feat: add fireworks integration

examples/fireworks/.env.example

@@ -0,0 +1 @@
+FIREWORKS_APIKEY="your fireworks api key"

examples/fireworks/smart_scraper_fireworks.py

@@ -0,0 +1,52 @@
+""" 
+Basic example of scraping pipeline using SmartScraper
+"""
+
+import os, json
+from dotenv import load_dotenv
+from scrapegraphai.graphs import SmartScraperGraph
+from scrapegraphai.utils import prettify_exec_info
+
+load_dotenv()
+
+
+# ************************************************
+# Define the configuration for the graph
+# ************************************************
+
+fireworks_api_key = os.getenv("FIREWORKS_APIKEY")
+
+graph_config = {
+    "llm": {
+        "api_key": fireworks_api_key,
+        "model": "fireworks/accounts/fireworks/models/mixtral-8x7b-instruct"
+    },
+     "embeddings": {
+        "model": "ollama/nomic-embed-text",
+        "temperature": 0,
+        # "base_url": "http://localhost:11434",  # set ollama URL arbitrarily
+    },
+    "verbose": True,
+    "headless": False,
+}
+
+# ************************************************
+# Create the SmartScraperGraph instance and run it
+# ************************************************
+
+smart_scraper_graph = SmartScraperGraph(
+    prompt="List me all the projects with their description",
+    # also accepts a string with the already downloaded HTML code
+    source="https://perinim.github.io/projects/",
+    config=graph_config,
+)
+
+result = smart_scraper_graph.run()
+print(json.dumps(result, indent=4))
+
+# ************************************************
+# Get graph execution info
+# ************************************************
+
+graph_exec_info = smart_scraper_graph.get_execution_info()
+print(prettify_exec_info(graph_exec_info))

pyproject.toml

@@ -33,6 +33,7 @@ dependencies = [
     "google==3.0.0",
     "undetected-playwright==0.3.0",
     "semchunk==1.0.1",
+    "langchain-fireworks==0.1.3"
 ]
 
 license = "MIT"

requirements-dev.lock

@@ -13,6 +13,7 @@ aiofiles==23.2.1
 aiohttp==3.9.5
     # via langchain
     # via langchain-community
+    # via langchain-fireworks
 aiosignal==1.3.1
     # via aiohttp
 alabaster==0.7.16
@@ -93,6 +94,8 @@ fastapi-pagination==0.12.24
     # via burr
 filelock==3.14.0
     # via huggingface-hub
+fireworks-ai==0.14.0
+    # via langchain-fireworks
 fonttools==4.52.1
     # via matplotlib
 free-proxy==1.1.1
@@ -158,8 +161,11 @@ httptools==0.6.1
 httpx==0.27.0
     # via anthropic
     # via fastapi
+    # via fireworks-ai
     # via groq
     # via openai
+httpx-sse==0.4.0
+    # via fireworks-ai
 huggingface-hub==0.23.1
     # via tokenizers
 idna==3.7
@@ -207,10 +213,13 @@ langchain-core==0.1.52
     # via langchain-anthropic
     # via langchain-aws
     # via langchain-community
+    # via langchain-fireworks
     # via langchain-google-genai
     # via langchain-groq
     # via langchain-openai
     # via langchain-text-splitters
+langchain-fireworks==0.1.3
+    # via scrapegraphai
 langchain-google-genai==1.0.3
     # via scrapegraphai
 langchain-groq==0.1.3
@@ -259,6 +268,7 @@ numpy==1.26.4
     # via streamlit
 openai==1.30.3
     # via burr
+    # via langchain-fireworks
     # via langchain-openai
 orjson==3.10.3
     # via fastapi
@@ -278,6 +288,7 @@ pandas==2.2.2
     # via sf-hamilton
     # via streamlit
 pillow==10.3.0
+    # via fireworks-ai
     # via matplotlib
     # via streamlit
 playwright==1.43.0
@@ -308,6 +319,7 @@ pydantic==2.7.1
     # via burr
     # via fastapi
     # via fastapi-pagination
+    # via fireworks-ai
     # via google-generativeai
     # via groq
     # via langchain
@@ -359,6 +371,7 @@ requests==2.32.2
     # via huggingface-hub
     # via langchain
     # via langchain-community
+    # via langchain-fireworks
     # via langsmith
     # via sphinx
     # via streamlit

