diff --git a/.gitignore b/.gitignore
index 8adcec9..f7ab5d7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -163,4 +163,3 @@ cython_debug/
 config.json
 data.db
 posts/
-plots/
diff --git a/main.py b/main.py
index 83e5abe..a6f0074 100644
--- a/main.py
+++ b/main.py
@@ -10,10 +10,6 @@ import asyncio
 import aiosqlite
 import base64
 import logging
-import pandas as pd
-import plotly.express as px
-import plotly.graph_objs as go
-import plotly.io as pio
 from collections import defaultdict, Counter
 from pathlib import Path
 from urllib.parse import urlparse
@@ -67,7 +63,7 @@ class DDInterrogator(Interrogator):
             else:
                 original_danbooru_tag = tag
             if original_danbooru_tag == "safe":
-                original_danbooru_tag = "general"
+                continue
             new_lst.append(original_danbooru_tag)
         return new_lst
 
@@ -161,13 +157,13 @@ class Danbooru(Booru):
     title = "Danbooru"
     base_url = "https://danbooru.donmai.us"
 
-    async def posts(self, tag_query: str, limit, page: int):
+    async def posts(self, tag_query: str, limit):
         log.info("%s: submit %r", self.title, tag_query)
         async with self.limiter:
             log.info("%s: submit upstream %r", self.title, tag_query)
             async with self.session.get(
                 f"{self.base_url}/posts.json",
-                params={"tags": tag_query, "limit": limit, "page": page},
+                params={"tags": tag_query, "limit": limit},
             ) as resp:
                 assert resp.status == 200
                 rjson = await resp.json()
@@ -194,12 +190,7 @@ async def download_images(ctx):
     try:
         limit = int(sys.argv[3])
     except IndexError:
-        limit = 30
-
-    try:
-        pageskip = int(sys.argv[4])
-    except IndexError:
-        pageskip = 150
+        limit = 10
 
     danbooru = Danbooru(
         ctx.session,
@@ -207,7 +198,7 @@ async def download_images(ctx):
         AsyncLimiter(1, 3),
     )
 
-    posts = await danbooru.posts(tagquery, limit, pageskip)
+    posts = await danbooru.posts(tagquery, limit)
     for post in posts:
         if "md5" not in post:
             continue
@@ -408,101 +399,6 @@ async def scores(ctx):
             print("]")
         print("most incorrect tags", incorrect_tags_counters[model].most_common(5))
 
-    PLOTS = Path.cwd() / "plots"
-    PLOTS.mkdir(exist_ok=True)
-
-    log.info("plotting score histogram...")
-
-    data_for_df = {}
-    data_for_df["scores"] = []
-    data_for_df["model"] = []
-
-    for model in sorted(
-        normalized_scores.keys(),
-        key=lambda model: normalized_scores[model],
-        reverse=True,
-    ):
-        for post_score in (d["score"] for d in model_scores[model].values()):
-            data_for_df["scores"].append(post_score)
-            data_for_df["model"].append(model)
-
-    df = pd.DataFrame(data_for_df)
-    fig = px.histogram(
-        df,
-        x="scores",
-        color="model",
-        histfunc="count",
-        marginal="rug",
-        histnorm="probability",
-    )
-    pio.write_image(fig, PLOTS / "score_histogram.png", width=1024, height=800)
-
-    log.info("plotting positive histogram...")
-    plot2(PLOTS / "positive_score_histogram.png", normalized_scores, model_scores)
-    log.info("plotting error rates...")
-    plot3(PLOTS / "error_rate.png", normalized_scores, model_scores)
-
-
-def plot2(output_path, normalized_scores, model_scores):
-    data_for_df = {}
-    data_for_df["scores"] = []
-    data_for_df["model"] = []
-
-    for model in sorted(
-        normalized_scores.keys(),
-        key=lambda model: normalized_scores[model],
-        reverse=True,
-    ):
-        for post_score in (d["score"] for d in model_scores[model].values()):
-            if post_score < 0:
-                continue
-            data_for_df["scores"].append(post_score)
-            data_for_df["model"].append(model)
-
-    df = pd.DataFrame(data_for_df)
-    fig = px.histogram(
-        df,
-        x="scores",
-        color="model",
-        histfunc="count",
-        marginal="rug",
-        histnorm="probability",
-    )
-    pio.write_image(fig, output_path, width=1024, height=800)
-
-
-def plot3(output_path, normalized_scores, model_scores):
-    data_for_df = {"model": [], "errors": [], "rating_errors": []}
-
-    for model in sorted(
-        normalized_scores.keys(),
-        key=lambda model: normalized_scores[model],
-        reverse=True,
-    ):
-        total_incorrect_tags = 0
-        total_rating_errors = 0
-        for score_data in model_scores[model].values():
-            total_incorrect_tags += len(score_data["incorrect_tags"])
-            total_rating_errors += sum(
-                1
-                for rating in ["general", "sensitive", "questionable", "explicit"]
-                if rating in score_data["incorrect_tags"]
-            )
-
-        data_for_df["errors"].append(total_incorrect_tags)
-        data_for_df["rating_errors"].append(total_rating_errors)
-        data_for_df["model"].append(model)
-
-    df = pd.DataFrame(data_for_df)
-
-    fig = go.Figure(
-        data=[
-            go.Bar(name="incorrect tags", x=df.model, y=df.errors),
-            go.Bar(name="incorrect ratings", x=df.model, y=df.rating_errors),
-        ]
-    )
-    pio.write_image(fig, output_path, width=1024, height=800)
-
 
 async def realmain(ctx):
     await ctx.db.executescript(
diff --git a/requirements.txt b/requirements.txt
index 391859f..db0e4df 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,8 +1,3 @@
 aiosqlite==0.19.0
 aiohttp==3.8.4
-aiolimiter>1.1.0<2.0
-
-
-plotly>5.15.0<6.0
-pandas==2.0.2
-kaleido==0.2.1
\ No newline at end of file
+aiolimiter==1.1.0
\ No newline at end of file