diff --git a/.gitignore b/.gitignore
index c1e69543e..a4d2733b7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -79,3 +79,5 @@ paulgraham.py
 supabase/seed-airwallex.sql
 airwallexpayouts.py
 application.log
+backend/celerybeat-schedule.db
+
diff --git a/Pipfile b/Pipfile
index 091a4d72a..d006103fc 100644
--- a/Pipfile
+++ b/Pipfile
@@ -47,8 +47,12 @@ watchdog = "*"
 langchain-community = "*"
 langchain-openai = "*"
 pydantic-settings = "*"
-unstructured = {extras = ["all-docs"], version = "*"}
 langfuse = "*"
+pandasai = "*"
+colorlog = "*"
+psycopg2-binary = "*"
+psycopg2 = "*"
+unstructured = {extras = ["all-docs"], version = "*"}
 
 [dev-packages]
 black = "*"
diff --git a/Pipfile.lock b/Pipfile.lock
index c438fe314..cc0d09907 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "7b0a7a1d9a850c686e65ee17aecfe4de8b84e92c7b4b155dcda21e64a75257d4"
+            "sha256": "c655d8a43b0a0a2d3460e7707c2059601ec2bf2830d20a6ed7cf45f07d7d844b"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -136,6 +136,14 @@
             "markers": "python_version >= '3.8'",
             "version": "==4.2.0"
         },
+        "astor": {
+            "hashes": [
+                "sha256:070a54e890cefb5b3739d19f30f5a5ec840ffc9c50ffa7d23cc9fc1a38ebbfc5",
+                "sha256:6a6effda93f4e1ce9f618779b2dd1d9d84f1e32812c23a29b3fff6fd7f63fa5e"
+            ],
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
+            "version": "==0.8.1"
+        },
         "async-generator": {
             "hashes": [
                 "sha256:01c7bf666359b4967d2cda0000cc2e4af16a0ae098cbffcb8472fb9e8ad6585b",
@@ -251,21 +259,21 @@
         },
         "boto3": {
             "hashes": [
-                "sha256:9fd66f22a4cdd63165a7a19186fff9b6e3d742e83498ea3f3231bab6ae4bf0f3",
-                "sha256:ae1a974c728c076a49392a695102124f650f45361c654bb7c0bef1bb644c52d5"
+                "sha256:2ed136f9cf79e783e12424db23e970d1c50e65a8d7a9077efa71cbf8496fb7a3",
+                "sha256:5069b2c647c73c8428378e88b32bd23f568001f897a6f01179fae25de72a7ca6"
             ],
             "index": "pypi",
             "markers": "python_version >= '3.8'",
-            "version": "==1.34.41"
+            "version": "==1.34.42"
         },
         "botocore": {
             "hashes": [
-                "sha256:3a6943c75a0d292ab6e008bce58ee6503776969479f991f5ad03a5d877af29ae",
-                "sha256:9b5827332da766da487e5a5b14b36e02528be9f2e899f909577afb7001eb441d"
+                "sha256:93755c3ede4bd9f6180b3118f6b607acca8b633fd2668226794a543ce79a2434",
+                "sha256:cf4fad50d09686f03e44418fcae9dd24369658daa556357cedc0790cfcd6fdac"
             ],
             "index": "pypi",
             "markers": "python_version >= '3.8'",
-            "version": "==1.34.41"
+            "version": "==1.34.42"
         },
         "bytecode": {
             "hashes": [
@@ -510,6 +518,15 @@
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'",
             "version": "==15.0.1"
         },
+        "colorlog": {
+            "hashes": [
+                "sha256:3e3e079a41feb5a1b64f978b5ea4f46040a94f11f0e8bbb8261e3dbbeca64d44",
+                "sha256:4dcbb62368e2800cb3c5abd348da7e53f6c362dda502ec27c560b2e58a66bd33"
+            ],
+            "index": "pypi",
+            "markers": "python_version >= '3.6'",
+            "version": "==6.8.2"
+        },
         "contourpy": {
             "hashes": [
                 "sha256:0274c1cb63625972c0c007ab14dd9ba9e199c36ae1a231ce45d725cbcbfd10a8",
@@ -640,70 +657,70 @@
         },
         "ddtrace": {
             "hashes": [
-                "sha256:0239709913f4f7a008a4e4ebd9f7810640bdb73ca68308804cbf884d510cf240",
-                "sha256:0abc759f5e4d6fcc59dbb7de300a8550005071aef41b29ceda37a9cf8a45bd2e",
-                "sha256:0cc2b7e45ae870dd9d2beb172d36810893a94bb1a605ba3a8e746f3e9bc88a55",
-                "sha256:0def60135e371fc2b5ace1f6c6c21073d1723506245c512eb8a8fc0406159a87",
-                "sha256:1013e6c0026035744f463a3a252b4b810c090974564a5e5dcb047b9d30d5a18b",
-                "sha256:11252ce5fb68f8c89d7866f001d8f744fa10f07da0a35a57fa261fec1409bb2b",
-                "sha256:12439445bc6a6cdeca0cb781c4cea37461fc7ab65ea5aeaace76329d5b645e2e",
-                "sha256:13412381b0eee7079701d8e3ec9b6963f6de405c8ec49d977be65ec5d4e987dc",
-                "sha256:17d4338961b00aa17590237c07b61c60357fbe6577b02159d6dba496063cc2cc",
-                "sha256:2352f4ae5140e919aeb5f3c7c19b58333d601f6f1982baeeac4a737b572661cc",
-                "sha256:2d8a34b41a1672119adca2c6f3b064c6346f5f4499218199697575bf2c0400df",
-                "sha256:326460202d801d0bb409b42727f2344798e74511febe11091b09b07344ceece2",
-                "sha256:364d452ccfded04db36a93a253e4e3ab00290ea5416a2c86c3091e06d1a70aff",
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+                "sha256:059c21dd3eb58d7ce2def5820af9819aa8c659e30cbec8bbda32f3c49480c513",
+                "sha256:064dadaa8033fd56f9e8d498c16382f01f65a471c46150b5557106b8a781a379",
+                "sha256:0b3e79c04702b516ca769fd5589c39e6392a8bc9d5ec9dac544f05ebe0fd06b9",
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+                "sha256:22ea21aa27801b0b2ff4def039b7f04ac1226685246e726f2010a52c58bc91f0",
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+                "sha256:3ad54bbdb675b81001372396171a72aa02c36dd203bea6f3d64dbdf50aec4b26",
+                "sha256:3b5a236513b3027fcf5069bba91e0795c528a16ceb6317398737b0f09864fea6",
+                "sha256:40f14644b553230c57def0d9febca122b847bf210ea777a924a0ee5e1b4cd92c",
+                "sha256:42c77dd11a3aa44cc6f7ff0de961a2651c19e048901ec7df32a0cdad45cc41d6",
+                "sha256:4905e66b133ba1e1e383af7df4978554ce98d753dedbd290f5425bc971df88ad",
+                "sha256:4c8cf7856ed0038bc6095435109523395bfa5aadaaecf860dd358f299a3d6d58",