requirements.lock

@@ -11,6 +11,7 @@
 aiohttp==3.9.5
     # via langchain
     # via langchain-community
+    # via langchain-fireworks
 aiosignal==1.3.1
     # via aiohttp
 annotated-types==0.7.0
@@ -53,6 +54,8 @@ faiss-cpu==1.8.0
     # via scrapegraphai
 filelock==3.14.0
     # via huggingface-hub
+fireworks-ai==0.14.0
+    # via langchain-fireworks
 free-proxy==1.1.1
     # via scrapegraphai
 frozenlist==1.4.1
@@ -105,8 +108,11 @@ httplib2==0.22.0
     # via google-auth-httplib2
 httpx==0.27.0
     # via anthropic
+    # via fireworks-ai
     # via groq
     # via openai
+httpx-sse==0.4.0
+    # via fireworks-ai
 huggingface-hub==0.23.1
     # via tokenizers
 idna==3.7
@@ -137,10 +143,13 @@ langchain-core==0.1.52
     # via langchain-anthropic
     # via langchain-aws
     # via langchain-community
+    # via langchain-fireworks
     # via langchain-google-genai
     # via langchain-groq
     # via langchain-openai
     # via langchain-text-splitters
+langchain-fireworks==0.1.3
+    # via scrapegraphai
 langchain-google-genai==1.0.3
     # via scrapegraphai
 langchain-groq==0.1.3
@@ -171,6 +180,7 @@ numpy==1.26.4
     # via langchain-community
     # via pandas
 openai==1.30.3
+    # via langchain-fireworks
     # via langchain-openai
 orjson==3.10.3
     # via langsmith
@@ -180,6 +190,8 @@ packaging==23.2
     # via marshmallow
 pandas==2.2.2
     # via scrapegraphai
+pillow==10.3.0
+    # via fireworks-ai
 playwright==1.43.0
     # via scrapegraphai
     # via undetected-playwright
@@ -200,6 +212,7 @@ pyasn1-modules==0.4.0
     # via google-auth
 pydantic==2.7.1
     # via anthropic
+    # via fireworks-ai
     # via google-generativeai
     # via groq
     # via langchain
@@ -232,6 +245,7 @@ requests==2.32.2
     # via huggingface-hub
     # via langchain
     # via langchain-community
+    # via langchain-fireworks
     # via langsmith
     # via tiktoken
 rsa==4.9

requirements.txt

@@ -17,4 +17,5 @@ langchain-groq==0.1.3
 playwright==1.43.0
 langchain-aws==0.1.2
 undetected-playwright==0.3.0
-semchunk==1.0.1
+semchunk==1.0.1
+langchain-fireworks==0.1.3

scrapegraphai/graphs/abstract_graph.py

@@ -11,6 +11,7 @@ from langchain_aws import BedrockEmbeddings
 from langchain_community.embeddings import HuggingFaceHubEmbeddings, OllamaEmbeddings
 from langchain_google_genai import GoogleGenerativeAIEmbeddings
 from langchain_google_genai.embeddings import GoogleGenerativeAIEmbeddings
+from langchain_fireworks import FireworksEmbeddings
 from langchain_openai import AzureOpenAIEmbeddings, OpenAIEmbeddings
 
 from ..helpers import models_tokens
@@ -23,7 +24,8 @@ from ..models import (
     HuggingFace,
     Ollama,
     OpenAI,
-    OneApi
+    OneApi,
+    Fireworks
 )
 from ..models.ernie import Ernie
 from ..utils.logging import set_verbosity_debug, set_verbosity_warning, set_verbosity_info
@@ -102,7 +104,7 @@ class AbstractGraph(ABC):
             "embedder_model": self.embedder_model,
             "cache_path": self.cache_path,
             }
-       
+
         self.set_common_params(common_params, overwrite=True)
 
         # set burr config
@@ -125,7 +127,7 @@ class AbstractGraph(ABC):
 
         for node in self.graph.nodes:
             node.update_config(params, overwrite)
-    
+
     def _create_llm(self, llm_config: dict, chat=False) -> object:
         """
         Create a large language model instance based on the configuration provided.
@@ -160,8 +162,15 @@ class AbstractGraph(ABC):
             try:
                 self.model_token = models_tokens["oneapi"][llm_params["model"]]
             except KeyError as exc:
-                raise KeyError("Model Model not supported") from exc
+                raise KeyError("Model not supported") from exc
             return OneApi(llm_params)
+        elif "fireworks" in llm_params["model"]:
+            try:
+                self.model_token = models_tokens["fireworks"][llm_params["model"].split("/")[-1]]
+                llm_params["model"] = "/".join(llm_params["model"].split("/")[1:])
+            except KeyError as exc:
+                raise KeyError("Model not supported") from exc
+            return Fireworks(llm_params)
         elif "azure" in llm_params["model"]:
             # take the model after the last dash
             llm_params["model"] = llm_params["model"].split("/")[-1]
@@ -172,12 +181,14 @@ class AbstractGraph(ABC):
             return AzureOpenAI(llm_params)
 
