fix: async invocation

VinciGit00 · VinciGit00 · commit c2179abc60d1 · 2024-10-13T11:30:39.000+02:00
diff --git a/scrapegraphai/builders/graph_builder.py b/scrapegraphai/builders/graph_builder.py
@@ -119,7 +119,7 @@ def build_graph(self):
         Returns:
             dict: A JSON representation of the graph configuration.
         """
-        return self.chain.ainvoke(self.prompt)
+        return self.chain.invoke(self.prompt)
 
     @staticmethod
     def convert_json_to_graphviz(json_data, format: str = 'pdf'):
diff --git a/scrapegraphai/nodes/generate_answer_csv_node.py b/scrapegraphai/nodes/generate_answer_csv_node.py
@@ -126,7 +126,7 @@ def execute(self, state):
             )
 
             chain =  prompt | self.llm_model | output_parser
-            answer = chain.ainvoke({"question": user_prompt})
+            answer = chain.invoke({"question": user_prompt})
             state.update({self.output[0]: answer})
             return state
 
diff --git a/scrapegraphai/nodes/generate_answer_node_k_level.py b/scrapegraphai/nodes/generate_answer_node_k_level.py
@@ -143,7 +143,7 @@ def execute(self, state: dict) -> dict:
         merge_chain = merge_prompt | self.llm_model
         if output_parser:
             merge_chain = merge_chain | output_parser
-        answer = merge_chain.ainvoke({"context": batch_results, "question": user_prompt})
+        answer = merge_chain.invoke({"context": batch_results, "question": user_prompt})
 
         state["answer"] = answer
 
diff --git a/scrapegraphai/nodes/generate_answer_omni_node.py b/scrapegraphai/nodes/generate_answer_omni_node.py
@@ -117,7 +117,7 @@ def execute(self, state: dict) -> dict:
             )
 
             chain =  prompt | self.llm_model | output_parser
-            answer = chain.ainvoke({"question": user_prompt})
+            answer = chain.invoke({"question": user_prompt})
 
             state.update({self.output[0]: answer})
             return state
@@ -149,7 +149,7 @@ def execute(self, state: dict) -> dict:
             )
 
         merge_chain = merge_prompt | self.llm_model | output_parser
-        answer = merge_chain.ainvoke({"context": batch_results, "question": user_prompt})
+        answer = merge_chain.invoke({"context": batch_results, "question": user_prompt})
 
         state.update({self.output[0]: answer})
         return state
diff --git a/scrapegraphai/nodes/generate_code_node.py b/scrapegraphai/nodes/generate_code_node.py
@@ -325,7 +325,7 @@ def generate_initial_code(self, state: dict) -> str:
         output_parser = StrOutputParser()
 
         chain =  prompt | self.llm_model | output_parser
-        generated_code = chain.ainvoke({})
+        generated_code = chain.invoke({})
         return generated_code
 
     def semantic_comparison(self, generated_result: Any, reference_result: Any) -> Dict[str, Any]:
@@ -368,7 +368,7 @@ def semantic_comparison(self, generated_result: Any, reference_result: Any) -> D
         )
 
         chain = prompt | self.llm_model | output_parser
-        return chain.ainvoke({
+        return chain.invoke({
             "generated_result": json.dumps(generated_result, indent=2),
             "reference_result": json.dumps(reference_result_dict, indent=2)
         })
diff --git a/scrapegraphai/nodes/generate_scraper_node.py b/scrapegraphai/nodes/generate_scraper_node.py
@@ -130,7 +130,7 @@ def execute(self, state: dict) -> dict:
         )
         map_chain = prompt | self.llm_model | StrOutputParser()
 
-        answer = map_chain.ainvoke({"question": user_prompt})
+        answer = map_chain.invoke({"question": user_prompt})
 
         state.update({self.output[0]: answer})
         return state
diff --git a/scrapegraphai/nodes/html_analyzer_node.py b/scrapegraphai/nodes/html_analyzer_node.py
@@ -93,7 +93,7 @@ def execute(self, state: dict) -> dict:
         output_parser = StrOutputParser()
 
         chain =  prompt | self.llm_model | output_parser
-        html_analysis = chain.ainvoke({})
+        html_analysis = chain.invoke({})
 
         state.update({self.output[0]: html_analysis, self.output[1]: reduced_html})
         return state
diff --git a/scrapegraphai/nodes/merge_answers_node.py b/scrapegraphai/nodes/merge_answers_node.py
@@ -95,7 +95,7 @@ def execute(self, state: dict) -> dict:
         )
 
