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Merge branch 'main' into train-lora

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This commit is contained in:
Jason Schleifer
2024-10-11 14:02:16 +13:00
parent bb9e5f6911 edb075fdc6
commit fc064d3b8a
22 changed files with 383 additions and 57 deletions
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README.md
+6 -1
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@@ -103,7 +103,12 @@ You can previous and download more examples [here](examples/README.md).
## Recent Changelog
### Setp 20, 2024
### Oct 10, 2024
* Updated to Griptape Framework v0.33
* Added `TavilyWebSearchDriver`. Requires a Tavily [api key](https://app.tavily.com/).
* Added `ExaWebSearchDriver`. Requires an Exa [api key](https://dashboard.exa.ai/api-keys).
### Sept 20, 2024
* Hotfix for `Griptape Agent Config: LM Studio Drivers`. The `base_url` parameter wasn't being set properly causing a connection error.
### Sept 12, 2024
TODO
-3
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@@ -1,3 +0,0 @@
* Ollama3.1 doesn't handle tools well - need to resolve it.
* Check GriptapeCloudKnowledgeBaseVectorStoreDriver
* check BaseVectorStoreDriver
__init__.py
+11 -3
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@@ -133,14 +133,17 @@ from .nodes.drivers.gtUIElevenLabsTextToSpeechDriver import (
gtUIElevenLabsTextToSpeechDriver,
)
# - Exa
from .nodes.drivers.gtUIExaWebSearchDriver import gtUIExaWebSearchDriver
# - Google
from .nodes.drivers.gtUIGoogleEmbeddingDriver import gtUIGoogleEmbeddingDriver
from .nodes.drivers.gtUIGooglePromptDriver import gtUIGooglePromptDriver
from .nodes.drivers.gtUIGoogleWebSearchDriver import gtUIGoogleWebSearchDriver
# - Griptape
from .nodes.drivers.gtUIGriptapeCloudKnowledgeBaseVectorStoreDriver import (
gtUIGriptapeCloudKnowledgeBaseVectorStoreDriver,
from .nodes.drivers.gtUIGriptapeCloudVectorStoreDriver import (
gtUIGriptapeCloudVectorStoreDriver,
)
# - HuggingFace
@@ -205,6 +208,9 @@ from .nodes.drivers.gtUIQdrantVectorStoreDriver import gtUIQdrantVectorStoreDriv
# - Redis
from .nodes.drivers.gtUIRedisVectorStoreDriver import gtUIRedisVectorStoreDriver
# - Tavily
from .nodes.drivers.gtUITavilyWebSearchDriver import gtUITavilyWebSearchDriver
# - Voyage AI
from .nodes.drivers.gtUIVoyageAiEmbeddingDriver import gtUIVoyageAiEmbeddingDriver
from .nodes.expand.ExpandAgent import ExpandAgent
@@ -384,7 +390,7 @@ NODE_CLASS_MAPPINGS = {
# VECTOR STORE DRIVERS
"Griptape Vector Store Driver: Amazon OpenSearch": gtUIAmazonOpenSearchVectorStoreDriver,
"Griptape Vector Store Driver: Azure MongoDB": gtUIAzureMongoDbVectorStoreDriver,
"Griptape Vector Store Driver: Griptape Cloud KnowledgeBase": gtUIGriptapeCloudKnowledgeBaseVectorStoreDriver,
"Griptape Vector Store Driver: Griptape Cloud": gtUIGriptapeCloudVectorStoreDriver,
"Griptape Vector Store Driver: Marqo": gtUIMarqoVectorStoreDriver,
"Griptape Vector Store Driver: MongoDB Atlas": gtUIMongoDbAtlasVectorStoreDriver,
"Griptape Vector Store Driver: Local": gtUILocalVectorStoreDriver,
@@ -399,7 +405,9 @@ NODE_CLASS_MAPPINGS = {
"Griptape Audio Transcription Driver: OpenAI": gtUIOpenAiAudioTranscriptionDriver,
# WEBSEARCH DRIVERS
"Griptape WebSearch Driver: DuckDuckGo": gtUIDuckDuckGoWebSearchDriver,
"Griptape WebSearch Driver: Exa": gtUIExaWebSearchDriver,
"Griptape WebSearch Driver: Google": gtUIGoogleWebSearchDriver,
"Griptape WebSearch Driver: Tavily": gtUITavilyWebSearchDriver,
# AGENT RULES
"Griptape Create: Rules": gtUIRule,
"Griptape Combine: Rules List": RulesList,
examples/retrieval_augmented_generation.png
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js/nodeFixes.js
+1
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@@ -77,5 +77,6 @@ export const nodeFixes = {
"Griptape Agent Config: Ollama": "Griptape Agent Config: Ollama [DEPRICATED]",
"Griptape Agent Config: OpenAI Compatible": "Griptape Agent Config: OpenAI Compatible [DEPRICATED]",
