = False
+        yield make_message({"type": "started", "description": "Waking up the Deep Research Backend"}, session_key)
+        error_event_encountered = False
         if do_research:
             async for event in research_fn:
                 if event["type"] == "error":
                     error_event_encountered = True
                 yield make_message(event, session_key)
-
         if not error_event_encountered:
             async for event in reporting_fn:
                 yield make_message(event, session_key)
-
-            # Send completion message
-            yield make_message(
-                {
-                    "type": "completed",
-                    "description": "Research and reporting completed",
-                },
-                session_key,
-            )
+            yield make_message({"type": "completed", "description": "Research and reporting completed"}, session_key)
     except asyncio.CancelledError:
-        # Send cancellation message before propagating the exception
-        yield make_message(
-            {
-                "type": "cancelled",
-                "description": "Research was cancelled",
-            },
-            session_key,
-        )
+        yield make_message({"type": "cancelled", "description": "Research was cancelled"}, session_key)
         raise
 
-
-@app.post("/api/research2")
-async def start_research2(request: ResearchRequest):
-    # Validate request parameters
-    if request.start_from not in ["research"]:
-        raise HTTPException(status_code=400, detail="start_from must be 'research'")
-
-    if request.start_from == "research" and not request.prompt:
-        raise HTTPException(
-            status_code=400,
-            detail="prompt is required when starting from research phase",
-        )
-
-    # Generate or use provided session key
-    session_key = generate_session_key()
-
-    if request.strategy_id is None or request.strategy_id == "default":
-        # Validate request parameters
-        if request.start_from not in ["research", "reporting"]:
-            raise HTTPException(
-                status_code=400,
-                detail="start_from must be either 'research' or 'reporting'",
-            )
-
-        if request.start_from == "reporting" and not request.session_key:
-            raise HTTPException(
-                status_code=400,
-                detail="session_key is required when starting from reporting phase",
-            )
-
-        if request.start_from == "research" and not request.prompt:
-            raise HTTPException(
-                status_code=400,
-                detail="prompt is required when starting from research phase",
-            )
-
-        # Choose implementation
-        research_impl = (
-            (
-                lambda session_key, prompt: dry_research(
-                    session_key, prompt, "mock_instances/stocks_24th_3_sections"
-                )
-            )
-            if request.dry
-            else real_research
-        )
-        reporting_impl = (
-            (
-                lambda session_key: dry_reporting(
-                    session_key, "mock_instances/stocks_24th_3_sections"
-                )
-            )
-            if request.dry
-            else real_reporting
-        )
-
-        # Generate or use provided session key
-        session_key = request.session_key or generate_session_key()
-
-        # Prepare generators
-        research_gen = (
-            research_impl(session_key, request.prompt)
-            if request.start_from == "research"
-            else None
-        )
-        reporting_gen = reporting_impl(session_key)
-
-        return StreamingResponse(
-            stream_research_events(
-                research_gen,
-                reporting_gen,
-                request.start_from == "research",
-                session_key,
-            ),
-            media_type="application/x-ndjson",
-            headers={
-                "Cache-Control": "no-cache",
-                "Connection": "keep-alive",
-                "Content-Encoding": "none",
-            },
-        )
-
-    return StreamingResponse(
-        stream_research2_events(
-            session_key, request.prompt, request.strategy_id, request.strategy_content
-        ),
-        media_type="application/x-ndjson",
-        headers={
-            "Cache-Control": "no-cache",
-            "Connection": "keep-alive",
-            "Content-Encoding": "none",
-        },
-    )
-
-
 async def stream_research2_events(
     session_key: str, prompt: str, strategy_id: str, strategy_content: str
 ) -> AsyncGenerator[str, None]:
     try:
-        yield make_message(
-            {
-                "type": "started",
-                "description": "Waking up the Universal Deep Research Backend",
-            },
-            session_key,
-        )
-
-        # Set the random seed from configuration
+        yield make_message({"type": "started", "description": "Waking up the Universal Deep Research Backend"}, session_key)
         random.seed(config.research.random_seed)
-
-        # Set trace filename using configuration
-        comm_trace_timestamp: str = datetime.now().strftime("%Y%m%d_%H-%M-%S")