+                "sha256:4e436c9345f61c373f87cc49b2f99dcd3a89c8147c9932f729ed92f5f3a27eab",
+                "sha256:511b6c7f710f98136584074c886b14e46d08901a85fabcc533d4a9cc1ef2ee85",
+                "sha256:56b808a15d898d3028b36d6c86d7664a0825e20a446d6c9ab968c22c946a9358",
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+                "sha256:636130d37e1961184a7761bc4116753ba63a738fa4fe3ef9474a1b030539ba58",
+                "sha256:6714164e19486ef0a671569108b04a07ca7d24155d9743b4b8d703e1a0c1ba52",
+                "sha256:6849606c45e26211b8a2574eae776d6d2793e9567888c27b5bbb8946bf8921e1",
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+                "sha256:6c37fef0710fd20faba2d1b53c5b6de31396f6a1b5fe5635248a9a01b1c7b7ce",
+                "sha256:6f44cc317d13edd81ed46bb1fe4f3d17342734a231543a5f76c10c671ec827e8",
+                "sha256:7132d3036ecb3129232cdeb2a7962c0aa39c8d4529478c014dcd75fbca121356",
+                "sha256:7c49abd723f9fe530d5c57395dc4324fd0bffe97619e835fea82871b0d855f4e",
+                "sha256:833c7609122a3cb5357d8c78454f64d06b56dd4d4a9446390169c6371a57bfc3",
+                "sha256:838dd8f11786305f5b5df00a430238711e8887000ca7c077587ca2c582403181",
+                "sha256:9690dd3509e6d2854f2054fd994b0548fe6c5d20af72b457fd704c7e7120ff03",
+                "sha256:9dc46a2ac1f2b24a8f802151d5befede387c083e02b78e4b8930447ad9dfad38",
+                "sha256:9f34eb5074e8915835383c0b8887bab988b054fac2ab3ece0fe35ffaa7b1aff4",
+                "sha256:a81d054720d6441b258f2fd9212d6b735a76fbb7d90201a1787fbb072d422dd6",
+                "sha256:ac4225c297256dfaf012eee2e803d87471699b2978a4bd24e188f5a49bcbd08f",
+                "sha256:ad1e8762814b438bd00bc5000aebfc57d1648fc836f65b3659d37ddff5fccb30",
+                "sha256:b1ee27f9b863dd24ef3f30bdf0e2dee7d959b49eb6c67ac08c16fb74eb758962",
+                "sha256:b2a6bd2e957e3c55d039304a09e3566bee85bf112319bb790eacea8d570a0c0a",
+                "sha256:c2ae27d019c3e3bfb8a731413dd650d6e447dc41979ee4dcad5b77ed8917e5d9",
+                "sha256:cf070c21e90db2c8bfeb4571dcfecbedec4392afdbcf3196ec772ee476be3852",
+                "sha256:d06766a7daae9eab8e81583c98eab8ca284027eaaac714e9621deec56e528b3e",
+                "sha256:d8de058bc65e670661e56f715a47a844e923b9d7ce8eb971d100480ef60b4673",
+                "sha256:dc4c5cbfa264e3a459b980f1d6dbd03a224c47297714f9f7aa2d763667db1f9d",
+                "sha256:ddbd82d61a338570e8a2ff3b55ce8af31251959f90fb09e6784fdbb311cdaa21",
+                "sha256:e3885af6449987e02a9fadd9132e7227825968c803ce9f164aeab01f9d23fbe2",
+                "sha256:eaf335dc2cf92627d3192134d54b063bc998d2ac4f25ae0fe3e2b36e8af92566",
+                "sha256:ec14250ce150f6c69de4a94d0da34702397564a6c118c550687adbfbfec4e075",
+                "sha256:edbf02d7be60cc743b76d8efe0d1953fa2f97d01f805a621f913bdc78c516d64",
+                "sha256:ee0ecdc9df9113e76d21d6a22c6c572ab1ddb198a498a19416b1e46605234f8d",
+                "sha256:f1064509f258bee5ae6a4d417c7f4d8ca28664edfdc6b4b978f07801aa7b16c5",
+                "sha256:f2f21519c0260f4fbaed12996de0e1940739706bfa9f92868e0ef27322c6f9aa",
+                "sha256:f61ea2d3e608d14ee2f4e3111c559d95db21762756214d05de8b980c1aae9265",
+                "sha256:fc77de2e3adb2e2b261adbcfe0b1f7288586e1d1ca775555f321e22259cad02a",
+                "sha256:fd06242bebbeed67e456a43bd678f28f30f98c6634e75e1aaf9c4905833d2f04",
+                "sha256:fe1e1fe9a2a32402e91184273434cbacf5dc007f2ba97fcd717028f13e99be6d",
+                "sha256:fe47433f3463434c4ced69652c58a4eef96518ff29a473d9587655ab797d086f"
             ],
             "index": "pypi",
             "markers": "python_version >= '3.7'",
-            "version": "==2.6.1"
+            "version": "==2.6.2"
         },
         "deprecated": {
             "hashes": [
@@ -740,7 +757,7 @@
                 "sha256:190348041559e21b22a1d65cee485282ca11a6f81d503fddb84d5017e9ed1e49",
                 "sha256:80600258e7ed2f16b9aa1d7c295bd70194109ad5a30fdee0eaeefef1d4c559dd"
             ],
-            "markers": "python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2'",
+            "markers": "python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'",
             "version": "==0.18.0"
         },
         "effdet": {
@@ -1029,11 +1046,11 @@
         },
         "httpcore": {
             "hashes": [
-                "sha256:096cc05bca73b8e459a1fc3dcf585148f63e534eae4339559c9b8a8d6399acc7",
-                "sha256:9fc092e4799b26174648e54b74ed5f683132a464e95643b226e00c2ed2fa6535"
+                "sha256:5c0f9546ad17dac4d0772b0808856eb616eb8b48ce94f49ed819fd6982a8a544",
+                "sha256:9a6a501c3099307d9fd76ac244e08503427679b1e81ceb1d922485e2f2462ad2"
             ],
             "markers": "python_version >= '3.8'",
-            "version": "==1.0.2"
+            "version": "==1.0.3"
         },
         "httpx": {
             "hashes": [
@@ -1359,7 +1376,7 @@
                 "sha256:b40fbe2b65360afe6c0d5bbf37e79469f990779460640edde5b906175c49807e"
             ],
             "index": "pypi",
-            "markers": "python_full_version >= '3.8.1' and python_version < '4.0'",
+            "markers": "python_version < '4.0' and python_full_version >= '3.8.1'",
             "version": "==0.1.7"
         },
         "langchain-community": {
@@ -1368,7 +1385,7 @@
                 "sha256:c56c48bc77d24e1fc399a9ee9a637d96e3b2ff952e3a080b5a41820d9d00fb3c"
             ],
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-            "markers": "python_full_version >= '3.8.1' and python_version < '4.0'",
+            "markers": "python_version < '4.0' and python_full_version >= '3.8.1'",
             "version": "==0.0.20"
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         "langchain-core": {
@@ -1376,7 +1393,7 @@