"Griptape Agent Config: OpenAI": "Griptape Agent Config: OpenAI [DEPRICATED]",
"Griptape Vector Store Driver: Griptape Cloud KnowledgeBase": "Griptape Vector Store Driver: Griptape Cloud"
}
}
js/versions.js
+9 -2
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@@ -1,11 +1,18 @@
export const versions = {
"version": "0.31.0e",
"releaseDate": "2024-09-20",
"version": "0.33.0",
"releaseDate": "2024-10-11",
"name": "ComfyUI-Griptape",
"description": "Griptape integration for ComfyUI",
"author": "Jason Schleifer",
"repository": "https://github.com/griptape-ai/ComfyUI-Griptape",
"changelog": [
{
"version": "0.33.0",
"date": "2024-10-11",
"changes": [
"Update to Griptape v0.33.0",
]
},
{
"version": "0.31.0e",
"date": "2024-09-20",
nodes/drivers/gtUIAzureOpenAiChatPromptDriver.py
+4 -1
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@@ -63,12 +63,15 @@ class gtUIAzureOpenAiChatPromptDriver(gtUIBasePromptDriver):
"azure_endpoint": azure_endpoint_env_var,
"model": model,
"azure_deployment": deployment_name,
"response_format": response_format,
"seed": seed,
"temperature": temperature,
"max_attempts": max_attempts_on_fail,
"use_native_tools": use_native_tools,
}
if response_format == "json_object":
response_format = {"type": "json_object"}
params["response_format"] = response_format
if max_tokens > 0:
params["max_tokens"] = max_tokens
nodes/drivers/gtUIExaWebSearchDriver.py
+142
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@@ -0,0 +1,142 @@
from dotenv import load_dotenv
from griptape.drivers import ExaWebSearchDriver
from .gtUIBaseWebSearchDriver import gtUIBaseWebSearchDriver
load_dotenv()
DEFAULT_API_KEY_ENV_VAR = "EXA_API_KEY"
class gtUIExaWebSearchDriver(gtUIBaseWebSearchDriver):
DESCRIPTION = "Exa Web Search Driver. Requires environment variables EXA_API_KEY."
@classmethod
def INPUT_TYPES(s):
inputs = super().INPUT_TYPES()
inputs["required"].update(
{
"type": (
["keyword", "neural", "auto"],
{"default": "neural", "tooltip": "The type of search"},
),
"highlights": (
"BOOLEAN",
{
"default": False,
"tooltip": "Extracts relevant excerpts or highlights from retrieved content.",
},
),
"use_autoprompt": (
"BOOLEAN",
{
"default": False,
"tooltip": "If true, your query will be converted to a Exa query. Default false. Neural or Auto search only.",
},
),
"category": (
[
"none",
"company",
"research paper",
"news",
"github",
"tweet",
"movie",
"song",
"personal site",
"pdf",
],
{
"default": "none",
"tooltop": "(beta) A data category to focus on, with higher comprehensitivity and cleanliness.)",
},
),
"num_results": (
"INT",
{
"default": 10,
"tooltip": "The maximum number of search results to return.",
},
),
"include_domains": (
"STRING",
{
"multiline": True,
"tooltip": "A list of domains to include in the search results",
},
),
"exclude_domains": (
"STRING",
{
"multiline": True,
"tooltip": "A list of domains to exclude from the search results",
},
),
"include_text": (
"STRING",
{
"multiline": True,
"tooltip": "A list of words to include in the search results",
},
),
"exclude_text": (
"STRING",
{
"multiline": True,
"tooltip": "A list of words to exclude from the search results",
},
),
}
)
inputs["optional"].update(
{
"api_key_env_var": (
"STRING",
{"default": DEFAULT_API_KEY_ENV_VAR},
),
}
)
return inputs
def create(self, **kwargs):
highlights = kwargs.get("highlights", False)
type = kwargs.get("type", "neural")
use_autoprompt = kwargs.get("use_autoprompt", False)
category = kwargs.get("category", "none")
num_results = kwargs.get("num_results", 10)
include_domains = kwargs.get("include_domains", None)
exclude_domains = kwargs.get("exclude_domains", None)
include_text = kwargs.get("include_text", None)
exclude_text = kwargs.get("exclude_text", None)
EXA_API_KEY = self.getenv(
kwargs.get("api_key_env_var", DEFAULT_API_KEY_ENV_VAR)
)
if not EXA_API_KEY:
raise Exception(
"Exa API Key not found. Please set the environment variable EXA_API_KEY."
