diff --git a/docs/docs/components/embeddings.mdx b/docs/docs/components/embeddings.mdx
index 015ba1ce1..d4ad17542 100644
--- a/docs/docs/components/embeddings.mdx
+++ b/docs/docs/components/embeddings.mdx
@@ -98,9 +98,9 @@ Used to load [OpenAI’s](https://openai.com/) embedding models.
Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) [Embeddings API](https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings).
-:::info
+
Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
-:::
+
- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
- **location:** The default location to use when making API calls – defaults to `us-central1`.
diff --git a/docs/docs/components/io.mdx b/docs/docs/components/io.mdx
index e0b8fb87d..0ef93d684 100644
--- a/docs/docs/components/io.mdx
+++ b/docs/docs/components/io.mdx
@@ -1,9 +1,8 @@
-
-import Admonition from '@theme/Admonition';
+import Admonition from "@theme/Admonition";
# I/O
-## ChatInput
+### ChatInput
This component is designed to get user input from the chat.
@@ -15,9 +14,7 @@ This component is designed to get user input from the chat.
- **Message:** specifies the message text. It is a multiline text input.
-- **Session ID:** specifies the session ID of the chat history.
-
-- **As Record:** if true, the message will be returned as a _`Record`_. Defaults to _`false`_.
+- **Session ID:** specifies the session ID of the chat history. If provided, the message will be saved in the Message History.
@@ -25,7 +22,7 @@ This component is designed to get user input from the chat.
-## ChatOutput
+### ChatOutput
This component is designed to send a message to the chat.
@@ -35,65 +32,21 @@ This component is designed to send a message to the chat.
- **Sender Name:** specifies the name of the sender. Defaults to _`"AI"`_.
-- **Session ID:** specifies the session ID of the chat history.
+- **Session ID:** specifies the session ID of the chat history. If provided, the message will be saved in the Message History.
- **Message:** specifies the message text.
-- **As Record:** if true, the message will be returned as a _`Record`_. Defaults to _`false`_.
-
If _`As Record`_ is _`true`_ and the _`Message`_ is a _`Record`_, the data of the _`Record`_ will be updated with the _`Sender`_, _`Sender Name`_, and _`Session ID`_.
-## StoreMessages
-This component is designed to store messages in a structured format. It can store messages provided directly as records or construct records from provided texts and metadata.
+### TextInput
-**Params**
+This component is designed for simple text input, allowing users to pass textual data to subsequent components in the workflow. It's particularly useful for scenarios where a brief user input is required to initiate or influence the flow.
-- **Records:** (Optional) Specifies the list of records to store. Each `Record` should contain the keys `'sender'`, `'sender_name'`, and `'session_id'`. If not provided, `texts` must be used along with `session_id`, `sender`, and `sender_name` to construct the records.
-
-- **Texts:** (Optional) Specifies the list of text messages to store. If `records` is not provided, `texts` must be provided along with `session_id`, `sender`, and `sender_name`.
-
-- **Session ID:** (Optional) Specifies the session ID associated with the messages. Required if `records` is not provided and `texts` are used.
-
-- **Sender:** (Optional) Specifies the identifier of the sender. Required if `records` is not provided and `texts` are used.
-
-- **Sender Name:** (Optional) Specifies the name of the sender. Required if `records` is not provided and `texts` are used.
-
-
-
- The component prioritizes the use of `Records` for storing messages. If `Records` are not provided, it requires `Texts`, `Session ID`, `Sender`, and `Sender Name` to construct and store records. Ensure that either `Records` or the combination of `Texts`, `Session ID`, `Sender`, and `Sender Name` is provided.
-
-
-
-## MessageHistory
-
-This component is designed to retrieve stored messages based on various filters such as sender type, sender name, and session ID. It allows for a flexible retrieval of chat history, providing insights into past interactions.
-
-**Params**
-
-- **Sender Type:** (Optional) Specifies the type of the sender. Options are _`"Machine"`_ or _`"User"`_. Filters the messages by the type of sender.
-
-- **Sender Name:** (Optional) Specifies the name of the sender. Filters the messages by the name of the sender.
-
-- **Session ID:** (Optional) Specifies the session ID of the chat history. Filters the messages belonging to a specific session.
-
-- **Number of Messages:** Specifies the number of messages to retrieve. Defaults to _`5`_. Determines how many recent messages from the chat history to fetch.
-
-
-
- The component retrieves messages based on the provided criteria. If no specific criteria are provided, it will return the most recent messages up to the specified limit. This component can be used to review past interactions and analyze the flow of conversations.
