Telemetry support for ec cli commands (#1030)
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@@ -70,7 +70,7 @@ Feel free to edit the files as required.
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- `.env`: Contains environment variables for production
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- `.env.example`: Contains dummy environment variables (can ignore this file)
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- `embedchain.json`: Contains embedchain specific configuration for deployment (you don't need to configure this)
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- `requirements.txt`: Contains python dependencies for your FastAPI application
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- `requirements.txt`: Contains python dependencies for your application
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## Step-3: Test app locally
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@@ -8,6 +8,8 @@ import click
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import pkg_resources
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from rich.console import Console
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from embedchain.telemetry.posthog import AnonymousTelemetry
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console = Console()
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@@ -16,6 +18,26 @@ def cli():
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pass
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anonymous_telemetry = AnonymousTelemetry()
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def get_pkg_path_from_name(template: str):
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try:
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# Determine the installation location of the embedchain package
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package_path = pkg_resources.resource_filename("embedchain", "")
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except ImportError:
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console.print("❌ [bold red]Failed to locate the 'embedchain' package. Is it installed?[/bold red]")
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return
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# Construct the source path from the embedchain package
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src_path = os.path.join(package_path, "deployment", template)
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if not os.path.exists(src_path):
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console.print(f"❌ [bold red]Template '{template}' not found.[/bold red]")
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return
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return src_path
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def setup_fly_io_app(extra_args):
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fly_launch_command = ["fly", "launch", "--region", "sjc", "--no-deploy"] + list(extra_args)
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try:
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@@ -49,20 +71,10 @@ def setup_modal_com_app(extra_args):
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@click.option("--template", default="fly.io", help="The template to use.")
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@click.argument("extra_args", nargs=-1, type=click.UNPROCESSED)
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def create(template, extra_args):
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try:
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# Determine the installation location of the embedchain package
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package_path = pkg_resources.resource_filename("embedchain", "")
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except ImportError:
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console.print("❌ [bold red]Failed to locate the 'embedchain' package. Is it installed?[/bold red]")
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return
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# Construct the source path from the embedchain package
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src_path = os.path.join(package_path, "deployment", template)
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if not os.path.exists(src_path):
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console.print(f"❌ [bold red]Template '{template}' not found.[/bold red]")
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return
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anonymous_telemetry.capture(
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event_name="ec_create", properties={"template_used": template}
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)
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src_path = get_pkg_path_from_name(template)
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shutil.copytree(src_path, os.getcwd(), dirs_exist_ok=True)
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env_sample_path = os.path.join(src_path, ".env.example")
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if os.path.exists(env_sample_path):
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@@ -122,6 +134,9 @@ def dev(debug, host, port):
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embedchain_config = json.load(file)
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template = embedchain_config["provider"]
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anonymous_telemetry.capture(
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event_name="ec_dev", properties={"template_used": template}
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)
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if template == "fly.io":
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run_dev_fly_io(debug, host, port)
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elif template == "modal.com":
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@@ -207,6 +222,10 @@ def deploy():
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with open("embedchain.json", "r") as file:
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embedchain_config = json.load(file)
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template = embedchain_config["provider"]
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anonymous_telemetry.capture(
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event_name="ec_deploy", properties={"template_used": template}
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)
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if template == "fly.io":
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deploy_fly()
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elif template == "modal.com":
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@@ -2,6 +2,9 @@ from fastapi import FastAPI, responses
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from pydantic import BaseModel
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from embedchain import Pipeline
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from dotenv import load_dotenv
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load_dotenv(".env")
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app = FastAPI(title="Embedchain FastAPI App")
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embedchain_app = Pipeline()
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@@ -1,4 +1,4 @@
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fastapi==0.104.0
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uvicorn==0.23.2
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embedchain==0.1.34
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embedchain
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beautifulsoup4
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@@ -1,4 +1,4 @@
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modal==0.56.4329
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fastapi==0.104.0
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uvicorn==0.23.2
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embedchain==0.1.34
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embedchain
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@@ -33,14 +33,16 @@ class OpenAILlm(BaseLlm):
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if config.top_p:
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kwargs["model_kwargs"]["top_p"] = config.top_p
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if config.stream:
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from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
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from langchain.callbacks.streaming_stdout import \
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StreamingStdOutCallbackHandler
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callbacks = config.callbacks if config.callbacks else [StreamingStdOutCallbackHandler()]
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chat = ChatOpenAI(**kwargs, streaming=config.stream, callbacks=callbacks)
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else:
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chat = ChatOpenAI(**kwargs)
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if self.functions is not None:
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from langchain.chains.openai_functions import create_openai_fn_runnable
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from langchain.chains.openai_functions import \
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create_openai_fn_runnable
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from langchain.prompts import ChatPromptTemplate
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structured_prompt = ChatPromptTemplate.from_messages(messages)
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@@ -1,7 +1,9 @@
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import os
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from embedchain import Pipeline as App
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import streamlit as st
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from embedchain import Pipeline as App
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with st.sidebar:
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huggingface_access_token = st.text_input("Hugging face Token", key="chatbot_api_key", type="password")
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"[Get Hugging Face Access Token](https://huggingface.co/settings/tokens)"
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@@ -1,6 +1,6 @@
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[tool.poetry]
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name = "embedchain"
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version = "0.1.35"
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version = "0.1.36"
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description = "Data platform for LLMs - Load, index, retrieve and sync any unstructured data"
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authors = [
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"Taranjeet Singh <taranjeet@embedchain.ai>",
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