)
exa_params = {}
addl_params = {}
exa_params["highlights"] = highlights
if not type == "keyword":
exa_params["use_autoprompt"] = use_autoprompt
exa_params["results_count"] = num_results
addl_params["category"] = category
addl_params["type"] = type
if include_domains:
addl_params["include_domains"] = include_domains
if exclude_domains:
addl_params["exclude_domains"] = exclude_domains
if include_text.strip() != "":
addl_params["include_text"] = include_text
if exclude_text.strip() != "":
addl_params["exclude_text"] = exclude_text
if EXA_API_KEY:
exa_params["api_key"] = EXA_API_KEY
driver = ExaWebSearchDriver(**exa_params, params=addl_params)
return (driver,)
nodes/drivers/gtUIGriptapeCloudKnowledgeBaseVectorStoreDriver.py → nodes/drivers/gtUIGriptapeCloudVectorStoreDriver.py
+5 -6
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@@ -1,4 +1,5 @@
from griptape.drivers import GriptapeCloudKnowledgeBaseVectorStoreDriver
# from griptape.drivers import GriptapeCloudKnowledgeBaseVectorStoreDriver
from griptape.drivers import GriptapeCloudVectorStoreDriver
from .gtUIBaseVectorStoreDriver import gtUIBaseVectorStoreDriver
@@ -7,10 +8,8 @@ BASE_URL = "https://cloud.griptape.ai"
API_KEY_ENV = "GRIPTAPE_CLOUD_API_KEY"
class gtUIGriptapeCloudKnowledgeBaseVectorStoreDriver(gtUIBaseVectorStoreDriver):
DESCRIPTION = (
"Griptape Cloud KnowledgeBase Vector Store Driver: https://cloud.griptape.ai"
)
class gtUIGriptapeCloudVectorStoreDriver(gtUIBaseVectorStoreDriver):
DESCRIPTION = "Griptape Cloud Vector Store Driver: https://cloud.griptape.ai"
@classmethod
def INPUT_TYPES(s):
@@ -46,5 +45,5 @@ class gtUIGriptapeCloudKnowledgeBaseVectorStoreDriver(gtUIBaseVectorStoreDriver)
params["base_url"] = base_url
if knowledge_base_id:
params["knowledge_base_id"] = knowledge_base_id
driver = GriptapeCloudKnowledgeBaseVectorStoreDriver(**params)
driver = GriptapeCloudVectorStoreDriver(**params)
return (driver,)
nodes/drivers/gtUILMStudioChatPromptDriver.py
+2 -2
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@@ -47,8 +47,8 @@ class gtUILMStudioChatPromptDriver(gtUIOpenAiCompatibleChatPromptDriver):
"use_native_tools": use_native_tools,
"max_attempts": max_attempts,
}
if response_format:
params["response_format"] = response_format
if response_format == "json_object":
params["response_format"] = {"type": response_format}
if max_tokens > 0:
params["max_tokens"] = max_tokens
nodes/drivers/gtUIOpenAiChatPromptDriver.py
+2 -1
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@@ -54,7 +54,8 @@ class gtUIOpenAiChatPromptDriver(gtUIBasePromptDriver):
params["api_key"] = api_key
if model:
params["model"] = model
if not response_format == "default":
if response_format == "json_object":
response_format = {"type": "json_object"}
params["response_format"] = response_format
if seed:
params["seed"] = seed
nodes/drivers/gtUIOpenAiCompatibleChatPromptDriver.py
+2 -1
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@@ -48,7 +48,8 @@ class gtUIOpenAiCompatibleChatPromptDriver(gtUIOpenAiChatPromptDriver):
"use_native_tools": use_native_tools,
"max_attempts": max_attempts,
}
if response_format:
if response_format == "json_object":
response_format = {"type": "json_object"}
params["response_format"] = response_format
if max_tokens > 0:
params["max_tokens"] = max_tokens
nodes/drivers/gtUITavilyWebSearchDriver.py
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@@ -0,0 +1,119 @@
from dotenv import load_dotenv
from griptape.drivers import TavilyWebSearchDriver
from .gtUIBaseWebSearchDriver import gtUIBaseWebSearchDriver
load_dotenv()
DEFAULT_API_KEY_ENV_VAR = "TAVILY_API_KEY"
class gtUITavilyWebSearchDriver(gtUIBaseWebSearchDriver):
DESCRIPTION = (
"Tavily Web Search Driver. Requires environment variables TAVILY_API_KEY."
