konjacpotato
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195 lines
6.9 KiB
Python
195 lines
6.9 KiB
Python
import json
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from datetime import datetime, timedelta, timezone
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import re
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from typing import Any, Dict, List, Optional
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from openai import OpenAI
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from config.settings import settings
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from llm import prompt as prompts
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from utils.logger import logger
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BASE_URL = "https://dashscope.aliyuncs.com/compatible-mode/v1"
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MODEL = "deepseek-v3.2"
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def _make_client() -> OpenAI:
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return OpenAI(api_key=settings.DASHSCOPE_API_KEY, base_url=BASE_URL)
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def _call_model(system_prompt: Optional[str], user_prompt: str, stream: bool = False, enable_search: bool = False) -> Any:
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client = _make_client()
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messages = []
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if system_prompt:
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messages.append({"role": "system", "content": system_prompt})
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messages.append({"role": "user", "content": user_prompt})
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# Non-streaming call for simplicity
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resp = client.chat.completions.create(model=MODEL, messages=messages, stream=stream, extra_body={"enable_search": enable_search})
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# When stream=False the SDK typically returns a full object; content location may vary.
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# We'll try common access patterns.
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try:
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# OpenAI-compatible: resp.choices[0].message.content
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return resp.choices[0].message.content
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except Exception:
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try:
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# fallback: resp.choices[0].text
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return resp.choices[0].text
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except Exception:
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# As last resort, return raw resp
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return resp
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def _extract_json(text: str) -> str:
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"""Attempt to extract the first JSON object/array from text."""
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if not isinstance(text, str):
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raise ValueError("Expected text to be str")
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# Find first '[' or '{'
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start_idx = None
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for i, ch in enumerate(text):
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if ch in "[{":
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start_idx = i
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break
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if start_idx is None:
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raise ValueError("No JSON object/array found in text")
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# Try to find a matching closing bracket by scanning and counting
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stack = []
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for j in range(start_idx, len(text)):
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ch = text[j]
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if ch in "{[":
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stack.append(ch)
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elif ch in "]}":
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if not stack:
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continue
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opening = stack.pop()
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if (opening == "{" and ch != "}") or (opening == "[" and ch != "]"):
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# mismatched, continue
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continue
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if not stack:
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return text[start_idx : j + 1]
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# Fallback: try regex to capture last '}' or ']' occurrence
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m = re.search(r"(\{.*\}|\[.*\])", text, re.S)
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if m:
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return m.group(1)
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raise ValueError("Could not extract JSON from model output")
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def _parse_json_safe(text: str) -> Any:
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try:
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return json.loads(text)
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except Exception:
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# try to extract JSON substring
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jtext = _extract_json(text)
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return json.loads(jtext)
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def generate_topics(start_time: Optional[str] = None, end_time: Optional[str] = None) -> List[Dict[str, Any]]:
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"""Call prompt_a to get a list of candidate meme topics.
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If start_time/end_time are provided (YYYY-MM-DD), they will be injected into the prompt
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to limit the timeframe the model should scan.
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If start_time/end_time are not provided, default to the last 7 days:
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end_time = today (UTC, YYYY-MM-DD)
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start_time = end_time - 7 days
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Both parameters should be strings in YYYY-MM-DD format when provided.
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"""
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# compute defaults (UTC)
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if end_time is None:
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end_date = datetime.now(timezone.utc).date()
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end_time = end_date.isoformat()
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if start_time is None:
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start_date = end_date - timedelta(days=7)
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start_time = start_date.isoformat()
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user_prompt = prompts.prompt_a
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# If the prompt contains the literal placeholder, replace it; otherwise append a time line.
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if "start_time ~ end_time" in user_prompt:
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if start_time is None:
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start_time = ""
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if end_time is None:
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end_time = ""
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user_prompt = user_prompt.replace("start_time ~ end_time", f"{start_time} ~ {end_time}")
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logger.debug(f"prompt for generate_topics:\n{user_prompt}")
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content = _call_model(system_prompt=None, user_prompt=user_prompt, enable_search=True)
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logger.debug(f"raw output from generate_topics:\n{content}")
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if isinstance(content, (dict, list)):
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return content
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text = content if isinstance(content, str) else str(content)
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data = _parse_json_safe(text)
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if not isinstance(data, list):
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raise ValueError("prompt_a did not return a JSON array")
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logger.debug(f"result for generate_topics:\n{data}")
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return data
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def generate_bits(meme_name: str, research_text: str, prompt_bit: str = prompts.prompt_b) -> Dict[str, Any]:
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user_prompt = prompt_bit + f"\n\nmeme_name: {meme_name}\nresearch:\n{research_text}\n"
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content = _call_model(system_prompt=None, user_prompt=user_prompt)
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text = content if isinstance(content, str) else str(content)
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data = _parse_json_safe(text)
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return data
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def generate_bit(meme_name: str, research_text: str, prompt_bit: str) -> Dict[str, Any]:
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user_prompt = prompt_bit + f"\n\nmeme_name: {meme_name}\nresearch:\n{research_text}\n"
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content = _call_model(system_prompt=None, user_prompt=user_prompt)
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text = content if isinstance(content, str) else str(content)
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data = _parse_json_safe(text)
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return data
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def generate_script(meme_name: str, materials_text: str) -> Dict[str, Any]:
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user_prompt = prompts.prompt_c + f"\n\nmeme_name: {meme_name}\nmaterials:\n{materials_text}\n"
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content = _call_model(system_prompt=None, user_prompt=user_prompt)
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text = content if isinstance(content, str) else str(content)
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data = _parse_json_safe(text)
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return data
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def orchestrate_for_first_topic() -> Dict[str, Any]:
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"""High-level orchestration: pick first topic, synthesize research, create bits and final script."""
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topics = generate_topics()
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if not topics:
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raise RuntimeError("No topics returned")
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top = topics[0]
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meme = top.get("title") or top.get("name") or "未知梗"
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# Build a concise research text from topic fields
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parts = []
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if "summary" in top:
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parts.append(f"简介：{top['summary']}")
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if "origin" in top:
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parts.append(f"可能起源：{top['origin']}")
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if "reach_estimate" in top:
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parts.append(f"传播估计：{top['reach_estimate']}")
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if "angles" in top:
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parts.append("角度：" + "; ".join(top.get("angles", [])))
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research_text = "\n".join(parts)
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bits = generate_bits(meme, research_text)
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# Combine materials: human-crafted research + selected bits
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materials = research_text + "\n\n" + json.dumps(bits, ensure_ascii=False, indent=2)
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script = generate_script(meme, materials)
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return {"topic": top, "bits": bits, "script": script}
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# if __name__ == "__main__":
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# # quick sanity check when run as script (will call API if keys present)
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# try:
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# out = orchestrate_for_first_topic()
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# print(json.dumps(out, ensure_ascii=False, indent=2))
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# except Exception as e:
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# print(f"Error during orchestration: {e}")
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