-
-
-
-
-
-## TextInput
-
-This component is designed for simple text input, allowing users to pass textual data to subsequent components in the workflow. It's particularly useful for scenarios where a brief user input is required to initiate or influence the process flow.
**Params**
@@ -101,6 +54,20 @@ This component is designed for simple text input, allowing users to pass textual
- The `TextInput` component serves as a straightforward means for capturing user input. It ensures that textual data can be seamlessly integrated into the Langflow's component-based processing pipeline, fostering interactivity within automated workflows.
+ The `TextInput` component serves as a straightforward means for setting Text input values in the chat window. It ensures that textual data can be seamlessly passed to subsequent components in the flow.
+
+### TextOutput
+
+This component is designed to display text data to the user. It's particularly useful for scenarios where you don't want to send the text data to the chat, but still want to display it.
+
+**Params**
+
+- **Value:** Specifies the text data to be displayed. This is where the text data to be displayed is provided. If no value is provided, it defaults to an empty string.
+
+
+
+ The `TextOutput` component serves as a straightforward means for displaying text data. It ensures that textual data can be seamlessly observed in the chat window throughout your flow.
+
+
\ No newline at end of file
diff --git a/docs/docs/components/llms.mdx b/docs/docs/components/llms.mdx
index 088556d2f..d72364376 100644
--- a/docs/docs/components/llms.mdx
+++ b/docs/docs/components/llms.mdx
@@ -40,9 +40,10 @@ Wrapper around Anthropic's large language model used for chat-based interactions
The `CTransformers` component provides access to the Transformer models implemented in C/C++ using the [GGML](https://github.com/ggerganov/ggml) library.
-:::info
+
+
Make sure to have the `ctransformers` python package installed. Learn more about installation, supported models, and usage [here](https://github.com/marella/ctransformers).
-:::
+
**config:** Configuration for the Transformer models. Check out [config](https://github.com/marella/ctransformers#config). Defaults to:
@@ -115,9 +116,9 @@ Wrapper around [Cohere's](https://cohere.com) large language models.
Wrapper around [HuggingFace](https://www.huggingface.co/models) models.
-:::info
+
The HuggingFace Hub is an online platform that hosts over 120k models, 20k datasets, and 50k demo apps, all of which are open-source and publicly available. Discover more at [HuggingFace](http://www.huggingface.co).
-:::
+
- **huggingfacehub_api_token:** Token needed to authenticate the API.
- **model_kwargs:** Keyword arguments to pass to the model.
@@ -130,9 +131,9 @@ The HuggingFace Hub is an online platform that hosts over 120k models, 20k datas
The `LlamaCpp` component provides access to the `llama.cpp` models.
-:::info
+
Make sure to have the `llama.cpp` python package installed. Learn more about installation, supported models, and usage [here](https://github.com/ggerganov/llama.cpp).
-:::
+
- **echo:** Whether to echo the prompt – defaults to `False`.
- **f16_kv:** Use half-precision for key/value cache – defaults to `True`.
@@ -181,9 +182,9 @@ Wrapper around [OpenAI's](https://openai.com) large language models.
Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) large language models.
-:::info
+
Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
-:::
+
- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
- **location:** The default location to use when making API calls – defaults to `us-central1`.
@@ -203,9 +204,9 @@ Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP).
Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) large language models.
-:::info
+
Vertex AI is a cloud computing platform offered by Google Cloud Platform (GCP). It provides access, management, and development of applications and services through global data centers. To use Vertex AI PaLM, you need to have the [google-cloud-aiplatform](https://pypi.org/project/google-cloud-aiplatform/) Python package installed and credentials configured for your environment.
-:::
+
- **credentials:** The default custom credentials (google.auth.credentials.Credentials) to use.
- **location:** The default location to use when making API calls – defaults to `us-central1`.
diff --git a/docs/docs/components/memories.mdx b/docs/docs/components/memories.mdx
index 3bf9a957c..b92538134 100644
--- a/docs/docs/components/memories.mdx
+++ b/docs/docs/components/memories.mdx
@@ -12,6 +12,26 @@ Memory is a concept in chat-based applications that allows the system to remembe
---
+### MessageHistory
+
+This component is designed to retrieve stored messages based on various filters such as sender type, sender name, session ID, and a specific file path where messages are stored. It allows for a flexible retrieval of chat history, providing insights into past interactions.
+
+**Params**
+
+- **Sender Type:** (Optional) Specifies the type of the sender. Options are _`"Machine"`_, _`"User"`_, or _`"Machine and User"`_. Filters the messages by the type of the sender.
+
+- **Sender Name:** (Optional) Specifies the name of the sender. Filters the messages by the name of the sender.
