Merge pull request #137 from openchatai/feature/response-slim-compres…

…sion

Context size reduction

llm-server/routes/workflow/extractors/example_generator.py

@@ -96,4 +96,4 @@ def generate_example_with_format(property_schema: Dict[str, Any]) -> Any:
 
 
 def gen_ex_from_schema(schema: Any) -> Any:
-    return json.dumps(generate_example_json(schema))
+    return json.dumps(generate_example_json(schema), separators=(',', ':'))

llm-server/routes/workflow/extractors/extract_body.py

@@ -30,7 +30,7 @@ def gen_body_from_schema(
         HumanMessage(content="User input: {}".format(text)),
         HumanMessage(content="prev api responses: {}".format(prev_api_response)),
         HumanMessage(
-            content="Given the provided information, generate the appropriate JSON payload to use as body for the API request."
+            content="Given the provided information, generate the appropriate minified JSON payload to use as body for the API request."
         ),
     ]
     result = chat(messages)

llm-server/routes/workflow/extractors/transform_api_response.py

@@ -27,7 +27,7 @@ def transform_api_response_from_schema(server_url: str, responseText: str) -> st
             )
         ),
         HumanMessage(
-            content="Analyze the provided API responses and extract only the essential fields required for subsequent API interactions. Disregard any non-essential attributes such as CSS or color-related data. If there are generic fields like 'id,' provide them with more descriptive names in your response. Format your response as a JSON object with clear and meaningful keys that map to their respective values from the API response."
+            content="Analyze the provided API responses and extract only the essential fields required for subsequent API interactions. Disregard any non-essential attributes such as CSS or color-related data. If there are generic fields like 'id,' provide them with more descriptive names in your response. Format your response as a minified JSON object with clear and meaningful keys that map to their respective values from the API response."
         ),
     ]
 

llm-server/routes/workflow/generate_openapi_payload.py

@@ -94,21 +94,21 @@ def generate_openapi_payload(
         {}
         if not api_info.path_params["properties"]
         else gen_params_from_schema(
-            json.dumps(api_info.path_params), text, prev_api_response
+            json.dumps(api_info.path_params, separators=(',', ':')), text, prev_api_response
         )
     )
     api_info.query_params = (
         {}
         if not api_info.query_params["properties"]
         else gen_params_from_schema(
-            json.dumps(api_info.query_params), text, prev_api_response
+            json.dumps(api_info.query_params, separators=(',', ':')), text, prev_api_response
         )
     )
 
     if api_info.body_schema:
         example = gen_ex_from_schema(api_info.body_schema)
         api_info.body_schema = gen_body_from_schema(
-            json.dumps(api_info.body_schema), text, prev_api_response, example
+            json.dumps(api_info.body_schema, separators=(',', ':')), text, prev_api_response, example
         )
 
     else:

llm-server/routes/workflow/utils/detect_multiple_intents.py

@@ -76,7 +76,7 @@ def hasSingleIntent(swagger_doc: Any, user_requirement: str) -> BotMessage:
     )
     messages = [
         SystemMessage(
-            content="You serve as an AI co-pilot tasked with identifying the correct sequence of API calls necessary to execute a user's action. If the user is asking you to perform a `CRUD` operation, provide the list of operation ids of api calls needed in the `ids` field of the json. `bot_message` should consist of a straightforward sentence, free from any special characters. Your response MUST be a valid json"
+            content="You serve as an AI co-pilot tasked with identifying the correct sequence of API calls necessary to execute a user's action. If the user is asking you to perform a `CRUD` operation, provide the list of operation ids of api calls needed in the `ids` field of the json. `bot_message` should consist of a straightforward sentence, free from any special characters. Your response MUST be a valid minified json"
         ),
         HumanMessage(
             content="Here's a list of api summaries {}.".format(summaries),

llm-server/routes/workflow/utils/fetch_swagger_text.py

@@ -16,13 +16,13 @@ def fetch_swagger_text(swagger_url: str) -> str:
             try:
                 # Try parsing the content as JSON
                 json_content = json.loads(response.text)
-                return json.dumps(json_content, indent=2)
+                return json.dumps(json_content, separators=(',', ':'))
             except json.JSONDecodeError:
                 try:
                     # Try parsing the content as YAML
                     yaml_content = yaml.safe_load(response.text)
                     if isinstance(yaml_content, dict):
-                        return json.dumps(yaml_content, indent=2)
+                        return json.dumps(yaml_content, separators=(',', ':'))
                     else:
                         raise Exception("Invalid YAML content")
                 except ParserError:
@@ -36,13 +36,13 @@ def fetch_swagger_text(swagger_url: str) -> str:
             try:
                 # Try parsing the content as JSON
                 json_content = json.loads(content)
-                return json.dumps(json_content, indent=2)
+                return json.dumps(json_content, separators=(',', ':'))
             except json.JSONDecodeError:
                 try:
                     # Try parsing the content as YAML
                     yaml_content = yaml.safe_load(content)
                     if isinstance(yaml_content, dict):
-                        return json.dumps(yaml_content, indent=2)
+                        return json.dumps(yaml_content, separators=(',', ':'))
                     else:
                         raise Exception("Invalid YAML content")
                 except ParserError:

llm-server/routes/workflow/utils/run_workflow.py

@@ -32,6 +32,6 @@ def run_workflow(
 
     output = {"response": result if not error else "", "error": error}
 
-    logging.info("[OpenCopilot] Workflow output %s", json.dumps(output))
+    logging.info("[OpenCopilot] Workflow output %s", json.dumps(output, separators=(',', ':')))
 
     return output

llm-server/utils/make_api_call.py

@@ -33,17 +33,17 @@ def make_api_request(
     headers,
     servers,
 ) -> Response:
-    endpoint = replace_url_placeholders(endpoint, path_params)
-    url = servers[0] + endpoint
-    # Create a session and configure it with headers
-    session = requests.Session()
+    try:
+        endpoint = replace_url_placeholders(endpoint, path_params)
+        url = servers[0] + endpoint
+        # Create a session and configure it with headers
+        session = requests.Session()
 
-    # Add the "Content-Type" header with the value "application/json" to the headers
-    headers["Content-Type"] = "application/json"
+        # Add the "Content-Type" header with the value "application/json" to the headers
+        headers["Content-Type"] = "application/json"
 
-    if headers:
-        session.headers.update(headers)
-    try:
+        if headers:
+            session.headers.update(headers)
         # Perform the HTTP request based on the request type
         if method == "GET":
             response = session.get(url, params=query_params)