From 6a83c2306d6d1a9dc5a96af5dd6a6064519f1e3b Mon Sep 17 00:00:00 2001 From: "EURAC\\marperini" Date: Sun, 7 Apr 2024 11:08:08 +0200 Subject: [PATCH 1/4] docker compose working ollama implementation --- .streamlit/config.toml | 6 -- .streamlit/credentials.toml | 2 - docker-compose.yml | 13 +++ examples/graph_evaluation_example.py | 43 --------- examples/ollama-example.py | 7 ++ pyproject.toml | 1 - requirements.txt | 1 - scrapegraphai/evaluators/__init__.py | 4 - scrapegraphai/evaluators/trulens_evaluator.py | 88 ------------------- scrapegraphai/graphs/search_graph.py | 4 +- scrapegraphai/models/__init__.py | 1 + scrapegraphai/models/ollama.py | 19 ++++ scrapegraphai/nodes/search_internet_node.py | 3 +- 13 files changed, 45 insertions(+), 147 deletions(-) delete mode 100644 .streamlit/config.toml delete mode 100644 .streamlit/credentials.toml create mode 100644 docker-compose.yml delete mode 100644 examples/graph_evaluation_example.py create mode 100644 examples/ollama-example.py delete mode 100644 scrapegraphai/evaluators/__init__.py delete mode 100644 scrapegraphai/evaluators/trulens_evaluator.py create mode 100644 scrapegraphai/models/ollama.py diff --git a/.streamlit/config.toml b/.streamlit/config.toml deleted file mode 100644 index 43a50cbc..00000000 --- a/.streamlit/config.toml +++ /dev/null @@ -1,6 +0,0 @@ -[theme] -primaryColor="#0A2C37" -backgroundColor="#FFFFFF" -secondaryBackgroundColor="F5F5F5" -textColor="#0A2C37" -font="sans serif" diff --git a/.streamlit/credentials.toml b/.streamlit/credentials.toml deleted file mode 100644 index b87ca415..00000000 --- a/.streamlit/credentials.toml +++ /dev/null @@ -1,2 +0,0 @@ -[general] -email="" diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 00000000..abcceb27 --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,13 @@ +version: '3.8' +services: + ollama: + image: ollama/ollama + container_name: ollama + ports: + - "11434:11434" + volumes: + - ollama_volume:/root/.ollama + restart: unless-stopped + +volumes: + ollama_volume: diff --git a/examples/graph_evaluation_example.py b/examples/graph_evaluation_example.py deleted file mode 100644 index f5970de7..00000000 --- a/examples/graph_evaluation_example.py +++ /dev/null @@ -1,43 +0,0 @@ -""" -Module for evaluating the graph -""" -import os -from dotenv import load_dotenv -from scrapegraphai.evaluators import TrulensEvaluator - -load_dotenv() -openai_key = os.getenv("OPENAI_APIKEY") - -# Define the configuration for the graph -graph_config = { - "llm": { - "api_key": openai_key, - "model": "gpt-3.5-turbo", - }, -} - -list_of_inputs = [ - ( - "List me all the titles and project descriptions", - "https://perinim.github.io/projects/", - graph_config - ), - ( - "Who is the author of the project?", - "https://perinim.github.io/projects/", - graph_config - ), - ( - "What are the projects about?", - "https://perinim.github.io/projects/", - graph_config - ), -] - -# Create the TrulensEvaluator instance -trulens_evaluator = TrulensEvaluator(graph_config["llm"]["api_key"]) -# Evaluate SmartScraperGraph on the list of inputs -(results_df, answer) = trulens_evaluator.evaluate( - list_of_inputs, dashboard=True) - -print(answer) diff --git a/examples/ollama-example.py b/examples/ollama-example.py new file mode 100644 index 00000000..2b7e79a5 --- /dev/null +++ b/examples/ollama-example.py @@ -0,0 +1,7 @@ +from langchain_community.llms import Ollama + +llm = Ollama(model="llama2") + +answer = llm.invoke("Tell me a joke") + +print(answer) \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 7f53d3aa..28d73018 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,7 +30,6 @@ langchain_google_genai = "0.0.11" html2text = "2020.1.16" faiss-cpu = "1.7.4" beautifulsoup4 = "4.12.3" -trulens_eval = "0.23.0" pandas = "2.0.3" python-dotenv = "1.0.1" tiktoken = {version = ">=0.5.2,<0.6.0"} diff --git a/requirements.txt b/requirements.txt index 3f387f1a..3197e199 100644 --- a/requirements.txt +++ b/requirements.txt @@ -10,4 +10,3 @@ pandas==2.0.3 python-dotenv==1.0.1 tiktoken>=0.5.2,<0.6.0 tqdm==4.66.1 -trulens_eval==0.23.0 diff --git a/scrapegraphai/evaluators/__init__.py b/scrapegraphai/evaluators/__init__.py deleted file mode 100644 index 98d738f2..00000000 --- a/scrapegraphai/evaluators/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -""" -__init__.py file for evaluetor folder -""" -from .trulens_evaluator import TrulensEvaluator diff --git a/scrapegraphai/evaluators/trulens_evaluator.py b/scrapegraphai/evaluators/trulens_evaluator.py deleted file mode 100644 index d6011a95..00000000 --- a/scrapegraphai/evaluators/trulens_evaluator.py +++ /dev/null @@ -1,88 +0,0 @@ -"""Module for making the RAG""" -from trulens_eval import Feedback, OpenAI, Tru, Provider, Select, TruBasicApp -from scrapegraphai.graphs import SmartScraperGraph - - -class TrulensEvaluator: - """ - Class for evaluating Trulens using SmartScraperGraph. - - Attributes: - - tru_llm_standalone_recorder: TruBasicApp instance for recording. - - Methods: - evaluate: Evaluates Trulens using SmartScraperGraph. - llm_standalone: Standalone function for Trulens evaluation. - """ - - def __init__(self, key: str): - """ - Initialization of the class - Arguments: - - key (str): openai key - """ - standalone = StandAlone() - self.f_custom_function = Feedback(standalone.json_complaint).on( - my_text_field=Select.RecordOutput - ) - self.tru = Tru() - self.tru.reset_database() - self.openai = OpenAI(api_key=key) - self.f_relevance = Feedback(self.openai.relevance).on_input_output() - self.tru_llm_standalone_recorder = TruBasicApp(self.llm_standalone, - app_id="smart_scraper_evaluator", - feedbacks=[self.f_relevance, - self.f_custom_function]) - self.graph_output = [] - - def evaluate(self, graph_params: list[tuple[str, str, dict]], dashboard: bool = True): - """ - Evaluates Trulens using SmartScraperGraph and starts the dashboard. - - Args: - graph_params: List of tuples containing graph parameters. - - Returns: - None - """ - - with self.tru_llm_standalone_recorder as recording: - for params in graph_params: - output = SmartScraperGraph(*params).run() - self.tru_llm_standalone_recorder.app(params[0], output) - self.graph_output.append(output) - - if