数据导入分析接口调整

.env

@@ -1,12 +1,13 @@
 # LLM provider API keys
 OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
-OPENROUTER_API_KEY=
+OPENROUTER_API_KEY="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"
 OPENROUTER_SITE_URL=
 OPENROUTER_APP_NAME=
 GEMINI_API_KEY=
 QWEN_API_KEY=
 DEEPSEEK_API_KEY="sk-657f0752a1564563be7ce35b6a0a7b46"
+DEEPSEEK_TIMEOUT_SECONDS=120
 
 # Data import analysis defaults
 IMPORT_SUPPORTED_MODELS=openai:gpt-5,deepseek:deepseek-chat,openrouter:anthropic/claude-4.0-sonnet
@@ -14,3 +15,15 @@ DEFAULT_IMPORT_MODEL=deepseek:deepseek-chat
 
 # Service configuration
 IMPORT_GATEWAY_BASE_URL=http://localhost:8000
+
+# HTTP client configuration
+HTTP_CLIENT_TIMEOUT=30
+HTTP_CLIENT_TRUST_ENV=false
+# HTTP_CLIENT_PROXY=
+
+# Import analysis configuration
+IMPORT_CHAT_TIMEOUT_SECONDS=120
+
+# Logging
+LOG_LEVEL=INFO
+# LOG_FORMAT=%(asctime)s %(levelname)s %(name)s:%(lineno)d %(message)s

app/providers/deepseek.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import logging
+import os
 from typing import Any, Dict, List
 
 import httpx
@@ -13,6 +14,23 @@ from app.providers.base import LLMProviderClient
 logger = logging.getLogger(__name__)
 
 
+def _resolve_timeout_seconds() -> float:
+    raw = os.getenv("DEEPSEEK_TIMEOUT_SECONDS")
+    if raw is None:
+        return 60.0
+    try:
+        return float(raw)
+    except ValueError:
+        logger.warning(
+            "Invalid value for DEEPSEEK_TIMEOUT_SECONDS=%r, falling back to 60 seconds",
+            raw,
+        )
+        return 60.0
+
+
+DEEPSEEK_TIMEOUT_SECONDS = _resolve_timeout_seconds()
+
+
 class DeepSeekProvider(LLMProviderClient):
     name = LLMProvider.DEEPSEEK.value
     api_key_env = "DEEPSEEK_API_KEY"
@@ -40,9 +58,12 @@ class DeepSeekProvider(LLMProviderClient):
             "Authorization": f"Bearer {self.api_key}",
             "Content-Type": "application/json",
         }
+        timeout = httpx.Timeout(DEEPSEEK_TIMEOUT_SECONDS)
 
         try:
-            response = await client.post(self.base_url, json=payload, headers=headers)
+            response = await client.post(
+                self.base_url, json=payload, headers=headers, timeout=timeout
+            )
             response.raise_for_status()
         except httpx.HTTPStatusError as exc:
             status_code = exc.response.status_code

app/services/import_analysis.py

@@ -4,6 +4,7 @@ import csv
 import json
 import logging
 import os
+import re
 from functools import lru_cache
 from io import StringIO
 from pathlib import Path
@@ -29,6 +30,20 @@ IMPORT_GATEWAY_BASE_URL = os.getenv(
     "IMPORT_GATEWAY_BASE_URL", "http://localhost:8000"
 )
 
+
+def _env_float(name: str, default: float) -> float:
+    raw = os.getenv(name)
+    if raw is None:
+        return default
+    try:
+        return float(raw)
+    except ValueError:
+        logger.warning("Invalid value for %s=%r, falling back to %.2f", name, raw, default)
+        return default
+
+
+IMPORT_CHAT_TIMEOUT_SECONDS = _env_float("IMPORT_CHAT_TIMEOUT_SECONDS", 90.0)
+
 SUPPORTED_IMPORT_MODELS = get_supported_import_models()
 
 
@@ -208,7 +223,7 @@ def build_analysis_request(
 
     example_data = "\n\n".join(sections) if sections else "未提供样本数据。"
 
-    max_length = 30_000
+    max_length = 30000
     if len(example_data) > max_length:
         example_data = example_data[: max_length - 3] + "..."
 