         merge_chain = prompt_template | self.llm_model | output_parser
-        answer = merge_chain.ainvoke({"user_prompt": user_prompt})
+        answer = merge_chain.invoke({"user_prompt": user_prompt})
         answer["sources"] = state.get("urls", [])
 
         state.update({self.output[0]: answer})
diff --git a/scrapegraphai/nodes/merge_generated_scripts_node.py b/scrapegraphai/nodes/merge_generated_scripts_node.py
@@ -74,7 +74,7 @@ def execute(self, state: dict) -> dict:
         )
 
         merge_chain = prompt_template | self.llm_model | StrOutputParser()
-        answer = merge_chain.ainvoke({"user_prompt": user_prompt})
+        answer = merge_chain.invoke({"user_prompt": user_prompt})
 
         state.update({self.output[0]: answer})
         return state
diff --git a/scrapegraphai/nodes/prompt_refiner_node.py b/scrapegraphai/nodes/prompt_refiner_node.py
@@ -96,7 +96,7 @@ def execute(self, state: dict) -> dict:
         output_parser = StrOutputParser()
 
         chain =  prompt | self.llm_model | output_parser
-        refined_prompt = chain.ainvoke({})
+        refined_prompt = chain.invoke({})
 
         state.update({self.output[0]: refined_prompt})
         return state
diff --git a/scrapegraphai/nodes/reasoning_node.py b/scrapegraphai/nodes/reasoning_node.py
@@ -91,7 +91,7 @@ def execute(self, state: dict) -> dict:
         output_parser = StrOutputParser()
 
         chain =  prompt | self.llm_model | output_parser
-        refined_prompt = chain.ainvoke({})
+        refined_prompt = chain.invoke({})
 
         state.update({self.output[0]: refined_prompt})
         return state
diff --git a/scrapegraphai/nodes/robots_node.py b/scrapegraphai/nodes/robots_node.py
@@ -108,7 +108,7 @@ def execute(self, state: dict) -> dict:
             )
 
             chain = prompt | self.llm_model | output_parser
-            is_scrapable = chain.ainvoke({"path": source})[0]
+            is_scrapable = chain.invoke({"path": source})[0]
 
             if "no" in is_scrapable:
                 self.logger.warning(
diff --git a/scrapegraphai/nodes/search_link_node.py b/scrapegraphai/nodes/search_link_node.py
@@ -142,7 +142,7 @@ def execute(self, state: dict) -> dict:
                     input_variables=["content", "user_prompt"],
                 )
                 merge_chain = merge_prompt | self.llm_model | output_parser
-                answer = merge_chain.ainvoke(
+                answer = merge_chain.invoke(
                     {"content": chunk.page_content}
                 )
                 relevant_links += answer
diff --git a/scrapegraphai/utils/code_error_analysis.py b/scrapegraphai/utils/code_error_analysis.py
@@ -33,7 +33,7 @@ def syntax_focused_analysis(state: dict, llm_model) -> str:
     prompt = PromptTemplate(template=TEMPLATE_SYNTAX_ANALYSIS,
                             input_variables=["generated_code", "errors"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "generated_code": state["generated_code"],
         "errors": state["errors"]["syntax"]
     })
@@ -53,7 +53,7 @@ def execution_focused_analysis(state: dict, llm_model) -> str:
                             input_variables=["generated_code", "errors",
                                               "html_code", "html_analysis"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "generated_code": state["generated_code"],
         "errors": state["errors"]["execution"],
         "html_code": state["html_code"],
@@ -76,7 +76,7 @@ def validation_focused_analysis(state: dict, llm_model) -> str:
                             input_variables=["generated_code", "errors", 
                                              "json_schema", "execution_result"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "generated_code": state["generated_code"],
         "errors": state["errors"]["validation"],
         "json_schema": state["json_schema"],
@@ -100,7 +100,7 @@ def semantic_focused_analysis(state: dict, comparison_result: Dict[str, Any], ll
                             input_variables=["generated_code", 
                                              "differences", "explanation"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "generated_code": state["generated_code"],
         "differences": json.dumps(comparison_result["differences"], indent=2),
         "explanation": comparison_result["explanation"]
diff --git a/scrapegraphai/utils/code_error_correction.py b/scrapegraphai/utils/code_error_correction.py
@@ -32,7 +32,7 @@ def syntax_focused_code_generation(state: dict, analysis: str, llm_model) -> str
     prompt = PromptTemplate(template=TEMPLATE_SYNTAX_CODE_GENERATION,
                             input_variables=["analysis", "generated_code"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "analysis": analysis,
         "generated_code": state["generated_code"]
     })
@@ -52,7 +52,7 @@ def execution_focused_code_generation(state: dict, analysis: str, llm_model) ->
     prompt = PromptTemplate(template=TEMPLATE_EXECUTION_CODE_GENERATION,
                             input_variables=["analysis", "generated_code"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "analysis": analysis,
         "generated_code": state["generated_code"]
     })
@@ -72,7 +72,7 @@ def validation_focused_code_generation(state: dict, analysis: str, llm_model) ->
     prompt = PromptTemplate(template=TEMPLATE_VALIDATION_CODE_GENERATION,
                             input_variables=["analysis", "generated_code", "json_schema"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "analysis": analysis,
         "generated_code": state["generated_code"],
         "json_schema": state["json_schema"]
@@ -93,7 +93,7 @@ def semantic_focused_code_generation(state: dict, analysis: str, llm_model) -> s
     prompt = PromptTemplate(template=TEMPLATE_SEMANTIC_CODE_GENERATION,
                             input_variables=["analysis", "generated_code", "generated_result", "reference_result"])
     chain = prompt | llm_model | StrOutputParser()
-    return chain.ainvoke({
+    return chain.invoke({
         "analysis": analysis,
         "generated_code": state["generated_code"],
         "generated_result": json.dumps(state["execution_result"], indent=2),