dashboard: - self.tru.run_dashboard() - - return (self.tru.get_records_and_feedback(app_ids=[])[0], self.graph_output) - - def llm_standalone(self, prompt, response): - """ - Standalone function for Trulens evaluation. Private method. - - Args: - prompt: Prompt for evaluation. - response: Response from evaluation. - - Returns: - str: Response as a string. - """ - print(f"Prompt: {prompt}") - return str(response) - - -class StandAlone(Provider): - """ - Class for standalone Trulens evaluation. - """ - - def json_complaint(self, my_text_field: str) -> float: - """ - Args: - - my_text_field (str): textfield - """ - if '{' in my_text_field and '}' in my_text_field and ':' in my_text_field: - return 1.0 - return 0.0 diff --git a/scrapegraphai/graphs/search_graph.py b/scrapegraphai/graphs/search_graph.py index c5f3a6a5..88c3fc4d 100644 --- a/scrapegraphai/graphs/search_graph.py +++ b/scrapegraphai/graphs/search_graph.py @@ -1,7 +1,7 @@ """ Module for making the search on the intenet """ -from ..models import OpenAI, Gemini +from ..models import OpenAI, Gemini, Ollama from .base_graph import BaseGraph from ..nodes import ( SearchInternetNode, @@ -33,6 +33,8 @@ def _create_llm(self, llm_config: dict): return OpenAI(llm_params) elif "gemini" in llm_params["model"]: return Gemini(llm_params) + elif "llama2" in llm_params["model"]: + return Ollama(llm_params) else: raise ValueError("Model not supported") diff --git a/scrapegraphai/models/__init__.py b/scrapegraphai/models/__init__.py index 985a9153..4d2d9134 100644 --- a/scrapegraphai/models/__init__.py +++ b/scrapegraphai/models/__init__.py @@ -6,3 +6,4 @@ from .openai_itt import OpenAIImageToText from .openai_tts import OpenAITextToSpeech from .gemini import Gemini +from .ollama import Ollama diff --git a/scrapegraphai/models/ollama.py b/scrapegraphai/models/ollama.py new file mode 100644 index 00000000..9636a257 --- /dev/null +++ b/scrapegraphai/models/ollama.py @@ -0,0 +1,19 @@ +""" +openai configuration wrapper +""" +from langchain_community.chat_models import ChatOllama + + +class Ollama(ChatOllama): + """Class for wrapping ollama module""" + + def __init__(self, llm_config: dict): + """ + A wrapper for the ChatOllama class that provides default configuration + and could be extended with additional methods if needed. + + Args: + llm_config (dict): Configuration parameters for the language model. + """ + # Initialize the superclass (ChatOllama) with provided config parameters + super().__init__(**llm_config) diff --git a/scrapegraphai/nodes/search_internet_node.py b/scrapegraphai/nodes/search_internet_node.py index 88297c1d..2d49b8f6 100644 --- a/scrapegraphai/nodes/search_internet_node.py +++ b/scrapegraphai/nodes/search_internet_node.py @@ -82,7 +82,8 @@ def execute(self, state): search_template = """Given the following user prompt, return a query that can be used to search the internet for relevant information. \n - You should return only the query string. \n + You should return only the query string without any additional sentences. \n + You are taught to reply directly giving the search query. \n User Prompt: {user_prompt}""" search_prompt = PromptTemplate( From 17add20c1364e4b73bd76bbaac1f2a822a09acaf Mon Sep 17 00:00:00 2001 From: "EURAC\\marperini" Date: Mon, 8 Apr 2024 12:18:32 +0200 Subject: [PATCH 2/4] implemented node_config, add embedder model choice, add azure endpoint, refactor graphs and exmaples --- examples/.env.example | 6 +- examples/custom_graph_gemini.py | 25 +- examples/custom_graph_openai.py | 25 +- examples/ollama-example.py | 7 - examples/scrape_plain_text.py | 28 +- examples/scrape_xml_document.py | 27 +- examples/search_graph_example.py | 18 +- examples/smart_scraper_example.py | 15 +- examples/speech_graph_example.py | 18 +- poetry.lock | 1758 ++----------------- pyproject.toml | 10 +- scrapegraphai/graphs/abstract_graph.py | 30 +- scrapegraphai/graphs/search_graph.py | 31 +- scrapegraphai/graphs/smart_scraper_graph.py | 23 +- scrapegraphai/graphs/speech_graph.py | 26 +- scrapegraphai/models/__init__.py | 1 + scrapegraphai/models/azure_openai.py | 18 + scrapegraphai/nodes/base_node.py | 4 +- scrapegraphai/nodes/fetch_node.py | 3 +- scrapegraphai/nodes/generate_answer_node.py | 6 +- scrapegraphai/nodes/image_to_text_node.py | 8 +- scrapegraphai/nodes/rag_node.py | 30 +- scrapegraphai/nodes/search_internet_node.py | 8 +- scrapegraphai/nodes/text_to_speech_node.py | 6 +- 24 files changed, 333 insertions(+), 1798 deletions(-) delete mode 100644 examples/ollama-example.py create mode 100644 scrapegraphai/models/azure_openai.py diff --git a/examples/.env.example b/examples/.env.example index 7340d180..1f38084e 100644 --- a/examples/.env.example +++ b/examples/.env.example @@ -1,2 +1,4 @@ -OPENAI_APIKEY="your openai.com api key" -GOOGLE_APIKEY="your google.com api key" \ No newline at end of file +OPENAI_APIKEY="your openai api key" +GOOGLE_APIKEY="your google api key" +AZURE_OPENAI_API_KEY="your azure api key" +AZURE_OPENAI_ENDPOINT="https://.openai.azure.com/" \ No newline at end of file diff --git a/examples/custom_graph_gemini.py b/examples/custom_graph_gemini.py index 581d186d..9ecae73b 100644 --- a/examples/custom_graph_gemini.py +++ b/examples/custom_graph_gemini.py @@ -7,11 +7,14 @@ from scrapegraphai.models import Gemini from scrapegraphai.graphs import BaseGraph from scrapegraphai.nodes import FetchNode, ParseNode, RAGNode, GenerateAnswerNode - load_dotenv() -gemini_key = os.getenv("GOOGLE_APIKEY") +# ************************************************ # Define the configuration for the graph +# ************************************************ + +gemini_key = os.getenv("GOOGLE_APIKEY") + graph_config = { "llm": { "api_key": gemini_key, @@ -21,6 +24,10 @@ }, } +# ************************************************ +# Define the graph nodes +# ************************************************ + llm_model = Gemini(graph_config["llm"]) # define the nodes for the graph @@ -35,15 +42,18 @@ rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", output=["relevant_chunks"], - model_config={"llm_model": llm_model}, + node_config={"llm": llm_model}, ) generate_answer_node = GenerateAnswerNode( input="user_prompt & (relevant_chunks | parsed_doc | doc)", output=["answer"], - model_config={"llm_model": llm_model}, + node_config={"llm": llm_model}, ) -# create the graph by defining the nodes and their connections +# ************************************************ +# Create the graph by defining the connections +# ************************************************ + graph = BaseGraph( nodes={ fetch_node, @@ -59,7 +69,10 @@ entry_point=fetch_node ) -# execute the graph +# ************************************************ +# Execute the graph +# ************************************************ + result = graph.execute({ "user_prompt": "List me the projects with their description", "url": "https://perinim.github.io/projects/" diff --git a/examples/custom_graph_openai.py b/examples/custom_graph_openai.py index 48fbc9d6..943838fc 100644 --- a/examples/custom_graph_openai.py +++ b/examples/custom_graph_openai.py @@ -7,11 +7,14 @@ from scrapegraphai.models import OpenAI from scrapegraphai.graphs import BaseGraph from scrapegraphai.nodes import FetchNode, ParseNode, RAGNode, GenerateAnswerNode - load_dotenv() -openai_key = os.getenv("OPENAI_APIKEY") +# ************************************************ # Define the configuration for the graph +# ************************************************ + +openai_key = os.getenv("OPENAI_APIKEY") + graph_config = { "llm": { "api_key": openai_key, @@ -21,6 +24,10 @@ }, } +# ************************************************ +# Define the graph nodes +# ************************************************ + llm_model = OpenAI(graph_config["llm"]) # define the nodes for the graph @@ -35,15 +42,18 @@ rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", output=["relevant_chunks"], - model_config={"llm_model": llm_model}, + node_config={"llm": llm_model}, ) generate_answer_node = GenerateAnswerNode( input="user_prompt & (relevant_chunks | parsed_doc | doc)", output=["answer"], - model_config={"llm_model": llm_model}, + node_config={"llm": llm_model}, ) -# create the graph by defining the nodes and their connections +# ************************************************ +# Create the graph by defining the connections +# ************************************************ + graph = BaseGraph( nodes={ fetch_node, @@ -59,7 +69,10 @@ entry_point=fetch_node ) -# execute the graph +# ************************************************ +# Execute the graph +# ************************************************ + result = graph.execute({ "user_prompt": "List me the projects with their description", "url": "https://perinim.github.io/projects/" diff --git a/examples/ollama-example.py b/examples/ollama-example.py deleted file mode 100644 index 2b7e79a5..00000000 --- a/examples/ollama-example.py +++ /dev/null @@ -1,7 +0,0 @@ -from langchain_community.llms import Ollama - -llm = Ollama(model="llama2") - -answer = llm.invoke("Tell me a joke") - -print(answer) \ No newline at end of file diff --git a/examples/scrape_plain_text.py b/examples/scrape_plain_text.py index 03dccdf0..a259ed6f 100644 --- a/examples/scrape_plain_text.py +++ b/examples/scrape_plain_text.py @@ -6,11 +6,26 @@ from dotenv import load_dotenv from scrapegraphai.graphs import SmartScraperGraph from scrapegraphai.utils import convert_to_csv, convert_to_json - load_dotenv() -openai_key = os.getenv("OPENAI_APIKEY") +# ************************************************ +# Read the text file +# ************************************************ + +FILE_NAME = "inputs/plain_html_example.txt" +curr_dir = os.path.dirname(os.path.realpath(__file__)) +file_path = os.path.join(curr_dir, FILE_NAME) + +# It could be also a http request using the request model +with open(file_path, 'r', encoding="utf-8") as file: + text = file.read() + +# ************************************************ # Define the configuration for the graph +# ************************************************ + +openai_key = os.getenv("OPENAI_APIKEY") + graph_config = { "llm": { "api_key": openai_key, @@ -18,14 +33,13 @@ }, } +# ************************************************ +# Create the SmartScraperGraph instance and run it +# ************************************************ -# It could be also a http request using the request model -text = open('inputs/plain_html_example.txt', 'r', encoding="utf-8") - -# Create the SmartScraperGraph instance smart_scraper_graph = SmartScraperGraph( prompt="List me all the news with their description.", - file_source=str(text), + source=text, config=graph_config ) diff --git a/examples/scrape_xml_document.py b/examples/scrape_xml_document.py index c4ed4d4e..be25e556 100644 --- a/examples/scrape_xml_document.py +++ b/examples/scrape_xml_document.py @@ -6,11 +6,25 @@ from dotenv import load_dotenv from scrapegraphai.graphs import SmartScraperGraph from scrapegraphai.utils import convert_to_csv, convert_to_json - load_dotenv() -openai_key = os.getenv("OPENAI_APIKEY") +# ************************************************ +# Read the XML file +# ************************************************ + +FILE_NAME = "inputs/books.xml" +curr_dir = os.path.dirname(os.path.realpath(__file__)) +file_path = os.path.join(curr_dir, FILE_NAME) + +with open(file_path, 'r', encoding="utf-8") as file: + text = file.read() + +# ************************************************ # Define the configuration for the graph +# ************************************************ + +openai_key = os.getenv("OPENAI_APIKEY") + graph_config = { "llm": { "api_key": openai_key, @@ -18,14 +32,13 @@ }, } -# Read the XML file -with open('inputs/books.xml', 'r', encoding="utf-8") as file: - text = file.read() +# ************************************************ +# Create the SmartScraperGraph instance and run it +# ************************************************ -# Create the SmartScraperGraph instance smart_scraper_graph = SmartScraperGraph( prompt="List me all the authors, title and genres of the books", - file_source=text, # Pass the content of the file, not the file object + source=text, # Pass the content of the file, not the file object config=graph_config ) diff --git a/examples/search_graph_example.py b/examples/search_graph_example.py