-        comm_trace_filename = (
-            f"{config.logging.log_dir}/comms_{comm_trace_timestamp}.log"
-        )
-        comm_trace = Trace(
-            comm_trace_filename, copy_into_stdout=config.logging.copy_into_stdout
-        )
-
-        client: Client = OpenAIClient(
-            base_url="https://integrate.api.nvidia.com/v1",
-            model="nvdev/meta/llama-3.1-70b-instruct",
-            trace=comm_trace,
-        )
-
+        comm_trace_timestamp = datetime.now().strftime("%Y%m%d_%H-%M-%S")
+        comm_trace_filename = f"{config.logging.log_dir}/comms_{comm_trace_timestamp}.log"
+        comm_trace = Trace(comm_trace_filename, copy_into_stdout=config.logging.copy_into_stdout)
+        client: Client = OpenAIClient(base_url="https://integrate.api.nvidia.com/v1", model="nvdev/meta/llama-3.1-70b-instruct", trace=comm_trace)
         frame_config = FrameConfigV4(
             long_context_cutoff=config.frame.long_context_cutoff,
             force_long_context=config.frame.force_long_context,
             max_iterations=config.frame.max_iterations,
             interaction_level=config.frame.interaction_level,
         )
-        harness = FrameV4(
-            client_profile=client,
-            errand_profile={},
-            compilation_trace=True,
-            execution_trace="file_and_stdout",
-        )
-
+        harness = FrameV4(client_profile=client, errand_profile={}, compilation_trace=True, execution_trace="file_and_stdout")
         messages = []
-        preamble_files = [
-            "frame/prompts/udr_minimal_generating/0.code_skill.py",
-        ]
+        preamble_files = ["frame/prompts/udr_minimal_generating/0.code_skill.py"]
         for path in preamble_files:
             type = path.split(".")[-2]
             with open(path, "r") as f:
-                messages.append(
-                    {
-                        "mid": len(messages),
-                        "role": "user",
-                        "content": f.read(),
-                        "type": type,
-                    }
-                )
-
-        messages.append(
-            {
-                "mid": len(messages),
-                "role": "user",
-                "content": "The following is the prompt data to be used in later procedures.\n\nPROMPT:\n"
-                + prompt,
-                "type": "data",
-            }
-        )
-
-        messages.append(
-            {
-                "mid": len(messages),
-                "role": "user",
-                "content": strategy_content,
-                "type": "generating_routine",
-            }
-        )
-
+                messages.append({"mid": len(messages), "role": "user", "content": f.read(), "type": type})
+        messages.append({"mid": len(messages), "role": "user", "content": "The following is the prompt data to be used in later procedures.\n\nPROMPT:\n" + prompt, "type": "data"})
+        messages.append({"mid": len(messages), "role": "user", "content": strategy_content, "type": "generating_routine"})
         for i in range(len(messages)):
             messages_so_far = messages[: i + 1]
-            yield make_message(
-                {
-                    "type": "generic",
-                    "description": "Processing agentic instructions: "
-                    + str(i + 1)
-                    + " of "
-                    + str(len(messages)),
-                },
-                session_key,
-            )
-            for notification in harness.generate_with_notifications(
-                messages=messages_so_far,
-                frame_config=frame_config,
-            ):
+            yield make_message({"type": "generic", "description": f"Processing agentic instructions: {i + 1} of {len(messages)}"}, session_key)
+            for notification in harness.generate_with_notifications(messages=messages_so_far, frame_config=frame_config):
                 yield make_message(notification, session_key)
-
-        yield make_message(
-            {
-                "type": "completed",
-                "description": "Research completed",
-            },
-            session_key,
-        )
+        yield make_message({"type": "completed", "description": "Research completed"}, session_key)
     except asyncio.CancelledError:
-        # Send cancellation message before propagating the exception
-        yield make_message(
-            {
-                "type": "cancelled",
-                "description": "Research was cancelled",
-            },
-            session_key,
-        )
+        yield make_message({"type": "cancelled", "description": "Research was cancelled"}, session_key)
         raise
+
+# ========================================================================================
+#                    ИЗМЕНЕНИЕ ДЛЯ HUGGING FACE SPACES
+#
+# 3. Создаем главное приложение `app`.
+# 4. Монтируем `api_app` на `/api`.
+# 5. Монтируем статический фронтенд в корень `/`.
+# ========================================================================================
+
+app = FastAPI()
+
+# Монтируем API
+app.mount("/api", api_app)
+
+# Монтируем статический фронтенд
+# Это должно быть в самом конце файла!
+app.mount("/", StaticFiles(directory="/app/static_frontend", html=True), name="static")