Update app.py
Browse files
app.py
CHANGED
@@ -7,9 +7,8 @@ import gradio as gr
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# Constants
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MAX_MODEL_TOKENS = 131072
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MAX_NEW_TOKENS = 4096
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MAX_CHUNK_TOKENS = 8192
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PROMPT_OVERHEAD = 300
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BATCH_SIZE = 10 # Bigger batch for faster processing
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# Paths
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persistent_dir = "/data/hf_cache"
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@@ -47,14 +46,13 @@ def extract_text_from_excel(path: str) -> str:
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try:
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df = xls.parse(sheet_name).astype(str).fillna("")
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except Exception:
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continue
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for idx, row in df.iterrows():
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# If the row has at least 2 non-empty values and is not totally empty
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non_empty = [cell.strip() for cell in row if cell.strip() != ""]
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if len(non_empty) >= 2:
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text_line = " | ".join(non_empty)
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if len(text_line) > 15:
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all_text.append(f"[{sheet_name}] {text_line}")
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return "\n".join(all_text)
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@@ -94,13 +92,12 @@ def init_agent() -> TxAgent:
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agent.init_model()
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return agent
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def analyze_serial(agent, batch_chunks: List[List[str]]) -> List[str]:
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results = []
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for idx,
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prompt =
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if estimate_tokens(prompt) > MAX_MODEL_TOKENS:
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results.append(f"β
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continue
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response = ""
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try:
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@@ -123,7 +120,7 @@ def analyze_serial(agent, batch_chunks: List[List[str]]) -> List[str]:
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response += r.content
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results.append(clean_response(response))
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except Exception as e:
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results.append(f"β Error in
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gc.collect()
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return results
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@@ -158,14 +155,13 @@ def process_report(agent, file, messages: List[Dict[str, str]]) -> Tuple[List[Di
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try:
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extracted = extract_text_from_excel(file.name)
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chunks = split_text(extracted)
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messages.append({"role": "assistant", "content": f"π Split into {len(batch_chunks)} batches. Analyzing..."})
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chunk_results = analyze_serial(agent,
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valid = [res for res in chunk_results if not res.startswith("β")]
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if not valid:
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messages.append({"role": "assistant", "content": "β No valid
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return messages, None
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summary = generate_final_summary(agent, "\n\n".join(valid))
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# Constants
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MAX_MODEL_TOKENS = 131072
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MAX_NEW_TOKENS = 4096
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MAX_CHUNK_TOKENS = 8192 # IMPORTANT: Split input into 8k tokens chunks
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PROMPT_OVERHEAD = 300
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# Paths
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persistent_dir = "/data/hf_cache"
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try:
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df = xls.parse(sheet_name).astype(str).fillna("")
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except Exception:
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continue
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for idx, row in df.iterrows():
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non_empty = [cell.strip() for cell in row if cell.strip() != ""]
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if len(non_empty) >= 2:
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text_line = " | ".join(non_empty)
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if len(text_line) > 15:
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all_text.append(f"[{sheet_name}] {text_line}")
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return "\n".join(all_text)
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agent.init_model()
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return agent
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def analyze_serial(agent, chunks: List[str]) -> List[str]:
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results = []
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for idx, chunk in enumerate(chunks):
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prompt = build_prompt(chunk)
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if estimate_tokens(prompt) > MAX_MODEL_TOKENS:
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results.append(f"β Chunk {idx+1} too long. Skipped.")
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continue
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response = ""
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try:
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response += r.content
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results.append(clean_response(response))
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except Exception as e:
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results.append(f"β Error in chunk {idx+1}: {str(e)}")
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gc.collect()
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return results
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try:
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extracted = extract_text_from_excel(file.name)
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chunks = split_text(extracted)
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messages.append({"role": "assistant", "content": f"π Split into {len(chunks)} chunks. Analyzing..."})
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chunk_results = analyze_serial(agent, chunks)
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valid = [res for res in chunk_results if not res.startswith("β")]
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if not valid:
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messages.append({"role": "assistant", "content": "β No valid chunk outputs."})
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return messages, None
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summary = generate_final_summary(agent, "\n\n".join(valid))
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