changed the response

phase1_agents.py

@@ -33,7 +33,8 @@ company_search_agent = Agent(
 
 def search_company(company_name: str):
     query = f"Find detailed company information for {company_name}. Extract its official website, mission, services, and any AI-related initiatives. Prioritize official sources and provide links where available."
-    return company_search_agent.print_response(query)
+    response = company_search_agent.run(query)
+    return response.content
 
 
 ##############################
@@ -48,8 +49,8 @@ firecrawl_agent = Agent(
 )
 
 def scrape_website(url: str):
-    return firecrawl_agent.print_response(f"Extract all relevant business information from {url}, including mission statement, services, case studies, and AI-related content. Provide structured output.")
-
+    response = firecrawl_agent.run(f"Extract all relevant business information from {url}, including mission statement, services, case studies, and AI-related content. Provide structured output.")
+    return response.content
 
 ##############################
 # 3️⃣ Text Processing Agent   #
@@ -64,8 +65,8 @@ text_processing_agent = Agent(
 )
 
 def process_company_description(text: str):
-    return text_processing_agent.print_response(f"Summarize the following company description: {text}. Focus on key services, mission, industry, and potential AI use cases where applicable.")
-
+    response = text_processing_agent.run(f"Summarize the following company description: {text}. Focus on key services, mission, industry, and potential AI use cases where applicable.")
+    return response.content
 
 #################################
 # 4️⃣ Document Processing Agent  #
@@ -75,6 +76,8 @@ embedding_model = OpenAIEmbedder(model="text-embedding-3-small")
 dimension = 1536  # OpenAI's embedding dimension
 faiss_index = faiss.IndexFlatL2(dimension)
 
+
+
 def process_uploaded_document(file: UploadFile):
     file_path = f"tmp/{file.filename}"
     with open(file_path, "wb") as buffer:
@@ -83,8 +86,20 @@ def process_uploaded_document(file: UploadFile):
     with open(file_path, "r", encoding="utf-8") as f:
         document_text = f.read()
     
-    # Generate embedding
-    embedding = np.array(embedding_model.embed([document_text])).astype("float32")
-    faiss_index.add(embedding)
+    # Optionally, you can generate an embedding if needed, but return the raw content for further phases.
+    return document_text  # Return the processed document text
+
+
+# def process_uploaded_document(file: UploadFile):
+#     file_path = f"tmp/{file.filename}"
+#     with open(file_path, "wb") as buffer:
+#         buffer.write(file.file.read())
+    
+#     with open(file_path, "r", encoding="utf-8") as f:
+#         document_text = f.read()
+    
+#     # Generate embedding
+#     embedding = np.array(embedding_model.embed([document_text])).astype("float32")
+#     faiss_index.add(embedding)
     
-    return f"Document processed and stored in FAISS index: {file.filename}"
+#     return f"Document processed and stored in FAISS index: {file.filename}"