+
+- **Session ID:** (Optional) Specifies the session ID of the chat history. Filters the messages belonging to a specific session.
+
+- **Number of Messages:** Specifies the number of messages to retrieve. Defaults to _`5`_. Determines how many recent messages from the chat history to fetch.
+
+
+
+ The component retrieves messages based on the provided criteria, including the specific file path for stored messages. If no specific criteria are provided, it will return the most recent messages up to the specified limit. This component can be used to review past interactions and analyze the flow of conversations.
+
+
+
### ConversationBufferMemory
The `ConversationBufferMemory` component is a type of memory system that plainly stores the last few inputs and outputs of a conversation.
@@ -27,7 +47,7 @@ The `ConversationBufferMemory` component is a type of memory system that plainly
### ConversationBufferWindowMemory
-`ConversationBufferWindowMemory` is a variation of the `ConversationBufferMemory` that maintains a list of the recent interactions in a conversation. It only keeps the last K interactions in memory, which can be useful for maintaining a sliding window of the most recent interactions without letting the buffer get too large.
+`ConversationBufferWindowMemory` is a variation of the `ConversationBufferMemory` that maintains a list of the recent interactions in a conversation. It only keeps the last K interactions in memory, which can be useful for maintaining a sliding window of the most recent interactions without letting the buffer get too large.
**Params**
@@ -72,7 +92,7 @@ The `ConversationEntityMemory` component incorporates intricate memory structure
### ConversationSummaryMemory
-The `ConversationSummaryMemory` is a memory component that creates a summary of the conversation over time. It condenses information from the conversation and stores the current summary in memory. It is particularly useful for longer conversations where keeping the entire message history in the prompt would take up too many tokens.
+The `ConversationSummaryMemory` is a memory component that creates a summary of the conversation over time. It condenses information from the conversation and stores the current summary in memory. It is particularly useful for longer conversations where keeping the entire message history in the prompt would take up too many tokens.
**Params**
diff --git a/docs/docs/components/tools.mdx b/docs/docs/components/tools.mdx
index c92d6eee0..40fb2c5c2 100644
--- a/docs/docs/components/tools.mdx
+++ b/docs/docs/components/tools.mdx
@@ -9,6 +9,21 @@ import Admonition from '@theme/Admonition';
+### SearchApi
+
+Real-time search engine results API. Returns structured JSON data that includes answer box, knowledge graph, organic results, and more.
+
+**Parameters**
+
+- **Api Key:** A unique identifier for the SearchApi, necessary for authenticating requests to real-time search engines. This key can be retrieved from the [SearchApi dashboard](https://www.searchapi.io/).
+- **Engine:** Specifies the search engine. For instance: google, google_scholar, bing, youtube, and youtube_transcripts. A full list of supported engines is available in the [documentation](https://www.searchapi.io/docs/google).
+- **Parameters:** Allows the selection of any parameters recognized by SearchApi, with some being required and others optional.
+
+**Output**
+
+- **Document:** The JSON response from the request as a Document.
+
+
### BingSearchRun
Bing Search is a web search engine owned and operated by Microsoft. It provides search results for various types of content, including web pages, images, videos, and news articles. It uses a combination of algorithms and human editors to deliver search results to users.
@@ -60,4 +75,4 @@ Tool for getting metadata about a SQL database. The input to this tool is a comm
**Params**
-- **Db:** SQLDatabase to query.
\ No newline at end of file
+- **Db:** SQLDatabase to query.
diff --git a/docs/docs/contributing/community.md b/docs/docs/contributing/community.md
index 51016f508..6bb62641d 100644
--- a/docs/docs/contributing/community.md
+++ b/docs/docs/contributing/community.md
@@ -12,7 +12,7 @@
## 🐦 Stay tunned for **Langflow** on Twitter
-Follow [@logspace_ai](https://twitter.com/langflow_ai) on **Twitter** to get the latest news about **Langflow**.
+Follow [@langflow_ai](https://twitter.com/langflow_ai) on **Twitter** to get the latest news about **Langflow**.
---
## ⭐️ Star **Langflow** on GitHub
diff --git a/docs/docs/deployment/gcp-deployment.md b/docs/docs/deployment/gcp-deployment.md
index 771550f24..032426d94 100644
--- a/docs/docs/deployment/gcp-deployment.md
+++ b/docs/docs/deployment/gcp-deployment.md
@@ -4,9 +4,8 @@
This guide will help you set up a Langflow development VM in a Google Cloud Platform project using Google Cloud Shell.