)
@classmethod
def INPUT_TYPES(s):
inputs = super().INPUT_TYPES()
inputs["required"].update(
{
"search_depth": (
["basic", "advanced"],
{"default": "basic", "tooltip": "The depth of the search"},
),
"topic": (
["general", "news"],
{"default": "general", "tooltop": "The category of the search"},
),
"days": (
"INT",
{
"default": 3,
"tooltip": "The number of days back from the current date to include in the search results.\nOnly when using 'news' search topic.",
},
),
"max_results": (
"INT",
{
"default": 5,
"tooltip": "The maximum number of search results to return.",
},
),
"include_answer": (
"BOOLEAN",
{
"default": False,
"tooltip": "include a short answer to the search query",
},
),
"include_raw_content": (
"BOOLEAN",
{
"default": False,
"tooltip": "include the cleaned and parsed HTML content",
},
),
"include_domains": (
"STRING",
{
"multiline": True,
"tooltip": "A list of domains to include in the search results",
},
),
"exclude_domains": (
"STRING",
{
"multiline": True,
"tooltip": "A list of domains to exclude from the search results",
},
),
}
)
inputs["optional"].update(
{
"api_key_env_var": (
"STRING",
{"default": DEFAULT_API_KEY_ENV_VAR},
),
}
)
return inputs
def create(self, **kwargs):
search_depth = kwargs.get("search_depth", "basic")
topic = kwargs.get("topic", "general")
days = kwargs.get("days", 3)
max_results = kwargs.get("max_results", 5)
include_answer = kwargs.get("include_answer", False)
include_raw_content = kwargs.get("include_raw_content", False)
include_domains = kwargs.get("include_domains", None)
exclude_domains = kwargs.get("exclude_domains", None)
TAVILY_API_KEY = self.getenv(
kwargs.get("api_key_env_var", DEFAULT_API_KEY_ENV_VAR)
)
if not TAVILY_API_KEY:
raise Exception(
"Tavily API Key not found. Please set the environment variable TAVILY_API_KEY."
)
tavily_params = {}
addl_params = {}
addl_params["search_depth"] = search_depth
addl_params["topic"] = topic
if topic == "news":
addl_params["days"] = days
tavily_params["results_count"] = max_results
addl_params["include_answer"] = include_answer
addl_params["include_raw_content"] = include_raw_content
if include_domains:
addl_params["include_domains"] = include_domains.split("\n")
if exclude_domains:
addl_params["exclude_domains"] = exclude_domains.split("\n")
if TAVILY_API_KEY:
tavily_params["api_key"] = TAVILY_API_KEY
driver = TavilyWebSearchDriver(**tavily_params, params=addl_params)
return (driver,)
nodes/rag/gtUITextLoaderRetrievalRagModule.py
+9 -1
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@@ -1,3 +1,5 @@
import tempfile
from griptape.engines.rag.modules import TextLoaderRetrievalRagModule
from griptape.loaders import CsvLoader, TextLoader, WebLoader
@@ -53,8 +55,14 @@ class gtUITextLoaderRetrievalRagModule(gtUIBaseRetrievalRagModule):
params["query_params"] = self.get_query_params(kwargs)
params["vector_store_driver"] = vector_store_driver
if loader == "TextLoader":
# write the text to a temnporary file
with tempfile.NamedTemporaryFile(delete=False) as temp_file:
temp_file.write(text.encode())
temp_filename = temp_file.name
temp_file.close()
params["loader"] = TextLoader()
params["source"] = temp_filename
params["loader"] = TextLoader()
params["source"] = text
if loader == "WebLoader":
params["loader"] = WebLoader()
params["source"] = url
nodes/tasks/gtUIAudioTranscriptionTask.py
+1 -2
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@@ -13,7 +13,6 @@ from griptape.structures import Pipeline
from griptape.tasks import (
AudioTranscriptionTask,
)
from griptape.utils import load_file
from ..agent.gtComfyAgent import gtComfyAgent as Agent
from .gtUIBaseAudioTask import gtUIBaseAudioTask
