Merge pull request #1064 from cheshire-cat-ai/develop

1.9.1

Author: pieroit

.gitignore

@@ -19,6 +19,7 @@ local_vector_memory
 *metadata.json
 *metadata-test.json
 test_db.db
+/qdrant
 
 # old admin folder
 admin

core/cat/auth/connection.py

@@ -43,10 +43,10 @@ async def __call__(
         # extract credentials (user_id, token_or_key) from connection
         user_id, credential = self.extract_credentials(connection)
         auth_handlers = [
-            # try to get user from local idp
-            connection.app.state.ccat.core_auth_handler,
             # try to get user from auth_handler
             connection.app.state.ccat.custom_auth_handler,
+            # try to get user from local idp
+            connection.app.state.ccat.core_auth_handler,
         ]
         for ah in auth_handlers:
             user: AuthUserInfo = ah.authorize_user_from_credential(

core/cat/looking_glass/stray_cat.py

@@ -575,7 +575,7 @@ def run(self, user_message_json, return_message=False):
                     log.warning(ex)
 
     def classify(
-        self, sentence: str, labels: List[str] | Dict[str, List[str]]
+        self, sentence: str, labels: List[str] | Dict[str, List[str]], score_threshold: float = 0.5
     ) -> str | None:
         """Classify a sentence.
 
@@ -635,8 +635,7 @@ def classify(
             key=lambda x: x[1],
         )
 
-        # set 0.5 as threshold - let's see if it works properly
-        return best_label if score < 0.5 else None
+        return best_label if score < score_threshold else None
 
     def langchainfy_chat_history(self, latest_n: int = 20) -> List[BaseMessage]:
         """Redirects to WorkingMemory.langchainfy_chat_history. Will be removed from this class in v2."""

core/cat/memory/vector_memory_collection.py

@@ -95,7 +95,7 @@ def create_db_collection_if_not_exists(self):
     # create collection
     def create_collection(self):
         log.warning(f'Creating collection "{self.collection_name}" ...')
-        self.client.recreate_collection(
+        self.client.create_collection(
             collection_name=self.collection_name,
             vectors_config=VectorParams(
                 size=self.embedder_size, distance=Distance.COSINE
@@ -107,7 +107,6 @@ def create_collection(self):
                     type=ScalarType.INT8, quantile=0.95, always_ram=True
                 )
             ),
-            # shard_number=3,
         )
 
         self.client.update_collection_aliases(
@@ -219,9 +218,9 @@ def recall_memories_from_embedding(
     ):
         """Retrieve similar memories from embedding"""
 
-        memories = self.client.search(
+        memories = self.client.query_points(
             collection_name=self.collection_name,
-            query_vector=embedding,
+            query=embedding,
             query_filter=self._qdrant_filter_from_dict(metadata),
             with_payload=True,
             with_vectors=True,
@@ -234,7 +233,7 @@ def recall_memories_from_embedding(
                     oversampling=2.0,  # Available as of v1.3.0
                 )
             ),
-        )
+        ).points
 
         # convert Qdrant points to langchain.Document
         langchain_documents_from_points = []

core/cat/startup.py

@@ -124,11 +124,11 @@ async def validation_exception_handler(request, exc):
 # openapi customization
 cheshire_cat_api.openapi = get_openapi_configuration_function(cheshire_cat_api)
 
-
-@cheshire_cat_api.get("/docs", include_in_schema=False)
-async def scalar_docs():
-    return get_scalar_api_reference(
-        openapi_url=cheshire_cat_api.openapi_url,
-        title=cheshire_cat_api.title,
-        scalar_favicon_url="https://cheshirecat.ai/wp-content/uploads/2023/10/Logo-Cheshire-Cat.svg",
-    )
+if get_env("CCAT_DEBUG") == "true":
+    @cheshire_cat_api.get("/docs", include_in_schema=False)
+    async def scalar_docs():
+        return get_scalar_api_reference(
+            openapi_url=cheshire_cat_api.openapi_url,
+            title=cheshire_cat_api.title,
+            scalar_favicon_url="https://cheshirecat.ai/wp-content/uploads/2023/10/Logo-Cheshire-Cat.svg",
+        )

core/pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "Cheshire-Cat"
 description = "Production ready AI assistant framework"
-version = "1.9.0"
+version = "1.9.1"
 requires-python = ">=3.10"
 license = { file = "LICENSE" }
 authors = [
@@ -21,7 +21,7 @@ dependencies = [
     "Jinja2==3.1.4",
     "pandas==1.5.3",
     "scikit-learn==1.2.1",
-    "qdrant_client==1.11.0",
+    "qdrant_client==1.13.3",
     "langchain==0.2.1",
     "langchain-community==0.2.1",
     "langchain-ollama==0.1.3",