                 "sha256:34359cc8b6f8c3d45098c54a6a9b35c9f538ef58329cd943a2249d6d7b4e5806",
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+            "markers": "python_version < '4.0' and python_full_version >= '3.8.1'",
             "version": "==0.1.23"
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         "langchain-openai": {
@@ -1385,7 +1402,7 @@
                 "sha256:f5c4ebe46f2c8635c8f0c26cc8df27700aacafea025410e418d5a080039974dd"
             ],
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-            "markers": "python_full_version >= '3.8.1' and python_version < '4.0'",
+            "markers": "python_version < '4.0' and python_full_version >= '3.8.1'",
             "version": "==0.0.6"
         },
         "langdetect": {
@@ -1397,19 +1414,19 @@
         },
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-            "markers": "python_full_version >= '3.8.1' and python_version < '4.0'",
-            "version": "==2.13.2"
+            "markers": "python_version < '4.0' and python_full_version >= '3.8.1'",
+            "version": "==2.13.3"
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+            "markers": "python_version < '4.0' and python_full_version >= '3.8.1'",
             "version": "==0.0.87"
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@@ -1426,12 +1443,12 @@
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-            "version": "==1.23.14"
+            "version": "==1.23.15"
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@@ -1600,37 +1617,37 @@
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@@ -1999,8 +2016,18 @@
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@@ -2241,11 +2268,11 @@
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@@ -2272,6 +2299,105 @@
             "markers": "python_version >= '3.8'",
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+                "sha256:b58b4710c7f4161b5e9dcbe73bb7c62d65670a87df7bcce9e1faaad43e715245",
+                "sha256:b6356793b84728d9d50ead16ab43c187673831e9d4019013f1402c41b1db9b27",
+                "sha256:b76bedd166805480ab069612119ea636f5ab8f8771e640ae103e05a4aae3e417",
+                "sha256:bc7bb56d04601d443f24094e9e31ae6deec9ccb23581f75343feebaf30423359",
+                "sha256:c2470da5418b76232f02a2fcd2229537bb2d5a7096674ce61859c3229f2eb202",
+                "sha256:c332c8d69fb64979ebf76613c66b985414927a40f8defa16cf1bc028b7b0a7b0",
+                "sha256:c6af2a6d4b7ee9615cbb162b0738f6e1fd1f5c3eda7e5da17861eacf4c717ea7",
+                "sha256:c77e3d1862452565875eb31bdb45ac62502feabbd53429fdc39a1cc341d681ba",
+                "sha256:ca08decd2697fdea0aea364b370b1249d47336aec935f87b8bbfd7da5b2ee9c1",
+                "sha256:ca49a8119c6cbd77375ae303b0cfd8c11f011abbbd64601167ecca18a87e7cdd",
+                "sha256:cb16c65dcb648d0a43a2521f2f0a2300f40639f6f8c1ecbc662141e4e3e1ee07",
+                "sha256:d2997c458c690ec2bc6b0b7ecbafd02b029b7b4283078d3b32a852a7ce3ddd98",
+                "sha256:d3f82c171b4ccd83bbaf35aa05e44e690113bd4f3b7b6cc54d2219b132f3ae55",
+                "sha256:dc4926288b2a3e9fd7b50dc6a1909a13bbdadfc67d93f3374d984e56f885579d",
+                "sha256:ead20f7913a9c1e894aebe47cccf9dc834e1618b7aa96155d2091a626e59c972",
+                "sha256:ebdc36bea43063116f0486869652cb2ed7032dbc59fbcb4445c4862b5c1ecf7f",
+                "sha256:ed1184ab8f113e8d660ce49a56390ca181f2981066acc27cf637d5c1e10ce46e",
+                "sha256:ee825e70b1a209475622f7f7b776785bd68f34af6e7a46e2e42f27b659b5bc26",
+                "sha256:f7ae5d65ccfbebdfa761585228eb4d0df3a8b15cfb53bd953e713e09fbb12957",
+                "sha256:f7fc5a5acafb7d6ccca13bfa8c90f8c51f13d8fb87d95656d3950f0158d3ce53",
+                "sha256:f9b5571d33660d5009a8b3c25dc1db560206e2d2f89d3df1cb32d72c0d117d52"
+            ],
+            "index": "pypi",
+            "markers": "python_version >= '3.7'",
+            "version": "==2.9.9"
+        },
         "pyasn1": {
             "hashes": [
                 "sha256:4439847c58d40b1d0a573d07e3856e95333f1976294494c325775aeca506eb58",
@@ -2531,7 +2657,7 @@
                 "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86",
                 "sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9"
             ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2'",
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
             "version": "==2.8.2"
         },
         "python-docx": {
@@ -3082,7 +3208,7 @@
                 "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926",
                 "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"
             ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2'",
+            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
             "version": "==1.16.0"
         },
         "smmap": {
@@ -3533,6 +3659,7 @@
                 "sha256:019cf52e9e2bfa286e61ffa0d7d336e1645280f9a0f165e697583143fcfe708a",
                 "sha256:f1aa046297a3afba3aa16895e513aca6a93802ef73b7a18080656435c4deb217"
             ],
+            "index": "pypi",
             "markers": "python_version < '3.12' and python_full_version >= '3.9.0'",
             "version": "==0.12.4"
         },
@@ -3563,7 +3690,7 @@
                 "sha256:c97dfde1f7bd43a71c8d2a58e369e9b2bf692d1334ea9f9cae55add7d0dd0f84",
                 "sha256:fdb6d215c776278489906c2f8916e6e7d4f5a9b602ccbcfdf7f016fc8da0596e"
             ],
-            "markers": "python_version >= '3.10'",
+            "markers": "python_version >= '3.7'",
             "version": "==2.0.7"
         },
         "uvicorn": {
diff --git a/backend/logger.py b/backend/logger.py
index ea144d7cd..0c7cef91f 100644
--- a/backend/logger.py
+++ b/backend/logger.py
@@ -1,6 +1,10 @@
 import logging
 from logging.handlers import RotatingFileHandler
 