index e9bd7c59..67fdee13 100644 --- a/examples/search_graph_example.py +++ b/examples/search_graph_example.py @@ -6,20 +6,30 @@ from dotenv import load_dotenv from scrapegraphai.graphs import SearchGraph from scrapegraphai.utils import convert_to_csv, convert_to_json - load_dotenv() -openai_key = os.getenv("OPENAI_APIKEY") +# ************************************************ # Define the configuration for the graph +# ************************************************ + +openai_key = os.getenv("OPENAI_APIKEY") + graph_config = { "llm": { + "model": "ollama/llama2", + "temperature": 0, + "format": "json", # Ollama needs the format to be specified explicitly + }, + "embeddings": { "api_key": openai_key, "model": "gpt-3.5-turbo", - "temperature": 0, }, } -# Create the SmartScraperGraph instance +# ************************************************ +# Create the SearchGraph instance and run it +# ************************************************ + search_graph = SearchGraph( prompt="List me all the regions of Italy.", config=graph_config diff --git a/examples/smart_scraper_example.py b/examples/smart_scraper_example.py index a8bc2d92..58f3788d 100644 --- a/examples/smart_scraper_example.py +++ b/examples/smart_scraper_example.py @@ -5,11 +5,15 @@ import os from dotenv import load_dotenv from scrapegraphai.graphs import SmartScraperGraph - load_dotenv() -openai_key = os.getenv("OPENAI_APIKEY") + +# ************************************************ # Define the configuration for the graph +# ************************************************ + +openai_key = os.getenv("OPENAI_APIKEY") + graph_config = { "llm": { "api_key": openai_key, @@ -17,11 +21,14 @@ }, } -# Create the SmartScraperGraph instance +# ************************************************ +# Create the SmartScraperGraph instance and run it +# ************************************************ + smart_scraper_graph = SmartScraperGraph( prompt="List me all the news with their description.", # also accepts a string with the already downloaded HTML code - file_source="https://www.wired.com", + source="https://www.wired.com", config=graph_config ) diff --git a/examples/speech_graph_example.py b/examples/speech_graph_example.py index 7afac269..051b33e6 100644 --- a/examples/speech_graph_example.py +++ b/examples/speech_graph_example.py @@ -5,16 +5,22 @@ import os from dotenv import load_dotenv from scrapegraphai.graphs import SpeechGraph - load_dotenv() -openai_key = os.getenv("OPENAI_APIKEY") -# Save the audio to a file +# ************************************************ +# Define audio output path +# ************************************************ + FILE_NAME = "website_summary.mp3" curr_dir = os.path.dirname(os.path.realpath(__file__)) output_path = os.path.join(curr_dir, FILE_NAME) +# ************************************************ # Define the configuration for the graph +# ************************************************ + +openai_key = os.getenv("OPENAI_APIKEY") + graph_config = { "llm": { "api_key": openai_key, @@ -28,9 +34,13 @@ "output_path": output_path, } +# ************************************************ +# Create the SpeechGraph instance and run it +# ************************************************ + speech_graph = SpeechGraph( prompt="Create a summary of the website", - file_source="https://perinim.github.io/projects/", + source="https://perinim.github.io/projects/", config=graph_config, ) diff --git a/poetry.lock b/poetry.lock index 761a8b70..f8db368b 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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"0.0.5" -langchain_google_genai = "0.0.11" +python = ">3.9,<4.0" +langchain = "0.1.14" +langchain-openai = "0.1.1" +langchain-google-genai = "1.0.1" html2text = "2020.1.16" faiss-cpu = "1.7.4" beautifulsoup4 = "4.12.3" diff --git a/scrapegraphai/graphs/abstract_graph.py b/scrapegraphai/graphs/abstract_graph.py index 31c0bfce..db8bddb7 100644 --- a/scrapegraphai/graphs/abstract_graph.py +++ b/scrapegraphai/graphs/abstract_graph.py @@ -3,30 +3,48 @@ """ from abc import ABC, abstractmethod from typing import Optional +from ..models import OpenAI, Gemini, Ollama, AzureOpenAI class AbstractGraph(ABC): """ Abstract class representing a generic graph-based tool. """ - def __init__(self, prompt: str, config: dict, file_source: Optional[str] = "url"): + def __init__(self, prompt: str, config: dict, source: Optional[str] = None): """ Initializes the AbstractGraph with a prompt, file source, and configuration. """ self.prompt = prompt - self.file_source = file_source - self.input_key = "url" if file_source.startswith( + self.source = source + self.input_key = "url" if source.startswith( "http") else "local_dir" self.config = config self.llm_model = self._create_llm(config["llm"]) + self.embedder_model = None if "embeddings" not in config else self._create_llm(config["embeddings"]) self.graph = self._create_graph() - @abstractmethod def _create_llm(self, llm_config: dict): """ - Abstract method to create a language model instance. + Creates an instance of the language model (OpenAI or Gemini) based on configuration. """ - pass + llm_defaults = { + "temperature": 0, + "streaming": True + } + llm_params = {**llm_defaults, **llm_config} + + if "gpt-" in llm_params["model"]: + return OpenAI(llm_params) + elif "azure" in llm_params["model"]: + return AzureOpenAI(llm_params) + elif "gemini" in llm_params["model"]: + return Gemini(llm_params) + elif "llama2" in llm_params["model"]: + # set model to llama2 if it has a different structure + llm_params["model"] = "llama2" + return Ollama(llm_params) + else: + raise ValueError("Model not supported") @abstractmethod def _create_graph(self): diff --git a/scrapegraphai/graphs/search_graph.py b/scrapegraphai/graphs/search_graph.py index 88c3fc4d..57a87868 100644 --- a/scrapegraphai/graphs/search_graph.py +++ b/scrapegraphai/graphs/search_graph.py @@ -1,7 +1,6 @@ """ Module for making the search on the intenet """ -from ..models import OpenAI, Gemini, Ollama from .base_graph import BaseGraph from ..nodes import ( SearchInternetNode, @@ -12,32 +11,11 @@ ) from .abstract_graph import AbstractGraph - class SearchGraph(AbstractGraph): """ Module for searching info on the internet """ - def _create_llm(self, llm_config: dict): - """ - Creates an instance of the language model (OpenAI or Gemini) based on configuration. - """ - llm_defaults = { - "temperature": 0, - "streaming": True - } - llm_params = {**llm_defaults, **llm_config} - if "api_key" not in llm_params: - raise ValueError("LLM configuration must include an 'api_key'.") - if "gpt-" in llm_params["model"]: - return OpenAI(llm_params) - elif "gemini" in llm_params["model"]: - return Gemini(llm_params) - elif "llama2" in llm_params["model"]: - return Ollama(llm_params) - else: - raise ValueError("Model not supported") - def _create_graph(self): """ Creates the graph of nodes representing the workflow for web scraping and searching. @@ -45,7 +23,7 @@ def _create_graph(self): search_internet_node = SearchInternetNode( input="user_prompt", output=["url"], - model_config={"llm_model": self.llm_model} + node_config={"llm": self.llm_model} ) fetch_node = FetchNode( input="url | local_dir", @@ -58,12 +36,15 @@ def _create_graph(self): rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", output=["relevant_chunks"], - model_config={"llm_model": self.llm_model}, + node_config={ + "llm": self.llm_model, + "embedder_model": self.embedder_model + } ) generate_answer_node = GenerateAnswerNode( input="user_prompt & (relevant_chunks | parsed_doc | doc)", output=["answer"], - model_config={"llm_model": self.llm_model}, + node_config={"llm": self.llm_model}, ) return BaseGraph( diff --git a/scrapegraphai/graphs/smart_scraper_graph.py b/scrapegraphai/graphs/smart_scraper_graph.py index 4f946435..56043183 100644 --- a/scrapegraphai/graphs/smart_scraper_graph.py +++ b/scrapegraphai/graphs/smart_scraper_graph.py @@ -18,23 +18,6 @@ class SmartScraperGraph(AbstractGraph): information from web pages using a natural language model to interpret and answer prompts. """ - def _create_llm(self, llm_config: dict): - """ - Creates an instance of the language model (OpenAI or Gemini) based on configuration. - """ - llm_defaults = { - "temperature": 0, - "streaming": True - } - llm_params = {**llm_defaults, **llm_config} - if "api_key" not in llm_params: - raise ValueError("LLM configuration must include an 'api_key'.") - if "gpt-" in llm_params["model"]: - return OpenAI(llm_params) - elif "gemini" in llm_params["model"]: - return Gemini(llm_params) - raise ValueError("Model not supported") - def _create_graph(self): """ Creates the graph of nodes representing the workflow for web scraping. @@ -50,12 +33,12 @@ def _create_graph(self): rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", output=["relevant_chunks"], - model_config={"llm_model": self.llm_model}, + node_config={"llm": self.llm_model}, ) generate_answer_node = GenerateAnswerNode( input="user_prompt & (relevant_chunks | parsed_doc | doc)", output=["answer"], - model_config={"llm_model": self.llm_model}, + node_config={"llm": self.llm_model}, ) return BaseGraph( @@ -77,7 +60,7 @@ def run(self) -> str: """ Executes the web scraping process and returns the answer to the prompt. """ - inputs = {"user_prompt": self.prompt, self.input_key: self.file_source} + inputs = {"user_prompt": self.prompt, self.input_key: self.source} final_state = self.graph.execute(inputs) return final_state.get("answer", "No answer found.") diff --git a/scrapegraphai/graphs/speech_graph.py b/scrapegraphai/graphs/speech_graph.py index da019698..d19acea9 100644 --- a/scrapegraphai/graphs/speech_graph.py +++ b/scrapegraphai/graphs/speech_graph.py @@ -20,24 +20,6 @@ class SpeechGraph(AbstractGraph): information from web pages, then converting that summary into spoken word via an MP3 file. """ - def _create_llm(self, llm_config: dict): - """ - Creates an instance of the language model (OpenAI or Gemini) based on configuration. - """ - llm_defaults = { - "temperature": 0, - "streaming": True - } - llm_params = {**llm_defaults, **llm_config} - if "api_key" not in llm_params: - raise ValueError("LLM configuration must include an 'api_key'.") - if "gpt-" in llm_params["model"]: - return OpenAI(llm_params) - elif "gemini" in llm_params["model"]: - return Gemini(llm_params) - else: - raise ValueError("Model not supported") - def _create_graph(self): """ Creates the graph of nodes representing the workflow for web scraping and summarization. @@ -53,17 +35,17 @@ def _create_graph(self): rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", output=["relevant_chunks"], - model_config={"llm_model": self.llm_model}, + node_config={"llm": self.llm_model}, ) generate_answer_node = GenerateAnswerNode( input="user_prompt & (relevant_chunks | parsed_doc | doc)", output=["answer"], - model_config={"llm_model": self.llm_model}, + node_config={"llm": self.llm_model}, ) text_to_speech_node = TextToSpeechNode( input="answer", output=["audio"], - model_config={"tts_model": OpenAITextToSpeech( + node_config={"tts_model": OpenAITextToSpeech( self.config["tts_model"])}, ) @@ -88,7 +70,7 @@ def run(self) -> str: """ Executes the web scraping, summarization, and text-to-speech process. """ - inputs = {"user_prompt": self.prompt, self.input_key: self.file_source} + inputs = {"user_prompt": self.prompt, self.input_key: self.source} final_state = self.graph.execute(inputs) audio = final_state.get("audio", None) diff --git a/scrapegraphai/models/__init__.py b/scrapegraphai/models/__init__.py index 4d2d9134..8d85cd60 100644 --- a/scrapegraphai/models/__init__.py +++ b/scrapegraphai/models/__init__.py @@ -3,6 +3,7 @@ """ from .openai import OpenAI +from .azure_openai import AzureOpenAI from .openai_itt import OpenAIImageToText from .openai_tts import OpenAITextToSpeech from .gemini import Gemini diff --git a/scrapegraphai/models/azure_openai.py b/scrapegraphai/models/azure_openai.py new file mode 100644 index 00000000..0d7f0582 --- /dev/null +++ b/scrapegraphai/models/azure_openai.py @@ -0,0 +1,18 @@ +""" +Azure Openai configuration wrapper +""" +from langchain_openai import AzureChatOpenAI + +class AzureOpenAI(AzureChatOpenAI): + """Class for wrapping openai module""" + + def __init__(self, llm_config: dict): + """ + A wrapper for the ChatOpenAI class that provides default configuration + and could be extended with additional methods if needed. + + Args: + llm_config (dict): Configuration parameters for the language model. + """ + # Initialize the superclass (AzureChatOpenAI) with provided config parameters + super().