WIP

.github/workflows/main.yml

@@ -18,26 +18,10 @@ permissions:
 env:
   PLUGIN_JSON: "0.0.1"
   TAG_EXISTS: false
-  PLUGIN_NAME: "my_plugin"
+  PLUGIN_NAME: "cranker"
 
 jobs:
-# This will be deleted by setup.py
-  check:
-    runs-on: ubuntu-latest
-    outputs:
-      plugin_name: ${{ steps.init.outputs.plugin_name }}
-    steps:
-    - name: Get plugin name
-      id: init
-      run: |
-        echo "plugin_name=${{ env.PLUGIN_NAME }}" >> $GITHUB_OUTPUT
-
-# This is the end of the removed section
   release:
-  # This will be deleted by setup.py
-    needs: check
-    if: startsWith(needs.check.outputs.plugin_name, 'MY_PLUGIN') == false
-  # This is the end of the removed section
     runs-on: ubuntu-latest
     steps:
       - name: Checkout

README.md

@@ -1,4 +1,4 @@
-# My plugin
+# Cranker
 
 [![awesome plugin](https://custom-icon-badges.demolab.com/static/v1?label=&message=awesome+plugin&color=383938&style=for-the-badge&logo=cheshire_cat_ai)](https://)  
 [![Awesome plugin](https://custom-icon-badges.demolab.com/static/v1?label=&message=Awesome+plugin&color=000000&style=for-the-badge&logo=cheshire_cat_ai)](https://)  

cranker.py

@@ -0,0 +1,39 @@
+from cat.mad_hatter.decorators import hook
+from .rankers import litm, get_settings, recentness
+
+
+@hook(priority=1)
+def after_cat_recalls_memories(cat) -> None:
+    """Hook after semantic search in memories.
+
+    The hook is executed just after the Cat searches for the meaningful context in memories
+    and stores it in the *Working Memory*.
+
+    Parameters
+    ----------
+    cat : CheshireCat
+        Cheshire Cat instance.
+
+    """
+    settings = get_settings()
+    if settings["RECENTNESS"]:
+        if cat.working_memory['episodic_memories']:
+            recent_docs = recentness(cat.working_memory['episodic_memories'])
+            cat.working_memory['episodic_memories'] = recent_docs
+        else:
+            print("#HicSuntGattones")
+
+    if settings["LITM"]:
+        if cat.working_memory['declarative_memories']:
+            litm_docs = litm(cat.working_memory['declarative_memories'])
+            cat.working_memory['declarative_memories'] = litm_docs
+        else:
+            print("#HicSuntGattones")
+
+    if settings["FILTER"]:
+        if cat.working_memory['procedural_memories']:
+            print("NON PUò ENTRAREEEEH!")
+        else:
+            print("#HicSuntGattones")
+    pass # do nothing
+

plugin.json

@@ -1,10 +1,10 @@
 {
-    "name": "My plugin",
+    "name": "Cheshire Cat Reranker",
     "version": "0.0.1",
-    "description": "Description of my_plugin.",
-    "author_name": "Me",
+    "description": "Description of cranker.",
+    "author_name": "nickprock",
     "author_url": "https://mywebsite.me",
-    "plugin_url": "https://github.com/my_name/my_plugin",
+    "plugin_url": "https://github.com/my_name/cranker",
     "tags": "cat, template, example",
-    "thumb": "https://raw.githubusercontent.com/my_repo_path/my_plugin.png"
+    "thumb": "https://raw.githubusercontent.com/my_repo_path/cranker.png"
 }

rankers.py

@@ -0,0 +1,67 @@
+import os
+import json
+def get_settings():
+    if os.path.isfile("cat/plugins/ccat_reranker/settings.json"):
+        with open("cat/plugins/ccat_reranker/settings.json", "r") as json_file:
+            settings = json.load(json_file)
+    return settings
+
+def recent_ranker(documents):
+    """
+    Returns document in memory sorted by date from most recent.
+
+    Parameters
+    ----------
+    documents: List of documents (the episodic working memories)
+
+    Returns
+    ----------
+    recent_docs: The same list but reordered
+    """
+    if len(documents) == 1:
+        return documents
+
+    recent_docs = sorted(documents, key=lambda d: d[0].metadata["when"], reverse=True)
+    return recent_docs
+
+def litm(documents):
+    """
+    Function based on Haystack's LITM ranker:
+    https://github.com/deepset-ai/haystack/blob/main/haystack/nodes/ranker/lost_in_the_middle.py
+
+    Lost In The Middle is based on the paper https://arxiv.org/abs/2307.03172
+    Check it for mor details.
+
+
+    Parameters
+    ----------
+    documents: List of documents (the declarative working memories)
+
+    Returns
+    ----------
+    litm_docs: The same list but reordered
+    """
+    if len(documents) == 1:
+        return documents
+
+    document_index = list(range(len(documents)))
+    lost_in_the_middle_indices = [0]
+
+    for doc_idx in document_index[1:]:
+        insertion_index = len(lost_in_the_middle_indices) // 2 + len(lost_in_the_middle_indices) % 2
+        lost_in_the_middle_indices.insert(insertion_index, doc_idx)
+        litm_docs = [documents[idx] for idx in lost_in_the_middle_indices]
+    return litm_docs
+
+def filter_ranker(documents):
+    """
+    Returns list of tools with a similarity score higher than 0.5.
+
+    Parameters
+    ----------
+    documents: List of documents (the procedural working memories)
+
+    Returns
+    ----------
+    tools: The same list but reordered
+    """