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Update pipeline/meta_review.py
Browse files- pipeline/meta_review.py +57 -49
pipeline/meta_review.py
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@@ -14,6 +14,13 @@ client = OpenAI(
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api_key=os.getenv("OPENROUTER_API_KEY"),
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class MetaReviewResult(BaseModel):
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meta_review: str
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@@ -25,15 +32,6 @@ def construct_meta_review_prompt(
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) -> tuple:
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"""
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Construct prompt for meta-review generation
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Args:
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paper_title: Paper title
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paper_abstract: Paper abstract
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resolutions: List of disagreement resolutions
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search_results: Search and retrieval results
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Returns:
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Tuple of (system_prompt, user_prompt)
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"""
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# Aggregate all resolutions
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all_accepted = {}
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@@ -110,20 +108,10 @@ async def generate_meta_review(
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paper_abstract: str,
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resolutions: List[Dict],
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search_results: Dict,
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retries: int =
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) -> str:
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"""
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Generate a meta-review using DeepSeek-R1
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Args:
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paper_title: Paper title
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paper_abstract: Paper abstract
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resolutions: List of disagreement resolutions
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search_results: Search and retrieval results
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retries: Maximum retry attempts
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Returns:
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Generated meta-review text
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"""
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if not resolutions:
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return "Unable to generate meta-review: No disagreement resolutions available."
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@@ -140,31 +128,51 @@ async def generate_meta_review(
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{"role": "user", "content": user_prompt},
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]
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api_key=os.getenv("OPENROUTER_API_KEY"),
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)
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# Priority list of models (Consistency with other files)
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MODELS = [
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"deepseek/deepseek-r1",
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"deepseek/deepseek-r1-distill-llama-70b",
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"google/gemini-2.0-flash-exp:free"
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]
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class MetaReviewResult(BaseModel):
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meta_review: str
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) -> tuple:
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"""
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Construct prompt for meta-review generation
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"""
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# Aggregate all resolutions
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all_accepted = {}
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paper_abstract: str,
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resolutions: List[Dict],
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search_results: Dict,
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retries: int = 3 # Reduced retries per model
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) -> str:
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"""
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Generate a meta-review using DeepSeek-R1 (with fallback)
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"""
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if not resolutions:
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return "Unable to generate meta-review: No disagreement resolutions available."
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{"role": "user", "content": user_prompt},
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]
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last_exception = None
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for model in MODELS:
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print(f"Generating Meta-Review with model: {model}")
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for attempt in range(retries):
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try:
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response = await asyncio.to_thread(
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client.chat.completions.create,
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model=model,
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messages=messages,
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# CRITICAL FIX: Limit max_tokens to prevent 402 Error
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# 8192 is plenty for a meta-review (~6000 words) but much cheaper than 64k
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max_tokens=8192,
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)
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if not response.choices or not response.choices[0].message.content.strip():
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raise ValueError("Empty response from AI")
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meta_review_text = response.choices[0].message.content.strip()
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# Remove any JSON formatting/thinking tags if present (cleanup)
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if meta_review_text.startswith("```"):
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lines = meta_review_text.split("\n")
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# Simple heuristic to strip markdown fences
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if lines[0].startswith("```"):
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lines = lines[1:]
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if lines and lines[-1].startswith("```"):
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lines = lines[:-1]
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meta_review_text = "\n".join(lines)
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return meta_review_text
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except Exception as e:
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last_exception = e
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error_msg = str(e)
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print(f"Model {model} - Attempt {attempt + 1} failed: {error_msg}")
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# Immediate fallback on payment errors
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if "402" in error_msg or "insufficient_quota" in error_msg:
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print("Insufficient credits detected. Switching to cheaper model...")
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break
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wait_time = 2 ** attempt
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if attempt < retries - 1:
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await asyncio.sleep(wait_time)
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return f"Error generating meta-review after trying all models: {str(last_exception)}"
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