__init__(**llm_config) diff --git a/scrapegraphai/nodes/base_node.py b/scrapegraphai/nodes/base_node.py index 781e35d7..f00fd869 100644 --- a/scrapegraphai/nodes/base_node.py +++ b/scrapegraphai/nodes/base_node.py @@ -41,7 +41,7 @@ class BaseNode(ABC): """ def __init__(self, node_name: str, node_type: str, input: str, output: List[str], - min_input_len: int = 1, model_config: Optional[dict] = None): + min_input_len: int = 1, node_config: Optional[dict] = None): """ Initialize the node with a unique identifier and a specified node type. @@ -56,7 +56,7 @@ def __init__(self, node_name: str, node_type: str, input: str, output: List[str] self.input = input self.output = output self.min_input_len = min_input_len - self.model_config = model_config + self.node_config = node_config if node_type not in ["node", "conditional_node"]: raise ValueError( diff --git a/scrapegraphai/nodes/fetch_node.py b/scrapegraphai/nodes/fetch_node.py index 892fb551..75f53655 100644 --- a/scrapegraphai/nodes/fetch_node.py +++ b/scrapegraphai/nodes/fetch_node.py @@ -68,8 +68,7 @@ def execute(self, state): input_data = [state[key] for key in input_keys] source = input_data[0] - - print(f"Fetching content from: {source}") + # if it is a local directory if not source.startswith("http"): document = [Document(page_content=source, metadata={ diff --git a/scrapegraphai/nodes/generate_answer_node.py b/scrapegraphai/nodes/generate_answer_node.py index 9a400d56..6dcf373a 100644 --- a/scrapegraphai/nodes/generate_answer_node.py +++ b/scrapegraphai/nodes/generate_answer_node.py @@ -39,7 +39,7 @@ class GenerateAnswerNode(BaseNode): updating the state with the generated answer under the 'answer' key. """ - def __init__(self, input: str, output: List[str], model_config: dict, + def __init__(self, input: str, output: List[str], node_config: dict, node_name: str = "GenerateAnswer"): """ Initializes the GenerateAnswerNode with a language model client and a node name. @@ -47,8 +47,8 @@ def __init__(self, input: str, output: List[str], model_config: dict, llm (OpenAIImageToText): An instance of the OpenAIImageToText class. node_name (str): name of the node """ - super().__init__(node_name, "node", input, output, 2, model_config) - self.llm_model = model_config["llm_model"] + super().__init__(node_name, "node", input, output, 2, node_config) + self.llm_model = node_config["llm"] def execute(self, state): """ diff --git a/scrapegraphai/nodes/image_to_text_node.py b/scrapegraphai/nodes/image_to_text_node.py index 5d0a4949..7be64ef3 100644 --- a/scrapegraphai/nodes/image_to_text_node.py +++ b/scrapegraphai/nodes/image_to_text_node.py @@ -16,7 +16,7 @@ class ImageToTextNode(BaseNode): execute(state, url): Execute the node's logic and return the updated state. """ - def __init__(self, input: str, output: List[str], model_config: dict, + def __init__(self, input: str, output: List[str], node_config: dict, node_name: str = "ImageToText"): """ Initializes an instance of the ImageToTextNode class. @@ -24,11 +24,11 @@ def __init__(self, input: str, output: List[str], model_config: dict, Args: input (str): The input for the node. output (List[str]): The output of the node. - model_config (dict): Configuration for the model. + node_config (dict): Configuration for the model. node_name (str): Name of the node. """ - super().__init__(node_name, "node", input, output, 1, model_config) - self.llm_model = model_config["llm_model"] + super().__init__(node_name, "node", input, output, 1, node_config) + self.llm_model = node_config["llm_model"] def execute(self, state: dict) -> dict: """ diff --git a/scrapegraphai/nodes/rag_node.py b/scrapegraphai/nodes/rag_node.py index 1bb648a6..4ddabe66 100644 --- a/scrapegraphai/nodes/rag_node.py +++ b/scrapegraphai/nodes/rag_node.py @@ -8,7 +8,9 @@ from langchain.retrievers.document_compressors import EmbeddingsFilter, DocumentCompressorPipeline from langchain_community.document_transformers import EmbeddingsRedundantFilter from langchain_community.vectorstores import FAISS -from langchain_openai import OpenAIEmbeddings +from ..models import OpenAI, Gemini, Ollama, AzureOpenAI +from langchain_openai import OpenAIEmbeddings, AzureOpenAIEmbeddings +from langchain_community.embeddings import OllamaEmbeddings from .base_node import BaseNode @@ -32,12 +34,13 @@ class RAGNode(BaseNode): the specified tags, if provided, and updates the state with the parsed content. """ - def __init__(self, input: str, output: List[str], model_config: dict, node_name: str = "RAG"): + def __init__(self, input: str, output: List[str], node_config: dict, node_name: str = "RAG"): """ Initializes the ParseHTMLNode with a node name. """ - super().__init__(node_name, "node", input, output, 2, model_config) - self.llm_model = model_config["llm_model"] + super().__init__(node_name, "node", input, output, 2, node_config) + self.llm_model = node_config["llm"] + self.embedder_model = node_config.get("embedder_model", None) def execute(self, state): """ @@ -79,11 +82,20 @@ def execute(self, state): print("--- (updated chunks metadata) ---") - openai_key = self.llm_model.openai_api_key - retriever = FAISS.from_documents(chunked_docs, - OpenAIEmbeddings(api_key=openai_key)).as_retriever() - # could be any embedding of your choice - embeddings = OpenAIEmbeddings(api_key=openai_key) + # check if embedder_model is provided, if not use llm_model + embedding_model = self.embedder_model if self.embedder_model else self.llm_model + + if isinstance(embedding_model, OpenAI): + embeddings = OpenAIEmbeddings(api_key=embedding_model.openai_api_key) + elif isinstance(embedding_model, AzureOpenAI): + embeddings = AzureOpenAIEmbeddings() + elif isinstance(embedding_model, Ollama): + embeddings = OllamaEmbeddings() + else: + raise ValueError("Embedding Model missing or not supported") + + retriever = FAISS.from_documents(chunked_docs, embeddings).as_retriever() + redundant_filter = EmbeddingsRedundantFilter(embeddings=embeddings) # similarity_threshold could be set, now k=20 relevant_filter = EmbeddingsFilter(embeddings=embeddings) diff --git a/scrapegraphai/nodes/search_internet_node.py b/scrapegraphai/nodes/search_internet_node.py index 2d49b8f6..6220441d 100644 --- a/scrapegraphai/nodes/search_internet_node.py +++ b/scrapegraphai/nodes/search_internet_node.py @@ -36,7 +36,7 @@ class SearchInternetNode(BaseNode): updating the state with the generated answer under the 'answer' key. """ - def __init__(self, input: str, output: List[str], model_config: dict, + def __init__(self, input: str, output: List[str], node_config: dict, node_name: str = "SearchInternet"): """ Initializes the SearchInternetNode with input, output, model configuration, and a node name. @@ -47,8 +47,8 @@ def __init__(self, input: str, output: List[str], model_config: dict, model_config (dict): Configuration parameters for the language model client. node_name (str): The unique identifier name for the node. """ - super().__init__(node_name, "node", input, output, 1, model_config) - self.llm_model = model_config["llm_model"] + super().__init__(node_name, "node", input, output, 1, node_config) + self.llm_model = node_config["llm"] def execute(self, state): """ @@ -94,7 +94,7 @@ def execute(self, state): # Execute the chain to get the search query search_answer = search_prompt | self.llm_model | output_parser search_query = search_answer.invoke({"user_prompt": user_prompt})[0] - + print(f"Search Query: {search_query}") # TODO: handle multiple URLs answer = search_on_web(query=search_query, max_results=1)[0] diff --git a/scrapegraphai/nodes/text_to_speech_node.py b/scrapegraphai/nodes/text_to_speech_node.py index a9250842..980f33e1 100644 --- a/scrapegraphai/nodes/text_to_speech_node.py +++ b/scrapegraphai/nodes/text_to_speech_node.py @@ -18,12 +18,12 @@ class TextToSpeechNode(BaseNode): """ def __init__(self, input: str, output: List[str], - model_config: dict, node_name: str = "TextToSpeech"): + node_config: dict, node_name: str = "TextToSpeech"): """ Initializes an instance of the TextToSpeechNode class. """ - super().__init__(node_name, "node", input, output, 1, model_config) - self.tts_model = model_config["tts_model"] + super().__init__(node_name, "node", input, output, 1, node_config) + self.tts_model = node_config["tts_model"] def execute(self, state): """ From dee1a4262936464e6683dfc2f09bc8e640bd7bf2 Mon Sep 17 00:00:00 2001 From: "EURAC\\marperini" Date: Mon, 8 Apr 2024 15:21:06 +0200 Subject: [PATCH 3/4] fixed token models, added mistral support --- examples/custom_graph_gemini.py | 2 ++ examples/custom_graph_openai.py | 2 ++ examples/search_graph_example.py | 2 +- scrapegraphai/graphs/abstract_graph.py | 32 +++++++++++++++--- scrapegraphai/graphs/search_graph.py | 1 + scrapegraphai/graphs/smart_scraper_graph.py | 9 ++++++ scrapegraphai/graphs/speech_graph.py | 9 ++++++ scrapegraphai/helpers/models_tokens.py | 36 ++++++++++++++------- scrapegraphai/nodes/parse_node.py | 6 ++-- 9 files changed, 78 insertions(+), 21 deletions(-) diff --git a/examples/custom_graph_gemini.py b/examples/custom_graph_gemini.py index 9ecae73b..7d663773 100644 --- a/examples/custom_graph_gemini.py +++ b/examples/custom_graph_gemini.py @@ -7,6 +7,7 @@ from scrapegraphai.models import Gemini from scrapegraphai.graphs import BaseGraph from scrapegraphai.nodes import FetchNode, ParseNode, RAGNode, GenerateAnswerNode +from scrapegraphai.helpers import models_tokens load_dotenv() # ************************************************ @@ -38,6 +39,7 @@ parse_node = ParseNode( input="doc", output=["parsed_doc"], + node_config={"chunk_size": 4096} ) rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", diff --git a/examples/custom_graph_openai.py b/examples/custom_graph_openai.py index 943838fc..d92cf3dd 100644 --- a/examples/custom_graph_openai.py +++ b/examples/custom_graph_openai.py @@ -7,6 +7,7 @@ from scrapegraphai.models import OpenAI from scrapegraphai.graphs import BaseGraph from scrapegraphai.nodes import FetchNode, ParseNode, RAGNode, GenerateAnswerNode +from scrapegraphai.helpers import models_tokens load_dotenv() # ************************************************ @@ -38,6 +39,7 @@ parse_node = ParseNode( input="doc", output=["parsed_doc"], + node_config={"chunk_size": 4096} ) rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", diff --git a/examples/search_graph_example.py b/examples/search_graph_example.py index 67fdee13..8624024f 100644 --- a/examples/search_graph_example.py +++ b/examples/search_graph_example.py @@ -16,7 +16,7 @@ graph_config = { "llm": { - "model": "ollama/llama2", + "model": "ollama/mistral", "temperature": 0, "format": "json", # Ollama needs the format to be specified explicitly }, diff --git a/scrapegraphai/graphs/abstract_graph.py b/scrapegraphai/graphs/abstract_graph.py index db8bddb7..79eea199 100644 --- a/scrapegraphai/graphs/abstract_graph.py +++ b/scrapegraphai/graphs/abstract_graph.py @@ -4,6 +4,7 @@ from abc import ABC, abstractmethod from typing import Optional from ..models import OpenAI, Gemini, Ollama, AzureOpenAI +from ..helpers import models_tokens class AbstractGraph(ABC): """ @@ -16,8 +17,6 @@ def __init__(self, prompt: str, config: dict, source: Optional[str] = None): """ self.prompt = prompt self.source = source - self.input_key = "url" if source.startswith( - "http") else "local_dir" self.config = config self.llm_model = self._create_llm(config["llm"]) self.embedder_model = None if "embeddings" not in config else self._create_llm(config["embeddings"]) @@ -33,16 +32,39 @@ def _create_llm(self, llm_config: dict): } llm_params = {**llm_defaults, **llm_config} + # Instantiate the language model based on the model name if "gpt-" in llm_params["model"]: + try: + self.model_token = models_tokens["openai"][llm_params["model"]] + except KeyError: + raise ValueError("Model not supported") return OpenAI(llm_params) + elif "azure" in llm_params["model"]: + # take the model after the last dash + llm_params["model"] = llm_params["model"].split("/")[-1] + try: + self.model_token = models_tokens["openai"][llm_params["model"]] + except KeyError: + raise ValueError("Model not