+from colorlog import (
+    ColoredFormatter,
+)  # You need to install this package: pip install colorlog
+
 
 def get_logger(logger_name, log_level=logging.INFO, log_file="application.log"):
     logger = logging.getLogger(logger_name)
@@ -8,11 +12,24 @@ def get_logger(logger_name, log_level=logging.INFO, log_file="application.log"):
     logger.propagate = False  # Prevent log propagation to avoid double logging
 
     formatter = logging.Formatter(
-        "%(asctime)s [%(levelname)s] %(name)s [%(lineno)d]: %(message)s"
+        "[%(levelname)s] %(name)s [%(filename)s:%(lineno)d]: %(message)s"
+    )
+
+    color_formatter = ColoredFormatter(
+        "%(log_color)s[%(levelname)s]%(reset)s %(name)s [%(filename)s:%(lineno)d]: %(message)s",
+        log_colors={
+            "DEBUG": "cyan",
+            "INFO": "green",
+            "WARNING": "yellow",
+            "ERROR": "red",
+            "CRITICAL": "red,bg_white",
+        },
+        reset=True,
+        style="%",
     )
 
     console_handler = logging.StreamHandler()
-    console_handler.setFormatter(formatter)
+    console_handler.setFormatter(color_formatter)
 
     file_handler = RotatingFileHandler(
         log_file, maxBytes=5000000, backupCount=5
diff --git a/backend/manage_services.sh b/backend/manage_services.sh
new file mode 100755
index 000000000..333cfde3d
--- /dev/null
+++ b/backend/manage_services.sh
@@ -0,0 +1,44 @@
+#!/bin/bash
+
+SESSION_NAME="my_services"
+
+start_services() {
+    # Create a new tmux session
+    tmux new-session -d -s $SESSION_NAME
+
+    # Split the window into panes for each service
+    tmux split-window -h
+    tmux split-window -v
+    tmux select-pane -t 0
+    tmux split-window -v
+
+    # Start each service in its pane
+    tmux send-keys -t $SESSION_NAME:0.0 'echo "Starting backend-core...";pipenv run uvicorn main:app --reload --host 0.0.0.0 --port 5050 --workers 6' C-m
+    tmux send-keys -t $SESSION_NAME:0.1 'echo "Starting worker...";pipenv run celery -A celery_worker worker -l info' C-m
+    tmux send-keys -t $SESSION_NAME:0.2 'echo "Starting beat...";pipenv run celery -A celery_worker beat -l info' C-m
+    tmux send-keys -t $SESSION_NAME:0.3 'echo "Starting flower...";pipenv run celery -A celery_worker flower -l info --port=5555' C-m
+
+    echo "Services started in tmux session '$SESSION_NAME'"
+    echo "Use 'tmux attach-session -t $SESSION_NAME' to view logs"
+}
+
+stop_services() {
+    # Kill the tmux session
+    tmux kill-session -t $SESSION_NAME
+    echo "Services stopped"
+}
+
+view_logs() {
+    # Attach to the tmux session to view logs
+    tmux attach-session -t $SESSION_NAME
+}
+
+if [ "$1" == "start" ]; then
+    start_services
+elif [ "$1" == "stop" ]; then
+    stop_services
+elif [ "$1" == "logs" ]; then
+    view_logs
+else
+    echo "Usage: $0 {start|stop|logs}"
+fi
diff --git a/backend/modules/brain/entity/integration_brain.py b/backend/modules/brain/entity/integration_brain.py
index 89756d008..b180150b0 100644
--- a/backend/modules/brain/entity/integration_brain.py
+++ b/backend/modules/brain/entity/integration_brain.py
@@ -12,7 +12,7 @@ class IntegrationDescriptionEntity(BaseModel):
 