@@ -250,6 +265,44 @@ def build_chat_payload(request: DataImportAnalysisJobRequest) -> Dict[str, Any]:
     return payload
 
 
+def _extract_json_payload(content: str) -> str:
+    """Try to pull a JSON object from an LLM content string."""
+    # Prefer fenced code blocks such as ```json { ... } ```
+    fenced = re.search(r"```(?:json)?\s*(\{.*?\})\s*```", content, flags=re.DOTALL | re.IGNORECASE)
+    if fenced:
+        return fenced.group(1).strip()
+
+    stripped = content.strip()
+    if stripped.startswith("{") and stripped.endswith("}"):
+        return stripped
+
+    start = stripped.find("{")
+    end = stripped.rfind("}")
+    if start != -1 and end != -1 and end > start:
+        return stripped[start : end + 1].strip()
+
+    return stripped
+
+
+def parse_llm_analysis_json(llm_response: LLMResponse) -> Dict[str, Any]:
+    """Extract and parse the structured JSON payload from an LLM response."""
+    if not llm_response.choices:
+        raise ProviderAPICallError("LLM response did not include any choices to parse.")
+
+    content = llm_response.choices[0].message.content or ""
+    if not content.strip():
+        raise ProviderAPICallError("LLM response content is empty.")
+
+    json_payload = _extract_json_payload(content)
+
+    try:
+        return json.loads(json_payload)
+    except json.JSONDecodeError as exc:
+        preview = json_payload[:2000]
+        logger.error("Failed to parse JSON from LLM response content: %s", preview, exc_info=True)
+        raise ProviderAPICallError("LLM response JSON could not be parsed.") from exc
+
+
 async def dispatch_import_analysis_job(
     request: DataImportAnalysisJobRequest,
     client: httpx.AsyncClient,
@@ -259,13 +312,17 @@ async def dispatch_import_analysis_job(
     payload = build_chat_payload(request)
     url = f"{IMPORT_GATEWAY_BASE_URL.rstrip('/')}/v1/chat/completions"
 
-    print(
+    logger.info(
-        f"[ImportAnalysis] Dispatching import {request.import_record_id} to {url}: "
+        "Dispatching import %s to %s: %s",
-        f"{json.dumps(payload, ensure_ascii=False)}"
+        request.import_record_id,
+        url,
+        json.dumps(payload, ensure_ascii=False),
     )
 
+    timeout = httpx.Timeout(IMPORT_CHAT_TIMEOUT_SECONDS)
+
     try:
-        response = await client.post(url, json=payload)
+        response = await client.post(url, json=payload, timeout=timeout)
         response.raise_for_status()
     except httpx.HTTPStatusError as exc:
         body_preview = ""
@@ -284,13 +341,15 @@ async def dispatch_import_analysis_job(
     except ValueError as exc:
         raise ProviderAPICallError("Chat completions endpoint returned invalid JSON") from exc
 
-    print(
+    logger.info(
-        f"[ImportAnalysis] LLM HTTP status for {request.import_record_id}: "
+        "LLM HTTP status for %s: %s",
-        f"{response.status_code}"
+        request.import_record_id,
+        response.status_code,
     )
-    print(
+    logger.info(
-        f"[ImportAnalysis] LLM response for {request.import_record_id}: "
+        "LLM response for %s: %s",
-        f"{json.dumps(response_data, ensure_ascii=False)}"
+        request.import_record_id,
+        json.dumps(response_data, ensure_ascii=False),
     )
 
     try:
@@ -300,13 +359,33 @@ async def dispatch_import_analysis_job(
             "Chat completions endpoint returned unexpected schema"
         ) from exc
 
+    structured_json = parse_llm_analysis_json(llm_response)
+    usage_data = extract_usage(llm_response.raw)
+
     logger.info("Completed import analysis job %s", request.import_record_id)
-    return {
+    result: Dict[str, Any] = {
         "import_record_id": request.import_record_id,
         "status": "succeeded",
         "llm_response": llm_response.model_dump(),
+        "analysis": structured_json
     }
 