-:::note
-When Cloud Shell opens, be sure to select **Trust repo**. Some `gcloud` commands might not run in an ephemeral Cloud Shell environment.
-:::
+> Note: When Cloud Shell opens, be sure to select **Trust repo**. Some `gcloud` commands might not run in an ephemeral Cloud Shell environment.
+
## Standard VM
diff --git a/docs/docs/examples/buffer-memory.mdx b/docs/docs/examples/buffer-memory.mdx
index 2b5b76586..3167081a5 100644
--- a/docs/docs/examples/buffer-memory.mdx
+++ b/docs/docs/examples/buffer-memory.mdx
@@ -14,6 +14,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
alt="Docusaurus themed image"
sources={{
light: "img/buffer-memory.png",
+ dark: "img/buffer-memory.png",
}}
/>
diff --git a/docs/docs/examples/conversation-chain.mdx b/docs/docs/examples/conversation-chain.mdx
index db3181881..1cd59ca55 100644
--- a/docs/docs/examples/conversation-chain.mdx
+++ b/docs/docs/examples/conversation-chain.mdx
@@ -20,6 +20,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
alt="Docusaurus themed image"
sources={{
light: "img/basic-chat.png",
+ dark: "img/basic-chat.png",
}}
/>
diff --git a/docs/docs/examples/csv-loader.mdx b/docs/docs/examples/csv-loader.mdx
index c59dfc1e7..351e99440 100644
--- a/docs/docs/examples/csv-loader.mdx
+++ b/docs/docs/examples/csv-loader.mdx
@@ -32,6 +32,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
alt="Docusaurus themed image"
sources={{
light: "img/csv-loader.png",
+ dark: "img/csv-loader.png",
}}
/>
@@ -39,12 +40,12 @@ import ZoomableImage from "/src/theme/ZoomableImage.js";
-
-
-
-
-
-
-
-
-
# 📦 Installation
@@ -65,7 +46,7 @@ This will install the following dependencies:
- [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)
- [sentence-transformers](https://github.com/UKPLab/sentence-transformers)
-You can still use models from projects like LocalAI
+You can still use models from projects like LocalAI, Ollama, LM Studio, Jan and others.
Next, run:
@@ -117,7 +98,7 @@ Each option is detailed below:
- `--backend-only`: This parameter, with a default value of `False`, allows running only the backend server without the frontend. It can also be set using the `LANGFLOW_BACKEND_ONLY` environment variable.
- `--store`: This parameter, with a default value of `True`, enables the store features, use `--no-store` to deactivate it. It can be configured using the `LANGFLOW_STORE` environment variable.
-These parameters are important for users who need to customize the behavior of Langflow, especially in development or specialized deployment scenarios. You may want to update the documentation to include these parameters for completeness and clarity.
+These parameters are important for users who need to customize the behavior of Langflow, especially in development or specialized deployment scenarios.
### Environment Variables
@@ -147,19 +128,19 @@ Alternatively, click the **"Open in Cloud Shell"** button below to launch Google
# 🎨 Creating Flows
-Creating flows with Langflow is easy. Simply drag sidebar components onto the canvas and connect them together to create your pipeline. Langflow provides a range of [LangChain components](https://python.langchain.com/docs/integrations/components) to choose from, including LLMs, prompt serializers, agents, and chains.
+Creating flows with Langflow is easy. Simply drag components from the sidebar onto the canvas and connect them to start building your application.
-Explore by editing prompt parameters, link chains and agents, track an agent's thought process, and export your flow.
+Explore by editing prompt parameters, grouping components into a single high-level component, and building your own Custom Components.
-Once you're done, you can export your flow as a JSON file to use with LangChain.
-To do so, click the "Export" button in the top right corner of the canvas, then
-in Python, you can load the flow with:
+Once you’re done, you can export your flow as a JSON file.
+
+Load the flow with:
```python
from langflow import load_flow_from_json
flow = load_flow_from_json("path/to/flow.json")
-# Now you can use it like any chain
+# Now you can use it
flow("Hey, have you heard of Langflow?")
```
@@ -167,15 +148,16 @@ flow("Hey, have you heard of Langflow?")
We welcome contributions from developers of all levels to our open-source project on GitHub. If you'd like to contribute, please check our [contributing guidelines](./CONTRIBUTING.md) and help make Langflow more accessible.
+Join our [Discord](https://discord.com/invite/EqksyE2EX9) server to ask questions, make suggestions, and showcase your projects! 🦾
+
---
-Join our [Discord](https://discord.com/invite/EqksyE2EX9) server to ask questions, make suggestions and showcase your projects! 🦾
-
-