 
 class IntegrationEntity(BaseModel):
-    id: str
+    id: int
     user_id: str
     brain_id: str
     integration_id: str
diff --git a/backend/modules/brain/integrations/GPT4/Brain.py b/backend/modules/brain/integrations/GPT4/Brain.py
new file mode 100644
index 000000000..03db2cd1d
--- /dev/null
+++ b/backend/modules/brain/integrations/GPT4/Brain.py
@@ -0,0 +1,62 @@
+import json
+from typing import AsyncIterable
+from uuid import UUID
+
+from langchain_community.chat_models import ChatLiteLLM
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from modules.brain.knowledge_brain_qa import KnowledgeBrainQA
+from modules.chat.dto.chats import ChatQuestion
+
+
+class GPT4Brain(KnowledgeBrainQA):
+    """This is the Notion brain class. it is a KnowledgeBrainQA has the data is stored locally.
+    It is going to call the Data Store internally to get the data.
+
+    Args:
+        KnowledgeBrainQA (_type_): A brain that store the knowledge internaly
+    """
+
+    def __init__(
+        self,
+        **kwargs,
+    ):
+        super().__init__(
+            **kwargs,
+        )
+
+    def get_chain(self):
+
+        prompt = ChatPromptTemplate.from_messages(
+            [
+                ("system", "You are GPT-4 powered by Quivr. You are an assistant."),
+                MessagesPlaceholder(variable_name="chat_history"),
+                ("human", "{question}"),
+            ]
+        )
+
+        chain = prompt | ChatLiteLLM(
+            model="gpt-4-0125-preview", max_tokens=self.max_tokens
+        )
+
+        return chain
+
+    async def generate_stream(
+        self, chat_id: UUID, question: ChatQuestion, save_answer: bool = True
+    ) -> AsyncIterable:
+        conversational_qa_chain = self.get_chain()
+        transformed_history, streamed_chat_history = (
+            self.initialize_streamed_chat_history(chat_id, question)
+        )
+        response_tokens = []
+
+        async for chunk in conversational_qa_chain.astream(
+            {
+                "question": question.question,
+                "chat_history": transformed_history,
+            }
+        ):
+            response_tokens.append(chunk.content)
+            streamed_chat_history.assistant = chunk.content
+            yield f"data: {json.dumps(streamed_chat_history.dict())}"
+
+        self.save_answer(question, response_tokens, streamed_chat_history, save_answer)
diff --git a/backend/modules/brain/integrations/GPT4/__init__.py b/backend/modules/brain/integrations/GPT4/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/backend/modules/brain/integrations/SQL/Brain.py b/backend/modules/brain/integrations/SQL/Brain.py
new file mode 100644
index 000000000..4354d2d6d
--- /dev/null
+++ b/backend/modules/brain/integrations/SQL/Brain.py
@@ -0,0 +1,100 @@
+import json
+from typing import AsyncIterable
+from uuid import UUID
+
+from langchain_community.chat_models import ChatLiteLLM
+from langchain_community.utilities import SQLDatabase
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.runnables import RunnablePassthrough
+from modules.brain.integrations.SQL.SQL_connector import SQLConnector
+from modules.brain.knowledge_brain_qa import KnowledgeBrainQA
+from modules.brain.repository.integration_brains import IntegrationBrain
+from modules.chat.dto.chats import ChatQuestion
+
+
+class SQLBrain(KnowledgeBrainQA, IntegrationBrain):
+    """This is the Notion brain class. it is a KnowledgeBrainQA has the data is stored locally.
+    It is going to call the Data Store internally to get the data.
+
+    Args:
+        KnowledgeBrainQA (_type_): A brain that store the knowledge internaly
+    """
+
+    uri: str = None
+    db: SQLDatabase = None
+    sql_connector: SQLConnector = None
+
+    def __init__(
+        self,
+        **kwargs,
+    ):
+        super().__init__(
+            **kwargs,
+        )
+        self.sql_connector = SQLConnector(self.brain_id, self.user_id)
+
+    def get_schema(self, _):
+        return self.db.get_table_info()
+
+    def run_query(self, query):
+        return self.db.run(query)
+
+    def get_chain(self):
+        template = """Based on the table schema below, write a SQL query that would answer the user's question:
+        {schema}
+
+        Question: {question}
+        SQL Query:"""
+        prompt = ChatPromptTemplate.from_template(template)
+
+        self.db = SQLDatabase.from_uri(self.sql_connector.credentials["uri"])
+
+        model = ChatLiteLLM(model=self.model)
+
+        sql_response = (
+            RunnablePassthrough.assign(schema=self.get_schema)
+            | prompt
+            | model.bind(stop=["\nSQLResult:"])
+            | StrOutputParser()
+        )
+
+        template = """Based on the table schema below, question, sql query, and sql response, write a natural language response and the query that was used to generate it.:
+            {schema}
+
+            Question: {question}
+            SQL Query: {query}
+            SQL Response: {response}"""
+        prompt_response = ChatPromptTemplate.from_template(template)
+
+        full_chain = (
+            RunnablePassthrough.assign(query=sql_response).assign(
+                schema=self.get_schema,
+                response=lambda x: self.db.run(x["query"]),
+            )
+            | prompt_response
+            | model
+        )
+
+        return full_chain
+
+    async def generate_stream(
+        self, chat_id: UUID, question: ChatQuestion, save_answer: bool = True
+    ) -> AsyncIterable:
+
+        conversational_qa_chain = self.get_chain()
+        transformed_history, streamed_chat_history = (
+            self.initialize_streamed_chat_history(chat_id, question)
+        )
+        response_tokens = []
+
+        async for chunk in conversational_qa_chain.astream(
+            {
+                "question": question.question,
+            }
+        ):
+            response_tokens.append(chunk.content)
+            streamed_chat_history.assistant = chunk.content
+            yield f"data: {json.dumps(streamed_chat_history.dict())}"
+
+        self.save_answer(question, response_tokens, streamed_chat_history, save_answer)
diff --git a/backend/modules/brain/integrations/SQL/SQL_connector.py b/backend/modules/brain/integrations/SQL/SQL_connector.py
new file mode 100644
index 000000000..4cbc858b0
--- /dev/null
+++ b/backend/modules/brain/integrations/SQL/SQL_connector.py
@@ -0,0 +1,41 @@
+from logger import get_logger
+from modules.brain.entity.integration_brain import IntegrationEntity
+from modules.brain.repository.integration_brains import IntegrationBrain
+from modules.knowledge.repository.knowledge_interface import KnowledgeInterface
+from modules.knowledge.service.knowledge_service import KnowledgeService
+
+logger = get_logger(__name__)
+
+
+class SQLConnector(IntegrationBrain):
+    """A class to interact with an SQL database"""
+
+    credentials: dict[str, str] = None
+    integration_details: IntegrationEntity = None
+    brain_id: str = None
+    user_id: str = None
+    knowledge_service: KnowledgeInterface
+
+    def __init__(self, brain_id: str, user_id: str):
+        super().__init__()
+        self.brain_id = brain_id
+        self.user_id = user_id
+        self._load_credentials()
+        self.knowledge_service = KnowledgeService()
+
+    def _load_credentials(self) -> dict[str, str]:
+        """Load the Notion credentials"""
+        self.integration_details = self.get_integration_brain(
+            self.brain_id, self.user_id
+        )
+        if self.credentials is None:
+            logger.info("Loading Notion credentials")
+            self.integration_details.credentials = {
+                "uri": self.integration_details.settings.get("uri", "")
+            }
+            self.update_integration_brain(
+                self.brain_id, self.user_id, self.integration_details
+            )
+            self.credentials = self.integration_details.credentials
+        else:  # pragma: no cover
+            self.credentials = self.integration_details.credentials
diff --git a/backend/modules/brain/integrations/SQL/__init__.py b/backend/modules/brain/integrations/SQL/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/backend/modules/brain/knowledge_brain_qa.py b/backend/modules/brain/knowledge_brain_qa.py
index 450aaf751..7eeaa4bbd 100644
--- a/backend/modules/brain/knowledge_brain_qa.py
+++ b/backend/modules/brain/knowledge_brain_qa.py
@@ -38,7 +38,7 @@ def is_valid_uuid(uuid_to_test, version=4):
     return str(uuid_obj) == uuid_to_test
 
 
-def generate_source(result, brain):
+def generate_source(source_documents, brain_id):
     # Initialize an empty list for sources
     sources_list: List[Sources] = []
 
@@ -46,27 +46,28 @@ def generate_source(result, brain):
     generated_urls = {}
 
     # Get source documents from the result, default to an empty list if not found
-    source_documents = result.get("source_documents", [])
 
     # If source documents exist
     if source_documents:
         logger.info(f"Source documents found: {source_documents}")
         # Iterate over each document
         for doc in source_documents:
+            doc0 = doc[0]
+            logger.info("Document: %s", doc0)
             # Check if 'url' is in the document metadata
-            logger.info(f"Metadata 1: {doc.metadata}")
+            logger.info(f"Metadata 1: {doc0.metadata}")
             is_url = (
-                "original_file_name" in doc.metadata
-                and doc.metadata["original_file_name"] is not None
-                and doc.metadata["original_file_name"].startswith("http")
+                "original_file_name" in doc0.metadata
+                and doc0.metadata["original_file_name"] is not None
+                and doc0.metadata["original_file_name"].startswith("http")
             )
             logger.info(f"Is URL: {is_url}")
 
