From 5a21c8598a8b5675233daf2ebd17ee02d49c60f9 Mon Sep 17 00:00:00 2001
From: carry <luokairui@carry.fit>
Date: Sat, 19 Apr 2025 21:10:22 +0800
Subject: [PATCH] =?UTF-8?q?feat(tools):=20=E6=94=AF=E6=8C=81=20OpenAI=20AP?=
 =?UTF-8?q?I=20=E7=9A=84=20JSON=20=E6=A0=BC=E5=BC=8F=E8=BF=94=E5=9B=9E?=
 =?UTF-8?q?=E7=BB=93=E6=9E=9C?=
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- 在 call_openai_api 函数中添加对 JSON 格式返回结果的支持
- 增加 llm_request.format 参数处理，将用户 prompt 与格式要求合并
- 添加 response_format 参数到 OpenAI API 请求
- 更新示例，使用 JSON 格式返回结果
---
 tools/reasoning.py | 43 ++++++++++++++++++++++++++++---------------
 1 file changed, 28 insertions(+), 15 deletions(-)

diff --git a/tools/reasoning.py b/tools/reasoning.py
index a50a69f..27cc718 100644
--- a/tools/reasoning.py
+++ b/tools/reasoning.py
@@ -16,21 +16,30 @@ async def call_openai_api(llm_request: LLMRequest, rounds: int = 1, llm_paramete
     
     total_duration = 0.0
     total_tokens = TokensUsage()
-    
+    prompt = llm_request.prompt
+    round_start = datetime.now(timezone.utc)
+    if llm_request.format:
+        prompt += "\n请以JSON格式返回结果" + llm_request.format
+
     for i in range(rounds):
+        round_start = datetime.now(timezone.utc)
         try:
-            round_start = datetime.now(timezone.utc)
-            messages = [{"role": "user", "content": llm_request.prompt}]
-            response = await client.chat.completions.create(
-                model=llm_request.api_provider.model_id,
-                messages=messages,
-                temperature=llm_parameters.temperature if llm_parameters else None,
-                max_tokens=llm_parameters.max_tokens if llm_parameters else None,
-                top_p=llm_parameters.top_p if llm_parameters else None,
-                frequency_penalty=llm_parameters.frequency_penalty if llm_parameters else None,
-                presence_penalty=llm_parameters.presence_penalty if llm_parameters else None,
-                seed=llm_parameters.seed if llm_parameters else None
-            )
+            messages = [{"role": "user", "content": prompt}]
+            create_args = {
+                "model": llm_request.api_provider.model_id,
+                "messages": messages,
+                "temperature": llm_parameters.temperature if llm_parameters else None,
+                "max_tokens": llm_parameters.max_tokens if llm_parameters else None,
+                "top_p": llm_parameters.top_p if llm_parameters else None,
+                "frequency_penalty": llm_parameters.frequency_penalty if llm_parameters else None,
+                "presence_penalty": llm_parameters.presence_penalty if llm_parameters else None,
+                "seed": llm_parameters.seed if llm_parameters else None
+            }    # 处理format参数
+
+            if llm_request.format:
+                create_args["response_format"] = {"type": "json_object"}
+
+            response = await client.chat.completions.create(**create_args)
             
             round_end = datetime.now(timezone.utc)
             duration = (round_end - round_start).total_seconds()
@@ -84,15 +93,19 @@ async def call_openai_api(llm_request: LLMRequest, rounds: int = 1, llm_paramete
     return llm_request
 
 if __name__ == "__main__":
+    from json_example import generate_example_json
     from sqlmodel import Session, select
     from global_var import get_sql_engine, init_global_var
+    from schema import dataset_item
+
     init_global_var("workdir")
     api_state = "1 deepseek-chat"
     with Session(get_sql_engine()) as session:
         api_provider = session.exec(select(APIProvider).where(APIProvider.id == int(api_state.split(" ")[0]))).first()
     llm_request = LLMRequest(
-        prompt="你好，世界！",
-        api_provider=api_provider
+        prompt="测试，随便说点什么",
+        api_provider=api_provider,
+        format=generate_example_json(dataset_item)
     )
 
     # # 单次调用示例