supported") return AzureOpenAI(llm_params) + elif "gemini" in llm_params["model"]: + try: + self.model_token = models_tokens["gemini"][llm_params["model"]] + except KeyError: + raise ValueError("Model not supported") return Gemini(llm_params) - elif "llama2" in llm_params["model"]: - # set model to llama2 if it has a different structure - llm_params["model"] = "llama2" + + elif "ollama" in llm_params["model"]: + # take the model after the last dash + llm_params["model"] = llm_params["model"].split("/")[-1] + try: + self.model_token = models_tokens["ollama"][llm_params["model"]] + except KeyError: + raise ValueError("Model not supported") return Ollama(llm_params) + else: raise ValueError("Model not supported") diff --git a/scrapegraphai/graphs/search_graph.py b/scrapegraphai/graphs/search_graph.py index 57a87868..2f8ef6a8 100644 --- a/scrapegraphai/graphs/search_graph.py +++ b/scrapegraphai/graphs/search_graph.py @@ -32,6 +32,7 @@ def _create_graph(self): parse_node = ParseNode( input="doc", output=["parsed_doc"], + node_config={"chunk_size": self.model_token} ) rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", diff --git a/scrapegraphai/graphs/smart_scraper_graph.py b/scrapegraphai/graphs/smart_scraper_graph.py index 56043183..06f7d010 100644 --- a/scrapegraphai/graphs/smart_scraper_graph.py +++ b/scrapegraphai/graphs/smart_scraper_graph.py @@ -18,6 +18,14 @@ class SmartScraperGraph(AbstractGraph): information from web pages using a natural language model to interpret and answer prompts. """ + def __init__(self, prompt: str, source: str, config: dict): + """ + Initializes the SmartScraperGraph with a prompt, source, and configuration. + """ + super().__init__(prompt, config, source) + + self.input_key = "url" if source.startswith("http") else "local_dir" + def _create_graph(self): """ Creates the graph of nodes representing the workflow for web scraping. @@ -29,6 +37,7 @@ def _create_graph(self): parse_node = ParseNode( input="doc", output=["parsed_doc"], + node_config={"chunk_size": self.model_token} ) rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", diff --git a/scrapegraphai/graphs/speech_graph.py b/scrapegraphai/graphs/speech_graph.py index d19acea9..28d0cdfa 100644 --- a/scrapegraphai/graphs/speech_graph.py +++ b/scrapegraphai/graphs/speech_graph.py @@ -20,6 +20,14 @@ class SpeechGraph(AbstractGraph): information from web pages, then converting that summary into spoken word via an MP3 file. """ + def __init__(self, prompt: str, source: str, config: dict): + """ + Initializes the SmartScraperGraph with a prompt, source, and configuration. + """ + super().__init__(prompt, config, source) + + self.input_key = "url" if source.startswith("http") else "local_dir" + def _create_graph(self): """ Creates the graph of nodes representing the workflow for web scraping and summarization. @@ -31,6 +39,7 @@ def _create_graph(self): parse_node = ParseNode( input="doc", output=["parsed_doc"], + node_config={"chunk_size": self.model_token} ) rag_node = RAGNode( input="user_prompt & (parsed_doc | doc)", diff --git a/scrapegraphai/helpers/models_tokens.py b/scrapegraphai/helpers/models_tokens.py index abdfc4b0..dc286526 100644 --- a/scrapegraphai/helpers/models_tokens.py +++ b/scrapegraphai/helpers/models_tokens.py @@ -2,16 +2,28 @@ Models token """ models_tokens = { - "gpt-3.5-turbo-0125": 16385, - "gpt-3.5-turbo": 4096, - "gpt-3.5-turbo-1106": 16385, - "gpt-3.5-turbo-instruct": 4096, - "gpt-4-0125-preview": 128000, - "gpt-4-turbo-preview": 128000, - "gpt-4-1106-preview": 128000, - "gpt-4-vision-preview": 128000, - "gpt-4": 8192, - "gpt-4-0613": 8192, - "gpt-4-32k": 32768, - "gpt-4-32k-0613": 32768, + "openai": { + "gpt-3.5-turbo-0125": 16385, + "gpt-3.5-turbo": 4096, + "gpt-3.5-turbo-1106": 16385, + "gpt-3.5-turbo-instruct": 4096, + "gpt-4-0125-preview": 128000, + "gpt-4-turbo-preview": 128000, + "gpt-4-1106-preview": 128000, + "gpt-4-vision-preview": 128000, + "gpt-4": 8192, + "gpt-4-0613": 8192, + "gpt-4-32k": 32768, + "gpt-4-32k-0613": 32768, + }, + + "gemini": { + "gemini-pro": 128000, + }, + + "ollama":{ + "llama2": 4096, + "mistral": 8192, + } + } diff --git a/scrapegraphai/nodes/parse_node.py b/scrapegraphai/nodes/parse_node.py index 866487d8..357b39fb 100644 --- a/scrapegraphai/nodes/parse_node.py +++ b/scrapegraphai/nodes/parse_node.py @@ -29,7 +29,7 @@ class ParseNode(BaseNode): the specified tags, if provided, and updates the state with the parsed content. """ - def __init__(self, input: str, output: List[str], node_name: str = "Parse"): + def __init__(self, input: str, output: List[str], node_config: dict, node_name: str = "Parse"): """ Initializes the ParseHTMLNode with a node name. Args: @@ -38,7 +38,7 @@ def __init__(self, input: str, output: List[str], node_name: str = "Parse"): node_name (str): name of the node node_type (str, optional): type of the node """ - super().__init__(node_name, "node", input, output, 1) + super().__init__(node_name, "node", input, output, 1, node_config) def execute(self, state): """ @@ -69,7 +69,7 @@ def execute(self, state): input_data = [state[key] for key in input_keys] text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder( - chunk_size=4000, + chunk_size=self.node_config.get("chunk_size", 4096), chunk_overlap=0, ) From a601695fd5fe8a282ab19fdb26da33bbd54232c7 Mon Sep 17 00:00:00 2001 From: "EURAC\\marperini" Date: Mon, 8 Apr 2024 15:23:23 +0200 Subject: [PATCH 4/4] updated nodes metadata --- scrapegraphai/helpers/nodes_metadata.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/scrapegraphai/helpers/nodes_metadata.py b/scrapegraphai/helpers/nodes_metadata.py index ac25eca2..65dec933 100644 --- a/scrapegraphai/helpers/nodes_metadata.py +++ b/scrapegraphai/helpers/nodes_metadata.py @@ -3,6 +3,14 @@ """ nodes_metadata = { + "SearchInternetNode": { + "description": "Refactors the user's query into a search query and fetches the search result URLs.", + "type": "node", + "args": { + "user_input": "User's query or question." + }, + "returns": "Updated state with the URL of the search result under 'url' key." + }, "FetchNode": { "description": "Fetches input content from a given URL or file path.", "type": "node",