@@ -61,7 +60,7 @@ class gtUIAudioTranscriptionTask(gtUIBaseAudioTask):
return ("There is no audio file.",)
try:
audio_artifact = AudioLoader().load(load_file(audio))
audio_artifact = AudioLoader().load(audio)
except Exception as e:
print(f"Error loading audio file: {e}")
if audio_artifact:
nodes/tasks/gtUIImageQueryTask.py
+1 -1
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@@ -43,7 +43,7 @@ class gtUIImageQueryTask(gtUIBaseImageTask):
for base64Image in images:
try:
image_artifacts.append(
ImageLoader().load(base64.b64decode(base64Image))
ImageLoader().parse(base64.b64decode(base64Image))
)
except Exception as e:
raise (f"Couldn't load image {e}")
nodes/tasks/gtUIParallelImageQueryTask.py
+1 -1
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@@ -42,7 +42,7 @@ class gtUIParallelImageQueryTask(gtUIBaseImageTask):
prompt_driver = agent.drivers_config.prompt_driver
rulesets = agent.rulesets
image_artifact = ImageLoader().load(base64.b64decode(final_image[0]))
image_artifact = ImageLoader().parse(base64.b64decode(final_image[0]))
prompt_text = self.get_prompt_text(STRING, input_string)
nodes/tasks/gtUIPromptImageVariationTask.py
+1 -1
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@@ -64,7 +64,7 @@ class gtUIPromptImageVariationTask(gtUIBaseImageTask):
engine = VariationImageGenerationEngine(
image_generation_driver=driver,
)
image_artifact = ImageLoader().load(base64.b64decode(final_image[0]))
image_artifact = ImageLoader().parse(base64.b64decode(final_image[0]))
output_dir = folder_paths.get_temp_directory()
variation_task = VariationImageGenerationTask(
input=(prompt_text, image_artifact),
nodes/tasks/gtUIVectorStoreUpsertTextTask.py
+5 -27
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@@ -1,6 +1,4 @@
from griptape.artifacts import TextArtifact
from griptape.chunkers import TextChunker
from griptape.loaders import TextLoader
from ..agent.gtComfyAgent import gtComfyAgent as Agent
from .gtUIBaseVectorStoreTask import gtUIBaseVectorStoreTask
@@ -52,31 +50,11 @@ class gtUIVectorStoreUpsertTextTask(gtUIBaseVectorStoreTask):
driver = kwargs.get("driver", None)
max_tokens = kwargs.get("max_chunk_tokens", 100)
namespace = kwargs.get("namespace", default_namespace)
# get all the inputs that start with "input_"
inputs = [value for key, value in kwargs.items() if key.startswith("input")]
input = kwargs.get("input", None)
vector_store_driver = self.get_vector_store_driver(agent, driver)
embedding_driver = agent.drivers_config.embedding_driver
# generate artifacts for each input
artifacts = []
for input in inputs:
if isinstance(input, str):
# Use a TextLoader
artifacts = TextLoader(
chunker=TextChunker(max_tokens=max_tokens),
embedding_driver=embedding_driver,
).load(input)
# artifacts.append(TextArtifact(input))
elif isinstance(input, TextArtifact):
artifacts.append(input)
chunker = TextChunker(max_tokens=max_tokens)
chunks = chunker.chunk(input)
# Upsert Artifacts into the Vector Store Driver
[
vector_store_driver.upsert_text_artifact(a, namespace=namespace)
for a in artifacts
]
vector_store_driver.upsert_text_artifacts({namespace: chunks})
return (
agent,
# vector_store_driver,
)
return (agent,)
pyproject.toml
+3 -3
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@@ -7,7 +7,7 @@ readme = "README.md"
[tool.poetry.dependencies]
python = "^3.11"