             # Determine the name based on whether it's a URL or a file
             name = (
-                doc.metadata["original_file_name"]
+                doc0.metadata["original_file_name"]
                 if is_url
-                else doc.metadata["file_name"]
+                else doc0.metadata["file_name"]
             )
 
             # Determine the type based on whether it's a URL or a file
@@ -74,9 +75,9 @@ def generate_source(result, brain):
 
             # Determine the source URL based on whether it's a URL or a file
             if is_url:
-                source_url = doc.metadata["original_file_name"]
+                source_url = doc0.metadata["original_file_name"]
             else:
-                file_path = f"{brain.brain_id}/{doc.metadata['file_name']}"
+                file_path = f"{brain_id}/{doc0.metadata['file_name']}"
                 # Check if the URL has already been generated
                 if file_path in generated_urls:
                     source_url = generated_urls[file_path]
@@ -126,6 +127,7 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
     streaming: bool = False
     knowledge_qa: Optional[RAGInterface] = None
     metadata: Optional[dict] = None
+    user_id: str = None
 
     callbacks: List[AsyncIteratorCallbackHandler] = (
         None  # pyright: ignore reportPrivateUsage=none
@@ -142,6 +144,7 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
         streaming: bool = False,
         prompt_id: Optional[UUID] = None,
         metadata: Optional[dict] = None,
+        user_id: str = None,
         **kwargs,
     ):
         super().__init__(
@@ -161,6 +164,7 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
         )
         self.metadata = metadata
         self.max_tokens = max_tokens
+        self.user_id = user_id
 
     @property
     def prompt_to_use(self):
@@ -259,14 +263,42 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
     async def generate_stream(
         self, chat_id: UUID, question: ChatQuestion, save_answer: bool = True
     ) -> AsyncIterable:
-        history = chat_service.get_chat_history(self.chat_id)
-
         conversational_qa_chain = self.knowledge_qa.get_chain()
-
-        transformed_history = format_chat_history(history)
-
+        transformed_history, streamed_chat_history = (
+            self.initialize_streamed_chat_history(chat_id, question)
+        )
         response_tokens = []
+        sources = []
 
+        async for chunk in conversational_qa_chain.astream(
+            {
+                "question": question.question,
+                "chat_history": transformed_history,
+                "custom_personality": (
+                    self.prompt_to_use.content if self.prompt_to_use else None
+                ),
+            }
+        ):
+            if chunk.get("answer"):
+                logger.info(f"Chunk: {chunk}")
+                response_tokens.append(chunk["answer"].content)
+                streamed_chat_history.assistant = chunk["answer"].content
+                yield f"data: {json.dumps(streamed_chat_history.dict())}"
+            if chunk.get("docs"):
+                sources = chunk["docs"]
+
+        sources_list = generate_source(sources, self.brain_id)
+        if not streamed_chat_history.metadata:
+            streamed_chat_history.metadata = {}
+            # Serialize the sources list
+        serialized_sources_list = [source.dict() for source in sources_list]
+        streamed_chat_history.metadata["sources"] = serialized_sources_list
+        yield f"data: {json.dumps(streamed_chat_history.dict())}"
+        self.save_answer(question, response_tokens, streamed_chat_history, save_answer)
+
+    def initialize_streamed_chat_history(self, chat_id, question):
+        history = chat_service.get_chat_history(self.chat_id)
+        transformed_history = format_chat_history(history)
         brain = brain_service.get_brain_by_id(self.brain_id)
 
         streamed_chat_history = chat_service.update_chat_history(
@@ -297,24 +329,11 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
             }
         )
 
-        try:
-
-            async for chunk in conversational_qa_chain.astream(
-                {
-                    "question": question.question,
-                    "chat_history": transformed_history,
-                    "custom_personality": (
-                        self.prompt_to_use.content if self.prompt_to_use else None
-                    ),
-                }
-            ):
-                response_tokens.append(chunk.content)
-                streamed_chat_history.assistant = chunk.content
-                yield f"data: {json.dumps(streamed_chat_history.dict())}"
-
-        except Exception as e:
-            logger.error("Error generating stream: %s", e)
+        return transformed_history, streamed_chat_history
 
+    def save_answer(
+        self, question, response_tokens, streamed_chat_history, save_answer
+    ):
         assistant = "".join(response_tokens)
 
         try:
diff --git a/backend/modules/brain/rags/quivr_rag.py b/backend/modules/brain/rags/quivr_rag.py
index ca6b6da07..a62e03efe 100644
--- a/backend/modules/brain/rags/quivr_rag.py
+++ b/backend/modules/brain/rags/quivr_rag.py
@@ -5,14 +5,15 @@ from uuid import UUID
 from langchain.chains import ConversationalRetrievalChain
 from langchain.embeddings.ollama import OllamaEmbeddings
 from langchain.llms.base import BaseLLM
+from langchain.memory import ConversationBufferMemory
 from langchain.prompts import HumanMessagePromptTemplate
 from langchain.schema import format_document
 from langchain_community.chat_models import ChatLiteLLM
 from langchain_core.messages import SystemMessage, get_buffer_string
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
-from langchain_core.runnables import RunnableParallel, RunnablePassthrough
-from langchain_openai import ChatOpenAI, OpenAIEmbeddings
+from langchain_core.runnables import RunnableLambda, RunnablePassthrough
+from langchain_openai import OpenAIEmbeddings
 from llm.utils.get_prompt_to_use import get_prompt_to_use
 from logger import get_logger
 from models import BrainSettings  # Importing settings related to the 'brain'
@@ -57,8 +58,6 @@ ANSWER_PROMPT = ChatPromptTemplate.from_messages(
 )
 
 
-ChatPromptTemplate.from_template(template_answer)
-
 # How we format documents
 
 DEFAULT_DOCUMENT_PROMPT = PromptTemplate.from_template(
@@ -205,29 +204,49 @@ class QuivrRAG(BaseModel):
 
     def get_chain(self):
         retriever_doc = self.get_retriever()
-
-        _inputs = RunnableParallel(
-            standalone_question=RunnablePassthrough.assign(
-                chat_history=lambda x: get_buffer_string(x["chat_history"])
-            )
-            | CONDENSE_QUESTION_PROMPT
-            | ChatOpenAI(temperature=0)
-            | StrOutputParser(),
+        memory = ConversationBufferMemory(
+            return_messages=True, output_key="answer", input_key="question"
         )
 