         elif "gemini" in llm_params["model"]:
+            llm_params["model"] = llm_params["model"].split("/")[-1]
             try:
                 self.model_token = models_tokens["gemini"][llm_params["model"]]
             except KeyError as exc:
                 raise KeyError("Model not supported") from exc
             return Gemini(llm_params)
         elif llm_params["model"].startswith("claude"):
+            llm_params["model"] = llm_params["model"].split("/")[-1]
             try:
                 self.model_token = models_tokens["claude"][llm_params["model"]]
             except KeyError as exc:
@@ -203,6 +214,7 @@ class AbstractGraph(ABC):
 
             return Ollama(llm_params)
         elif "hugging_face" in llm_params["model"]:
+            llm_params["model"] = llm_params["model"].split("/")[-1]
             try:
                 self.model_token = models_tokens["hugging_face"][llm_params["model"]]
             except KeyError:
@@ -277,12 +289,13 @@ class AbstractGraph(ABC):
         if isinstance(self.llm_model, OpenAI):
             return OpenAIEmbeddings(api_key=self.llm_model.openai_api_key, base_url=self.llm_model.openai_api_base)
         elif isinstance(self.llm_model, DeepSeek):
-            return OpenAIEmbeddings(api_key=self.llm_model.openai_api_key)   
+            return OpenAIEmbeddings(api_key=self.llm_model.openai_api_key)
-
         elif isinstance(self.llm_model, AzureOpenAIEmbeddings):
             return self.llm_model
         elif isinstance(self.llm_model, AzureOpenAI):
             return AzureOpenAIEmbeddings()
+        elif isinstance(self.llm_model, Fireworks):
+            return FireworksEmbeddings(model=self.llm_model.model_name)
         elif isinstance(self.llm_model, Ollama):
             # unwrap the kwargs from the model whihc is a dict
             params = self.llm_model._lc_kwargs
@@ -333,6 +346,13 @@ class AbstractGraph(ABC):
             except KeyError as exc:
                 raise KeyError("Model not supported") from exc
             return HuggingFaceHubEmbeddings(model=embedder_params["model"])
+        elif "fireworks" in embedder_params["model"]:
+            embedder_params["model"] = "/".join(embedder_params["model"].split("/")[1:])
+            try:
+                models_tokens["fireworks"][embedder_params["model"]]
+            except KeyError as exc:
+                raise KeyError("Model not supported") from exc
+            return FireworksEmbeddings(model=embedder_params["model"])
         elif "gemini" in embedder_params["model"]:
             try:
                 models_tokens["gemini"][embedder_params["model"]]

scrapegraphai/helpers/models_tokens.py

@@ -143,5 +143,10 @@ models_tokens = {
         "ernie-bot-2-base-en": 4096,
         "ernie-bot-2-base-en-zh": 4096,
         "ernie-bot-2-base-zh-en": 4096
-    }
+    },
+    "fireworks": {
+        "llama-v2-7b": 4096,
+        "mixtral-8x7b-instruct": 4096,
+        "nomic-ai/nomic-embed-text-v1.5": 8192        
+    },
 }

scrapegraphai/models/__init__.py

@@ -14,3 +14,4 @@ from .bedrock import Bedrock
 from .anthropic import Anthropic
 from .deepseek import DeepSeek
 from .oneapi import OneApi
+from .fireworks import Fireworks

scrapegraphai/models/fireworks.py

@@ -0,0 +1,33 @@
+"""
+Fireworks Module
+"""
+from langchain_fireworks import ChatFireworks
+
+
+class Fireworks(ChatFireworks):
+  """
+  Initializes the Fireworks class.
+
+  Args:
+      llm_config (dict): A dictionary containing configuration parameters for the LLM (required).
+          The specific keys and values will depend on the LLM implementation
+          used by the underlying `ChatFireworks` class. Consult its documentation
+          for details.
+
+  Raises:
+      ValueError: If required keys are missing from the llm_config dictionary.
+  """
+
+  def __init__(self, llm_config: dict):
+      """
+      Initializes the Fireworks class.
+
+      Args:
+          llm_config (dict): A dictionary containing configuration parameters for the LLM.
+              The specific keys and values will depend on the LLM implementation.
+
+      Raises:
+          ValueError: If required keys are missing from the llm_config dictionary.
+      """
+
+      super().__init__(**llm_config)