fix: add guidance parameters for LC wrapper models (#255)

* fix: add docstring to LC wrapper models

* fix: fix metadata passing with LC embedding wrapper

flowsettings.py

@@ -208,6 +208,7 @@ KH_EMBEDDINGS["cohere"] = {
         "__type__": "kotaemon.embeddings.LCCohereEmbeddings",
         "model": "embed-multilingual-v2.0",
         "cohere_api_key": "your-key",
+        "user_agent": "default",
     },
     "default": False,
 }

libs/kotaemon/kotaemon/embeddings/langchain_based.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from kotaemon.base import Document, DocumentWithEmbedding
+from kotaemon.base import DocumentWithEmbedding, Param
 
 from .base import BaseEmbeddings
 
@@ -19,25 +19,14 @@ class LCEmbeddingMixin:
         super().__init__()
 
     def run(self, text):
-        input_: list[str] = []
+        input_docs = self.prepare_input(text)
-        if not isinstance(text, list):
+        input_ = [doc.text for doc in input_docs]
-            text = [text]
-
-        for item in text:
-            if isinstance(item, str):
-                input_.append(item)
-            elif isinstance(item, Document):
-                input_.append(item.text)
-            else:
-                raise ValueError(
-                    f"Invalid input type {type(item)}, should be str or Document"
-                )
 
         embeddings = self._obj.embed_documents(input_)
 
         return [
-            DocumentWithEmbedding(text=each_text, embedding=each_embedding)
+            DocumentWithEmbedding(content=doc, embedding=each_embedding)
-            for each_text, each_embedding in zip(input_, embeddings)
+            for doc, each_embedding in zip(input_docs, embeddings)
         ]
 
     def __repr__(self):
@@ -162,6 +151,20 @@ class LCAzureOpenAIEmbeddings(LCEmbeddingMixin, BaseEmbeddings):
 class LCCohereEmbeddings(LCEmbeddingMixin, BaseEmbeddings):
     """Wrapper around Langchain's Cohere embedding, focusing on key parameters"""
 
+    cohere_api_key: str = Param(
+        help="API key (https://dashboard.cohere.com/api-keys)",
+        default=None,
+        required=True,
+    )
+    model: str = Param(
+        help="Model name to use (https://docs.cohere.com/docs/models)",
+        default=None,
+        required=True,
+    )
+    user_agent: str = Param(
+        help="User agent (leave default)", default="default", required=True
+    )
+
     def __init__(
         self,
         model: str = "embed-english-v2.0",
@@ -190,6 +193,15 @@ class LCCohereEmbeddings(LCEmbeddingMixin, BaseEmbeddings):
 class LCHuggingFaceEmbeddings(LCEmbeddingMixin, BaseEmbeddings):
     """Wrapper around Langchain's HuggingFace embedding, focusing on key parameters"""
 
+    model_name: str = Param(
+        help=(
+            "Model name to use (https://huggingface.co/models?"
+            "pipeline_tag=sentence-similarity&sort=trending)"
+        ),
+        default=None,
+        required=True,
+    )
+
     def __init__(
         self,
         model_name: str = "sentence-transformers/all-mpnet-base-v2",

libs/kotaemon/kotaemon/llms/chats/langchain_based.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import logging
 from typing import AsyncGenerator, Iterator
 
-from kotaemon.base import BaseMessage, HumanMessage, LLMInterface
+from kotaemon.base import BaseMessage, HumanMessage, LLMInterface, Param
 
 from .base import ChatLLM
 
@@ -224,6 +224,17 @@ class LCAzureChatOpenAI(LCChatMixin, ChatLLM):  # type: ignore
 
 
 class LCAnthropicChat(LCChatMixin, ChatLLM):  # type: ignore
+    api_key: str = Param(
+        help="API key (https://console.anthropic.com/settings/keys)", required=True
+    )
+    model_name: str = Param(
+        help=(
+            "Model name to use "
+            "(https://docs.anthropic.com/en/docs/about-claude/models)"
+        ),
+        required=True,
+    )
+
     def __init__(
         self,
         api_key: str | None = None,
@@ -248,6 +259,17 @@ class LCAnthropicChat(LCChatMixin, ChatLLM):  # type: ignore
 
 
 class LCGeminiChat(LCChatMixin, ChatLLM):  # type: ignore
+    api_key: str = Param(
+        help="API key (https://aistudio.google.com/app/apikey)", required=True
+    )
+    model_name: str = Param(
+        help=(
+            "Model name to use (https://cloud.google"
+            ".com/vertex-ai/generative-ai/docs/learn/models)"
+        ),
+        required=True,
+    )
+
     def __init__(
         self,
         api_key: str | None = None,

libs/ktem/ktem/embeddings/manager.py

@@ -50,6 +50,7 @@ class EmbeddingManager:
                 }
                 if item.default:
                     self._default = item.name
+                    self._models["default"] = self._models[item.name]
 
     def load_vendors(self):
         from kotaemon.embeddings import (

libs/ktem/ktem/index/file/index.py

@@ -344,7 +344,7 @@ class FileIndex(BaseIndex):
     def get_admin_settings(cls):
         from ktem.embeddings.manager import embedding_models_manager
 
-        embedding_default = embedding_models_manager.get_default_name()
+        embedding_default = "default"
         embedding_choices = list(embedding_models_manager.options().keys())
 
         return {