Update agent.py
Browse files
agent.py
CHANGED
@@ -1,3 +1,4 @@
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import os
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import re
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import io
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@@ -23,145 +24,131 @@ class GaiaAgent:
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except Exception:
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return None, None
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def
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try:
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result = self.search_tool.run(question)
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return result[:1500] # Truncate to reduce GPT load
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except Exception:
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return "[NO WEB INFO FOUND]"
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def ask(self, context, question, model="gpt-4-turbo"):
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try:
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messages = [
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{"role": "system", "content": "You are a precise factual assistant. Use the context and answer only with the correct value. No explanation, no preface, only the final result."},
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{"role": "user", "content": f"Context:\n{context}\n\nQuestion:\n{question}\n\nAnswer:"}
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]
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response = self.client.chat.completions.create(
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model=
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messages=
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)
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return response.choices[0].message.content.strip()
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except Exception as e:
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return f"[ERROR: {e}]"
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def
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return
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if "algebraic notation" in q:
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match = re.search(r"\b([KQBNR]?[a-h]?[1-8]?x?[a-h][1-8][+#]?)\b",
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return match.group(1) if match else
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if "
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if "first name" in q:
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return
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if "page numbers" in q:
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nums = sorted(set(re.findall(r"\
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return ", ".join(nums)
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if "at bats" in q:
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match = re.search(r"\b
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return match.group(
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if "studio albums" in q or "how many" in q:
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try:
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return str(w2n.word_to_num(a))
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except:
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match = re.search(r"\b\d+\b", a)
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return match.group(0) if match else a
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if "
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match = re.search(r"
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return match.group(
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if "commutative" in q:
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clean = re.findall(r"[abcde]", a.lower())
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return ", ".join(sorted(set(clean)))
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if "vegetables" in q or "ingredients" in q:
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tokens = [t.lower() for t in re.findall(r"[a-zA-Z]+", a)]
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blacklist = {"extract", "juice", "pure", "vanilla", "sugar", "granulated", "fresh", "ripe", "pinch", "water", "whole", "cups", "salt"}
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clean = sorted(set(t for t in tokens if t not in blacklist and len(t) > 2))
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return ", ".join(clean)
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return a
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image_b64 = base64.b64encode(file_bytes).decode("utf-8")
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messages = [
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{"role": "system", "content": "You're a visual reasoning assistant. Answer based on the image. Return only the final move in chess notation."},
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{
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"role": "user",
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"content": [
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{"type": "text", "text": question},
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{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_b64}"}}
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]
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}
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]
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response = self.client.chat.completions.create(model="gpt-4o", messages=messages, timeout=25)
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return response.choices[0].message.content.strip()
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except Exception:
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return "[IMG ERROR]"
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elif "audio" in ctype or question.endswith(".mp3"):
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try:
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path = "/tmp/audio.mp3"
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with open(path, "wb") as f:
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f.write(file_bytes)
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transcript = self.client.audio.transcriptions.create(model="whisper-1", file=open(path, "rb"))
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return transcript.text[:2000]
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except:
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return "[AUDIO ERROR]"
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elif "excel" in ctype or question.endswith(".xlsx"):
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try:
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df = pd.read_excel(io.BytesIO(file_bytes), engine="openpyxl")
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df.columns = [c.lower() for c in df.columns]
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df['sales'] = pd.to_numeric(df['sales'], errors='coerce')
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food_df = df[df['category'].str.lower() == 'food']
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total = food_df['sales'].sum()
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return f"${total:.2f}" if not pd.isna(total) else "$0.00"
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except Exception:
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return "[EXCEL ERROR]"
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else:
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try:
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return file_bytes.decode("utf-8")[:3000]
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except:
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return ""
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def __call__(self, question, task_id=None):
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file_bytes,
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if task_id:
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file_bytes,
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if
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alt_prompt = "equine veterinarian name site:libretexts.org site:ck12.org"
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web_context = self.search_web_context(alt_prompt)
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raw = self.ask(web_context, question)
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return self.format_answer(raw, question)
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# agent_v34.py (wersja oparta na stabilnym V26 + precyzyjne poprawki logiczne)
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import os
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import re
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import io
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except Exception:
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return None, None
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def ask(self, context, question):
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try:
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response = self.client.chat.completions.create(