+        loaded_memory = RunnablePassthrough.assign(
+            chat_history=RunnableLambda(memory.load_memory_variables)
+            | itemgetter("history"),
+        )
+
+        standalone_question = {
+            "standalone_question": {
+                "question": lambda x: x["question"],
+                "chat_history": lambda x: get_buffer_string(x["chat_history"]),
+            }
+            | CONDENSE_QUESTION_PROMPT
+            | ChatLiteLLM(temperature=0, model=self.model)
+            | StrOutputParser(),
+        }
+
         prompt_custom_user = self.prompt_to_use()
         prompt_to_use = "None"
         if prompt_custom_user:
             prompt_to_use = prompt_custom_user.content
-        logger.info(f"Prompt to use: {prompt_custom_user}")
-        _context = {
-            "context": itemgetter("standalone_question")
-            | retriever_doc
-            | self._combine_documents,
+
+        # Now we retrieve the documents
+        retrieved_documents = {
+            "docs": itemgetter("standalone_question") | retriever_doc,
             "question": lambda x: x["standalone_question"],
             "custom_instructions": lambda x: prompt_to_use,
         }
 
-        conversational_qa_chain = _inputs | _context | ANSWER_PROMPT | ChatOpenAI()
+        final_inputs = {
+            "context": lambda x: self._combine_documents(x["docs"]),
+            "question": itemgetter("question"),
+            "custom_instructions": itemgetter("custom_instructions"),
+        }
 
-        return conversational_qa_chain
+        # And finally, we do the part that returns the answers
+        answer = {
+            "answer": final_inputs
+            | ANSWER_PROMPT
+            | ChatLiteLLM(max_tokens=self.max_tokens, model=self.model),
+            "docs": itemgetter("docs"),
+        }
+
+        return loaded_memory | standalone_question | retrieved_documents | answer
diff --git a/backend/modules/brain/service/brain_service.py b/backend/modules/brain/service/brain_service.py
index 0f2475021..876f53631 100644
--- a/backend/modules/brain/service/brain_service.py
+++ b/backend/modules/brain/service/brain_service.py
@@ -202,8 +202,8 @@ class BrainService:
         if (
             self.integration_description_repository.get_integration_description(
                 brain.integration.integration_id
-            ).integration_name
-            == "Notion"
+            ).integration_name.lower()
+            == "notion"
         ):
             celery.send_task(
                 "NotionConnectorLoad",
diff --git a/backend/modules/chat/controller/chat/brainful_chat.py b/backend/modules/chat/controller/chat/brainful_chat.py
index e166f84ad..9b75434ca 100644
--- a/backend/modules/chat/controller/chat/brainful_chat.py
+++ b/backend/modules/chat/controller/chat/brainful_chat.py
@@ -1,7 +1,9 @@
 from logger import get_logger
 from modules.brain.api_brain_qa import APIBrainQA
 from modules.brain.entity.brain_entity import BrainType, RoleEnum
+from modules.brain.integrations.GPT4.Brain import GPT4Brain
 from modules.brain.integrations.Notion.Brain import NotionBrain
+from modules.brain.integrations.SQL.Brain import SQLBrain
 from modules.brain.knowledge_brain_qa import KnowledgeBrainQA
 from modules.brain.service.api_brain_definition_service import ApiBrainDefinitionService
 from modules.brain.service.brain_authorization_service import (
@@ -31,6 +33,13 @@ models_supporting_function_calls = [
     "gpt-3.5-turbo",
 ]
 
+
+integration_list = {
+    "notion": NotionBrain,
+    "gpt4": GPT4Brain,
+    "sql": SQLBrain,
+}
+
 brain_service = BrainService()
 
 
@@ -67,6 +76,7 @@ class BrainfulChat(ChatInterface):
                 streaming=streaming,
                 prompt_id=prompt_id,
                 metadata=metadata,
+                user_id=user_id,
             )
 
         if brain.brain_type == BrainType.API:
@@ -94,8 +104,11 @@ class BrainfulChat(ChatInterface):
                 brain.brain_id, user_id
             )
 
