1 line
3.3 KiB
JSON
1 line
3.3 KiB
JSON
{"repo": "asfritecx/miniprojects", "files": {"Python/AIProjects/testproject/DeepseekStreaming.py": {"bd0dc089d0856583456ed9b92f7a35d254226844": {"t": 1785746642.9911397, "n": 917, "h": "29d86f99e2009669", "c": "from openai import OpenAI\nclient = OpenAI(api_key=\"\", base_url=\"https://api.deepseek.com\")\n\n# Get user input\nuser_prompt = input(\"What would you like to ask? \")\n\n# Round 1\nmessages = [{\"role\": \"user\", \"content\": user_prompt}]\nresponse = client.chat.completions.create(\n model=\"deepseek-reasoner\",\n messages=messages,\n stream=True,\n temperature=0.6\n)\n\nreasoning_content = \"\"\ncontent = \"\"\n\nfor chunk in response:\n if chunk.choices[0].delta.reasoning_content:\n reasoning_content += chunk.choices[0].delta.reasoning_content\n else:\n content += chunk.choices[0].delta.content\n\n# Round 2\nmessages.append({\"role\": \"assistant\", \"content\": content})\nuser_followup = input(\"Any follow-up question? \")\nmessages.append({'role': 'user', 'content': user_followup})\nresponse = client.chat.completions.create(\n model=\"deepseek-reasoner\",\n messages=messages,\n stream=True,\n temperature=0.6\n)"}, "e8a5bf25b06af18b5422a08d1e04fac0838e88fb": {"t": 1785766524.212504, "n": 917, "h": "29d86f99e2009669", "c": "from openai import OpenAI\nclient = OpenAI(api_key=\"\", base_url=\"https://api.deepseek.com\")\n\n# Get user input\nuser_prompt = input(\"What would you like to ask? \")\n\n# Round 1\nmessages = [{\"role\": \"user\", \"content\": user_prompt}]\nresponse = client.chat.completions.create(\n model=\"deepseek-reasoner\",\n messages=messages,\n stream=True,\n temperature=0.6\n)\n\nreasoning_content = \"\"\ncontent = \"\"\n\nfor chunk in response:\n if chunk.choices[0].delta.reasoning_content:\n reasoning_content += chunk.choices[0].delta.reasoning_content\n else:\n content += chunk.choices[0].delta.content\n\n# Round 2\nmessages.append({\"role\": \"assistant\", \"content\": content})\nuser_followup = input(\"Any follow-up question? \")\nmessages.append({'role': 'user', 'content': user_followup})\nresponse = client.chat.completions.create(\n model=\"deepseek-reasoner\",\n messages=messages,\n stream=True,\n temperature=0.6\n)"}, "25fa4706fc4f68c8c2a4ecc478b5da31dda54f45": {"t": 1785766525.643699, "n": 877, "h": "9ab1f1c4e6367657", "c": "from openai import OpenAI\nclient = OpenAI(api_key=\"\", base_url=\"https://api.deepseek.com\")\n\n# Round 1\nmessages = [{\"role\": \"user\", \"content\": \"Write a simple api interface in asp.net core 8\"}]\nresponse = client.chat.completions.create(\n model=\"deepseek-reasoner\",\n messages=messages,\n stream=True,\n temperature=0.0\n)\n\nreasoning_content = \"\"\ncontent = \"\"\n\nfor chunk in response:\n if chunk.choices[0].delta.reasoning_content:\n reasoning_content += chunk.choices[0].delta.reasoning_content\n else:\n content += chunk.choices[0].delta.content\n\n# Round 2\nmessages.append({\"role\": \"assistant\", \"content\": content})\nmessages.append({'role': 'user', 'content': \"Create the client api request to interact with the api\"})\nresponse = client.chat.completions.create(\n model=\"deepseek-reasoner\",\n messages=messages,\n stream=True,\n temperature=0.0\n)"}}}} |