+    if usage_data:
+        result["usage"] = usage_data
+
+    return result
+
+# 兼容处理多模型的使用量字段提取
+def extract_usage(resp_json: dict) -> dict:
+    usage = resp_json.get("usage") or resp_json.get("usageMetadata") or {}
+    return {
+        "prompt_tokens": usage.get("prompt_tokens") or usage.get("input_tokens") or usage.get("promptTokenCount"),
+        "completion_tokens": usage.get("completion_tokens") or usage.get("output_tokens") or usage.get("candidatesTokenCount"),
+        "total_tokens": usage.get("total_tokens") or usage.get("totalTokenCount") or (
+            (usage.get("prompt_tokens") or usage.get("input_tokens") or 0)
+            + (usage.get("completion_tokens") or usage.get("output_tokens") or 0)
+        )
+    }
 
 async def notify_import_analysis_callback(
     callback_url: str,
@@ -314,6 +393,12 @@ async def notify_import_analysis_callback(
     client: httpx.AsyncClient,
 ) -> None:
     callback_target = str(callback_url)
+    logger.info(
+        "Posting import analysis callback to %s: %s",
+        callback_target,
+        json.dumps(payload, ensure_ascii=False),
+    )
+    
 
     try:
         response = await client.post(callback_target, json=payload)
@@ -333,8 +418,10 @@ async def process_import_analysis_job(
     try:
         payload = await dispatch_import_analysis_job(request, client)
     except ProviderAPICallError as exc:
-        print(
+        logger.error(
-            f"[ImportAnalysis] LLM call failed for {request.import_record_id}: {exc}"
+            "LLM call failed for %s: %s",
+            request.import_record_id,
+            exc,
         )
         payload = {
             "import_record_id": request.import_record_id,
@@ -346,9 +433,6 @@ async def process_import_analysis_job(
             "Unexpected failure while processing import analysis job %s",
             request.import_record_id,
         )
-        print(
-            f"[ImportAnalysis] Unexpected error for {request.import_record_id}: {exc}"
-        )
         payload = {
             "import_record_id": request.import_record_id,
             "status": "failed",

prompt/data_import_analysis.md

@@ -12,7 +12,6 @@
 方向 2：字段数据类型与格式推断
 针对每列：输出推断数据类型（如 varchar(n) / int / bigint / tinyint / float / double / decimal(p,s) / date / datetime / text）。
 说明推断依据：样本值分布、长度范围、格式正则、是否存在空值、是否数值但含前导零等。
-指出数据质量初步观察：缺失率、是否有异常/离群值（简单规则即可）、是否需标准化（如去空格、去重、枚举值归一）。
 给出“建议处理动作”：如 trim、cast_float、cast_int、cast_double、cast_date、cast_time、cast_datetime，适用于将样本数据转换成数据库表字段兼容的格式。
 若为“可能是枚举”的字段，列出候选枚举值及占比。
 
@@ -23,12 +22,8 @@
   "columns": [{
     "original_name": "原始名称",
     "standard_name": "标准化后的名称: 下划线命名，大小写字母、数字、下划线",
-    "data_type": "数据类型限制为：number/string/datetime",
+    "data_type": "",
-    "db_type": "数据库字段类型",
-    "java_type": "java字段类型限制为: int/long/double/string/date",
     "nullable": true/false,
-    "distinct_count_sample": number,
-    "null_ratio_sample": 0.x,
     "is_enum_candidate": true/false,
     "description": "字段简短描述",
     "date_format": "转换成Date类型的pattern"

test/data_import_analysis_example.py

@@ -36,14 +36,13 @@ async def main() -> None:
         },
         "llm_model": "deepseek:deepseek-chat",
         "temperature": 0.2,
-        "max_output_tokens": 256,
         "callback_url": CALLBACK_URL,
     }
 
-    async with httpx.AsyncClient(timeout=httpx.Timeout(15.0)) as client:
+    async with httpx.AsyncClient(timeout=httpx.Timeout(60.0)) as client:
         response = await client.post(API_URL, json=payload)
         print("Status:", response.status_code)
-        print("Body:", response.json())
+
 
 
 if __name__ == "__main__":

test/openrouter_chat_example.py

@@ -35,7 +35,7 @@ async def main() -> None:
             }
         ],
         "temperature": 0.1,
-        "max_tokens": 1024,
+        "max_tokens": 2048,
     }
 
     async with httpx.AsyncClient(timeout=httpx.Timeout(15.0)) as client: