Pre/beta

CHANGELOG.md

@@ -1,3 +1,17 @@
+## [1.22.0-beta.5](https://github.com/ScrapeGraphAI/Scrapegraph-ai/compare/v1.22.0-beta.4...v1.22.0-beta.5) (2024-09-27)
+
+
+### Features
+
+* add reasoning integration ([b2822f6](https://github.com/ScrapeGraphAI/Scrapegraph-ai/commit/b2822f620a610e61d295cbf4b670aa08fde9de24))
+
+## [1.22.0-beta.4](https://github.com/ScrapeGraphAI/Scrapegraph-ai/compare/v1.22.0-beta.3...v1.22.0-beta.4) (2024-09-27)
+
+
+### Features
+
+* add html_mode to smart_scraper ([bdcffd6](https://github.com/ScrapeGraphAI/Scrapegraph-ai/commit/bdcffd6360237b27797546a198ceece55ce4bc81))
+
 ## [1.22.0-beta.3](https://github.com/ScrapeGraphAI/Scrapegraph-ai/compare/v1.22.0-beta.2...v1.22.0-beta.3) (2024-09-25)
 
 

examples/extras/html_mode.py

@@ -0,0 +1,49 @@
+""" 
+Basic example of scraping pipeline using SmartScraper
+By default smart scraper converts in md format the 
+code. If you want to just use the original code, you have
+to specify in the confi
+"""
+
+import os
+import 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
+# ************************************************
+
+
+graph_config = {
+    "llm": {
+        "api_key": os.getenv("OPENAI_API_KEY"),
+        "model": "openai/gpt-4o",
+    },
+    "html_mode": True,
+    "verbose": True,
+    "headless": False,
+}
+
+# ************************************************
+# Create the SmartScraperGraph instance and run it
+# ************************************************
+
+smart_scraper_graph = SmartScraperGraph(
+    prompt="List me what does the company do, the name and a contact email.",
+    source="https://scrapegraphai.com/",
+    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

@@ -1,7 +1,7 @@
 [project]
 name = "scrapegraphai"
 
-version = "1.22.0b3"
+version = "1.22.0b5"
 
 description = "A web scraping library based on LangChain which uses LLM and direct graph logic to create scraping pipelines."
 authors = [

scrapegraphai/graphs/smart_scraper_graph.py

@@ -70,14 +70,7 @@ def _create_graph(self) -> BaseGraph:
                 "scrape_do": self.config.get("scrape_do")
             }
         )
-        parse_node = ParseNode(
-            input="doc",
-            output=["parsed_doc"],
-            node_config={
-                "llm_model": self.llm_model,
-                "chunk_size": self.model_token
-            }
-        )
+
 
         generate_answer_node = GenerateAnswerNode(
             input="user_prompt & (relevant_chunks | parsed_doc | doc)",
@@ -89,6 +82,15 @@ def _create_graph(self) -> BaseGraph:
             }
         )
 
+        if self.config.get("html_mode") is not True:
+
+            parse_node = ParseNode(
+                input="doc",
+                output=["parsed_doc"],
+                node_config={
+                    "llm_model": self.llm_model,
+                    "chunk_size": self.model_token
+
         if self.config.get("reasoning"):
             reasoning_node =  ReasoningNode(
                 input="user_prompt & (relevant_chunks | parsed_doc | doc)",
@@ -104,11 +106,13 @@ def _create_graph(self) -> BaseGraph:
                 nodes=[
                     fetch_node,
                     parse_node,
+
                     reasoning_node,
                     generate_answer_node,
                 ],
                 edges=[
                     (fetch_node, parse_node),
+                    (parse_node, generate_answer_node)
                     (parse_node, reasoning_node),
                     (reasoning_node, generate_answer_node)
                 ],
@@ -117,18 +121,17 @@ def _create_graph(self) -> BaseGraph:
             )
 
         return BaseGraph(
-            nodes=[
-                fetch_node,
-                parse_node,
-                generate_answer_node,
-            ],
-            edges=[
-                (fetch_node, parse_node),
-                (parse_node, generate_answer_node)
-            ],
-            entry_point=fetch_node,
-            graph_name=self.__class__.__name__
-        )
+                nodes=[
+                    fetch_node,
+                    generate_answer_node,
+                ],
+                edges=[
+                    (fetch_node,  generate_answer_node)
+                ],
+                entry_point=fetch_node,
+                graph_name=self.__class__.__name__
+            )
+
 
     def run(self) -> str:
         """