Fix online feat and add docs (#1387)

embedchain/config/llm/base.py

@@ -89,6 +89,7 @@ class BaseLlmConfig(BaseConfig):
         max_tokens: int = 1000,
         top_p: float = 1,
         stream: bool = False,
+        online: bool = False,
         deployment_name: Optional[str] = None,
         system_prompt: Optional[str] = None,
         where: dict[str, Any] = None,
@@ -129,6 +130,8 @@ class BaseLlmConfig(BaseConfig):
         :type top_p: float, optional
         :param stream: Control if response is streamed back to user, defaults to False
         :type stream: bool, optional
+        :param online: Controls whether to use internet for answering query, defaults to False
+        :type online: bool, optional
         :param deployment_name: t.b.a., defaults to None
         :type deployment_name: Optional[str], optional
         :param system_prompt: System prompt string, defaults to None
@@ -181,6 +184,7 @@ class BaseLlmConfig(BaseConfig):
         self.http_async_client = http_async_client
         self.local = local
         self.default_headers = default_headers
+        self.online = online
 
         if isinstance(prompt, str):
             prompt = Template(prompt)

embedchain/embedchain.py

@@ -6,9 +6,7 @@ from typing import Any, Optional, Union
 from dotenv import load_dotenv
 from langchain.docstore.document import Document
 
-from embedchain.cache import (adapt, get_gptcache_session,
-                              gptcache_data_convert,
-                              gptcache_update_cache_callback)
+from embedchain.cache import adapt, get_gptcache_session, gptcache_data_convert, gptcache_update_cache_callback
 from embedchain.chunkers.base_chunker import BaseChunker
 from embedchain.config import AddConfig, BaseLlmConfig, ChunkerConfig
 from embedchain.config.base_app_config import BaseAppConfig
@@ -18,8 +16,7 @@ from embedchain.embedder.base import BaseEmbedder
 from embedchain.helpers.json_serializable import JSONSerializable
 from embedchain.llm.base import BaseLlm
 from embedchain.loaders.base_loader import BaseLoader
-from embedchain.models.data_type import (DataType, DirectDataType,
-                                         IndirectDataType, SpecialDataType)
+from embedchain.models.data_type import DataType, DirectDataType, IndirectDataType, SpecialDataType
 from embedchain.utils.misc import detect_datatype, is_valid_json_string
 from embedchain.vectordb.base import BaseVectorDB
 
@@ -97,13 +94,13 @@ class EmbedChain(JSONSerializable):
 
     @property
     def online(self):
-        return self.llm.online
+        return self.llm.config.online
 
     @online.setter
     def online(self, value):
         if not isinstance(value, bool):
             raise ValueError(f"Boolean value expected but got {type(value)}.")
-        self.llm.online = value
+        self.llm.config.online = value
 
     def add(
         self,

embedchain/llm/base.py

@@ -5,9 +5,7 @@ from typing import Any, Optional
 from langchain.schema import BaseMessage as LCBaseMessage
 
 from embedchain.config import BaseLlmConfig
-from embedchain.config.llm.base import (DEFAULT_PROMPT,
-                                        DEFAULT_PROMPT_WITH_HISTORY_TEMPLATE,
-                                        DOCS_SITE_PROMPT_TEMPLATE)
+from embedchain.config.llm.base import DEFAULT_PROMPT, DEFAULT_PROMPT_WITH_HISTORY_TEMPLATE, DOCS_SITE_PROMPT_TEMPLATE
 from embedchain.helpers.json_serializable import JSONSerializable
 from embedchain.memory.base import ChatHistory
 from embedchain.memory.message import ChatMessage
@@ -29,7 +27,6 @@ class BaseLlm(JSONSerializable):
 
         self.memory = ChatHistory()
         self.is_docs_site_instance = False
-        self.online = False
         self.history: Any = None
 
     def get_llm_model_answer(self):
@@ -213,7 +210,7 @@ class BaseLlm(JSONSerializable):
                 self.config.prompt = DOCS_SITE_PROMPT_TEMPLATE
                 self.config.number_documents = 5
             k = {}
-            if self.online:
+            if self.config.online:
                 k["web_search_result"] = self.access_search_and_get_results(input_query)
             prompt = self.generate_prompt(input_query, contexts, **k)
             logger.info(f"Prompt: {prompt}")
@@ -268,7 +265,7 @@ class BaseLlm(JSONSerializable):
                 self.config.prompt = DOCS_SITE_PROMPT_TEMPLATE
                 self.config.number_documents = 5
             k = {}
-            if self.online:
+            if self.config.online:
                 k["web_search_result"] = self.access_search_and_get_results(input_query)
 
             prompt = self.generate_prompt(input_query, contexts, **k)

embedchain/utils/misc.py

@@ -419,6 +419,7 @@ def validate_config(config_data):
                     Optional("max_tokens"): int,
                     Optional("top_p"): Or(float, int),
                     Optional("stream"): bool,
+                    Optional("online"): bool,
                     Optional("template"): str,
                     Optional("prompt"): str,
                     Optional("system_prompt"): str,