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model="gpt-4-turbo",
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messages=[
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{"role": "system", "content": "You are an expert assistant. Use the context to answer factually and precisely. Respond with only the final answer, without explanation."},
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{"role": "user", "content": f"Context:\n{context}\n\nQuestion:\n{question}\n\nAnswer:"}
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],
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temperature=0,
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timeout=25
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)
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return response.choices[0].message.content.strip()
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except Exception as e:
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return f"[ERROR: {e}]"
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def extract_web_context(self, question):
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try:
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return self.search_tool.run(question)[:1500]
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except:
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return ""
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def handle_file(self, content, content_type, question):
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if not content:
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return ""
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if "image" in content_type:
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image_b64 = base64.b64encode(content).decode("utf-8")
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messages = [
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{"role": "system", "content": "You're a chess assistant. Return only the best move for Black in algebraic notation. No commentary."},
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{
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"role": "user",
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"content": [
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{"type": "text", "text": question},
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{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_b64}"}}
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]
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}
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]
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response = self.client.chat.completions.create(model="gpt-4o", messages=messages, timeout=25)
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return response.choices[0].message.content.strip()
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if "audio" in content_type or question.endswith(".mp3"):
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try:
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path = "/tmp/audio.mp3"
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with open(path, "wb") as f:
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f.write(content)
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result = self.client.audio.transcriptions.create(model="whisper-1", file=open(path, "rb"))
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return result.text[:2000]
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except:
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return ""
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if "excel" in content_type:
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try:
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df = pd.read_excel(io.BytesIO(content), engine="openpyxl")
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df.columns = [c.lower() for c in df.columns]
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df['sales'] = pd.to_numeric(df['sales'], errors='coerce')
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df = df[df['category'].str.lower() == 'food']
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return f"${df['sales'].sum():.2f}"
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except:
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return "$0.00"
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try:
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return content.decode("utf-8")[:3000]
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except:
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return ""
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def format_answer(self, raw, question):
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q = question.lower()
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raw = raw.strip().strip("\"'")
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if "algebraic notation" in q:
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match = re.search(r"\b([KQBNR]?[a-h]?[1-8]?x?[a-h][1-8][+#]?)\b", raw)
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return match.group(1) if match else raw
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if "vegetables" in q or "ingredients" in q:
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tokens = re.findall(r"[a-zA-Z]+", raw.lower())
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ignored = {"extract", "juice", "pure", "vanilla", "sugar", "granulated", "fresh", "ripe", "pinch", "water", "whole", "cups", "salt"}
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items = sorted(set(t for t in tokens if t not in ignored and len(t) > 2))
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return ", ".join(items)
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if "commutative" in q:
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items = sorted(set(re.findall(r"[abcde]", raw)))
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return ", ".join(items)
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if "first name" in q:
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return raw.split()[0]
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if "award number" in q:
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match = re.search(r"80NSSC[0-9A-Z]+", raw)
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return match.group(0) if match else raw
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if "ioc country code" in q:
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match = re.search(r"\b[A-Z]{3}\b", raw.upper())
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return match.group(0) if match else raw
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if "page numbers" in q:
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nums = sorted(set(re.findall(r"\d+", raw)))
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return ", ".join(nums)
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if "at bats" in q:
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match = re.search(r"\b\d{3,4}\b", raw)
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return match.group(0) if match else raw
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if "usd with two decimal places" in q:
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match = re.search(r"([0-9]+(?:\.[0-9]{1,2})?)", raw)
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return f"${float(match.group(1)):.2f}" if match else "$0.00"
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try:
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return str(w2n.word_to_num(raw))
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except:
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match = re.search(r"\d+", raw)
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return match.group(0) if match else raw
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def __call__(self, question, task_id=None):
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file_bytes, file_type = (None, None)
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if task_id:
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file_bytes, file_type = self.fetch_file(task_id)
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context = self.handle_file(file_bytes, file_type, question) if file_bytes else self.extract_web_context(question)
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# fallback: use direct search prompt
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if not context.strip():
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prompt_map = {
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"youtube": "transcript of video site:youtube.com",
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"malko": "malko competition winner yugoslavia site:wikipedia.org",
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"veterinarian": "equine veterinarian site:libretexts.org site:ck12.org"
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}
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for k, v in prompt_map.items():
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if k in question.lower():
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context = self.extract_web_context(v)
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break
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raw = self.ask(context, question)
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return self.format_answer(raw, question)
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