Merge branch 'main' into refactoring_examples_folder

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Marco Vinciguerra 2024-04-09 11:46:34 +02:00 committed by GitHub
commit b4e640879d
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7 changed files with 20 additions and 11 deletions

8
poetry.lock generated
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@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
[[package]]
name = "aiohttp"
@ -1117,13 +1117,13 @@ extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
[[package]]
name = "langsmith"
version = "0.1.40"
version = "0.1.41"
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
optional = false
python-versions = "<4.0,>=3.8.1"
files = [
{file = "langsmith-0.1.40-py3-none-any.whl", hash = "sha256:aa47d0f5a1eabd5c05ac6ce2cd3e28ccfc554d366e856a27b7c3c17c443881cb"},
{file = "langsmith-0.1.40.tar.gz", hash = "sha256:50fdf313741cf94e978de06025fd180b56acf1d1a4549b0fd5453ef23d5461ef"},
{file = "langsmith-0.1.41-py3-none-any.whl", hash = "sha256:11de22b6990502c630fdfdf6906681e664c6659d2118bcd2b79d08016e770831"},
{file = "langsmith-0.1.41.tar.gz", hash = "sha256:1250cd6c9074ca10d40002b23d79b3017329b139fbe954248fdd7a79544e90d0"},
]
[package.dependencies]

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@ -1,6 +1,6 @@
[tool.poetry]
name = "scrapegraphai"
version = "0.1.0"
version = "0.1.1"
description = "A web scraping library based on LangChain which uses LLM and direct graph logic to create scraping pipelines."
authors = [
"Marco Vinciguerra <mvincig11@gmail.com>",

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@ -59,7 +59,14 @@ class AbstractGraph(ABC):
return Gemini(llm_params)
elif "ollama" in llm_params["model"]:
# take the model after the last dash
"""
Avaiable models:
- llama2
- mistral
- codellama
- dolphin-mixtral
- mistral-openorca
"""
llm_params["model"] = llm_params["model"].split("/")[-1]
try:
self.model_token = models_tokens["ollama"][llm_params["model"]]

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@ -2,7 +2,7 @@
Module for converting text to speach
"""
from scrapegraphai.utils.save_audio_from_bytes import save_audio_from_bytes
from ..models import OpenAI, Gemini, OpenAITextToSpeech
from ..models import OpenAITextToSpeech
from .base_graph import BaseGraph
from ..nodes import (
FetchNode,

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@ -24,6 +24,8 @@ models_tokens = {
"ollama": {
"llama2": 4096,
"mistral": 8192,
"codellama": 16000,
"dolphin-mixtral": 32000,
"mistral-openorca": 32000,
}
}

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@ -67,8 +67,8 @@ class FetchNode(BaseNode):
# Fetching data from the state based on the input keys
input_data = [state[key] for key in input_keys]
source = input_data[0]
source = input_data[0]
# if it is a local directory
if not source.startswith("http"):
document = [Document(page_content=source, metadata={

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@ -8,8 +8,8 @@ from langchain.retrievers import ContextualCompressionRetriever
from langchain.retrievers.document_compressors import EmbeddingsFilter, DocumentCompressorPipeline
from langchain_community.document_transformers import EmbeddingsRedundantFilter
from langchain_community.vectorstores import FAISS
from ..models import OpenAI, Gemini, Ollama, AzureOpenAI
from langchain_openai import OpenAIEmbeddings, AzureOpenAIEmbeddings
from ..models import OpenAI, Ollama, AzureOpenAI
from langchain_community.embeddings import OllamaEmbeddings
from .base_node import BaseNode