Original file line number	Diff line number	Diff line change
`@@ -126,7 +126,7 @@ def execute(self, state):`
`126`	`126`	`)`
`127`	`127`
`128`	`128`	`chain = prompt \| self.llm_model \| output_parser`
`129`		`- answer = chain.ainvoke({"question": user_prompt})`
	`129`	`+ answer = chain.invoke({"question": user_prompt})`
`130`	`130`	`state.update({self.output[0]: answer})`
`131`	`131`	`return state`
`132`	`132`
Original file line number	Diff line number	Diff line change
`@@ -117,7 +117,7 @@ def execute(self, state: dict) -> dict:`
`117`	`117`	`)`
`118`	`118`
`119`	`119`	`chain = prompt \| self.llm_model \| output_parser`
`120`		`- answer = chain.ainvoke({"question": user_prompt})`
	`120`	`+ answer = chain.invoke({"question": user_prompt})`
`121`	`121`
`122`	`122`	`state.update({self.output[0]: answer})`
`123`	`123`	`return state`
`@@ -149,7 +149,7 @@ def execute(self, state: dict) -> dict:`
`149`	`149`	`)`
`150`	`150`
`151`	`151`	`merge_chain = merge_prompt \| self.llm_model \| output_parser`
`152`		`- answer = merge_chain.ainvoke({"context": batch_results, "question": user_prompt})`
	`152`	`+ answer = merge_chain.invoke({"context": batch_results, "question": user_prompt})`
`153`	`153`
`154`	`154`	`state.update({self.output[0]: answer})`
`155`	`155`	`return state`
Original file line number	Diff line number	Diff line change
`@@ -130,7 +130,7 @@ def execute(self, state: dict) -> dict:`
`130`	`130`	`)`
`131`	`131`	`map_chain = prompt \| self.llm_model \| StrOutputParser()`
`132`	`132`
`133`		`- answer = map_chain.ainvoke({"question": user_prompt})`
	`133`	`+ answer = map_chain.invoke({"question": user_prompt})`
`134`	`134`
`135`	`135`	`state.update({self.output[0]: answer})`
`136`	`136`	`return state`
Original file line number	Diff line number	Diff line change
`@@ -95,7 +95,7 @@ def execute(self, state: dict) -> dict:`
`95`	`95`	`)`
`96`	`96`
`97`	`97`	`merge_chain = prompt_template \| self.llm_model \| output_parser`
`98`		`- answer = merge_chain.ainvoke({"user_prompt": user_prompt})`
	`98`	`+ answer = merge_chain.invoke({"user_prompt": user_prompt})`
`99`	`99`	`answer["sources"] = state.get("urls", [])`
`100`	`100`
`101`	`101`	`state.update({self.output[0]: answer})`
Original file line number	Diff line number	Diff line change
`@@ -74,7 +74,7 @@ def execute(self, state: dict) -> dict:`
`74`	`74`	`)`
`75`	`75`
`76`	`76`	`merge_chain = prompt_template \| self.llm_model \| StrOutputParser()`
`77`		`- answer = merge_chain.ainvoke({"user_prompt": user_prompt})`
	`77`	`+ answer = merge_chain.invoke({"user_prompt": user_prompt})`
`78`	`78`
`79`	`79`	`state.update({self.output[0]: answer})`
`80`	`80`	`return state`