-            if integration_brain.integration_name == "Notion":
-                return NotionBrain(
+            integration_class = integration_list.get(
+                integration_brain.integration_name.lower()
+            )
+            if integration_class:
+                return integration_class(
                     chat_id=chat_id,
                     model=model,
                     max_tokens=max_tokens,
@@ -105,4 +118,5 @@ class BrainfulChat(ChatInterface):
                     streaming=streaming,
                     prompt_id=prompt_id,
                     metadata=metadata,
+                    user_id=user_id,
                 )
diff --git a/backend/requirements.txt b/backend/requirements.txt
index 87d854986..9fe417f66 100644
--- a/backend/requirements.txt
+++ b/backend/requirements.txt
@@ -5,6 +5,7 @@ amqp==5.2.0; python_version >= '3.6'
 annotated-types==0.6.0; python_version >= '3.8'
 antlr4-python3-runtime==4.9.3
 anyio==4.2.0; python_version >= '3.8'
+astor==0.8.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 async-generator==1.10; python_version >= '3.5'
 asyncpg==0.27.0; python_full_version >= '3.7.0'
 attrs==23.2.0; python_version >= '3.7'
@@ -12,8 +13,8 @@ backoff==2.2.1; python_version >= '3.7' and python_version < '4.0'
 beautifulsoup4==4.12.3; python_full_version >= '3.6.0'
 billiard==4.2.0; python_version >= '3.7'
 black==24.2.0; python_version >= '3.8'
-boto3==1.34.41; python_version >= '3.8'
-botocore==1.34.41; python_version >= '3.8'
+boto3==1.34.42; python_version >= '3.8'
+botocore==1.34.42; python_version >= '3.8'
 bytecode==0.15.1; python_version >= '3.8'
 cattrs==23.2.3; python_version >= '3.8'
 celery[sqs]==5.3.6; python_version >= '3.8'
@@ -27,6 +28,7 @@ click-didyoumean==0.3.0; python_full_version >= '3.6.2' and python_full_version
 click-plugins==1.1.1
 click-repl==0.3.0; python_version >= '3.6'
 coloredlogs==15.0.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'
+colorlog==6.8.2; python_version >= '3.6'
 contourpy==1.2.0; python_version >= '3.9'
 cryptography==42.0.2; python_version >= '3.7'
 cssselect==1.2.0; python_version >= '3.7'
@@ -34,12 +36,12 @@ cycler==0.12.1; python_version >= '3.8'
 dataclasses-json==0.6.4; python_version >= '3.7' and python_version < '4.0'
 dataclasses-json-speakeasy==0.5.11; python_version >= '3.7' and python_version < '4.0'
 ddsketch==2.0.4; python_version >= '2.7'
-ddtrace==2.6.1; python_version >= '3.7'
+ddtrace==2.6.2; python_version >= '3.7'
 deprecated==1.2.14; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 deprecation==2.1.0
 distro==1.9.0; python_version >= '3.6'
 docx2txt==0.8
-ecdsa==0.18.0; python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2'
+ecdsa==0.18.0; python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'
 effdet==0.4.1
 emoji==2.10.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 envier==0.5.1; python_version >= '3.7'
@@ -61,7 +63,7 @@ gitpython==3.1.36; python_version >= '3.7'
 gotrue==2.1.0; python_version >= '3.8' and python_version < '4.0'
 h11==0.14.0; python_version >= '3.7'
 html5lib==1.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'
-httpcore==1.0.2; python_version >= '3.8'
+httpcore==1.0.3; python_version >= '3.8'
 httpx==0.25.2; python_version >= '3.8'
 huggingface-hub==0.20.3; python_full_version >= '3.8.0'
 humanfriendly==10.0; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'
@@ -80,20 +82,20 @@ jsonpath-python==1.0.6; python_version >= '3.6'
 jsonpointer==2.4; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6'
 kiwisolver==1.4.5; python_version >= '3.7'
 kombu[sqs]==5.3.5; python_version >= '3.8'
-langchain==0.1.7; python_full_version >= '3.8.1' and python_version < '4.0'
-langchain-community==0.0.20; python_full_version >= '3.8.1' and python_version < '4.0'
-langchain-core==0.1.23; python_full_version >= '3.8.1' and python_version < '4.0'
-langchain-openai==0.0.6; python_full_version >= '3.8.1' and python_version < '4.0'
+langchain==0.1.7; python_version < '4.0' and python_full_version >= '3.8.1'
+langchain-community==0.0.20; python_version < '4.0' and python_full_version >= '3.8.1'
+langchain-core==0.1.23; python_version < '4.0' and python_full_version >= '3.8.1'
+langchain-openai==0.0.6; python_version < '4.0' and python_full_version >= '3.8.1'
 langdetect==1.0.9
-langfuse==2.13.2; python_full_version >= '3.8.1' and python_version < '4.0'
-langsmith==0.0.87; python_full_version >= '3.8.1' and python_version < '4.0'
+langfuse==2.13.3; python_version < '4.0' and python_full_version >= '3.8.1'
+langsmith==0.0.87; python_version < '4.0' and python_full_version >= '3.8.1'
 layoutparser[layoutmodels,tesseract]==0.3.4; python_version >= '3.6'
-litellm==1.23.14; python_version not in '2.7, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7' and python_version >= '3.8'
+litellm==1.23.15; python_version not in '2.7, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7' and python_version >= '3.8'
 lxml==5.1.0; python_version >= '3.6'
 markdown==3.5.2
 markupsafe==2.1.5; python_version >= '3.7'
 marshmallow==3.20.2; python_version >= '3.8'
-matplotlib==3.8.2; python_version >= '3.9'
+matplotlib==3.8.3; python_version >= '3.9'
 mccabe==0.7.0; python_version >= '3.6'
 monotonic==1.6
 mpmath==1.3.0
@@ -115,7 +117,8 @@ opencv-python==4.9.0.80; python_version >= '3.6'
 openpyxl==3.1.2
 opentelemetry-api==1.22.0; python_version >= '3.7'
 packaging==23.2; python_version >= '3.7'
-pandas==2.2.0
+pandas==2.2.0; python_version >= '3.9'
+pandasai==0.1.0; python_version >= '3.9' and python_version < '4.0'
 pathspec==0.12.1; python_version >= '3.8'
 pdf2image==1.16.3
 pdfminer.six==20221105
@@ -128,9 +131,11 @@ pluggy==1.4.0; python_version >= '3.8'
 portalocker==2.8.2; python_version >= '3.8'
 postgrest==0.15.0; python_version >= '3.8' and python_version < '4.0'
 posthog==3.4.1
-prometheus-client==0.19.0; python_version >= '3.8'
+prometheus-client==0.20.0; python_version >= '3.8'
 prompt-toolkit==3.0.43; python_full_version >= '3.7.0'
 protobuf==4.25.2; python_version >= '3.8'
+psycopg2==2.9.9; python_version >= '3.7'
+psycopg2-binary==2.9.9; python_version >= '3.7'
 pyasn1==0.5.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'
 pycocotools==2.0.7; python_version >= '3.5'
 pycodestyle==2.11.1; python_version >= '3.8'
@@ -149,7 +154,7 @@ pytesseract==0.3.10; python_version >= '3.7'
 pytest==8.0.0; python_version >= '3.8'
 pytest-celery==0.0.0
 pytest-mock==3.12.0; python_version >= '3.8'
-python-dateutil==2.8.2; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2'
+python-dateutil==2.8.2; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 python-docx==1.1.0
 python-dotenv==1.0.1; python_version >= '3.8'
 python-iso639==2024.2.7; python_version >= '3.8'
@@ -173,7 +178,7 @@ scipy==1.12.0; python_version >= '3.9'
 sentry-sdk[fastapi]==1.40.4
 setuptools==69.1.0; python_version >= '3.8'
 sgmllib3k==1.0.0
-six==1.16.0; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2'
+six==1.16.0; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 smmap==5.0.1; python_version >= '3.7'
 sniffio==1.3.0; python_version >= '3.7'
 soupsieve==2.5; python_version >= '3.8'
@@ -203,7 +208,7 @@ unstructured[all-docs]==0.12.4; python_version < '3.12' and python_full_version
 unstructured-client==0.18.0; python_version >= '3.8'
 unstructured-inference==0.7.23
 unstructured.pytesseract==0.3.12
-urllib3==2.0.7; python_version >= '3.10'
+urllib3==2.0.7; python_version >= '3.7'
 uvicorn==0.22.0; python_version >= '3.7'
 vine==5.1.0; python_version >= '3.6'
 watchdog==4.0.0; python_version >= '3.8'
diff --git a/docker-compose.redis.yml b/docker-compose.redis.yml
new file mode 100644
index 000000000..06074ae2f
--- /dev/null
+++ b/docker-compose.redis.yml
@@ -0,0 +1,9 @@
+version: "3.8"
+
+services:
+  redis:
+    image: redis:latest@sha256:a7cee7c8178ff9b5297cb109e6240f5072cdaaafd775ce6b586c3c704b06458e
+    container_name: redis
+    restart: always
+    ports:
+      - 6379:6379