griptape = { version = "^0.31.0", extras = ["drivers-image-generation-huggingface","diffusers.pipelines.stable_diffusion_3.pipeline_stable_diffusion_3","drivers-prompt-cohere","drivers-prompt-anthropic","drivers-prompt-huggingface-hub","drivers-prompt-amazon-bedrock","drivers-prompt-amazon-sagemaker","drivers-prompt-google","drivers-prompt-ollama","drivers-embedding-amazon-bedrock","drivers-embedding-amazon-sagemaker","drivers-embedding-huggingface","drivers-embedding-voyageai","drivers-embedding-google","drivers-embedding-cohere","drivers-embedding-ollama","drivers-vector-pinecone","drivers-vector-marqo","drivers-vector-mongodb","drivers-vector-redis","drivers-vector-opensearch","drivers-vector-pgvector","drivers-vector-postgresql","drivers-vector-qdrant","drivers-web-scraper-trafilatura","drivers-web-scraper-markdownify","drivers-web-search-duckduckgo","loaders-dataframe","loaders-pdf","loaders-image","loaders-email","loaders-audio", "drivers-text-to-speech-elevenlabs"]}
griptape = { version = "^0.33.0", extras = ["drivers-web-search-tavily","drivers-web-search-exa","drivers-image-generation-huggingface","diffusers.pipelines.stable_diffusion_3.pipeline_stable_diffusion_3","drivers-prompt-cohere","drivers-prompt-anthropic","drivers-prompt-huggingface-hub","drivers-prompt-amazon-bedrock","drivers-prompt-amazon-sagemaker","drivers-prompt-google","drivers-prompt-ollama","drivers-embedding-amazon-bedrock","drivers-embedding-amazon-sagemaker","drivers-embedding-huggingface","drivers-embedding-voyageai","drivers-embedding-google","drivers-embedding-cohere","drivers-embedding-ollama","drivers-vector-pinecone","drivers-vector-marqo","drivers-vector-mongodb","drivers-vector-redis","drivers-vector-opensearch","drivers-vector-pgvector","drivers-vector-postgresql","drivers-vector-qdrant","drivers-web-scraper-trafilatura","drivers-web-scraper-markdownify","drivers-web-search-duckduckgo","loaders-dataframe","loaders-pdf","loaders-image","loaders-email", "drivers-text-to-speech-elevenlabs"]}
python-dotenv = "^1.0.1"
[tool.poetry.group.dev.dependencies]
@@ -26,9 +26,9 @@ priority = "explicit"
[project]
name = "comfyui-griptape"
description = "Griptape LLM(Large Language Model) Nodes for ComfyUI."
version = "1.0.5"
version = "1.0.6"
license = {file = "LICENSE"}
dependencies = ["griptape[drivers-prompt-cohere,drivers-prompt-anthropic,drivers-prompt-huggingface-hub,drivers-prompt-amazon-bedrock,drivers-prompt-amazon-sagemaker,drivers-prompt-google,drivers-prompt-ollama,drivers-embedding-amazon-bedrock,drivers-embedding-amazon-sagemaker,drivers-embedding-huggingface,drivers-embedding-voyageai,drivers-embedding-google,drivers-embedding-cohere,drivers-text-to-speech-elevenlabs,drivers-vector-pinecone,drivers-vector-marqo,drivers-vector-mongodb,drivers-vector-redis,drivers-vector-opensearch,drivers-vector-pgvector,drivers-vector-qdrant,drivers-web-scraper-trafilatura,drivers-web-scraper-markdownify,drivers-web-search-duckduckgo,loaders-dataframe,loaders-pdf,loaders-image,loaders-email,loaders-audio]==0.31.0", "python-dotenv"]
dependencies = ["griptape[drivers-web-search-tavily,drivers-web-search-exa,drivers-prompt-cohere,drivers-prompt-anthropic,drivers-prompt-huggingface-hub,drivers-prompt-amazon-bedrock,drivers-prompt-amazon-sagemaker,drivers-prompt-google,drivers-prompt-ollama,drivers-embedding-amazon-bedrock,drivers-embedding-amazon-sagemaker,drivers-embedding-huggingface,drivers-embedding-voyageai,drivers-embedding-google,drivers-embedding-cohere,drivers-text-to-speech-elevenlabs,drivers-vector-pinecone,drivers-vector-marqo,drivers-vector-mongodb,drivers-vector-redis,drivers-vector-opensearch,drivers-vector-pgvector,drivers-vector-qdrant,drivers-web-scraper-trafilatura,drivers-web-scraper-markdownify,drivers-web-search-duckduckgo,loaders-dataframe,loaders-pdf,loaders-image,loaders-email]==0.33.0", "python-dotenv"]
[project.urls]
Repository = "https://github.com/griptape-ai/ComfyUI-Griptape"
requirements.txt
+1 -1
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@@ -1,2 +1,2 @@
griptape[drivers-prompt-cohere,drivers-prompt-anthropic,drivers-prompt-huggingface-hub,drivers-prompt-amazon-bedrock,drivers-prompt-amazon-sagemaker,drivers-prompt-google,drivers-prompt-ollama,drivers-embedding-amazon-bedrock,drivers-embedding-amazon-sagemaker,drivers-embedding-huggingface,drivers-embedding-voyageai,drivers-embedding-google,drivers-embedding-cohere,drivers-text-to-speech-elevenlabs,drivers-vector-pinecone,drivers-vector-marqo,drivers-vector-mongodb,drivers-vector-redis,drivers-vector-opensearch,drivers-vector-pgvector,drivers-vector-qdrant,drivers-web-scraper-trafilatura,drivers-web-scraper-markdownify,drivers-web-search-duckduckgo,loaders-dataframe,loaders-pdf,loaders-image,loaders-email,loaders-audio]==0.31.0
griptape[drivers-web-search-tavily,drivers-web-search-exa,drivers-prompt-cohere,drivers-prompt-anthropic,drivers-prompt-huggingface-hub,drivers-prompt-amazon-bedrock,drivers-prompt-amazon-sagemaker,drivers-prompt-google,drivers-prompt-ollama,drivers-embedding-amazon-bedrock,drivers-embedding-amazon-sagemaker,drivers-embedding-huggingface,drivers-embedding-voyageai,drivers-embedding-google,drivers-embedding-cohere,drivers-text-to-speech-elevenlabs,drivers-vector-pinecone,drivers-vector-marqo,drivers-vector-mongodb,drivers-vector-redis,drivers-vector-opensearch,drivers-vector-pgvector,drivers-vector-qdrant,drivers-web-scraper-trafilatura,drivers-web-scraper-markdownify,drivers-web-search-duckduckgo,loaders-dataframe,loaders-pdf,loaders-image,loaders-email]==0.33.0
python-dotenv
tests/rag_workflow.py
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# use tempfile to create a temporary file
from dotenv import load_dotenv
from griptape.chunkers import TextChunker
from griptape.drivers import LocalVectorStoreDriver, OpenAiEmbeddingDriver
from griptape.engines.rag import RagEngine
from griptape.engines.rag.modules import TextLoaderRetrievalRagModule
from griptape.engines.rag.stages import RetrievalRagStage
from griptape.loaders import TextLoader
from griptape.structures import Agent
from griptape.tools import QueryTool, RagTool
load_dotenv()
text = """
Wonderbread.ai is a fictitional company that specializes in creating balloon animals for the future.
They are often confused with the bread company, Wonder Bread, but they are not the same.
Some of the services that Wonderbread.ai offers include:
- Balloon animal creation
- Balloon animal delivery
- Balloon animal training
- Balloon animal parties
- Balloon animal events
- Balloon animal consulting
- Balloon animal workshops
- Balloon animal classes
- Balloon animal seminars
- Balloon animal webinars
- Balloon animal conferences
Wonderbread.ai is a leader in the balloon animal industry and has been in business for over 100 years.
They have a team of experts who are dedicated to creating the best balloon animals in the world.
If you are interested in learning more about Wonderbread.ai, please visit their website at www.wonderbread.ai/balloonanimals
"""
chunker = TextChunker()
chunks = chunker.chunk(text)
module = TextLoaderRetrievalRagModule(
query_params={"namespace": "wonderbread"},
vector_store_driver=LocalVectorStoreDriver(
embedding_driver=OpenAiEmbeddingDriver()
),
loader=TextLoader().parse(text),
)
retrieval_modules = [module]
rag_engine = RagEngine(
retrieval_stage=RetrievalRagStage(retrieval_modules=retrieval_modules),
)
tool = RagTool(
off_prompt=True, description="Contains info about a company", rag_engine=rag_engine
)
agent = Agent(tools=[tool, QueryTool()])
agent.run("What does the company Wonderbread.ai do?")